Nauki Techniczne

Bulletin of the Polish Academy of Sciences Technical Sciences

Zawartość

Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | No. 1

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Abstrakt

Is the world’s power engineering at a crossroads? Will ongoing climate changes and rise of new technologies such as the Internet of Things (IoT), Smart City or e-mobility give us a completely different perspective on the world’s future energy? What are our actual visions and development forecasts in this matter? Who is right concerning this matter, large energy companies and some politicians, environmentalists, climate researchers and all kinds of visionaries? Is transformation based on solar energy and hydrogen a holy grail for the energy sector? The author of this article tries to find answers to these and many other questions. Today we can already accept as a proven thesis that rapid and dangerous climate changes for our civilisation can also be attributed to high carbon and low-efficient power engineering. Power engineering and climate neutrality are no longer just problems for politicians, companies, and scientists, but have become a challenge for our civilisation. If we are to save the Earth, our civilisation has to change its mentality and develop ideas that will not prioritise economic growth and high consumption but sustainable growth in harmony with nature. For this to happen, the way people think about energy and global transformation must also change. The foregoing general remarks, but also the fact that a gradual transition from traditional large-scale fossil fuel-based energy generation to distributed energy generation based on renewable resources is inevitable, constitute the main message of this article. The article also aims to discuss the role of the Institute of Fluid-Flow Machinery of the Polish Academy of Sciences (IMP PAN) in Gdańsk in the process of energy transformation in our country. The institute, as the coordinating entity of over a dozen of high-budgeted national and European projects in the field of environmentally-friendly power engineering, has contributed to some extent to the creation of conditions required for the development of prosumer power engineering (or more broadly: civic power engineering) in our country.

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Bibliografia

  1.  W. Steffen, et al., “Planetary boundaries: Guiding human development on a changing planet”, Science 347(6223), 1259855‒1, (2015).
  2.  Ch.H. Trisos, C. Merow, and A.L. Pigot, “The projected timing of abrupt ecological disruption from climate change”, Nature, 580, 496–501(2020).
  3. European Economic Congress Trends, Warszawa, 2020.
  4.  International Energy Agency, “World Energy Outlook”, 2013, 2014, 2015, 2016.
  5.  International Energy Agency, “Key World Energy Statistics”, 2015.
  6.  “Pictures of the Future”, Siemens, The Magazine for Research and Innovation, Fall (2009).
  7.  The energy future: how to provide energy after the depletion of fossil fuels? [Online]. www.futurenergia.org/ [in Polish].
  8.  The energy future. [Online]. www.shell.pl/ [in Polish].
  9.  Hawking warns: Doom awaits mankind. [Online]. www.rp.pl [in Polish].
  10.  Artificial intelligence for a billion dollars. [Online]. www.rp.pl [in Polish].
  11.  What will be the energy in the future? Exxon Mobil has given forecasts for 2040. [Online]. www.gazetaprawna.pl/ [in Polish].
  12.  Elon Musk predicts the world’s energy future. [Online]. http://www.odnawialnezrodlaenergii.pl [in Polish].
  13.  Distributed energy systems – on the way to low-carbon Poland, expert debate, Mariusz Wójcik. [Online]. http://www.chronmyklimat.pl/ [in Polish].
  14.  M. Nowicki, Dilemmas of the Polish energy sector. 01/2016 [Online]. www.csm.org.pl, [in Polish].
  15.  J. Rączka, M. Swora, and W. Stawiany, “Distributed generation in modern energy policy”, Materials of the forum Energy-Effect- Environment. [Online]. http://forumees.pl/ [in Polish].
  16.  IRENA International Renewable Energy Agency, Transforming the energy system – and holding the line on the rise of global temperatures, ISBN 978‒92‒9260‒149‒2, 2019. [Online]. www.irena.org/publications
  17.  Report: Global Commission on the Geopolitics, International Renewable Energy Agency IRENA, A New World. The Geopolitics of the Energy Transformation, January 2019, ISBN: 978-92-9260-097-6. [Online]. www.geopoliticsofrenewables.org
  18.  IRENA International Renewable Energy Agency, Global Energy Transformation. A Roadmap to 2050, 2019 edition, ISBN 978‒92‒9260‒121‒8. [Online]. www.irena.org/publications
  19.  IRENA International Renewable Energy Agency, Hydrogen: A renewable energy perspective, Tokyo, September 2019, ISBN: 978-92- 9260-151-5.
  20.  IRENA International Renewable Energy Agency, Off-grid renewable energy solutions to expand electricity access: An opportunity not to be missed, ISBN 978‒92‒9260‒101‒0, 2019.
  21.  T. Chmielniak, S. Lepszy, and P. Mońka, “Hydrogen energy – opportunities and barriers, Modern problems of thermodynamics”. Eds. T. Bury, A. Szlęk, Institute of Heat Engineering, Gliwice, 2017 [in Polish].
  22.  A. Cenian, J. Kiciński, P. Lampart, “New distributed sustainable prosumer power engineering”, Nowa Energia 6, 23–28 (2012) [in Polish].
  23.  A.Cenian, J.Kiciński, and P. Lampart, “Prosumer power engineering – a chance for the development of the domestic machine industry”, Czysta Energia 10 (2013) [in Polish].
  24.  A. Cenian, J. Kiciński, and P. Lampart, “Quo vadis power engineering? Why small and distributed is beautiful and rich?”, Czysta Energia 4, 30–31 (2012) [in Polish].
  25.  J. Kiciński, “Do we have a chance for small-scale energy generation? The examples of technologies and devices for distributed energy systems in micro & small scale in Poland”, Bull. Pol. Ac.: Tech. 61(4), 749‒756 (2013).
  26.  J. Kiciński and G. Żywica, “Prototype of the domestic CHP ORC energy system”, Bull. Pol. Ac.: Tech. 64(2), 417‒424 (2016).
  27.  J. Kiciński and G. Żywica, Steam Microturbines in Distributed Cogeneration, Springer, 2014.
  28.  A. Cenian, P. Lampart, K. Łapiński, and J. Kiciński, “Innovative eco-technologies for sustainable power engineering which are developed at IMP PAN in Gdańsk. Part I”, Przegląd Energetyczny 3, 36–39 (2015) [in Polish].
  29. J. Kiciński, “Examples of technologies and devices used in distributed energy systems based on energy produced from biomass and agricultural waste”, Nowa Energia 1, 119–122 (2014) [in Polish].
  30.  A. Cenian, M. Górski, and J. Kiciński, “Photovoltaics, biogas plants, biomass”, Przemysł Zarządzanie Środowisko, September-October 2011 [in Polish].
  31. J. Kiciński, A. Cenian, and K. Bogucka, “IMP PAN focuses on innovative solutions for the energy sector – we are discovering the potential of biogas”, Nasz Gdańsk, 11(112), 11–12 (2010), [in Polish].
  32.  J. Kiciński and P. Lampart, “Mini and micro CHP ORC power plants as a prospective form of implementation of renewable energy technologies in Poland”, Energetyka Cieplna i Zawodowa 6, 39–43 (2009), [in Polish].
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Autorzy i Afiliacje

Jan Kiciński
1

  1. Institute of Fluid Flow Machinery Polish Academy of Sciences, Fiszera 14, 80-231 Gdańsk, Poland
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Abstrakt

The effectiveness of lightning protection on the power and distribution grid is a significant factor, which influences the power distribution reliability and the failure rate of system elements. As part of this article, a mathematical model will be presented, taking into account selected parameters that affect the assessment of the lightning hazard of an overhead line. The proposed model will consider the location of the object near the line and the adjustment of line conductor overhangs. Moreover, the mentioned mathematical model allows for analyzing the impact of considered parameters on the protection level of the power system, and transient overvoltages that occur in this system. The article contains also a detailed description of an effective and fast method to assess the lightning discharge impact on the power system with insufficient data. The introduced model was tested to verify the correctness of its operation by comparison of calculation results and functional data. High convergence of calculated and functional data and uncomplicated model structure ensure a wide range of applications for the proposed solution to easily prevent emergency situations in the power system. Furthermore, the described model gives the opportunity to assess the reduction of the range of selectivity zone associated with the power line, in conjunction with the impact of constructional peculiarities and a near object.

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Bibliografia

  1.  J.L. He and R. Zeng, “Lightning shielding failure analysis of 1000 kV ultra-high voltage AC transmission line”, Proc. CIGRE Session, 2010, pp. 1‒9.
  2.  A. Borghetti, G. Martinez Figueiredo Ferraz, F. Napolitano, C.A. Nucci, A. Piantini, and F. Tossani, “Lightning protection of a multi- circuit HV-MV overhead line”, Electr. Power Syst. Res. 180, 1‒10 (2020).
  3.  A. Murphy, “Lightning strike direct effects”, Polymer Composites in the Aerospace Industry, 2nd Edition, Woodhead Publishing, 2020.
  4.  G. Shanqiang, W. Jian, W. Min, G. Juntian, Z. Chun, and L. Jian, “Study on lightning risk assessment and early warning for UHV DC transmission channel”, High Voltage 4(2), 144‒150 (2019).
  5.  R.G. Deshagoni, T. Auditore, R. Rayudu, and C.P. Moore, “Factors Determining the Effectiveness of a Wind Turbine Generator Lightning Protection System”, IEEE Trans. Ind. Appl 55(6), 6585‒6592 (2019).
  6.  J. Bendík, et al., “Experimental verification of material coefficient defining separation distance for external lightning protection system”, J. Electrostat. 98, 69‒74 (2019).
  7.  K. I. Pruslin, “Organization for increasing lightning resistance of overvoltage lines PJSC “FGC UES””, VI Russian Conference on Lightning Protection, 2018, pp. 1‒24.
  8.  G. E. Masin, “Indicators of lightning resistance of power facilities of Kubanenergo PJSC and measures to increase them”, VI Russian Conference on Lightning Protection, 2018, pp. 1‒9.
  9.  A. Andreotti, A. Pierno, and V.A. Rakov, “A new tool for calculation of lightning-induced voltages in power systems – ”Part I: Development of circuit model”, IEEE Trans. Power Del. 30(1), 326‒333 (2015).
  10.  C. Wooi, Z. Abul-Malek, M. Rohani, A. Yusof, S. Arshad, and A. Elgayar, “Comparison of lightning return stroke channel-base current models with measured lightning current”, Bull. EEI 8(4), 1478‒1488(2019).
  11.  T.H. Thang, Y. Baba, V.A. Rakov, and A. Piantini, “FDTD computation of lightning-induced voltages on multi-conductor lines with surge arresters and pole transformers”, IEEE Trans. Electromagn. Compat. 57(3), 442‒447(2015).
  12.  M. Brignone, F. Delfino, R. Procopio, M. Rossi, and F. Rachidi, “Evaluation of power system lightning performance Part I: Model and numerical solution using the PSCAD-EMTDC platform”, IEEE Trans. Electromagn. Compat. 59(1), 137‒145 (2017).
  13.  M.E.M. Rizk et al., “Protection Against Lightning-Induced Voltages: Transient Model for Points of Discontinuity on Multiconductor Overhead Line”, IEEE Trans. Electromagn. Compat. 62(4), 1209‒1218 (2020), doi: 10.1109/TEMC.2019.2940535.
  14.  J. Zhang et al., “Evaluation of the Lightning-Induced Voltages of Multiconductor Lines for Striking Cone-Shaped Mountain, ” IEEE Trans. Electromagn. Compat. 61(5), 1534‒1542 (2019).
  15.  Q. Li et al., “On the influence of the soil stratification and frequency-dependent parameters on lightning electromagnetic fields”, Electr. Power Syst. Res. 178, 1‒10(2020).
  16.  E. Soto and E. Perez, “Lightning-induced voltages on overhead lines over irregular terrains”, Electr. Power Syst. Res. 176, 105941 (2019).
  17.  M. Brignone, D. Mestriner, R. Procopio, M. Rossi, and F. Rachidi, “Evaluation of the mitigation effect of shield wires on lightning-induced overvoltages in MV distribution systems using statistical analysis”, IEEE Trans. Electromagn. Compat. 60(5), 1‒10 (2018).
  18.  M.R. Bank Tavakoli and B. Vahidi, “Shielding failure rate calculation by means of downward and upward lightning leader movement models: Effect of environmental conditions”, J. Electrostat. 68, 275‒283 (2010).
  19.  Y. Xu and M. Chen, “Striking Distance Calculation for Flat Ground and Lightning Rod by a 3D Self-Organized Leader Propagation Model”, Intern. Conf. on Lightning Protection, Vienna, Austria, 2012.
  20.  V. Cooray, C.A. Nucci, and F. Rachidi, “On the Possible Variation of the Lightning Striking Distance as Defined in the IEC Lightning Protection Standard as a Function of Structure Height”. Intern. Conf. on Lightning Protection, Vienna, Austria, 2012.
  21.  M.E.M. Rizk and G.N. Trinh, High voltage engineering, p. 804, Taylor and Francis Group, LLC, 2014.
  22.  Lightning protection guide. Dehn + Sohne GmbH + Co.KG., Germany, 2007/2012.
  23.  S. Takatoshi, “Lightning striking characteristics to tall structures”, IEEJ Trans. Electr. Electron. Eng. 13, 938‒947 (2017).
  24.  P.N. Mikropoulos and T.E. Tsovilis, “Striking Distance and Interception Probability, ” IEEE Trans. Power Delivery 23(3), 1571‒1580 (2008).
  25.  Y. Xie, M. Dong, H. He, J. He, H. Cai, and X. Chen, “A new tool for lightning performance assessment of overhead transmission lines”, Proc. 7th Asia-Pacific Int. Conf. Light., 2011, pp. 513‒519.
  26.  D. Spalek, “Proposal of the criterion for transmission line lumped parameters analysis”, Bull. Pol. Ac.: Tech. 67(6), 1181‒1186 (2019).
  27.  G. Benysek, M.P. Kazmierkowski, J. Popczyk, and R. Strzelecki, “Power electronic systems as a crucial part of Smart Grid infrastructure – a survey”, Bull. Pol. Ac.: Tech. 59(4), 455‒473 (2011).
  28.  S. Robak and R.M. Raczkowski, “Substations for offshore wind farms: a review from the perspective of the needs of the Polish wind energy”, Bull. Pol. Ac.: Tech. 66(4), 517‒528 (2018).
  29.  M. Borecki and J. Starzyński, “Selected Aspects of Numerical Models and Cost Comparison Analysis of Surge Protection Device”, Progress in Applied Electrical Engineering (PAEE), Poland, 2019, pp. 1‒4.
  30.  M. Borecki, M. Ciuba, Y. Kharchenko, and Y. Khanas, “Substation reliability evaluation in the context of the stability prediction of power grids”, Bull. Pol. Ac.: Tech. 68(4), 769‒776 (2020).
  31.  M. Borecki, “A Proposed New Approach for the Assessment of Selected Operating Conditions of the High Voltage Cable Line”, Energies 13, 5275(1‒15) (2020).
  32.  Z. Flisowski, Calculation of atmospheric surges in power lines based on antenna wave theory. Electrotechnical Dissertations, Volume XV, Z.1, pp. 177‒194, 1968.
  33.  M. Borecki, Analysis of atmospheric overvoltages protection of medium voltage overhead lines with covered conductors, pp. 1‒128, Warszawa, Wyd. P.W. 2017.
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Autorzy i Afiliacje

Michał Borecki
1
ORCID: ORCID
Maciej Ciuba
1
Yevhen Kharchenko
2 3
Yuriy Khanas
3

  1. Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland
  2. University of Warmia and Mazury in Olsztyn, ul. M. Oczapowskiego 2, 10-719 Olsztyn, Poland
  3. Lviv Polytechnic National University, ul. S. Bandery St 12, 79000 Lviv, Ukraine
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Abstrakt

In this paper, a novel Power-Frequency Droop Control (PFDC) is introduced to perfectly bring back the system frequency and share the reactive power in isolated microgrid with virtual power plant (VPP). The frequency-based power delivery must be essentially implemented in VPP which can operate as a conventional synchronous generator. It has been attained by enhancing the power processing unit of each VPP to operate as an active generator. The inverter coupling impedance which has been assigned by the virtual impedance technique has reduced the affected power coupling resulting from line resistance. The reference has been subsequently adjusted to compensate the frequency deviation caused by load variation and retrieve the VPP frequency to its nominal value. In addition, the line voltage drop has compensated the voltage drop and load sharing error to obliterate the reactive power sharing imprecision resulting from the voltage deviation. The voltage feedback confirms the correct voltage after compensating the voltage drop. As an illustration, conventional PFDC after a load change cannot restore the system frequency which is deviated from 50 Hz and rested in 49.9 Hz while, proposed PFDC strategy fades away the frequency deviation via compensating the variation of the frequency reference. Likewise, the frequency restoration factor ( γ) has an effective role in retrieving the system frequency, i.e., the restoration rate of the system frequency is in proportion with γ. As a whole, the simulation results have pointed to the high performance of proposed strategy in an isolated microgrid.
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Bibliografia

  1.  G.U. Atmo, C.F. Duffield, and D. Wilson, “Structuring procurement to improve sustainability outcomes of power plant projects”, Energy Technol. Policy 2(1), 47‒57 (2015).
  2.  P. Kumar, P.S. Sikder, and N. Pal, “Biomass fuel cell based distributed generation system for Sagar Island”, Bull. Pol. Ac.: Tech. 66(5), 665‒674 (2018).
  3.  M. Wieczorek, M. Lewandowski, and W. Jefimowski, “Cost comparison of different configurations of a hybrid energy storage system with battery-only and supercapacitor-only storage in an electric city bus”, Bull. Pol. Ac.: Tech. 44(6), 1095‒1106 (2019).
  4.  W. Marańda and M. Piotrowicz, “Efficiency of maximum power point tracking in photovoltaic system under variable solar irradiance”, Bull. Pol. Ac.: Tech. 62(4), 713‒721 (2014).
  5.  U. Akram, M. Khalid, and S. Shafiq, “An innovative hybrid wind-solar and battery-supercapacitor microgrid system-development and optimization”, IEEE Access 5(10), 25897‒25912 (2017).
  6.  M.A. Hannan, M.G.M. Abdolrasol, M. Faisal, P.J. Ker, R.A. Begum, and A. Hussain, “Binary particle swarm optimization for scheduling MG integrated virtual power plant toward energy saving”, IEEE Access 7(6), 107937‒07951 (2019).
  7.  T. Wu, Z. Liu, and J. Liu, “A unified virtual power decoupling method for droop-controlled parallel inverters in microgrids”, IEEE Trans. Power Electron. 31(8), 5587‒5603 (2016).
  8.  F. Shahnia and A. Ghosh, “Coupling of neighbouring low voltage residential distribution feeders for voltage profile improvement using power electronics converters”, IET Renew. Power Gener. 10(2), 535‒547 (2016).
  9.  X. Tang, X. Hu, and N. Li, “A novel frequency and voltage control method for islanded based on multienergy storages”, IEEE Trans. Smart Grid 7(1), 410‒419 (2016).
  10.  H. Zhang, S. Kim, Q. Sun, and J. Zhou, “Distributed adaptive virtual impedance control for accurate reactive power sharing based on consensus control in microgrids”, IEEE Trans. Smart Grid 8(4), 1749‒1761 (2017).
  11.  M. Eskandari and L. Li, “Microgrid Operation Improvement by Adaptive Virtual Impedance”, IET Renew. Power Gener. 13(2), 296‒307 (2018).
  12.  Z.A. Obaid, L.M. Cipcigan, L. Abrahim, and M.T. Muhsin, “Frequency control of future power systems: reviewing and evaluating challenges and new control methods”, J. Mod. Power Syst. Clean Energy 7(1), 9‒25 (2019).
  13.  R.M. Imran, S. Wang, and F.M.F. Flaih, “DQ-Voltage droop control and robust secondary restoration with eligibility to operate during communication failure in autonomous microgrid”, IEEE Access 7(12), 6353‒6361 (2019).
  14.  N.N. AbuBakar, M.Y. Hassan, M.F. Sulaima, M. Na’im, M. Nasir and A. Khamisd, “Microgrid and load shedding scheme during islanded mode: A review”, Renewable Sustainable Energy Rev., 71(6), 161‒169 (2017).
  15.  T.A. Jumani, M.W. Mustafa, M.M. Rasid, N.H. Mirjat, Z.H. Leghari, and M.S. Saeed, “Optimal Voltage and Frequency Control of an Islanded Microgrid Using Grasshopper Optimization Algorithm”, Energies 11(11), 1‒20 (2018).
  16.  Y. Han, P. Shen, and X. Zhao, “An enhanced power sharing scheme for voltage unbalance and harmonics compensation in an islanded AC microgrid”, IEEE Trans. Energy Convers. 31(3), 1037‒1050 (2016).
  17.  M. Kosari and S.H. Hosseinian, “Decentralized reactive power sharing and frequency restoration in islanded microgrid”, IEEE Trans. Power Syst. 32(4), 2901‒2912 (2017).
  18.  Y.A. Mohamed and E.F. El-Saadany, “Adaptive decentralized droop controller to preserve power sharing stability of paralleled inverters in distributed generation microgrids”, IEEE Trans. Power Electron. 23(6), 2806‒2816 (2008).
  19.  X. Hou, Y. Sun, H. Han, Z. Liu, W. Yuan, and M. Su, “A fully decentralized control of grid-connected cascaded inverters”, IEEE Trans. Power Deliv. 10(1), 315‒317 (2019).
  20.  L. Li, Y. Sun, Z. Liu, X. Hou, G. Shi, and M. Su, “A decentralized control with unique equilibrium point for cascaded-type microgrid”, IEEE Trans. Sustain. Energy 10(1), 324‒326 (2019).
  21.  F. Guo, C. Wen, and J. Mao, “Distributed secondary voltage and frequency restoration control of droop-con-trolled inverter-based microgrids”, IEEE Trans. Ind. Electron. 62(7), 4355‒4364 (2015).
  22.  S. Zuo, A. Davoudi, and Y. Song, “Distributed finite-time voltage and frequency restoration in islanded AC microgrids”, IEEE Trans. Ind. Electron. 63(10), 5988‒5997 (2016).
  23.  C. Dou, Z. Zhang, and D. Yu, “MAS-based hierarchical distributed coordinate control strategy of virtual power source voltage in low- voltage microgrid”, IEEE Access 5(1), 11381‒11390 (2017).
  24.  N.M. Dehkordi, N. Sadati, and M. Hamzeh, “Distributed robust finite-time secondary voltage and frequency control of islanded microgrids”, IEEE Trans. Power Syst., 32(5), 3648‒3659 (2017).
  25.  N.M. Dehkordi, N. Sadati, and M. Hamzeh, “Fully distributed cooperative secondary frequency and voltage control of islanded microgrids”, IEEE Trans. Energy Convers. 32(2), 675‒685 (2017).
  26.  D.O. Amoateng, M.A. Hosani, and M.S. Elmoursi, “Adaptive voltage and frequency control of islanded multi-microgrids”, IEEE Trans. Power Syst. 33(4), 4454‒4465 (2018).
  27.  Q. Shafiee, J.M. Guerrero, and J.C. Vasquez, “Distributed secondary control for islanded microgrids-a novel approach”, IEEE Trans. Power Electron. 29(2), 1018‒1031 (2014).
  28.  U. Sowmmiya and U. Govindarajan, “Control and power transfer operation of WRIG-based WECS in a hybrid AC/DC microgrid”, IET Renewable Power Gener. 12(3), 359‒373 (2018).
  29.  Z. Zhang, C. Dou, and D. Yu, “An event-triggered secondary control strategy with network delay in islanded microgrids”, IEEE Syst. J. 13(2), 1851‒1860 (2019).
  30.  J. He and Y. Li, “An enhanced microgrid load demand sharing strategy”, IEEE Trans. Power Electron. 27(9), 3984‒3995 (2012).
  31.  Y. Fan, G. Hu, and M. Egerstedt, “Distributed reactive power sharing control for microgrids with event-triggered communication”, IEEE Trans. Control Syst. Technol. 25(1), 118‒128 (2017).
  32.  X. Lu. J. Lai, and X. Yu, “Distributed coordination of islanded microgrid clusters using a two-layer intermittent communication network”, IEEE Trans. Ind. Inf. 14(9), 3956‒3969 (2018).
  33.  X. Wu, C. Shen, and R. Iravani, “A distributed, cooperative frequency and voltage control for microgrids”, IEEE Trans. Smart Grid, 9(4), 2764‒2776 (2018).
  34.  G. Lou, W. Gu, and L. Wang, “Decentralized secondary voltage and frequency control scheme for islanded microgrid based on adaptive state estimator”, IET Gener. Transm. Distrib., 11(15), 3683‒3693 (2017).
  35.  B. Wang, S. Liu, and Y. Zhang, “Reactive power sharing control based on voltage compensation strategy in microgrid”, 36th Chinese Control Conference (2017).
  36.  H.E.Z. Farag, S. Saxena, and A. Asif, “A robust dynamic state estimation for droop controlled islanded microgrids”, Electr. Power Syst. Res. 140(11), 445‒455 (2016).
  37.  K. Sabzevari, S. Karimi, F. Khosravi, and H. Abdi, “Modified droop control for improving adaptive virtual impedance strategy for parallel distributed generation units in islanded microgrids, Int. Trans. Electr. Energy Syst., 29(1), e2689 (2019).
  38.  C. Dou, Z. Zhang, D. Yue, and M. Song, “Improved droop control based on virtual impedance and virtual power source in low-voltage microgrid”, IET Gener. Transm. Distrib. 11(4), 1046‒1054 (2017).
  39.  P.K. Ray, N. Kishor, and S.R. Mohanty, “Islanding and power quality disturbance detection in grid-connected hybrid power system using wavelet and S-transform”, IEEE Trans. Smart Grid, 3(3), 1082‒1094 (2012).
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Autorzy i Afiliacje

Amir Khanjanzadeh
1
Soodabeh Soleymani
1
Babak Mozafari
1

  1. Electrical and Computer Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran
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Abstrakt

This paper is focusing on 3D Finite Elements Analysis (FEA) based modelling of protrusions as defects or imperfections in the XLPE high voltage cable. This study is aiming to examine the impact, protrusions have on the initiation of partial discharges. Spherical and ellipsoidal protrusions with different sizes at the conductor screen of the high voltage cable is an essential content of this paper. In addition, a spherical gas-filled void is placed inside and outside the protrusions, and a water tree produced from protrusions is under consideration. The partial discharge influence taking place at the protrusions and the stress enhancement factor is determined for all the variations mentioned to quantify the rise in the inception of partial discharges due to the protrusions.

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Bibliografia

  1.  S.M.S. Tohid Shahsavarian, “Modelling of aged cavities for partial discharge in power cable insulation”, IET Sci. Meas. Technol. 9(6), 661–670, 2015.
  2.  M.A. Saleh and S.S. Refaat, “The Impact of Water Trees and Cavities on the Electric Field Distribution in XLPE Power Cables”, in 2019 2nd International Conference on Smart Grid and Renewable Energy (SGRE), Doha, Qatar, 2019, pp. 1‒8.
  3.  N. Hampton, “Chapter 3: HV and EHV Cable System Aging and Testing Issues”, National Electric Energy Testing, Research and Applications Center, no. Feb. pp. 1–19, 2016.
  4.  T.L. Hanley, R.P. Burford, R.J. Fleming, and K.W. Barber, “A general review of polymeric insulation for use in HVDC cables”, in IEEE Electr. Insul. Mag. 19(1), 13‒24, (2003).
  5.  W. Guoming and G.-S. Kil, “Measurement and Analysis of Partial Discharge Using an Ultra-High Frequency Sensor for Gas Insulated Structures”, Metrol. Meas. Syst. 24 (3), 515–524 (2017).
  6.  K.Ch. Kao, “Electrical Aging, Discharge, and Breakdown Phenomena”, in Dielectric Phenomena in Solids, Ed(s): Kwan Chi Kao, pp. 515‒572, Academic Press, 2004.
  7.  J. Vedral and M. Kříž. “Signal Processing in Partial Discharge Measurement.” Metrol. Meas. Syst. XVII (1), 55−64 (2010).
  8.  S. Gutierrez, I. Sancho, L. Fontan, and J. D. No, “Effect of protrusions in HVDC cables”, in IEEE Trans. Dielectr. Electr. Insul. 19(5), 1774‒1781 (2012).
  9.  M.S. Amir and S.M.H. Hosseini, “Comparison of aged XLPE power cables restoration by injecting two various anti-failure nanofluids”, Eng. Failure Anal. 90, 262‒276 (2018).
  10.  L. Andrei, I. Vlad, and F. Ciuprina, “Electric field distribution in power cable insulation affected by various defects”, in 2014 International Symposium on Fundamentals of Electrical Engineering (ISFEE), Bucharest, 2014, pp. 1‒5.
  11.  P.H.F. Morshuis, “Degradation of solid dielectrics due to internal partial discharge: Some thoughts on progress made and where to go now”, IEEE Trans. Dielectr. Electr. Insul. 12(5), 905‒913 (2005).
  12.  P. Notingher, S. Holé, L. Berquez, and G.Teyssedre, “An Insight into Space Charge Measurements”, Int. J. Plasma Environ. Sci. Technol. 11, 26‒37 (2017).
  13.  D.A. do Nascimento, S.S. Refaat, A. Darwish, Q. Khan, H. Abu-Rub, and Y. Iano, “Investigation of Void Size and Location on Partial Discharge Activity in High Voltage XLPE Cable Insulation”, in 2019 Workshop on Communication Networks and Power Systems (WCNPS), Brasilia, Brazil, 2019, pp. 1‒6.
  14.  Z. Lei, J. Song, M. Tian, X. Cui, C. Li, and M. Wen, “Partial discharges of cavities in ethylene propylene rubber insulation”, IEEE Trans. Dielectr. Electr. Insul. 21(4), 1647‒1659 (2014).
  15.  M. Mahdipour, A. Akbari, and P. Werle, “Charge concept in partial discharge in power cables”, IEEE Trans. Dielectr. Electr. Insul. 24(2), 817–825 (2017).
  16.  D. He, W. Wang, J. Lu, G. Teyssedre, and C. Laurent, “Space charge characteristics of power cables under AC stress and temperature gradients”, IEEE Trans. Dielectr. Electr. Insul. 23(4), 2404‒2412 (2016).
  17.  M. Fu, L.A. Dissado, G. Chen, and J.C. Fothergill, “Space charge formation and its modified electric field under applied voltage reversal and temperature gradient in XLPE cable”, IEEE Trans. Dielectr. Electr. Insul. 15(3), 851‒860 (2008).
  18.  R. Ross, “Inception and propagation mechanisms of water treeing”, IEEE Trans. Dielectr. Electr. Insul. 5(5), 660‒680, (1998).
  19.  T. Boonraksa and B. Marungsri, “Role of Ionic Solutions Affect Water Treeing Propagation in XLPE Insulation for High Voltage Cable”, Int. J. Electr. Comput. Eng. 8(5) 795‒798 (2014).
  20.  G. Callender, Modelling Partial Discharge in Gaseous Voids by George Callender, University of Southampton, 2018.
  21.  G. Callender, P. Rapisarda, and P.L. Lewin, “Improving models of partial discharge activity using simulation”, in 2017 IEEE Electr. Insul. Conf. EIC 2017, 2017, pp. 392–395.
  22.  X. Zhou, J. Cao, S. Wang, Y. Jiang, T. Li, and Y. Zou, “Simulation of electric field around typical defects in 110kV XLPE power cable joints”, in 2017 International Conference on Circuits, Devices and Systems (ICCDS), Chengdu, 2017, pp. 21‒24.
  23.  L. Andrei, I. Vlad, and F. Ciuprina, “Electric field distribution in power cable insulation affected by water trees”, in 2015 9th International Symposium on Advanced Topics in Electrical Engineering (ATEE), Bucharest, 2015, pp. 426‒429.
  24.  S. Gutiérrez, I. Sancho, L. Fontán, and M. Martínez-Iturralde, “Influence of irregularities within electric fields in high voltage cables”, in 2011 Annual Report Conference on Electrical Insulation and Dielectric Phenomena, Cancun, 2011, pp. 752‒755.
  25.  S. Nakamura, T. Ozaki, N. Ito, I. Sengoku, J. Kawai “Dynamic behavior of interconnected channels in water-treed polyethylene subjected to high voltage”, IEEE Trans. Dielectr. Electr. Insul. 9, 390‒395 (2002).
  26.  T. Toyoda, S. Mukai, Y. Ohki, Y. Li, and T. Maeno, “Conductivity and permittivity of water tree in polyethylene”, in 1999 Annual Report Conference on Electrical Insulation and Dielectric Phenomena (Cat. No.99CH36319), Austin, TX, USA, 1999, 577‒580, vol. 2.
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Autorzy i Afiliacje

Mohammad AlShaikh Saleh
1 2
Shady S. Refaat
2
Marek Olesz
3
Haitham Abu-Rub
2
Jarosław Guziński
3

  1. Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany
  2. Department of Electrical and Computer Engineering, Texas A&M University at Qatar
  3. Departement of Electrical Engineering, Gdansk University of Technology, ul. Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland
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Abstrakt

The paper presents a multi-phase doubly fed induction machine operating as a DC voltage generator. The machine consists of a six-phase stator circuit and a three-phase rotor circuit. Two three-phase six-pulse diode rectifiers are connected to each three-phase machine section on the stator side and in parallel to the common DC circuit feeding the isolated load. The same DC bus is also common for the rotor side power electronics converter responsible for machine control. Two methods – direct torque control DTC and field oriented control FOC – were implemented for machine control and compared by means of simulation tests. Field oriented control was implemented in the laboratory test bench.

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Bibliografia

  1.  G.D. Marques, D. Sousa, and M. F. Iacchetti, “Sensorless torque control of a DFIG connected to a DC link”, IEEE Int. Symp. on Sensorless Control for Electrical Drives and Predictive Control of Electrical Drives and Power Electronics – SLED/PRECEDE’13, Munich, Germany, 2013, pp. 1‒7.
  2.  M.F. Iacchetti and G.D. Marques, “Enhanced torque control in a DFIG connected to a DC grid by a diode rectifier”, 16th Europ. Conf. Power Electron. and Appl. – EPE’14, Lappeenranta, Finland, 1‒9 (2014).
  3.  G.D. Marques and M.F. Iacchetti, “A self-sensing stator-current-based control system of a DFIG connected to a DC-link”, IEEE Trans. Ind. Electron. 62(10), 6140–6150 (2015).
  4.  Y. Li, et al, “The capacity optimization for the static excitation controller of the dual-stator-winding induction generator operating in a wide speed range”, IEEE Trans. Ind. Electron. 56(2), 530–541 (2009).
  5.  H. Misra, A. Gundavarapu, and A.K. Jain, “Control scheme for DC voltage regulation of stand-alone DFIG-DC system”, IEEE Trans. Ind. Electron. 64(4), 2700–2708 (2017).
  6.  N. Yu, H. Nian, and Y. Quan, “A novel DC grid connected DFIG system with active power filter based on predictive current control”, Int. Conf. Electr. Machines and Systems – ICEMS’11, Beijing, China, 2011, pp. 1–5.
  7.  M.F. Iacchetti, G.D. Marques, and R. Perini, “Torque ripple reduction in a DFIG-DC system by resonant current controllers”, IEEE Trans. Power Electron. 30(8), 4244–4254 (2015).
  8.  C. Wu and H. Nian, “Improved direct resonant control for suppressing torque ripple and reducing harmonic current losses of dfig-dc system”, IEEE Trans. Power Electron. 34(9), 8739–8748 (2019).
  9.  C. Wu, et al, “Adaptive repetitive control of DFIG-DC system considering stator frequency variation”, IEEE Trans. Power Electron. 34(4), 3302‒3312 (2018).
  10.  A. Gundavarapu, H. Misra, and A. K. Jain, “Direct torque control scheme for dc voltage regulation of the standalone DFIG-DC system”, IEEE Trans. Ind. Electron. 64(5), 3502–3512 (2017).
  11.  P. Maciejewski and G. Iwanski, “Direct torque control for autonomous doubly fed induction machine based DC generator”, 12th Int. Conf. Ecological Vehicles and Renewable Energies – EVER’17, Monte Carlo, Monaco, 2017, pp. 1–6.
  12.  P. Maciejewski and G. Iwanski, “Study on direct torque control methods of a doubly fed induction machine working as a stand-alone DC voltage generator”, IEEE Trans. Energy Conv. (to be published), doi: 10.1109/TEC.2020.3012589.
  13.  M. Gwóźdź et al, “Generator with modulated magnetic flux for wind turbines”, Bull. Pol. Ac.: Tech. 65(4), 469–478 (2017).
  14.  E. Levi, et al, “Multiphase induction motor drives – a technology status review”, IET Electric Power Applications 1(4), 489–516 (2007).
  15.  F. Bu, Y. Hu, W. Huang, S. Zhuang, and K. Shi, “Wide-speed-range-operation dual stator-winding induction generator DC generating system for wind power applications”, IEEE Trans. Power Electron. 30(2), 561–573 (2015).
  16.  B. Zhang et al., “Comparison of 3-, 5-, and 6-phase machines for automotive charging applications”, IEEE Int .Electric Machines and Drives Conf. 3, 1357–1362 (2003).
  17.  K.S. Khan, W.M. Arshad, and S. Kanerva, “On performance figures of multiphase machines”, 18th Int. Conf. Electr. Machines – ICELMACH’08, Vilamoura, Portugal, 2008, pp. 1‒5.
  18.  S. Williamson and S. Smith, “Pulsating torque and losses in multiphase induction machines”, IEEE Trans. Ind. Appl. 39(4), 986–993 (2003).
  19.  P.G. Holmes and N.A. Elsonbaty, “Cycloconvertor-excited divided-winding doubly-fed machine as a wind-power convertor”, IEE Proc. B Electr. Power Appl. 131(2), 61–69 (1984).
  20.  P. Maciejewski and G. Iwanski, “Modeling of six-phase double fed induction machine for autonomous DC voltage generation”, 10th Int. Conf. Ecological Vehicles and Renewable Energies – EVER’15, Monte Carlo, Monaco, 2015, pp. 1–6.
  21.  G.D. Marques and M.F. Iacchetti, “DFIG topologies for DC networks: a review on control and design features”, IEEE Trans. Power Electron. 34(2), 1299‒1316 (2019).
  22.  N.K. Mishra, Z. Husain, and M. Rizwan Khan, “DQ reference frames for the simulation of multiphase (six phase) wound rotor induction generator driven by a wind turbine for disperse generation”, Electr. Power Appl. IET, 13(11), 1823‒1834, (2019).
  23.  R. Bojoi, et al, “Dual-three phase induction machine drives control; A survey”, IEEJ Trans. Ind. Appl. 126(4), 420–429 (2006).
  24.  R. Nelson and P. Krause, “Induction machine analysis for arbitrary displacement between multiple winding sets”, IEEE Trans. Power Appar. Syst. 93(3), 841–848 (1974).
  25.  D. Forchetti, G. García, and M.I. Valla, “Vector control strategy for a doubly-fed stand-alone induction generator”, Ind. Electron. Conf. – IECON’12, Montreal, Canada, 2, 2002, pp. 991–995.
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Autorzy i Afiliacje

Paweł Maciejewski
1
Grzegorz Iwański
1

  1. Warsaw University of Technology, Institute of Control and Industrial Electronics, 75, Koszykowa St., 00-662 Warszawa, Poland
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Abstrakt

The purpose of this paper is to propose a model of a novel quasi-resonant boost converter with a tapped inductor. This converter combines the advantages of zero voltage quasi-resonant techniques and different conduction modes with the possibility of obtaining a high voltage conversion ratio by using a tapped inductor, which results in high converter efficiency and soft switching in the whole output power range. The paper contains an analysis of converter operation, a determination of voltage conversion ratio and the maximum voltage across power semiconductor switches as well as a discussion of control methods in discontinuous, critical, and continuous conduction modes. In order to verify the novelty of the proposed converter, a laboratory prototype of 300 W power was built. The highest efficiency η  = 94.7% was measured with the output power Po =  260 W and the input voltage Vin = 50 V. The lowest efficiency of 90.7% was obtained for the input voltage Vin  = 30 V and the output power Po = 75 W. The model was tested at input voltages (30–50) V, output voltage 380 V and maximum switching frequency 100 kHz.

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Bibliografia

  1.  M. Forouzesh, Y.P. Siwakoti, S.A. Gorji, F. Blaabjerg, and B. Lehman, “Step-Up DC-DC Converters: A Comprehensive Review of Voltage-Boosting Techniques, Topologies, and Applications”, IEEE Trans. Power Electron. 32(12), 9143‒9178 (2017), doi: 10.1109/ TPEL.2017.2652318.
  2.  W. Li and X. He, “Review of Nonisolated High-Step-Up DC/DC Converters in Photovoltaic Grid-Connected Applications”, IEEE Trans. Ind. Electron. 58(4), 1239‒1250 (2011), doi: 10.1109/TIE.2010.2049715.
  3.  H. Liu, H. Hu, H. Wu, Y. Xing, and I. Batarseh, “Overview of High-Step-Up Coupled-Inductor Boost Converters”, IEEE IEEE J. Emerg. Sel. Top. Power Electron. 4(2), 689‒704 (2016), doi: 10.1109/JESTPE.2016.2532930.
  4.  A. Tomaszuk and A. Krupa, “High efficiency high step-up DC/DC converters – a review”, Bull. Pol. Ac.: Tech. 59(4), 475‒483 (2011), doi: 10.2478/v10175-011-0059-1.
  5.  W. Janke, M. Bączek, and J. Kraśniewski, “Input characteristics of a non-ideal DC-DC flyback converter”, Bull. Pol. Ac.: Tech. 67(5), 841‒849 (2019), doi: 10.24425/bpasts.2019.130884.
  6.  F.C. Lee, “High-frequency quasi-resonant converter technologies”, Proc. IEEE 76(4), 377‒390 (1988), doi: 10.1109/5.4424.
  7.  W.A. Tabisz, P.M. Gradzki, and F.C.Y. Lee, “Zero-voltage-switched quasi-resonant buck and flyback converters-experimental results at 10 MHz”, IEEE Trans. Power Electron. 4(2), 194‒204, 1989, doi: 10.1109/63.24904.
  8.  M. Harasimczuk and A. Borchert, “Single switch quasi-resonant ZVS converter with tapped inductor”, Prz. Elektrotechniczny 3, 44‒48 (2018).
  9.  S. Sathyan, H.M. Suryawanshi, M.S. Ballal, and A.B. Shitole, “Soft-Switching DC-DC Converter for Distributed Energy Sources With High Step-Up Voltage Capability”, IEEE Trans. Ind. Electron. 62(11), 7039‒7050 (2015), doi: 10.1109/TIE.2015.2448515.
  10.  T.F. Wu, Y.S. Lai, J.C. Hung, and Y.M. Chen, “Boost Converter With Coupled Inductors and Buck-Boost Type of Active Clamp”, IEEE Trans. Ind. Electron. 55(1), 154‒162 (2008), doi: 10.1109/TIE.2007.903925.
  11.  J.H. Yi, W. Choi, and B.H. Cho, “Zero-Voltage-Transition Interleaved Boost Converter With an Auxiliary Coupled Inductor”, IEEE Trans. Power Electron. 32(8), 5917‒5930 (2017), doi: 10.1109/TPEL.2016.2614843.
  12.  Y. Chen, Z. Li, and R. Liang, “A Novel Soft-Switching Interleaved Coupled-Inductor Boost Converter With Only Single Auxiliary Circuit”, IEEE Trans. Power Electron. 33(3), 2267‒2281 (2018), doi: 10.1109/TPEL.2017.2692998.
  13.  R. Stala et al., “A family of high-power multilevel switched capacitor-based resonant DC-DC converters – operational parameters and novel concepts of topologies”, Bull. Pol. Ac.: Tech. 65(5), 639‒651 (2017).
  14.  M. Harasimczuk, “A QR-ZCS Boost Converter With Tapped Inductor and Active Edge-Resonant Cell”, IEEE Trans. Power Electron. 35(12), 13085‒13095 (2020), doi: 10.1109/TPEL.2020.2991363.
  15.  M. Harasimczuk, “Przekształtniki podwyższające napięcie z dławikami dzielonymi”, PL Patent, Poland, P.423354, 2017.
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Autorzy i Afiliacje

Jakub Dawidziuk
1
ORCID: ORCID
Michał Harasimczuk
2
ORCID: ORCID

  1. Department of Automatic Control and Robotics, Bialystok University of Technology, ul. Wiejska 45D, 15-351 Bialystok, Poland
  2. Department of Electrical Engineering, Power Electronics and Electrical Power Engineering, Bialystok University of Technology, ul. Wiejska 45D, 15-351 Bialystok, Poland
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Abstrakt

The paper presents an analytical solution of levitation problem for conductive, dielectric and magnetically anisotropic ball. The levitation exerts either an AC or impulse magnetic field. Both the Lorentz and material electromagnetic forces (of magnetic matter) could lift the ball in a gravitational field. The electromagnetic field distribution is derived by means of variables separation method. The total force is evaluated by Maxwell stress tensor (generalized), co-energy and Lorentz methods. Additionally, power losses are calculated by means of Joule density and the Poynting vector surface integrals. High frequency asymptotic formulas for the Lorentz force and power losses are presented. All analytical solutions derived could be useful for rapid analysis and design of levitations systems. Finally, some remarks about considered levitations are formulated.
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Bibliografia

  1.  K.J. Binns, P.J. Lawrenson, and C.W. Trowbridge, The analytical and numerical solution of electric and magnetic fields, John Wiley & Sons, 1992.
  2.  B.S. Guru and H.R. Hiziroglu, Electromagnetic field theory fundamentals, University Press, Cambridge, 2004.
  3.  V. Dolga and L. Dolga, “Modeling and simulation of a magnetic levitation system”, Annals of the Oradea University of Timisoara, Romania, VI (XVI) (2007).
  4.  H. Górecki and M. Zaczyk, “Determination of optimal controllers. Comparison of two methods for electric network chain”, Bull. Pol. Ac.: Tech.66 (3), 267–273 (2018).
  5.  E. Fromm and H. Jehn, “Electromagnetic forces and power absorption in levitation melting”, British Journal of Applied Physics, 16, 653–663 (1965).
  6.  M. Zdanowski and R. Barlik, “Analytical and experimental determination of the parasitic parameters in high-frequency inductor”, Bull. Pol. Ac.: Tech.65 (1), 107–112 (2017).
  7.  E.C. Okress, D.M. Wroughton, G. Comenetz, P.H. Brace, J.C.R. Kelly, “Electromagnetic levitation of solid and molten metals”, J. Appl. Phys. 23 (5), 545–552 (1952).
  8.  D. Spałek, “Theorem about electromagnetic force surface representation in anisotropic region”, J. Tech. Phys.XLVIII (3-4), 135–145 (2007).
  9.  W.R. Smythe, Static and dynamic electricity, McGraw–Hill Book Company, New York, 1950.
  10.  D. Spałek, “Electromagnetic torque components in synchronous salient-pole machine”, COMPEL. Int. J. Comput. . Math. Electr. Electron. Eng. 16 (3), 129–143 (1997).
  11.  D. Spałek, “Two theorems about surface-integral representation of electromagnetic force and torque”, IEEE Trans. Magn. 53 (7), 1–10 (2017).
  12.  W. He, J. Zhang, S. Yuan, A. Yang, and Ch. Qu, “Threedimensional magneto-electric vibration energy harvester based on magnetic levitation”, IEEE Magn. Lett. 8, 6104703 (2017).
  13.  L. Ułanowicz and G. Jastrze˛bski, “The analysis of working liquid flow in a hydrostatic line with the use of frequency characteristics”, Bull. Pol. Ac.: Tech. 68 (4), 949–956, (2020).
  14.  T. Kaczorek, “Stability analysis of positive linear systems by decomposition of the state matrices into symmetrical and antisymmetrical parts”, Bull. Pol. Ac.: Tech. 67 (4), 761–768 (2019).
  15.  B.P. Mann and N.D. Sims, “Energy Harvesting from the Nonlinear Oscillations of Magnetic Levitation”, Universities of Leeds, Sheffield and York (promoting access to White Rose research papers http://eprints.whiterose.ac.uk/), 2017.
  16.  D. Spałek, “Analytical electromagnetic field and forces calculation for linear, cylindrical and spherical electromechanical converters”, Bull. Pol. Ac.: Tech. 52 (3), 239–250 (2004).
  17.  D. Spałek, “Levitation of Conductive and Magnetically Anisotropic Ball”, IEEE Trans. Magn. 55 (3), 1000406 (2019).
  18.  D. Spałek, “Generalization of Maxwell Stress Tensor Method for Magnetically Anisotropic Regions”, IEEE Trans. Magn. 55 (12), 1000406 (2019).
  19.  J.R. Wait, “A conductive sphere in a time varying magnetic field”, Geophysics, 16 (4), 666–672 (1951).
  20.  K. Jayasekera and I. Ciric, “Benchmark Computations of the Fields, Losses, and Forces for Conducting Spheroids in the Proximity of Current- Carrying Turns”, IEEE Trans Magn. 42 (7), 1802–1811 (2006).
  21.  I.S. Gradshteyn and I.M. Ryzhik, Tables of Integrals, Series, and Products, Academic Press, 2015.
  22.  D. Spałek, “Fourth boundary condition for electromagnetic field problems”, J. Tech. Phys. XLI (2), 129–144 (2000).
  23.  D. Spałek, “Anisotropy component of electromagnetic force and torque”, Bull. Pol. Ac.: Tech. 58 (1), 107–117 (2010).
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Autorzy i Afiliacje

Dariusz Spałek
1
ORCID: ORCID

  1. Silesian University of Technology, Electrical Engineering Faculty, ul. Akademicka 10, 44-100 Gliwice, Poland
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Abstrakt

Short-circuit analysis is conducted based on the nodal impedance matrix, which is the inversion of the nodal admittance matrix. If analysis is conducted for sliding faults, then for each fault location four elements of the nodal admittance matrix are subject to changes and the calculation of the admittance matrix inversion needs to be repeated many times. For large-scale networks such an approach is time consuming and unsatisfactory. This paper proves that for each new fault location a new impedance matrix can be found without recalculation of the matrix inversion. It can be found by a simple extension of the initial nodal impedance matrix calculated once for the input model of the network. This paper derives formulas suitable for such an extension and presents a flowchart of the computational method. Numerical tests performed for a test power system confirm the validity and usefulness of the proposed method.

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Bibliografia

  1.  IEEE Recommended Practice for the Design of Reliable Industrial and Commercial Power Systems, IEEE Std P493/D4, 2006.
  2.  J. Machowski, Z. Lubośny, J. Bialek, and J. Bumby, Power System Dynamics. Stability and Control, 3rd ed., John Wiley & Sons, Chichester, New York, 2020.
  3.  C. Fan, K. Xu, and Q. Liu, “Short-circuit current calculation method for partial coupling transmission lines under different voltage levels”, Int. J. Electr. Power Energy Syst. 78, 647–654 (2016).
  4.  B. Dağ, A.R. Boynueğri, Y. Ateş, A. Karakaş, A. Nadar, and M. Uzunoğlu, “Static Modeling of Microgrids for Load Flow and Fault Analysis,” IEEE Trans. Power Syst. 32(3), 1990‒2000 (2017).
  5.  Ł. Nogal, S. Ribak, and J. Bialek: “Advances in electrical power engineering”, Bull. Pol. Ac.: Tech. 68(4), 647‒649 (2020).
  6.  H. Li, A. Bose, and Y. Zhang, “On-line short-circuit current analysis and preventive control to extend equipment life”, IET Gener. Transm. Distrib. 7(1), 69‒75 (2013).
  7.  S. Azizi and M. Sanaye-Pasand, “From Available Synchrophasor Data to Short-Circuit Fault Identity: Formulation and Feasibility Analysis”, IEEE Trans. Power Syst. 32(3), 2062‒2071 (2017).
  8.  V.A. Stanojević, G. Preston, and V. Terzija, “Synchronised Measurements Based Algorithm for Long Transmission Line Fault Analysis”, IEEE Trans. Smart Grid 9(5), 4448‒4457 (2018).
  9.  T. Gonen, Modern Power System Analysis, 2nd ed., CRC Press, 2013.
  10.  A.R. Bergen and V. Vittal, Power System Analysis, 2nd ed., Englewood Cliffs, NJ, USA: Prentice-Hall, 2000.
  11.  P. Kacejko and J. Machowski, Short-circuits in power systems, PWN/WNT Warszawa 2017, [in Polish].
  12.  P.M. Anderson, Analysis of Faulted Power Systems, New York: IEEE Press, 1995.
  13.  A.H. El-Abiad, “Digital Calculation of Line-to-Ground Short Circuits by Matrix Method”, rans. Am. Inst. Electr. Eng. Part III: Power Apparatus and Systems 79(3), 323‒331 (1960).
  14.  J.J. Grainger and W.D. Stevenson, JR, Power System Analysis, McGraw-Hill, New York, 1994
  15.  T.A. Davis, Direct methods for sparse linear systems, Society for Industrial and Applied Mathematics, 2006.
  16.  X. Luo et al., “An Efficient Second-Order Approach to Factorize Sparse Matrices in Recommender Systems”, IEEE Trans. Ind. Inform. 11(4) 946‒956 (2015).
  17.  X. Luo, M. Zhou, S. Li, and M. Shang, “An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications”, IEEE Trans. Ind. Inform. 14(5), 2011‒2022 (2018).
  18.  M.R. Araújo and C.R. Pereira, “A practical first-zone distance relaying algorithm for long parallel transmission lines”, Electr. Power Syst. Res. 146, 17‒24 (2017).
  19.  N. Abu Bakar, A. Mohamed, M. Ismail, and N. Hamzah, “A voltage sag analysis software tool for determine areas of vulnerability,” 2004 IEEE Region 10 Conference TENCON 2004., Chiang Mai, 2004, pp. 299‒302.
  20.  S.R. Naidu, G.V. de Andrade, and E.G. da Costa, “Voltage Sag Performance of a Distribution System and Its Improvement”, IEEE Trans. Ind. Appl. 48(1), 218‒224 (2012).
  21.  D. Ma and L. Tian, “Practical fault location estimation based on voltage sags magnitude,” 2016 China International Conference on Electricity Distribution (CICED), Xi’an, 2016, pp. 1‒5.
  22.  R.J. Gopi, V.K. Ramachandaramurthy, and M.T. Au, “Analytical approach to stochastic assessment for balanced voltage sags and duration on transmission networks”, 2009 10th International Conference on Electrical Power Quality and Utilisation, Lodz, 2009, pp. 1‒6.
  23.  NEPLAN Smarter Tools “Power System Analysis Software” NEPLAN AG Oberwachtstrasse 2 CH 8700 Küsnacht ZH, [Online]. Available https://www.neplan.ch/wp-content/uploads/2015/01/Electricity.pdf
  24.  A. Boboń, A. Nocoń, S. Paszek, and P. Pruski, “Determination of synchronous generator nonlinear model parameters based on power rejection tests using a gradient optimization algorithm”, Bull. Pol. Ac.: Tech. 65(4), 479‒488 (2017).
  25.  P. Kacejko and J. Machowski, “Application of the Sherman-Morrison formula to short-circuit analysis of transmission networks with phase-shifting transformers”, Electr. Power Syst. Res. 155, 289‒295 (2018).
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Autorzy i Afiliacje

Jan Machowski
1
ORCID: ORCID
Sylwester Robak
1
ORCID: ORCID

  1. Electrical Power Engineering Institute, Faculty of Electrical Engineering, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland
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Abstrakt

Load profiles of residential consumers are very diverse. This paper proposes the usage of a continuous wavelet transform and wavelet coherence to perform analysis of residential power consumer load profiles. The importance of load profiles in power engineering and common shapes of profiles along with the factors that cause them are described. The continuous wavelet transform and wavelet coherence has been presented. In contrast with other studies, this research has been conducted using detailed (not averaged) load profiles. Presented load profiles were measured separately on working day and weekend during winter in two urban households. Results of applying the continuous wavelet transform for load profiles analysis are presented as coloured scalograms. Moreover, the wavelet coherence was used to detect potential relationships between two consumers in power usage patterns. Results of coherence analysis are also presented in a colourful plots. The conducted studies show that the Morlet wavelet is slightly better suitable for load profiles analysis than the Meyer’s wavelet. Research of this type may be valuable for a power system operator and companies selling electricity in order to match their offer to customers better or for people managing electricity consumption in buildings.
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Bibliografia

  1.  M. Bicego, A. Farinelli, E. Grosso, D. Paolini, and S.D. Ramchurn, “On the distinctiveness of the electricity load profile”, Pattern Recognit. 74, 317‒325 (2018), doi: 10.1016/j.patcog.2017.09.039
  2.  P. Piotrowski, D. Baczyński, S. Robak, M. Kopyt, M. Piekarz, and M. Polewaczyk, “Comprehensive forecast of electromobility mid- term development in Poland and its impacts on power system demand”, Bull. Pol. Ac.: Tech, 68(4), 697‒709 (2020), doi: 10.24425/ bpasts.2020.134180
  3.  M. Sepehr, R. Eghtedaei, A. Toolabimoghadam, Y. Noorollahi, and M. Mohammadi, “Modeling the electrical energy consumption profile for residential buildings in Iran”, Sustain. Cities Soc. 41, 481‒489 (2018), doi: 10.1016/j.scs.2018.05.041
  4.  Z. Ning and D. Kirschen, “Preliminary Analisys of High Resolution Domestic Load Data, Part of Supergen Flexnet Project”, The University of Manchester, 2010. [Online]. https://labs.ece.uw.edu/real/Library/Reports/Preliminary_Analysis_of_High_Resolution_Domestic_Load_ Data_Compact.pdf
  5.  J.L. Ramirez-Mendiola, Ph. Grunewald, and N. Eyre, “Linking intra-day variations in residential electricity demand loads to consumer’s activities: What’s missing ?”, Energy Build. 161, 63‒71 (2018), doi: 10.1016/j.enbuild.2017.12.012
  6.  J.L. Ramirez-Mendiola, Ph. Grunewald, and N. Eyre, “The diversity of residential electricity demand – A comparative analysis of metered and simulated data”, Energy Build. 151, 121‒131 (2017), doi: 10.1016/j.enbuild.2017.06.006
  7.  M. Bartecka, P. Terlikowski, M. Kłos, and Ł. Michalski, „Sizing of prosumer hybrid renewable energy systems in Polnad”, Bull. Pol. Ac.: Tech, 68(4), 721‒731 (2020), doi: 10.24425/bpasts.2020.133125
  8.  D.S. Osipov, A.G. Lyutarevich, R.A. Gapirov, V.N. Gorunkov, and A.A. Bubenchikov, “Applications of Wavelet Transform for Analysis of Electrical Transients in Power Systems: The Review”, Prz. Elektrotechniczny (Electrical Review), 92(4), 162‒165 (2016), doi: 10.15199/48.2016.04.35
  9.  R. Kumar and H.O. Bansal, “Hardware in the loop implementation of wavelet based strategy in shunt active power filter to mitigate power quality issues”, Electr. Power Syst. Res. 169, 92‒104 (2019), doi: 10.1016/j.epsr.2019.01.001
  10.  R. Escudero, J. Noel, J. Elizondo, and J. Kirtley, “Microgrid fault detection based on wavelet transformation and Park’s vector approach”, Electr. Power Syst. Res. 152, 401‒410 (2017), doi: 10.1016/j.epsr.2017.07.028
  11.  M. El-Hendawi and Z. Wang, “An ensemble method of full wavelet packet transform and neural network for short term electrical load forecasting”, Electr. Power Syst. Res. 182 (2020), doi: 10.1016/j.epsr.2020.106265
  12.  K. Dowalla, W. Winiecki, R. Łukaszewski, and R. Kowalik, „Electrical appliances identyfication based on wavelet transform of power supply voltage signal”, Prz. Elektrotechniczny (Electrical Review), 94 (11), 43‒46 (2018), doi: 10.15199/48.2018.11.10 [in Polish].
  13.  A. Graps, “An introduction to wavelets”, IEEE Comput. Sci. Eng. 2, 50‒61 (1995), doi: 10.1109/99.388960
  14.  Ch. Chiann and P. A. Morettin, “A wavelet analysis for time series”, J. Nonparametr. Statist. 10(1), 1‒46, (1999), doi: 10.1080/10485259808832752
  15.  P. Sleziak, K. Hlavcova, and J. Szolgay, “Advanatges of a time series analysis using wavelet transform as compared with Fourier analysis”, Slov. J. Civ. Eng. 23(2), 30‒36, (2015), doi: 10.1515/sjce-2015-0010
  16.  S. Avdakovic, A. Nuhanovic, M. Kusljugic, E. Becirovic and E. Turkovic, “Wavelet multiscale analysis of a power system load variance”, Turk. J. Electr. Eng. Comp. Sci. 1035‒1043, (2013), doi: 10.3906/elk-1109-47
  17.  M. Hayn, V. Bertsch, and W. Fichtner, “Electricity load profiles in Europe: The importance of household segmentation”, Energy Res. Soc. Sci. 3, 30–45, (2014), doi: 10.1016/j.erss.2014.07.002
  18.  R. Cruickshank, G. Henze, R. Balaji, H. Br-Mathias, and A. Florita, “Quantifying the Opporturnity Limits of Automatic Residential Electric Load Shaping”, Energies 12, (2019), doi: 10.3390/en12173204
  19.  M. Kott, “The electricity Consumption in Polish Households”, Modern Electr. Power Syst. 2015 – MEPS’15, Wrocław, Poland, July 6‒9, 2015, doi: 10.1109/MEPS.2015.7477166
  20.  O. Elma and U.S. Selamogullar, “A Survey of a Residential Load Profile for Demand Side Managemenet Systems”, The 5th IEEE Internationl Conference on Smart Energy Grid Enegineering, 2017, doi: 10.1109/SEGE.2017.8052781
  21.  P. Kapler, “Utilization of the adaptive potential of individual power consumers in interaction with power system”, Ph.D. Thesis, Warsaw University of Technology, Faculty of Electrical Engineering, (2018), [in Polish].
  22.  A. Grinsted, J.C. Moore, and S. Jevrejeva, “Application of the cross wavelet transform and wavelet coherence to geophysical time series”, Nonlinear Process Geophys. European Geosciences Union (EGU), 11(5/6), 561‒566, (2004), doi: 10.5194/npg-11-561-2004
  23.  B. Cazelles, M. Chavez, D. Berteaux, F. Menard, J.O. Vik, S. Jenouvrier, and N. C. Stenseth, “Wavelet analysis of ecological time series”, Oecologia 156, 287‒304 (2008), doi: 10.1007/s00442-008-0993-2
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Autorzy i Afiliacje

Piotr Kapler
1
ORCID: ORCID

  1. Warsaw University of Technology, Faculty of Electrical Engineering, Power Engineering Institute, ul. Koszykowa 75, 00-662, Warsaw, Poland
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Abstrakt

This paper presents a concept of a shunt active power filter, which is able to provide more precise mapping of its input current drawn from a power line in a reference signal, as compared to a typical filter solution. It can be achieved by means of an interconnection of two separate power electronics converters making, as a whole, a controlled current source, which mainly determines the quality of the shunt active filter operation. One of these power devices, the “auxiliary converter”, corrects the total output current, being a sum of output currents of both converters, toward the reference signal. The rated output power of the auxiliary converter is much lower than the output power of the main one, while its frequency response is extended. Thanks to both these properties and the operation of the auxiliary converter in a continuous mode, pulse modulation components in the filter input current are minimized. Benefits of the filter are paid for by a relatively small increase in the complexity and cost of the system. The proposed solution can be especially attractive for devices with higher output power, where, due to dynamic power loss in power switches, a pulse modulation carrier frequency must be lowered, leading to the limitation of the “frequency response” of the converter. The concept of such a system was called the “hybrid converter topology”. In the first part of the paper, the rules of operation of the active filter based on this topology are presented. Also, the results of comparative studies of filter simulation models based on both typical, i.e. single converter, and hybrid converter topologies, are discussed.
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Bibliografia

  1.  B. Kroposki, C. Pink, R. DeBlasio, H. Thomas, M. Simões, and P. Sen, “Benefits of Power Electronic Interfaces for Distributed Energy Systems”, IEEE Trans. Energy Convers. 25, 901–908 (2010).
  2.  M. Pasko, D. Buła, K. Dębowski, D. Grabowski, and M. Maciążek, “Selected methods for improving operating conditions of three-phase systems working in the presence of current and voltage deformation — Part I”, Arch. .Electr. Eng. 67, 591–602 (2018).
  3.  A. Benchabira and M. Khiat, “A hybrid method for the optimal reactive power dispatch and the control of voltages in an electrical energy network”, Arch. Electr. Eng. 68, 535–551 (2019).
  4.  A. Nami, J.L. Rodríguez Amenedo, S. Arnaltes Gómez, and M.Á. Cardiel Álvarez, “Active power filtering embedded in the frequency control of an offshore wind farm connected to a diode-rectifier-based HVDC link”, Energies 11, 2718 (2018).
  5.  A.J. Christe, S. Negrashov, and P.M. Johnson, “Design, implementation, and evaluation of open power quality”, Energies 13, 4032 (2020).
  6.  B. Lewczuk, G. Redlarski, A. Zak, N. Ziółkowska, B. Przybylska-Gornowicz, and M. Krawczuk, “Influence of Electric, Magnetic, and Electromagnetic Fields on the Circadian System: Current Stage of Knowledge”, in BioMed Research International 2014, 2014, pp. 1–13.
  7.  M. Siwczyński and M. Jaraczewski, “Reactive compensator synthesis in time-domain”, Bull. Pol. Ac.: Tech. 60(1), 119–124 (2012).
  8.  Y. Chen, Z. Huang, Z. Duan, P. Fu, G. Zhou, and L. Luo, “A four-winding inductive filtering transformer to enhance power quality in a high-voltage distribution network supplying nonlinear loads”, Energies 12, 2021 (2019).
  9.  Y. Rozanov, S. Ryvkin, E. Chaplygin, and P. Voronin, Fundamentals of power electronics: operating principles, design, formulas, and applications, CRC Press, 2015.
  10.  M. Rashid, Power Electronics Handbook, Elsevier Ltd.: Oxford, 2018.
  11.  K. Shyu, M. Yang, Y. Chen, and Y. Lin, “Model Reference Adaptive Control Design for a Shunt Active-Power-Filter System”, IEEE Trans. Ind. Electron.55, 97–106 (2008).
  12.  A. Kouzou, M. Mahmoudi, and M. Boucherit, “Evaluation of the Shunt Active Power Filter apparent power ratio using particle swarm optimization”, Arch. Control Sci. 20, 47–76 (2010).
  13.  K. Mikołajuk and A. Toboła, “Average time–varying models of active power filters”, Prz. Elektrotechniczny 95, 53–55 (2010).
  14.  M. Gwóźdź, “Power electronics active shunt filter with controlled dynamics”, Compel-Int. J. Comp. Math. Electr. Electron. Eng. 32, 1337–1344 (2013).
  15.  S. Fryze, “Active, reactive, and apparent power in circuits with nonsinusoidal voltage and current”, Prz. Elektrotechniczny 13, 193–203 (1931).
  16.  M. Artemenko, L. Batrak, and S. Polishchuk, “New definition formulas for apparent power and active current of three-phase power system”, Prz. Elektrotechniczny 95, 81–85 (2019).
  17.  H. Akagi, “Modern active filters and traditional passive filters”, Bull. Pol. Ac.: Tech. 54(3), 255–269 (2006).
  18.  H. Akagi, E. Watanabe, and M. Aredes, Instantaneous power theory and applications to power conditioning, IEEE Press, Hoboken: Piscataway, 2017.
  19.  L. Czarnecki, “Effect of Supply Voltage Harmonics on IRP-Based Switching Compensator Control”, IEEE Trans. Power Electron. 24, 483–488 (2009).
  20.  J. Vásárhelyi, M. Imecs, C. Szabó, I. Incze, and Á. Tihamér, “Managing transients generated by the reconfiguration process at the tandem inverter fed induction motor”, Proceedings of IEEE 7th International Conference on Intelligent Engineering Systems, 2003, pp. 388–393.
  21.  K. Kaneko, J. Mitsuta, K. Matsuse, K. Sasagawa, Y. Abe, and L. Huang, “Analysis of dynamic variation on a combined control strategy for a five-level double converter”, Proceedings of Power Electronics Specialists Conference PESC ’05, 2005, pp. 885–891.
  22.  M. Imecs, A. Trzynadlowski, I. Incze, and C. Szabo, “Vector Control Schemes for Tandem-Converter Fed Induction Motor Drives”, IEEE Trans. Power Electron. 20, 493–501 (2005).
  23.  T. Morizane and N. Kimura, “Circulating current control of double converter system for wind power generation”, Proceedings of the 14th European Conference on Power Electronics and Applications (EPE 2011), 2011.
  24.  A. Tomaszuk and A. Krupa, “High efficiency high step-up DC/ DC converters – a review”, Bull. Pol. Ac.: Tech. 59(4), 475–483 (2011).
  25.  M. Gwóźdź, Ł. Ciepliński, and M. Krystkowiak, “Power supply with parallel reactive and distortion power compensation and tunable inductive filter — Part 1”, Bull. Pol. Ac.: Tech. 68(3), 401–408 (2020).
  26.  X. Rui, L. Jing, L. Fuzhong, and W. Zhi, “The application on active noise cancellation — Research on the series-parallel compensated UPS converter”, International Symposium on Electromagnetic Compatibility EMC 2007, China, 2007, pp.138–141.
  27.  L. Asiminoaei, E. Aeloiza, P. Enjeti, and F. Blaabjerg, “Shunt Active-Power-Filter Topology Based on Parallel Interleaved Inverters”, IEEE Trans. Ind. Electron. 55, 1175–1189 (2008).
  28.  G. Eirea and S. Sanders, “Phase Current Unbalance Estimation in Multiphase Buck Converters”, IEEE Trans. Power Electron. 23, 137–143 (2008).
  29.  M. Hirakawa, M. Nagano, Y. Watanabe, K. Ando, S. Nakatomi, S. Hashino, and T. Shimizu, “High power density interleaved dc/dc converter using a 3-phase integrated close-coupled inductor set aimed for electric vehicles”, Proceedings of Energy Conversion Congress and Exposition (ECCE) 2010, 2010, pp. 2451–2457.
  30.  J. Iwaszkiewicz, P. Bogusławski, A. Krahel, and E. Łowiec, “Three-phase voltage outages compensator with cascaded multilevel converter”, Arch. Electr. Eng. 61, 325–336 (2012).
  31.  J. Wu, H. Jou, P. Huang, and I. Chiu, “Current balancing control for an interleaved boost power converter”, Int. J. .Electron. 106, 1567–1582 (2019).
  32.  M. Schetzen, Linear time-invariant systems, Wiley-IEEE Press, 2003.
  33.  M. Gwóźdź, “Stability of discrete time systems on base of generalized sampling expansion”, Elektryka, Silesian University of Technology 57, 29–40 (2011).
  34.  J. Doyle, B. Francis, and A. Tannenbaum, Feedback Control Theory, Dover Publications, 2013.
  35.  Y. Hasegawa, Control Problems of Discrete-Time Dynamical Systems, Springer, 2015.
  36.  W. Kester, The Data Conversion Handbook, Analog Devices Inc, Newnes, 2005.
  37.  J. de la Rosa, “Sigma-Delta Modulators: Tutorial Overview, Design Guide, and State-of-the-Art Survey”, IEEE Trans. Circuits Syst. I-Regul. Pap. 58, 1–21 (2011).
  38.  A. Jain, M. Venkatesan, and S. Pavan, “Analysis and Design of a High Speed Continuous-time Delta Sigma Modulator Using the Assisted Opamp Technique”, IEEE J. Solid-State Circuit. 47, 1615–1625 (2012).
  39.  B. Razavi, “The Delta-Sigma Modulator [A Circuit for All Seasons]”, IEEE Solid-State Circuit. Mag. 8, 10–15 (2016).
  40.  M. Gwozdz and D. Matecki, “Power electronics inverter with a modified sigma-delta modulator and an output stage based on GaN E-HEMTs”, in Advanced Control of Electrical Drives and Power Electronic Converters, pp. 327–338 Springer, London, 2017.
  41.  J. Chen, Y. Hwang, C. Jheng, Y. Ku, and C. Yu, “A Low-Electromagnetic-Interference Buck Converter with Continuous-Time Delta- Sigma-Modulation and Burst-Mode Techniques”, IEEE Trans. Ind. Electron. 65, 6860–6869 (2018).
  42.  D. Gerber, C. Le, M. Kline, P. Kinget, and S. Sanders, “An Integrated Multilevel Converter with Sigma–Delta Control for LED Lighting”, IEEE Trans. Power Electron. 34, 3030–3040 (2019).
  43.  B. Jacob and M. Baiju, “Space-Vector-Quantized Dithered Sigma–Delta Modulator for Reducing the Harmonic Noise in Multilevel Converters”, IEEE Trans. Ind. Electron. 62, 2064–2072 (2015).
  44.  C. Chang, F. Wu, and Y. Chen, “Modularized Bidirectional Grid-Connected Inverter with Constant-Frequency Asynchronous Sigma-Delta Modulation”, IEEE Trans. Ind. Electron. 59, 4088–4100 (2012).
  45.  B. Wilamowski and J. Irwin, Fundamentals of Industrial Electronics, CRC Press: London, United Kingdom, 2017.
  46.  Y. Kang, T. Ge, H. He, and J. Chang, “A review of audio class D amplifiers”, 2016 International Symposium on Integrated Circuits (ISIC), Singapore, 12–14 (2016).
  47.  X. Jiang, “Fundamentals of Audio Class D Amplifier Design: A Review of Schemes and Architectures”, IEEE Solid-State Circuits Magazine 9, 14–25 (2017).
  48.  G. Scott, “Design Considerations for Class-D Audio Power Amplifiers”, in Application Report (SLOA242A), Texas Instruments, 2019.
  49.  A. Chatterjee, H. Nobahari, and P. Siarry, Advances in Heuristic Signal Processing and Applications, Springer: Berlin, Heidelberg, 2013.
  50.  H. Zhang, C. Qin, and Y. Luo, “Neural-Network-Based Constrained Optimal Control Scheme for Discrete-Time Switched Nonlinear System Using Dual Heuristic Programming”, IEEE Trans. Autom. Sci. Eng. 11, 839–849 (2014).
  51.  R. Kirlin, C. Lascu, and A. Trzynadlowski, “Shaping the Noise Spectrum in Power Electronic Converters”, IEEE Trans. Ind. Electron. 58, 2780–2788 (2011).
  52.  M. Auer and T. Karaca, “Spread spectrum techniques for Class-D audio amplifiers to reduce EMI”, e & i Elektrotechnik und Informationstechnik 133, 43–47 (2016).
  53.  MITSUBISHI ELECTRIC Semiconductors & Devices: Power Modules for Power Applications | Power supply / UPS. [Online]. https:// www.mitsubishielectric.com/semiconductors/application/ups/index.html (accessed Aug. 11 2020).
  54.  Silicon Carbide CoolSiC™ MOSFET Modules – Infineon Technologies. [Online] https://www.infineon.com/cms/en/product/power/mosfet/ silicon-carbide/modules/ (accessed Aug. 11 2020).
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Autorzy i Afiliacje

Michał Gwóźdź
1
ORCID: ORCID
Łukasz Ciepliński
1
ORCID: ORCID

  1. Poznan University of Technology, Faculty of Control, Robotics and Electrical Engineering, Piotrowo 3A, 60-965 Poznan, Poland
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Abstrakt

The article presents an identification method of the model of the ball-and-race coal mill motor power signal with the use of machine learning techniques. The stages of preparing training data for model parameters identification purposes are described, as well as these aimed at verifying the quality of the evaluated model. In order to meet the tasks of machine learning, additive regression model was applied. Identification of the additive model parameters was performed on the basis of iterative backfitting algorithm combined with nonparametric estimation techniques. The proposed models have predictive nature and are aimed at simulation of the motor power signal of a coal mill during its regular operation, startup and shutdown. A comparative analysis has been performed of the models structured differently in terms of identification quality and sensitivity to the existence of an exemplary disturbance in the form of overhangs in the coal bunker. Tests carried out on the basis of real measuring data registered in the Polish power unit with a capacity of 200 MW confirm the effectiveness of the method.
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Bibliografia

  1.  W. Wójcik, “Application of fibre-optic flame monitoring systems to diagnostics of combustion process in power boilers”, Bull. Pol. Ac.: Tech. 56(4), 177–196 (2008).
  2.  Sprawozdanie z działalności Prezesa Urzędu Regulacji Ener- getyki w 2017 r. [Online]. https://www.ure.gov.pl
  3.  W. Fennig, M. Kielian, M. Lipiński, A. Bielaczyc, M. Brzozowski, S. Lasota, and P. Sarnecki, “Układ do wykrywania i ostrzegania przed zakłóceniami w swobodnym spływie strumienia paliwa stałego w przykotłowym zasobniku węgla i jego praktyczne zastosowanie na obiekcie energetycznym”, Energetyka 12, 757–760 (2014) [in Polish].
  4.  M. Lipiński, “Detection and prevention systems of mills assembly emergency states”, in Advanced Solutions in Diagnostics and Fault Tolerant Control, DPS 2017; Advances in Intelligent Systems and Computing, Eds. J. Kościelny, M. Syfert, A. Sztyber, Springer, Cham, 2018.
  5.  A. Cortinovis, M. Mercangoz, T. Mathur, J. Poland, and M. Blaumann, “Nonlinear coal mill modeling and its application to model predictive control”, Control Eng. Practice 21(3), 308–320 (2013).
  6.  Y. Gao, D. Zeng, and J. Liu, “Modeling of a medium speed coal mill”, Powder Technol. 17(5), 1–27 (2017).
  7.  M. Mercangoez and J. Poland, “Coal mill modeling for monitoring and control”, IFAC Proc. Volumes, 44(1), 13163–13166 (2011).
  8.  N.W. Rees and G.Q. Fan, “Modeling and control of pulverized fuel coal mills”, in Thermal Power Plant Simulation and Control, Ed. D. Flynn, IET, UK, 2003.
  9.  G. Zhou, J. Si, and C.W. Taft, “Modeling and simulation of CE deep bowl pulverizer”, IEEE Trans. Energy Convers. 15(3), 312–322 (2000).
  10.  P. Niemczyk, J.D. Bendtsen, T.S. Pedersen, P. Andersen, and A.P. Ravn, “Derivation and validation of a coal mill model for control”, Control Eng. Practice 20(5), 519–530 (2012).
  11.  J.L. Wei, J.H. Wang, and Q.H. Wu, “Development of a multisegment coal mill model using an evolutionary computation technique”, IEEE Trans. Energy Convers. 22(3), 718–727 (2007).
  12.  V. Agrawal, B.K. Panigrahi, and P.M.V. Subbarao, “A unified thermo-mechanical model for coal mill operation”, Control Eng. Practice 44, 157–171 (2015).
  13.  P.F. Odgaard and B. Mataji, “Observer-based fault detection and moisture estimating in coal mills”, Control Eng. Practice 16, 909–921 (2008).
  14.  M. Krośnicki, “Current diagnosis of coal mill using evolutionary algorithm”, Warsaw University of Technology, Master thesis, 2015.
  15.  P. Pradeebha, N. Pappa, and D. Vasanthi, “Modeling and Control of Coal Mill”, IFAC Proc. Volumes 46(32), 797–802 (2013).
  16.  T. Chai, L. Zhai, and H. Yue, “Multiple models and neural networks based decoupling control of ball mill coal pulverising systems”, J. Process Control 21, 351–366 (2011).
  17.  X. Han and X. Jiang, “Fault Diagnosis of Pulverizing System Based on Fuzzy Decision-Making Fusion Method”, Fuzzy Info. Eng. 62, 1045–1056 (2009).
  18.  Y.G. Zhang, Q.H. Wu, J. Wang, and X.X. Zhou, “Coal mill modeling by machine learning based on onsite measurements”, IEEE Trans. Energy Convers. 17, 549–55 (2002).
  19.  T. Hastie and R. Tibshirani, “Generalized additive models”, CRC Monographs on Statistics and Applied Probability, Chapman & Hall/, 1990.
  20.  Z.M. Łabęda-Grudziak, “Smoothing parameters selection in the additive regression models approach for the fault detection scheme”, Pomiary Automatyka Kontrola 57(2), 197–200 (2010).
  21.  Z.M. Łabęda-Grudziak, “Diagnostic technique based on additive models in the tasks of the ongoing exploitation of gas network”, Eksploatacja i Niezawodność – Maintenance and Reliability 18(1), 50–56 (2016).
  22.  Z.M. Łabęda-Grudziak, “Identification of dynamic system additive models by KDD methods”, Pomiary Automatyka Kontrola 57(3), 249–252 (2010).
  23.  R.K. Pearson, Exploratory Data Analysis Using, R, Chapman & Hall, 2018.
  24.  V. Agrawal, B.K. Panigrahi, and P.M.V. Subbarao, “Review of control and fault diagnosis methods applied to coal mills”, J. Process Control 32, 138–153 (2015).
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Autorzy i Afiliacje

Zofia Magdalena Łabęda-Grudziak
1
ORCID: ORCID
Mariusz Lipiński
2

  1. Warsaw University of Technology, Institute of Automatic Control and Robotics, ul. św. Andrzeja Boboli 8, 02-525 Warsaw, Poland
  2. Institute of Power Systems Automation, ul. Wystawowa 113, 51-618 Wrocław, Poland
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Abstrakt

Convolutional Neural Networks (CNN) have achieved huge popularity in solving problems in image analysis and in text recognition. In this work, we assess the effectiveness of CNN-based architectures where a network is trained in recognizing handwritten characters based on Latin script. European languages such as Dutch, French, German, etc., use different variants of the Latin script, so in the conducted research, the Latin alphabet was extended by certain characters with diacritics used in Polish language. To evaluate the recognition results under the same conditions, a handwritten Latin dataset was also developed. The proposed CNN architecture produced an accuracy of 96% for the extended character set. This is comparable to state-of-the-art results found in the domain of identifying handwritten characters. The presented approach extends the usage of CNN-based recognition to different variants of the Latin characters and shows it can be successfully used for a set of languages based on that script. It seems to be an effective technique for a set of languages written using the Latin script.

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Bibliografia

  1.  E. Lukasik and T. Zientarski, “Comparative analysis of selected programs for optical text recognition”, J. Comput. Sci. Inst. 7, 191‒194 (2018).
  2.  P. Kusaj, M. Kosyra, and M. Charytanowicz, “Web-Page Classification Based on Wikipedia Structure. Recent Developments” in Mathematics and Informatics, Contemporary Mathematics and Computer Science 2, Part II, A. Zapała (red.), pp. 89‒102, Wydawnictwo KUL, 2016.
  3.  D. Połap and M. Woźniak, “Flexible neural network architecture for handwritten signatures recognition”, Int. J. Electron. Telecommun. 62, 197–202 (2016).
  4.  M. Milosz and J. Gazda, “Effectiveness of artificial neural networks in recognising handwriting characters”, J. Comput. Sci. Inst. 7, 210‒214 (2018).
  5.  Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, “Gradient-based learning applied to document recognition”. Proc. IEEE 86(11), 2278‒2324 (1998).
  6.  A. Pal and D. Singh, “Handwritten English character recognition using neural network”, Int. J. Comput. Sci. Commun. 1(2), 141‒144 (2010).
  7.  B.K. Verma, “Handwritten Hindi character recognition using multilayer perceptron and radial basis function neural network”, IEEE International Conference on Neural Network 4, 2111‒2115 (1995).
  8.  D. Singh, S.K. Singh, and M. Dutta, “Hand written character recognition using twelve directional feature input and neural network”, Int. J. Comput. Appl. 1(3), 94‒98 (2010).
  9.  Y. Perwej and A. Chatirvedi, “Neural networks for handwritten English alphabet recognition”, Int. J. Comput. Appl. 20(7), 1–5 (2011).
  10.  J. Pradeep, E. Srinivasan, and S. Himavathi, “Neural network based handwritten character recognition system without feature extraction”, 2011 International Conference on Computer, Communication and Electrical Technology (ICCCET), Tamilnadu, 2011, pp. 40‒44.
  11.  A.M. Obaid, H.M. El Bakry, M.A. Elodusuky, and A.I. Shehab, “Handwritten text recognition system based on neural network”, Int. J. Adv. Res. Comput. Sci. Technol. 4(1), 72‒77 (2016).
  12.  V. Lebedev and V. Lempitsky. “Speeding-up convolutional neural networks: A survey”, Bull. Pol. Ac.: Tech. 66(6), 799‒810 (2018).
  13.  D. Firmani, P. Merialdo, E. Nieddu, and S. Scardapane, “In codice ratio: OCR of handwritten Latin documents using deep convolutional networks”, in AI* CH@ AI* IA, 2017, pp. 9‒16.
  14.  F.P. Such, D. Peri, F. Brockler, P. Hutkowski, and R. Ptucha. “Fully convolutional networks for handwriting recognition”. In: 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), IEEE, 2018, pp. 86‒91.
  15.  P. Grother, “NIST special database 19 handprinted forms and characters database”, National Institute of Standards and Technology, Tech. Rep., 1995.
  16.  M. Lutf, X. You, Y. Cheung, and C.L.P. Chen, “Arabic font recognition based on diacritics features”, Pattern Recognit. 47, 672–684 (2014).
  17.  K.E. Gajoui, F.A. Allah, and M. Oumsis, “Diacritical Language OCR based on neural network: Case of Amazigh language”. Procedia Comput. Sci. 73, 298‒305 (2015).
  18.  J. Náplava, M. Straka, P. Straňák, and J. Hajič, “Diacritics Restoration Using Neural Networks”, Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC), 2018.
  19.  D. Grzelak, K. Podlaski, and G. Wiatrowski, “Analyze the effectiveness of an algorithm for identifying Polish characters in handwriting based on neural machine learning technologies”, Journal of King Saud University – Computer and Information Sciences, 2019, doi: 10.1016/j.jksuci.2019.08.001.
  20.  G. Cohen, S. Afshar, J. Tapson, and A. van Schaik, ”EMNIST: an extension of MNIST to handwritten letters”. Retrieved from: http:// arxiv.org/abs/1702.05373, 2017.
  21.   M. Tokovarov, M. Kaczorowska, and M. Milosz, “Development of Extensive Polish Handwritten Characters Database for Text Recognition Research”, Adv. Sci. Technol. Res. J. 14(3), 30–38 (2020), doi: 10.12913/22998624/122567.
  22.  M. Charytanowicz and P. Kulczycki, “An Image Analysis Algorithm for Soil Structure Identification“; in: Intelligent Systems’2014, pp. 681‒692, D. Filev, J. Jablkowski, J. Kacprzyk, I. Popchev, L. Rutkowski, V. Sgurev, E. Sotirova, P. Szynkarczyk, S. Zadrozny (eds.), Springer, Berlin, 2014.
  23.  The Polish Handwritten Characters Database, [Online]. https://cs.pollub.pl/phcd/?lang=en.
  24.  D.P. Kingma and J.L. Ba, “Adam: A method for stochastic optimization”. arXiv:1412.6980v9, 2014.
  25.  M. Abadi et al., “Tensorflow: A system for large-scale machine learning,” in 12th Symposium on Operating Systems Design and Implementation, 2016, pp. 265‒283.
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Autorzy i Afiliacje

Edyta Lukasik
ORCID: ORCID
Malgorzata Charytanowicz
ORCID: ORCID
Marek Milosz
ORCID: ORCID
Michail Tokovarov
Monika Kaczorowska
Dariusz Czerwinski
Tomasz Zientarski
ORCID: ORCID
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Abstrakt

The binary classifiers are appropriate for classification problems with two class labels. For multi-class problems, decomposition techniques, like one-vs-one strategy, are used because they allow the use of binary classifiers. The ensemble selection, on the other hand, is one of the most studied topics in multiple classifier systems because a selected subset of base classifiers may perform better than the whole set of base classifiers. Thus, we propose a novel concept of the dynamic ensemble selection based on values of the score function used in the one-vs-one decomposition scheme. The proposed algorithm has been verified on a real dataset regarding the classification of cutting tools. The proposed approach is compared with the static ensemble selection method based on the integration of base classifiers in geometric space, which also uses the one-vs-one decomposition scheme. In addition, other base classification algorithms are used to compare results in the conducted experiments. The obtained results demonstrate the effectiveness of our approach.

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Bibliografia

  1.  C. Sammut and G. I. Webb, Encyclopedia of Machine Learning and Data Mining. Springer US, 2016.
  2.  M. Mohri, A. Rostamizadeh, and A. Talwalkar, Foundations of machine learning. MIT press, 2018.
  3.  S. Osowski and K. Siwek, “Local dynamic integration of ensemble in prediction of time series”, Bull. Pol. Ac.: Tech. 67(3), 517–525 (2019).
  4.  O. Sagi and L. Rokach, “Ensemble learning: A survey”, Wiley Interdiscip. Rev.-Data Mining Knowl. Discov. 8(4), e1249 (2018).
  5.  R.M. Cruz, R. Sabourin, and G.D. Cavalcanti, “Dynamic classifier selection: Recent advances and perspectives”, Inf. Fusion 41, 195–216 (2018).
  6.  O.A. Alzubi, J.A. Alzubi, M. Alweshah, I. Qiqieh, S. AlShami, and M. Ramachandran, “An optimal pruning algorithm of classifier ensembles: dynamic programming approach”, Neural Comput. Appl. 32, 16091–16107 (2020).
  7.  Y. Bian, Y. Wang, Y. Yao, and H. Chen, “Ensemble pruning based on objection maximization with a general distributed framework”, IEEE Trans. Neural Netw. Learn. Syst. 31(9), 3766‒3774 (2020).
  8.  R.M. Cruz, D.V. Oliveira, G.D. Cavalcanti, and R. Sabourin, “Fire-des++: Enhanced online pruning of base classifiers for dynamic ensemble selection”, Pattern Recognit. 85, 149–160 (2019).
  9.  T.T. Nguyen, A.V. Luong, M.T. Dang, A.W.-C. Liew, and J. McCall, “Ensemble selection based on classifier prediction confidence”, Pattern Recognit. 100, 107104 (2020).
  10.  Z.-L. Zhang, X.-G. Luo, S. García, J.-F. Tang, and F. Herrera, “Exploring the effectiveness of dynamic ensemble selection in the one- versus-one scheme”, Knowledge-Based Syst. 125, 53–63 (2017).
  11.  M. Galar, A. Fernández, E. Barrenechea, H. Bustince, and F. Herrera, “Dynamic classifier selection for one-vs-one strategy: avoiding non-competent classifiers”, Pattern Recognit. 46(12), 3412–3424 (2013).
  12.  M. Pawlicki, A. Giełczyk, R. Kozik, and M. Choraś, “Faultprone software classes recognition via artificial neural network with granular dataset balancing”, in International Conference on Computer Recognition Systems 2019, Springer, 2019, pp. 130–140.
  13.  D. Rajeev, D. Dinakaran, and S. Singh, “Artificial neural network based tool wear estimation on dry hard turning processes of aisi4140 steel using coated carbide tool”, Bull. Pol. Ac.: Tech. 65(4), 553–559 (2017).
  14.  D. Więcek, A. Burduk, and I. Kuric, “The use of ann in improving efficiency and ensuring the stability of the copper ore mining process”, Acta Montanistica Slovaca 24(1), 1‒14 (2019).
  15.  P. Raja, R. Malayalamurthim, and M. Sakthivel, “Experimental investigation of cryogenically treated hss tool in turning on aisi1045 using fuzzy logic–taguchi approach”, Bull. Pol. Ac.: Tech. 67(4), 687–696 (2019).
  16.  T. Andrysiak and L. Saganowski, “Anomaly detection for smart lighting infrastructure with the use of time series analysis”, J. UCS 26(4), 508–527 (2020).
  17.  A. Burduk, K. Musiał, J. Kochańska, D. Górnicka, and A. Stetsenko, “Tabu search and genetic algorithm for production process scheduling problem”, LogForum 15, 181–189 (2019.
  18.  M. Choraś, M. Pawlicki, D. Puchalski, and R. Kozik, “Machine learning–the results are not the only thing that matters! what about security, explainability and fairness?”, in International Conference on Computational Science, Springer, 2020, pp. 615–628.
  19.  P. Zarychta, P. Badura, and E. Pietka, “Comparative analysis of selected classifiers in posterior cruciate ligaments computer aided diagnosis”, Bull. Pol. Ac.: Tech. 65(1), 63–70 (2017).
  20.  I. Rojek, E. Dostatni, and A. Hamrol, “Ecodesign of technological processes with the use of decision trees method”, in International Joint Conference SOCO’17-CISIS’17-ICEUTE’17, León, Spain, 2017, Springer, 2018, pp. 318–327.
  21.  I. Rojek and E. Dostatni, “Machine learning methods for optimal compatibility of materials in ecodesign”, Bull. Pol. Ac.: Tech. 68(2), 199–206 (2020).
  22.  P. Prokopowicz, D. Mikołajewski, K. Tyburek, and E. Mikołajewska, “Computational gait analysis for post-stroke rehabilitation purposes using fuzzy numbers, fractal dimension and neural networks”, Bull. Pol. Ac.: Tech. 68(2), 191–198 (2020).
  23.  S. Igari, F. Tanaka, and M. Onosato, “Customization of a micro process planning system for an actual machine tool based on updating a machining database and generating a database-oriented planning algorithm”, Trans. Inst. Syst. Control Inform. Eng. 26(3), 87–94 (2013).
  24.  C. Tan and S. Ranjit, “An expert carbide cutting tools selection system for cnc lathe machine”, Int. Rev. Mech. Eng. 6(7), 1402–1405 (2012).
  25.  I. Rojek, “Technological process planning by the use of neural networks”, AI EDAM – AI EDAM-Artif. Intell. Eng. Des. Anal. Manuf. 31(1), 1–15 (2017).
  26.  P. Heda, I. Rojek, and R. Burduk, “Dynamic ensemble selection – application to classification of cutting tools”, in International Conference on Computer Information Systems and Industrial Management LNCS(12133), Springer, 2020, pp. 345–354.
  27.  L.I. Kuncheva, Combining Pattern Classifiers. John Wiley & Sons, Inc., 2014.
  28.  E. Santucci, L. Didaci, G. Fumera, and F. Roli, “A parameter randomization approach for constructing classifier ensembles”, Pattern Recognit. 69, 1–13 (2017).
  29.  M. Mohandes, M. Deriche, and S. O. Aliyu, “Classifiers combination techniques: A comprehensive review”, IEEE Access 6, 19626–19639 (2018).
  30.  J. Yan, Z. Zhang, K. Lin, F. Yang, and X. Luo, “A hybrid scheme-based one-vs-all decision trees for multi-class classification tasks”, Knowledge-Based Syst. 198. 105922 (2020).
  31.  P. Chaitra and R.S. Kumar, “A review of multi-class classification algorithms”, Int. J. Pure Appl. Math. 118(14), 17–26 (2018).
  32.  M. Galar, A. Fernández, E. Barrenechea, H. Bustince, and F. Herrera, “An overview of ensemble methods for binary classifiers in multi- class problems: Experimental study on onevs-one and one-vs-all schemes”, Pattern Recognit. 44(8), 1761–1776 (2011).
  33.  R. Burduk, “Integration base classifiers based on their decision boundary”, in International Conference on Artificial Intelligence and Soft Computing, Springer, 2017, pp. 13–20.
  34.  M.P. Groover, Fundamentals of modern manufacturing: materials, processes and systems, Willey, 2010.
  35.  M. Sokolova and G. Lapalme, “A systematic analysis of performance measures for classification tasks”, Inf. Process. Manage. 45, 427–437 (2009).
  36.  I. Rojek, “Classifier models in intelligent capp systems”, in Man-Machine Interactions, pp. 311–319, Springer, 2009.
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Autorzy i Afiliacje

Izabela Rojek
1
ORCID: ORCID
Robert Burduk
2
ORCID: ORCID
Paulina Heda
2

  1. Institute of Computer Science, Kazimierz Wielki University, ul. Chodkiewicza 30, 85-064 Bydgoszcz, Poland
  2. Faculty of Electronic, Wroclaw University of Science and Technology, ul. Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland
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Abstrakt

Speech emotion recognition (SER) is a complicated and challenging task in the human-computer interaction because it is difficult to find the best feature set to discriminate the emotional state entirely. We always used the FFT to handle the raw signal in the process of extracting the low-level description features, such as short-time energy, fundamental frequency, formant, MFCC (mel frequency cepstral coefficient) and so on. However, these features are built on the domain of frequency and ignore the information from temporal domain. In this paper, we propose a novel framework that utilizes multi-layers wavelet sequence set from wavelet packet reconstruction (WPR) and conventional feature set to constitute mixed feature set for achieving the emotional recognition with recurrent neural networks (RNN) based on the attention mechanism. In addition, the silent frames have a disadvantageous effect on SER, so we adopt voice activity detection of autocorrelation function to eliminate the emotional irrelevant frames. We show that the application of proposed algorithm significantly outperforms traditional features set in the prediction of spontaneous emotional states on the IEMOCAP corpus and EMODB database respectively, and we achieve better classification for both speaker-independent and speaker-dependent experiment. It is noteworthy that we acquire 62.52% and 77.57% accuracy results with speaker-independent (SI) performance, 66.90% and 82.26% accuracy results with speaker-dependent (SD) experiment in final.
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Bibliografia

  1.  M. Gupta, et al., “Emotion recognition from speech using wavelet packet transform and prosodic features”, J. Intell. Fuzzy Syst. 35, 1541–1553 (2018).
  2.  M. El Ayadi, et al., “Survey on speech emotion recognition: Features, classification schemes, and databases”, Pattern Recognit. 44, 572–587 (2011).
  3.  P. Tzirakis, et al., “End-to-end speech emotion recognition using deep neural networks”, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Canada, 2018, pp. 5089‒5093, doi: 10.1109/ICASSP.2018.8462677.
  4.  J.M Liu, et al., “Learning Salient Features for Speech Emotion Recognition Using CNN”, 2018 First Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia), Beijing, China, 2018, pp. 1‒5, doi: 10.1109/ACIIAsia.2018.8470393.
  5.  J. Kim, et al., “Learning spectro-temporal features with 3D CNNs for speech emotion recognition”, 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), San Antonio, USA, 2017, pp. 383‒388, doi: 10.1109/ACII.2017.8273628.
  6.  M.Y Chen, X.J He, et al., “3-D Convolutional Recurrent Neural Networks with Attention Model for Speech Emotion Recognition”, IEEE Signal Process Lett. 25(10), 1440‒1444 (2018), doi: 10.1109/LSP.2018.2860246.
  7.  V.N. Degaonkar and S.D. Apte, “Emotion modeling from speech signal based on wavelet packet transform”, Int. J. Speech Technol. 16, 1‒5 (2013).
  8.  T. Feng and S. Yang, “Speech Emotion Recognition Based on LSTM and Mel Scale Wavelet Packet Decomposition”, Proceedings of the 2018 International Conference on Algorithms, Computing and Artificial Intelligence (ACAI 2018), New York, USA, 2018, art. 38.
  9.  P. Yenigalla, A. Kumar, et. al”, Speech Emotion Recognition Using Spectrogram & Phoneme Embedding Promod”, Proc. Interspeech 2018, 2018, pp. 3688‒3692, doi: 10.21437/Interspeech.2018-1811.
  10.  J. Kim, K.P. Truong, G. Englebienne, and V. Evers, “Learning spectro-temporal features with 3D CNNs for speech emotion recognition”, 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), San Antonio, USA, 2017, pp. 383‒388, doi: 10.1109/ACII.2017.8273628.
  11.  S. Jing, X. Mao, and L. Chen, “Prominence features: Effective emotional features for speech emotion recognition”, Digital Signal Process. 72, 216‒231 (2018).
  12.  L. Chen, X. Mao, P. Wei, and A. Compare, “Speech emotional features extraction based on electroglottograph”, Neural Comput. 25(12), 3294–3317 (2013).
  13.  J. Hook, et al., “Automatic speech based emotion recognition using paralinguistics features”, Bull. Pol. Ac.: Tech. 67(3), 479‒488, 2019.
  14.  A. Mencattini, E. Martinelli, G. Costantini, M. Todisco, B. Basile, M. Bozzali, and C. Di Natale, “Speech emotion recognition using amplitude modulation parameters and a combined feature selection procedure”, Knowl.-Based Syst. 63, 68–81 (2014).
  15.  H. Mori, T. Satake, M. Nakamura, and H. Kasuya, “Constructing a spoken dialogue corpus for studying paralinguistic information in expressive conversation and analyzing its statistical/acoustic characteristics”, Speech Commun. 53(1), 36–50 (2011).
  16.  B. Schuller, S. Steidl, A. Batliner, F. Burkhardt, L. Devillers, C. Müller, and S. Narayanan, “Paralinguistics in speech and language—state- of-the-art and the challenge”, Comput. Speech Lang. 27(1), 4–39 (2013).
  17.  S. Mariooryad and C. Busso, “Compensating for speaker or lexical variabilities in speech for emotion recognition”, Speech Commun. 57, 1–12 (2014).
  18.  G.Trigeorgis et.al, “Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network”, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, 2016, pp. 5200‒5204, doi: 10.1109/ ICASSP.2016.7472669.
  19.  Y. Xie et.al, “Attention-based dense LSTM for speech emotion recognition”, IEICE Trans. Inf. Syst. E102.D, 1426‒1429 (2019).
  20.  F. Tao and G.Liu, “Advanced LSTM: A Study about Better Time Dependency Modeling in Emotion Recognition”, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Canada, 2018, pp. 2906‒2910, doi: 10.1109/ ICASSP.2018.8461750.
  21.  Y.M. Huang and W. Ao, “Novel Sub-band Spectral Centroid Weighted Wavelet Packet Features with Importance-Weighted Support Vector Machines for Robust Speech Emotion Recognition”, Wireless Personal Commun. 95, 2223–2238 (2017).
  22.  Firoz Shah A. and Babu Anto P., “Wavelet Packets for Speech Emotion Recognition”, 2017 Third International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), Chennai, 2017, pp. 479‒481, doi: 10.1109/ AEEICB.2017.7972358.
  23.  K.Wang, N. An, and L. Li, “Speech Emotion Recognition Based on Wavelet Packet Coefficient Model”, The 9th International Symposium on Chinese Spoken Language Processing, Singapore, China, 2014, pp. 478‒482, doi: 10.1109/ISCSLP.2014.6936710.
  24.  S. Sekkate, et al., “An Investigation of a Feature-Level Fusion for Noisy Speech Emotion Recognition”, Computers 8, 91 (2019).
  25.  Varsha N. Degaonkar and Shaila D. Apte, “Emotion Modeling from Speech Signal based on Wavelet Packet Transform”, Int. J. Speech Technol. 16, 1–5 (2013).
  26.  F. Eyben, et al., “Opensmile: the munich versatile and fast open-source audio feature extractor”, MM ’10: Proceedings of the 18th ACM international conference on Multimedia, 2010, pp. 1459‒1462.
  27.  Ch.-N. Anagnostopoulos, T. Iliou, and I. Giannoukos, “Features and classifiers for emotion recognition from speech: a survey from 2000 to 2011,” Artif. Intell. 43(2), 155–177 (2015).
  28.  H. Meng, T. Yan, F. Yuan, and H. Wei, “Speech Emotion Recognition From 3D Log-Mel SpectrogramsWith Deep Learning Network”, IEEE Access 7, 125868‒125881 (2019).
  29.  Keren, Gil and B. Schuller. “Convolutional RNN: An enhanced model for extracting features from sequential data,” International Joint Conference on Neural Networks, 2016, pp. 3412‒3419.
  30.  C.W. Huang and S.S. Narayanan, “Deep convolutional recurrent neural network with attention mechanism for robust speech emotion recognition”, IEEE International Conference on Multimedia and Expo (ICME), Hong Kong, 2017, pp. 583‒588, doi: 10.1109/ ICME.2017.8019296.
  31.  S. Mirsamadi, E. Barsoum, and C. Zhang, “Automatic Speech Emotion Recognition using Recurrent Neural Networks with Local Attention”, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, USA, 2017, pp. 2227- 2231, doi: 10.1109/ICASSP.2017.7952552.
  32.  Ashish Vaswani, et al., “Attention Is All You Need”, 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, USA, 2017.
  33.  X.J Wang, et al., “Dynamic Attention Deep Model for Article Recommendation by Learning Human Editors’ Demonstration”, Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, Canada, 2017.
  34.  C. Busso, et al., “IEMOCAP: interactive emotional dyadic motion capture database,” Language Resources & Evaluation 42(4), 335 (2008).
  35.  F. Burkhardt, A. Paeschke, M. Rolfes, W.F. Sendlmeier, and B.Weiss, “A database of German emotional speech,” INTERSPEECH 2005 – Eurospeech, Lisbon, Portugal, 2005, pp. 1517‒1520.
  36.  D. Kingma and J. Ba, “International Conference on Learning Representations (ICLR)”, ICLR, San Diego, USA, 2015.
  37.  F. Vuckovic, G. Lauc, and Y. Aulchenko. “Normalization and batch correction methods for high-throughput glycomics”, Joint Meeting of the Society-For-Glycobiology 2016, pp. 1160‒1161.
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Autorzy i Afiliacje

Hao Meng
1
Tianhao Yan
1
Hongwei Wei
1
Xun Ji
2

  1. Key laboratory of Intelligent Technology and Application of Marine Equipment (Harbin Engineering University), Ministry of Education, Harbin, 150001, China
  2. College of Marine Electrical Engineering, Dalian Maritime University, Dalian, 116026, China
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Abstrakt

Sharing research data from public funding is an important topic, especially now, during times of global emergencies like the COVID-19 pandemic, when we need policies that enable rapid sharing of research data. Our aim is to discuss and review the revised Draft of the OECD Recommendation Concerning Access to Research Data from Public Funding. The Recommendation is based on ethical scientific practice, but in order to be able to apply it in real settings, we suggest several enhancements to make it more actionable. In particular, constant maintenance of provided software stipulated by the Recommendation is virtually impossible even for commercial software. Other major concerns are insufficient clarity regarding how to finance data repositories in joint private-public investments, inconsistencies between data security and user-friendliness of access, little focus on the reproducibility of submitted data, risks related to the mining of large data sets, and sensitive (particularly personal) data protection. In addition, we identify several risks and threats that need to be considered when designing and developing data platforms to implement the Recommendation (e.g., not only the descriptions of the data formats but also the data collection methods should be available). Furthermore, the non-even level of readiness of some countries for the practical implementation of the proposed Recommendation poses a risk of its delayed or incomplete implementation.
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Bibliografia

  1.  OECD, Recommendation of the council concerning access to research data from public funding. [Online]. https://legalinstruments.oecd. org/en/instruments/OECDLEGAL-0347
  2.  D.N. Le, A. Shahbazian, and N. Medvidovic, “An Empirical Study of Architectural Decay in Open-Source Software”, IEEE International Conference on Software Architecture (ICSA), 2018.
  3.  K.R. Sipido, “Irreproducible results in preclinical cardiovascular research: Opportunities in times of need”, Cardiovasc. Res. 115 (3), E34–E36 (2019).
  4.  D.A. Eisner, “Reproducibility of science: Fraud, impact factors and carelessness”, J. Mol. Cell. Cardiol. 114, 364‒368 (2018).
  5.  L. Madeyski and B. Kitchenham, “Would wider adoption of reproducible research be beneficial for Empir. Softw. Eng. research?”, J. Intell. Fuzzy Syst. 32(2), 1509–1521 (2017).
  6.  T. Lewowski and L. Madeyski, “Creating Evolving Project Data Sets in Software Engineering”, Integr. Res. Pract. Softw. Eng. 851, 1–14 (2020), doi: 10.1007/978-3-030-26574-8_1.
  7.  T. Moberly, “Should we be worried about the NHS selling patient data?”, BMJ 368, m113 (2020). doi: 10.1136/bmj.m113.
  8.  C. Aicardi, L. Del Savio, E.S. Dove, F. Lucivero, N. Tempini, and B. Prainsack, “Emerging ethical issues regarding digital health data. On the World Medical Association Draft Declaration on Ethical Considerations Regarding Health Databases and Biobanks”, Croat. Med. J. 57(2), 207–213 (2016), doi: 10.3325/cmj.2016.57.207.
  9.  E. Mahase, “Government hands Amazon free access to NHS information”, BMJ 367, l6901 (2019), doi: 10.1136/bmj.l6901.
  10.  A. Ballantyne, “How should we think about clinical data ownership?”, J. Med. Ethics 46(5), 289–294 (2020).
  11.  B. Kitchenham, L. Madeyski, D. Budgen, J. Keung, P. Brereton, S. Charters, S. Gibbs, and A. Pohthong, “Robust Statistical Methods for Empir. Softw. Eng.”, Empir. Softw. Eng. 22(2), 579–630 (2017).
  12.  Ch. Edwards, “Malevolent machine learning”, Commun. ACM 62(12), 13–15 (2019).
  13.  S. Greengard, “An inability to reproduce”, Commun. ACM 62(9), 13–15 (2019).
  14.  F. Pasquale, “When machine learning is facially invalid”, Commun. ACM 61(8), 25–27 (2018).
  15.  J.P.A. Ioannidis: “The mass production of redundant, misleading, and conflicted systematic reviews and meta-analyses”, Milbank Q. 94, 485–514 (2016).
  16.  J.B. Carlisle, “Data fabrication and other reasons for nonrandom sampling in 5087 randomised, controlled trials in anaesthetic and general medical journals”, Anaesthesia 72(8), 944–952, (2017)
  17.  Ch.H.J. Hartgerink, J.M. Wicherts, and M.A. van Assen, “The value of statistical tools to detect data fabrication”, Res. Ideas Outcomes 2, e8860 (2016).
  18.  Ch.H.J. Hartgerink, J.G. Voelkel, J.M. Wicherts, and Marcel A.L.M. van Assen. “Detection of Data Fabrication Using Statistical Tools”, PsyArXiv, 2019, doi: 10.31234/osf.io/jkws4.
  19.  N.J.L. Brown and J.A.J. Heathers, “The grim test: A simple technique detects numerous anomalies in the reporting of results in psychology”, Soc. Psychol. Personal Sci. 8(4), 363–369 (2017).
  20.  J.A. Heathers, J. Anaya, T. van der Zee, and N. Brown “Recovering data from summary statistics: Sample Parameter Reconstruction via Iterative TEchniques (SPRITE)”, PeerJ Preprints, e26968v1 (2018). doi: 10.7287/peerj.preprints.26968v1.
  21.  S. Al-Marzouki, S. Evans, T. Marshall, and I. Roberts, “Are these data real? Statistical methods for the detection of data fabrication in clinical trials”, BMJ, 331(7511), 267–270 (2005), doi: 10.1136/bmj.331.7511.267.
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Autorzy i Afiliacje

Lech Madeyski
1
ORCID: ORCID
Tomasz Lewowski
1
ORCID: ORCID
Barbara Kitchenham
2
ORCID: ORCID

  1. Faculty of Computer Science and Management, Wroclaw University of Science and Technology, ul. Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland
  2. School of Computing and Mathematics, Keele University, Keele, Staffordshire, ST5 5BG, UK
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Abstrakt

In this present study, the effect of the shot peening process on fatigue life, surface hardness and corrosion properties of a low carbon alloy steel is examined at room temperature. The research article addresses the effect of shot peening by varying the process parameters such as peening distance and pressure with amachrome as shots. The experiment is designed by means of full factorial design. The experimental result reveals that the pressure and distance are the most significant factors in the shot peening process. The results illustrate that the average pressure of 7 bar and distance of 100 mm improves fatigue life by 1.5% of unpeened material under 20 Hz frequency while corrosion resistance improves by 4% with unpeening of the low carbon alloy steel by using amachrome as a shot.
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Bibliografia

  1.  K. Miková, S. Bagherifard, O. Bokuvka, M. Guagliano, and L. Trško, “Fatigue behavior of X70 microalloyed steel after severe shot peening”, Int. J. Fatigue 55, 33‒42 (2013).
  2.  H. Kovacı, Y.B. Bozkurt, A.F. Yetim, M. Aslan, and A. Çelik, “The effect of surface plastic deformation produced by shot peening on corrosion behavior of a low-alloy steel”, Surf. Coat. Technol. 360, 78‒86 (2019).
  3.  O. Unal, Effect of pre-heat treatment on fatigue behavior of severe shot peened and plasma nitrided SAE4140 steel”, J. Aeronaut. Space Technol. 11(1), 57‒63 (2018).
  4.  O. Takakuwa and H. Soyama, “Effect of residual stress on the corrosion behavior of austenitic stainless steel”, Adv. Chem. Eng. Sci. 5(1), 62 (2014).
  5.  A.A. Ahmed, M. Mhaede, M. Wollmann, and L. Wagner, “Effect of micro shot peening on the mechanical properties and corrosion behavior of two microstructure Ti–6Al–4V alloy”, Appl. Surf. Sci. 363, 50‒58 (2016).
  6.  V. Azar, B. Hashemi, and M.R. Yazdi, “The effect of shot peening on fatigue and corrosion behavior of 316L stainless steel in Ringer’s solution”, Surf. Coat. Technol. 204(21‒22), 3546‒3551 (2010).
  7.  B. Hashemi, M.R. Yazdi, and V. Azar, “The wear and corrosion resistance of shot peened– nitrided 316L austenitic stainless steel”, Mater. Des. 32(6), 3287‒3292 (2011).
  8.  S.M. Hassani-Gangaraj, A. Moridi, M. Guagliano, A. Ghidini, and M. Boniardi, “The effect of nitriding, severe shot peening and their combination on the fatigue behavior and micro- structure of a low-alloy steel”, Int. J. Fatigue 62, 67‒76 (2014).
  9.  O. Hatamleh, J. Lyons, and R. Forman, “Laser peening and shot peening effects on fatigue life and surface roughness of friction stir welded 7075‐T7351 aluminum”, Fatigue Fract. Eng. Mater. Struct. 30(2), 115‒130 (2007).
  10.  M. Hilpert and L. Wagner, “Corrosion fatigue behavior of the high-strength magnesium alloy AZ 80”, J. Mater. Eng. Perform. 9(4), 402‒407 (2000).
  11.  S. Kalainathan, S. Sathyajith, and S. Swaroop, “Effect of laser shot peening without coating on the surface properties and corrosion behavior of 316L steel”, Opt. Lasers Eng. 50(12), 1740‒1745 (2012).
  12.  S.A. Khan, M.S. Bhuiyan, Y. Miyashita, Y. Mutoh, and T. Koike, “Corrosion fatigue behavior of die-cast and shot-blasted AM60 magnesium alloy”, Mater. Sci. Eng. A 528(4‒5), 1961‒1966 (2011).
  13.  G.H. Majzoobi, J. Nemati, A.N. Rooz, and G.H. Farrahi, “Modification of fretting fatigue behavior of AL7075–T6 alloy by the application of titanium coating using IBED technique and shot peening”, Tribol. Int. 42(1), 121‒129 (2009).
  14.  Y. Shadangi, K. Chattopadhyay, S.B. Rai, and V. Singh, “Effect of LASER shock peening on microstructure, mechanical properties and corrosion behavior of interstitial free steel”, Surf. Coat. Technol. 280, 216‒224 (2015).
  15.  Y. Tan, G. Wu, J.M. Yang, and T. Pan, “Laser shock peening on fatigue crack growth behaviour of aluminium alloy”, Fatigue Fract. Eng. Mater. Struct. 27(8), 649‒656 (2004).
  16.  C. Ye, S. Suslov, B.J. Kim, E.A. Stach, and G.J. Cheng, “Fatigue performance improvement in SAE4140 steel by dynamic strain aging and dynamic precipitation during warm laser shock peening”, Acta Mater. 59(3), 1014‒1025 (2011).
  17.  Standard practice for cleaning, descaling and passivation of stainless steels parts, equipment and systems, A380, Annual Book of ASTM Standards, American Society for Testing and Materials, 1999
  18.  C. Liu, H. Zheng, X. Gu, B. Jiang, and J. Liang, “Effect of severe shot peening on corrosion behavior of AZ31 and AZ91 magnesium alloys”, J. Alloy. Compd. 770 500‒506 (2019).
  19.  R. Ebner, P. Gruber, W. Ecker, O. Kolednik, M. Krobath, and G. Jesner, “Fatigue damage mechanisms and damage evolution near cyclically loaded edges”, Bull. Pol. Ac.: Tech. 58(2), 267‒279 (2010).
  20.  Standard test method for micro indentation hardness of materials, E384-99, Annual Book of ASTM Standards, American Society for Testing and Materials, 1999.
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Autorzy i Afiliacje

C. Selva Senthil Prabhu
1
P. Ashoka Varthanan
2
T. Ram Kumar
1

  1. Department of Mechanical Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi – 642003, India
  2. Department of Mechanical Engineering, Sri Krishna College of Engineering and Technology, Coimbatore – 642003, India
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Abstrakt

In the present research, the wear behaviour of magnesium alloy (MA) AZ91D is studied and optimized. MA AZ91D is casted using a die-casting method. The tribology experiments are tested using pin-on-disc tribometer. The input parameters are sliding velocity (1‒3 m/s), load (1‒5 kg), and distance (0.5‒1.5 km). The worn surfaces are characterized by a scanning electron microscope (SEM) with energy dispersive spectroscopy (EDS). The response surface method (RSM) is used for modelling and optimising wear parameters. This quadratic equation and RSM-optimized parameters are used in genetic algorithm (GA). The GA is used to search for the optimum values which give the minimum wear rate and lower coefficient of friction. The developed equations are compared with the experimental values to determine the accuracy of the prediction.
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Bibliografia

  1.  S. Kulkarni, D. Edwards, E. Parn, C. Chapman, C. Aigbavboa, and R. Cornish, “Evaluation of vehicle light-weighting to reduce greenhouse gas emissions with focus on magnesium substitution”, J. Eng. Design Technol. 16(6), 869‒888 (2018).
  2.  K. Kudła, J. Iwaszko, and M. Strzelecka, “Surface modification of AZ91 magnesium alloy using GTAW technology”, Bull. Pol. Ac.: Tech.65(6), 917‒926 (2017).
  3.  K. Soorya Prakash, P. Balasundar, S. Nagaraja, P.M. Gopal, and V. Kavimani, “Mechanical and wear behaviour of Mg–SiC–Gr hybrid composites”, J. Magnes. Alloy. 4, 197–206 (2016).
  4.  D. Mehra, M. Mahapatra, and S. Harsha, “Optimizations of RZ5-TiC magnesium matrix composite wear parameters using Taguchi approach”, Ind. Lubr. Tribol. 70(5), 907‒914 (2018).
  5.  E. Ilanaganar and S. Anbuselvan, “Wear mechanisms of AZ31B magnesium alloy during dry sliding condition, Mater. Today: Proceedings 5, 628–635 (2018).
  6.  E. Suneesh and M. Sivapragash, “Comprehensive studies on processing and characterization of hybrid magnesium composites”, Mater. Manuf. Process. 33, 1324‒1345 (2018).
  7.  T. Yue1 and K. Huang, “Laser cladding of Cu0.5NiAlCoCrFeSi high entropy alloy on AZ91D magnesium substrates for improving wear and corrosion resistance”, World J. Eng. 9(2), 119–124 (2012).
  8.  M. Mondet, E. Barraud, S. Lemonnier, J. Guyon, N. Allain, and T. Grosdidier, “Microstructure and mechanical properties of AZ91 magnesium alloy developed by Spark Plasma Sintering”, Acta Mater. 119, 55‒67 (2016).
  9.  P.J. Blau and M. Walukas, “Sliding friction and wear of magnesium alloy AZ91D produced by two different methods”, Tribol. Int. 33, 573–579 (2000).
  10.  S.C. Cagan, M. Aci, B.B. Buldum, and C. Aci, “Artificial neural networks in mechanical surface enhancement technique for the prediction of surface roughness and microhardness of magnesium alloy”, Bull. Pol. Ac.: Tech. 67(4), 729‒739 (2019).
  11.  S. García-Rodríguez, B. Torres, A. Maroto, A.J. Lopez, E. Otero, and J. Rams, “Dry sliding wear behavior of globular AZ91 magnesium alloy and AZ91/SiCp composites”, Wear 390–391, 1–10 (2017).
  12.  D. Thirumalaikumarasamy, V. Balasubramanian, and S. Sree Sabari, “Prediction and optimization of process variables to maximize the Young’s modulus of plasma sprayed alumina coatings on AZ31B magnesium alloy”, J. Magnes. Alloy. 5, 133–145 (2017).
  13.  A., Mohammadzadeha, M. Ramezania, and A.M. Ghaedib, “Synthesis and characterization of Fe2O3–ZnO–ZnFe2O4 / carbon nanocomposite and its application to removal of bromophenol blue dye using ultrasonic assisted method: Optimization by response surface methodology and genetic algorithm”, J. Taiwan Inst. Chem. Eng. 59, 1–10 (2015).
  14.  M. Vakili-Azghandi, A. Fattah-Alhosseini, and M.K. Keshavarz, “Optimizing the electrolyte chemistry parameters of PEO coating on 6061 Al alloy by corrosion rate measurement: Response surface methodology”, Measurement 124, 252‒259 (2018).
  15.  A. Ciszkiewicz and G. Milewski, “Ligament-based spine-segment mechanisms”, Bull. Pol. Ac.: Tech. 66(5), 705‒712 (2018).
  16.  M. Sivapragash, P. Kumaradhas, B. Stanly Jones Retnam, X. Felix Joseph, and U.T.S. Pillai, “Taguchi based genetic approach for optimizing the PVD process parameter for coating ZrN on AZ91D magnesium alloy”, Mater. Des. 90. 713–722 (2016).
  17.  Y. Li and X. Wang, “Improved dolphin swarm optimization algorithm based on information entropy”, Bull. Pol. Ac.: Tech. 67(4), 679‒685 (2019).
  18.  D. Zhang et al., “Effects of minor Sr addition on the microstructure, mechanical properties and creep behavior of high pressure die casting AZ91‒0.5RE based alloy”, Mater. Sci. Eng., A 693, 51‒59 (2017).
  19.  M. Nouioua et al., “Investigation of the performance of the MQL, dry, and wet turning by response surface methodology (RSM) and artificial neural network (ANN)”, Int. J. Adv. Manuf. Technol. 93, 2485–2504 (2017).
  20.  I.M. Yusri et al., “A review on the application of response surface method and artificial neural network in engine performance and exhaust emissions characteristics in alternative fuel”, Renew. Sust. Energy Rev. 90. 665–686 (2018).
  21.  S. Jacob and R. Banerjee, “Modeling and Optimization of Anaerobic Codigestion of Potato Waste and Aquatic Weed by Response Surface Methodology and Artificial Neural Network coupled Genetic Algorithm”, Bioresour. Technol. 214, 386-395 (2016).
  22.  S. Shanavas and J. Edwin Raja Dhas, “Parametric optimization of friction stir welding parameters of marine grade aluminium alloy using response surface methodology”, Trans. Nonferrous Met. Soc. China 27, 2334−2344 (2017).
  23.  M.N.M. Salleh, M. Ishak, M.M. Quazi, and M.H. Aiman, “Microstructure, mechanical, and failure characteristics of laser-microwelded AZ31B Mg alloy optimized by response surface methodology”, Int. J. Adv. Manuf. Technol. 99, 985–1001 (2018).
  24.  W. Yu, D. Chen, L. Tian, H. Zhao, and X. Wang, “Self-lubricate and anisotropic wear behavior of AZ91D magnesium alloy reinforced with ternary Ti2AlC MAX phases”, J. Mater. Sci. Technol. 35, 275‒284 (2019).
  25.  B.O. Ighose et al., “Optimization of biodiesel production from Thevetia peruviana seed oil by adaptive neuro-fuzzy inference system coupled with genetic algorithm and response surface methodology”, Energy Convers. Manage. 132. 231–240 (2017).
  26.  M.E. Turan, Y. Sun, and Y. Akgul, “Mechanical, tribological and corrosion properties of fullerene reinforced magnesium matrix composites fabricated by semi powder metallurgy”, J. Alloys Compd. 740, 1149‒1158 (2018).
  27.  C. Dong, J. Sun, Z. Cheng, and Y. Hou, “Preparation and tribological properties of a microemulsion for magnesium alloy warm rolling”, Ind. Lubr. Tribol. 71(1), 74‒82 (2018).
  28.  A. Zafari, H.M. Ghasemi, and R. Mahmudi, “Tribological behavior of AZ91D magnesium alloy at elevated temperatures”, Wear 292–293, 33–40 (2012).
  29.  C. Liang, X. Han, T.F. Su, C. Li, and J. An, “Sliding Wear Map for AZ31 Magnesium Alloy”, Tribol. Trans. 57, 1077‒1085 (2014).
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Autorzy i Afiliacje

M. Beniyel
1
M. Sivapragash
2
S.C. Vettivel
3
P. Senthil Kumar
4
K.K. Ajith Kumar
5
K. Niranjan
6

  1. Department of Mechanical Engineering, Anna University, Chennai, Tamil Nadu, India
  2. Department of Mechanical Engineering, Universal College of Engineering and Technology, Vallioor, Tirunelveli, Tamilnadu, India
  3. Department of Mechanical Engineering, Chandigarh College of Engineering and Technology, Chandigarh, India
  4. Department of Mechanical Engineering, MET Engineering College, Tamilnadu, India
  5. Department of Mechanical Engineering, Rohini College of Engineering and Technology, Tamilnadu, India
  6. Department of Manufacturing Engg, Annamalai University, Annamalai Nagar-608 002, Tamilnadu, India
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Abstrakt

Activated tungsten inert gas (ATIG) welding has a good depth of penetration (DOP) as compared to the conventional tungsten inert gas (TIG) welding. This paper is mainly focused on ATIG characterization and mechanical behavior of aluminum alloy (AA) 6063-T6 using SiO2 flux. The characterization of the base material (BM), fusion zone (FZ), heat affected zone (HAZ) and, partially melted zone is carried out using the suitable characterization methods. The weld quality is characterized using ultrasonic-assisted non-destructive evaluation. A-scan result confirms that the ATIG welded samples have more DOP and less bead width as compared to conventional TIG. The recorded tensile strength of ATIG with SiO2 is better than the conventional TIG welding. The failure mode is ductile for ATIG welding with larger fracture edges and is brittle in the case of conventional TIG welding.

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Bibliografia

  1.  S. Jannet, P.K. Mathews, and R. Raja, “Comparative investigation of friction stir welding and fusion welding of 6061T6 – 5083 O aluminum alloy based on mechanical properties and microstructure”, Bull. Pol. Ac.: Tech. 62(4), 791‒795 (2014), doi: 10.2478/bpasts-2014-0086.
  2.  S.T. Amancio-Filho, S. Sheikhi, J.F. dos Santos, and C. Bolfarini, “Preliminary study on the microstructure and mechanical properties of dissimilar friction stir welds in aircraft aluminium alloys 2024-T351 and 6056-T4”, J. Mater. Process. Technol. 206. 132–142 (2008), doi: 10.1016/j.jmatprotec.2007.12.008.
  3.  P. Mukhopadhyay, “Alloy Designation, Processing, and Use of AA6XXX Series Aluminium Alloys”, ISRN Metall. 2012, 165082 (2012), doi: 10.5402/2012/165082.
  4.  B. Choudhury and M. Chandrasekaran, “Investigation on welding characteristics of aerospace materials – A review”, Mater. Today Proc. 4, 7519–7526 (2017), doi: 10.1016/j.matpr.2017.07.083.
  5.  R.R. Ambriz and V. Mayagoitia, “Welding of Aluminum Alloys”, in Welding, Brazing and Soldering, pp. 722–739, ASM International, 2018. doi: 10.31399/asm.hb.v06.a0001436.
  6. [6]  P.J. Modenesi, “The chemistry of TIG weld bead formation”, Weld. Int. 29, 771–782 (2015), doi: 10.1080/09507116.2014.932990.
  7.  A.K. Singh, V. Dey, and R.N. Rai, “Techniques to improveweld penetration in TIG welding (A review)”, Mater. Today Proc. 4, 1252–1259 (2017), doi: 10.1016/j.matpr.2017.01.145.
  8.  R.S. Vidyarthy and D.K. Dwivedi, “Activating flux tungsten inert gas welding for enhanced weld penetration”, J. Manuf. Process. 22, 211–228 (2016), doi: 10.1016/j.jmapro.2016.03.012.
  9.  R.S. Vidyarthy and D.K. Dwivedi, “Microstructural and mechanical properties assessment of the P91 A-TIG weld joints”, J. Manuf. Process. 31, 523–535 (2018), doi: 10.1016/j.jmapro.2017.12.012.
  10.  K.D. Ramkumar, V. Varma, M. Prasad, N.D. Rajan, and N.S. Shanmugam, “Effect of activated flux on penetration depth, microstructure and mechanical properties of Ti-6Al-4V TIG welds”, J. Mater. Process. Technol. 261, 233–241 (2018), doi: 10.1016/j.jmatprotec.2018.06.024.
  11.  H. Kumar and N.K. Singh, “Performance of activated TIG welding in 304 austenitic stainless steel welds”, Mater. Today Proc. 4, 9914–9918 (2017), doi: 10.1016/j.matpr.2017.06.293.
  12.  R.S. Vidyarthy, A. Kulkarni, and D.K. Dwivedi, “Study of microstructure and mechanical property relationships of A-TIG welded P91–316L dissimilar steel joint”, Mater. Sci. Eng. A. 695, 249–257 (2017), doi: 10.1016/j.msea.2017.04.038.
  13.  E.R. Imam Fauzi, M.S. Che Jamil, Z. Samad, and P. Muangjunburee, “Microstructure analysis and mechanical characteristics of tungsten inert gas and metal inert gas welded AA6082-T6 tubular joint: A comparative study”, Trans. Nonferrous Met. Soc. China (English Ed.) 27, 17–24 (2017), doi: 10.1016/S1003-6326(17)60003-7.
  14.  R.S. Coelho, A. Kostka, J.F. dos Santos, and A. Kaysser-Pyzalla, “Friction-stir dissimilar welding of aluminium alloy to high strength steels: Mechanical properties and their relation to microstructure”, Mater. Sci. Eng. A. 556, 175–183 (2012), doi: 10.1016/j.msea.2012.06.076.
  15.  A.S. Zoeram, S.H.M. Anijdan, H.R. Jafarian, and T. Bhattacharjee, “Welding parameters analysis and microstructural evolution of dissimilar joints in Al/Bronze processed by friction stir welding and their effect on engineering tensile behavior”, Mater. Sci. Eng. A. 687, 288–297, (2017). doi: 10.1016/j.msea.2017.01.071.
  16.  K.H. Dhandha and V.J. Badheka, “Effect of activatingfluxes on weld bead morphology of P91 steelbead-on-platewelds by flux assisted tungsteninert gas welding process”, J. Manuf. Process. 17, 48–57 (2015), doi: 10.1016/j.jmapro.2014.10.004.
  17.  A. Krajewski, W. Włosiński, T. Chmielewski, and P. Kołodziejczak, “Ultrasonic-vibration assisted arc-welding of aluminum alloys”, Bull. Pol. Ac.: Tech. 60(4), 841‒852 (2012), doi: 10.2478/v10175-012-0098-2.
  18.  H.S. Patil and S.N. Soman, “Effect of tool geometry and welding speed on mechanical properties and microstructure of friction stir welded joints of aluminum alloys AA6082-T6”, Arch. Mech. Eng. 61, 455‒468 (2014), doi: 10.2478/meceng-2014-0026.
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Autorzy i Afiliacje

Rajiv Kumar
1
S.C. Vettivel
2
Harmesh Kumar Kansal
1

  1. Department of Mechanical Engineering, UIET, Panjab University, Chandigarh, India
  2. Department of Mechanical Engineering, Chandigarh College of Engineering and Technology (Degree Wing), Chandigarh, India
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Abstrakt

In this work, conversion coatings based on nitrates Ca(NO 3) 2 and Zn(NO 3) 2 were produced on the surface of MgZn49Ca4 to protect against corrosion. The main aim of this study was to prepare dense and uniform coatings using a conversion method (based on nitrates Ca(NO 3) 2 and Zn(NO 3) 2) for resorbable Mg alloys. The scientific goal of the work was to determine the pathway and main degradation mechanisms of samples with nitrate-based coatings as compared with an uncoated substrate. Determining the effect of the coatings produced on the Mg alloy was required to assess the protective properties of Mg alloy-coating systems. For this purpose, the morphology and chemical composition of coated samples, post corrosion tests and structural tests of the substrate were performed (optical microscopy, SEM/EDS). Immersion and electrochemical tests of samples were also carried out in Ringer’s solution at 37°C. The results of immersion and electrochemical tests indicated lower corrosion resistance of the substrate as compared with coated samples. The hydrogen evolution rate of the substrate increased with the immersion time. For coated samples, the hydrogen evolution rate was more stable. The ZnN coating (based on Zn(NO 3) 2) provides better corrosion protection because the corrosion product layer was uniform, while the sample with a CaN coating (based on Ca(NO 3) 2) displayed clusters of corrosion products. It was found that pitting corrosion on the substrate led to the complete disintegration and non-uniform corrosion of the coated samples, especially the CaN sample, due to the unevenly-distributed products on its surface.
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Bibliografia

  1.  K. Kowalski and M. Jurczyk, “Porous magnesium based bionanocomposites for medical application”, Arch. Metall. Mater. 60(2), 1433‒1435, (2015).
  2.  A. Milenin, M. Gzyl, T. Rec, and B. Plonka, “Computer aided design of wires extrusion from biocompatible mg-ca magnesium alloy”, Arch. Metall. Mater. 59(2), 551‒556 (2014).
  3.  F. Witte, N. Hort, C. Vogt, S. Cohen, K.U. Kainer, R. Willumeit, and F. Feyerabend, “Degradable biomaterials based on magnesium corrosion”, Curr. Opin. Solid. State Mater Sci. 12, 63‒72 (2008).
  4.  S. Kumar, D. Kumar, and J. Jain, “Surface and interface characteristics of CeO2 doped Al2O3 coating on solution treated and peak aged AZ91 Mg alloy”, Surf. Coat. Tech. 332, 511‒521 (2017).
  5.  Z.Xu, U.Eduok, and J.Szpunar, “Effect of annealing temperature on the corrosion resistance of MgO coatings on Mg alloy”, Surf. Coat. Tech. 357, 691‒697 (2019).
  6.  Y.Gao, L.Zhao, X.Yao, R.Hang, and B.Tang, “Corrosion behavior of porous ZrO2 ceramic coating on AZ31B magnesium alloy”, Surf. Coat. Tech. 349, 434‒441 (2018).
  7.  R. Ji, M. Ma, Y. He, C. Liu, and J. Wu, “Improved corrosion resistance of Al2O3 ceramic coatings on AZ31 magnesium alloy fabricated through cathode plasma electrolytic deposition combined with surface pore-sealing treatment”, Ceram. Int. 44, 15192‒15199 (2018).
  8.  P. Liu, X. Pan, W. Yang, K. Cai, and Y. Chen, “Al2O3-ZrO2 ceramic coatings fabricated on WE43 magnesium alloy by cathodic plasma electrolytic deposition”, Mater. Lett. 70, 16‒18 (2012).
  9.  J.V. Rau, I. Antoniac, M. Filipescu, C. Cotrut, and M. Dinescu, “Hydroxyapatite coatings on Mg-Ca alloy prepared by Pulsed Laser Deposition: Properties and corrosion resistance in Simulated Body Fluid”, Ceram. Int. 44, 16678‒16687 (2018).
  10.  S. Jiang, S. Cai, Y. Lin, X. Bao, and G. Xu, “Effect of alkali/acid pretreatment on the topography and corrosion resistance of as-deposited CaP coating on magnesium alloys”, J. Alloys. Compd. 793, 202‒211 (2019).
  11.  J.G. Acheson, S. McKillop, P. Lemoine, A.R. Boyd, and B.J. Meenan, “Control of magnesium alloy corrosion by bioactive calcium phosphate coating: Implications for resorbable orthopaedic implants”, Materialia 6, 1‒10 (2019).
  12.  P. Shi, B. Niu, E. Shanshan, Y. Chen, and Q. Li, “Preparation and characterization of PLA coating and PLA/MAO composite coatings on AZ31 magnesium alloy for improvement of corrosion resistance”, Surf. Coat. Tech. 262, 26‒32 (2015).
  13.  S. Manna, A.M. Donnell, N. Kaval, and F. Marwan, “Improved design and characterization of PLGA/PLA-coated Chitosan based micro- implants for controlled release of hydrophilic drugs”, Int. J. Pharm. 547(1–2), 122‒132 (2018).
  14.  L. Li, L. Cui, R. Zeng, S. Li, and M. Bobby Kannan, “Advances in functionalized polymer coatings on biodegradable magnesium alloys – A review”, Acta Biomater. 79, 23‒36 (2018).
  15.  Y. Lin, S. Cai, S. Jiang, D. Xie, and G. Xu, “Enhanced corrosion resistance and bonding strength of Mg substituted β-tricalcium phosphate/ Mg(OH)2 composite coating on magnesium alloys via one-step hydrothermal method”, J. Mech. Behav. Biomed. 90, 547‒555 (2019).
  16.  H.R. Bakhsheshi-Rad, E. Hamzah, A.F. Ismail, M. Aziz, and A. Chami, “In vitro degradation behavior, antibacterial activity and cytotoxicity of TiO2-MAO/ZnHA composite coating on Mg alloy for orthopedic implants”, Surf. Coat. Tech. 334, 450‒460 (2018).
  17.  H.R. Bakhsheshi-Rad, A.F. Ismail, M. Aziz, Z. Hadisi, M. Omidi, and X. Chen, “Antibacterial activity and corrosion resistance of Ta2O5 thin film and electrospun PCL/MgO-Ag nanofiber coatings on biodegradable Mg alloy implants”, Ceram. Int. 45, (9), 11883‒11892 (2019).
  18.  E. Yılmaz, B. Çakıroğlu, A. Gökçe, F. Findik, and M. Özacar, “Novel hydroxyapatite/graphene oxide/collagen bioactive composite coating on Ti16Nb alloys by electrodeposition”, Mater. Sci. Eng:. C 101, 292‒305 (2019).
  19.  M. Nowak, B. Płonka, A. Kozik, M. Karaś, M. Mitka, and M. Gawlik, “Conversion coatings produced on AZ61 magnesium alloy by low-voltage process”, Arch. Metall. Mater. 61, 419‒424 (2016).
  20.  R. Zen, G. Sun, Y. Song, F. Zhang, S. Li, H. Cui, and E. Han, “Influence of solution temperature on corrosion resistance of Zn-Ca phosphate conversion coating on biomedical Mg-Li-Ca alloys”, Trans. Nonferrous. Met. Soc. China 23(11), 3293‒3299 (2013).
  21.  W. Zai, X. Zhang, Y. Zhao, H.C. Man, G. Li, and J. Lian, “Comparison of corrosion resistance and biocompatibility of magnesium phosphate (MgP), zinc phosphate (ZnP) and calcium phosphate (CaP) conversion coatings on Mg alloy”, Surf. Coat. Tech. 397, 1‒17 (2020).
  22.  N. Van Phuong and S. Moon, “Comparative corrosion study of zinc phosphate and magnesium phosphate conversion coatings on AZ31 Mg alloy”, Mater. Lett. 122, 341‒344 (2014).
  23.  Z. Gao, X. Li, and S. Jiang, “Current status, opportunities and challenges in chemical conversion coatings for zinc”, Colloid Surface A 546, 221‒236 (2018).
  24.  J. Hofstetter, M. Becker, E. Martinelli, A.M. Weinberg, B. Mingler, H. Kilian, S. Pogatscher, P.J. Uggowitzer, and J.F. Loffler, High- Strength Low-Alloy (HSLA) Mg–Zn–Ca alloys with Excellent Biodegradation Performance, JOM 66(4), 566‒572 (2014).
  25.  S. Wasiur-Rahman, and M. Medraj, “Critical assessment and thermodynamic modeling of the binary Mg–Zn, Ca–Zn and ternary Mg– Ca–Zn systems”, Intermetallics 17, 847–864 (2009).
  26.  S. Kim, Y. Kim, Y.K. Lee, and M. Lee, “Determination of ideal Mg–35Zn–xCa alloy depending on Ca concentration for biomaterials”, J. Alloys Compd.766, 994‒1002 (2018).
  27.  P. Dudek, A. Fajkiel, T. Reguła, and K. Saja, “Selected problems of a technology of the AZ91 magnesium alloy melt treatment”, Prace Instytutu Odlewnictwa, zeszyt 1, Tom XLIX, 27‒42 (2009).
  28.  M. Liu, P. Schmutz, P.J. Uggowitzer, G. Song, and A. Atrens, “The influence of yttrium (Y) on the corrosion of Mg–Y binary alloys”, Corros. Sci. 52, 3687‒3701 (2010).
  29.  F. Qin, G. Xie, Z. Dan, S. Zhu, and I. Seki, “Corrosion behavior and mechanical properties of Mg-Zn-Ca amorphous alloys”, Intermetallics 42, 9‒13 (2013).
  30.  A. Srinivasan, C. Blawert, Y. Huang, C.L. Mendis, K.U. Kainer, and N. Hort, “Corrosion behavior of Mg-Gd-Zn based alloys in aqueous NaCl solution”, J. Magnes. Alloys. 2, 245‒256 (2014).
  31.  J. Sunb, S. Cai, Q. Li, Z. Li, and G. Xu, “UV-irradiation induced biological activity and antibacterial activity of ZnO coated magnesium alloy”, Mater. Sci. Eng: C 114, 1‒9 (2020).
  32.  H.R. Bakhsheshi-Rad, E. Hamzah, A.F. Ismail, M. Aziz, M. Kasiri-Asgarani, and H. Ghayour, “In vitro corrosion behavior, bioactivity, and antibacterial performance of the silver-doped zinc oxide coating on magnesium alloy”, Mater. Corros. 68, 1228‒1236 (2017).
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Autorzy i Afiliacje

Katarzyna Cesarz-Andraczke
1

  1. Department of Engineering Materials and Biomaterials, Faculty of Mechanical Engineering, Silesian University of Technology, ul. Konarskiego 18A, 44-100 Gliwice, Poland
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Abstrakt

This work attempts to use nitrogen gas as a shielding gas at the cutting zone, as well as for cooling purposes while machining stainless steel 304 (SS304) grade by Computer Numerical Control (CNC) lathe. The major influencing parameters of speed, feed and depth of cut were selected for experimentation with three levels each. Totally 27 experiments were conducted for dry cutting and N2 gaseous conditions. The major influencing parameters are optimized using Taguchi and Firefly Algorithm (FA). The improvement in obtaining better surface roughness and Material Removal Rate (MRR) is significant and the confirmation results revealed that the deviation of the experimental results from the empirical model is found to be within 5%. A significant improvement of reduction of the specific cutting energy by 2.57 % on average was achieved due to the reduction of friction at the cutting zone by nitrogen gas in CNC turning of SS 304 alloy.

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Bibliografia

  1.  Ch.Y. Nee, M.S. Saad, A.M. Nor, M.Z. Zakaria, and M.E. Baharudin, “Optimal process parameters for minimizing the surface roughness in CNC lathe machining of Co28Cr6Mo medical alloy using differential evolution”, Int. J. Adv. Manuf. Technol. 97(1‒4), 1541‒1555 (2018).
  2.  B. Naveena, S.S. MariyamThaslima, V. Savitha, B. Naveen Krishna, D. Samuel Raj, and L. Karunamoorthy, “Simplified MQL System for Drilling AISI 304 SS using Cryogenically Treated Drills”, Mater. Manuf. Process. 32 (15), 1679‒1684 (2017).
  3.  D. Murat, C. Ensarioglu, N. Gursakal, A. Oral, and M.C. Cakir, “Surface roughness analysis of greater cutting depths during hard turning”, Mater. Test. 59 (9), 795‒802 (2017).
  4.  D. Tanikić, V. Marinković, M. Manić, G. Devedžić, and S. Ranđelović, “Application of response surface methodology and fuzzy logic basedsystem for determining metal cutting temperature”, Bull. Pol Ac.: Tech. 64(2),435‒445 (2016).
  5.  M. Dhananchezian, M. Rishabapriyan, G. Rajashekar, and S. Sathya Narayanan, “Study the Effect of Cryogenic Cooling on Machinability Characteristics During Turning Duplex Stainless Steel 2205”, Mater. Today: Proc. 5, 12062–12070 (2018).
  6.  C.A. Bolu, O.S. Ohunakin, E.T. Akinlabi, and D.S. Adelekan, “A Review of Recent Application of Machining Techniques, based on the Phenomena of CNC Machining Operations”, Elsevier Procedia Manuf. 35, 1054‒1060 (2019).
  7.  D. Kondayyaand and A. Gopala Krishna, “An integrated evolutionary approach for modelling and optimisation of CNC end milling process”, Int. J. Comput. Integr. Manuf. 25(11), 1069‒1084 (2012).
  8.  W.A. Jensen, “Confirmation Runs in Design of Experiments”, J. Qual. Technol. 48(2), 162‒177 (2016).
  9.  S. Amini, H. Khakbaz, and A. Barani, “Improvement of Near-Dry Machining and Its Effect on Tool Wear in Turning of AISI 4142”, Mater. Manuf. Process. 30, 241‒247 (2015).
  10.  E. Natarajan, V. Kaviarasan, W.H. Lim, S.S. Tiang, S. Parasuraman, and S. Elango, “Non-dominated sorting modified teaching– learning-based optimization for multi-objective machining of polytetrafluoroethylene (PTFE)”, J. Intell. Manuf. 31, 911–935 (2020), doi: 10.1007/s10845-019-01486-9.
  11.  V. Kaviarasan, R. Venkatesan, and E. Natarajan, “Prediction of surface quality and optimization of process parameters in drilling of Delrin using neural network”, Prog. Rubber Plast. Recycl. Technol. 35(3), 149–169 (2019).
  12.  N Senthilkumar, T. Ganapathy, and T. Tamizharasan, “Optimisation of machining and geometrical parameters in turning process using Taguchi method”, Aust. J. Mech. Eng.12 (2), 233‒246 (2016).
  13.  F. Kahraman, “Optimization of cutting parameters for surface roughness in turning of studs manufactured from AISI 5140 steel using the Taguchi method”, Mater. Test. 59 (1), 77‒80 (2017).
  14.  J. Rajaparthiban and A.N. Sait, “Application of the grey-based Taguchi method and Deform-3D for optimizing multiple responses in turning of Inconel 718”, Mater. Test. 60(9), 907‒912 (2018).
  15.  T. Kıvak and Ş. Mert, “Application of the Taguchi technique for the optimization of surface roughness and tool life during the milling of Hastelloy C22”, Mater. Test. 59(1), 69‒76 (2017).
  16.  R.N. Yadav, “A Hybrid Approach of Taguchi-Response Surface Methodology for Modeling and Optimization of Duplex Turning Process”, Measurement 100, 131‒138 (2016).
  17.  D. Brahmeswararao, K. Venkatarao, and A.G. Krishna, “A hybrid approach to multi response optimization of micro milling process parameters using Taguchi method-based graph theory and matrix approach (GTMA) and utility concept”, Measurement 114, 332‒339 (2018).
  18.  P. Raja, R. Malayalamurthi, and M. Sakthivel, “Experimental investigation of cryogenically treated HSS tool in turning on AISI1045 using fuzzy logic – Taguchi approach”, Bull. Pol Ac.: Tech. 67(4),687‒696 (2019).
  19.  G.V. Chakaravarthy, S. Marimuthu, and A. Naveen Sait, “Comparison of Firefly algorithm and Artificial Immune System algorithm for lot streaming in m-machine flow shop scheduling”, Int. J. Comput. Intell. Syst. 5(6), 1184‒1199 (2012).
  20.  X.S. Yang, Firefly algorithm in Engineering Optimization, John Wiley & Sons, New York, USA (2010).
  21.  X.-S. Yang, “Firefly algorithm, stochastic test functions and design optimization”, Int. J. Bio-Inspired Comput. 2(2), 78‒84 (2010).
  22.  S. Kamarian, M. Shakeriand, and M.H. Yas, “Thermal buckling optimization of composite plates using firefly algorithm”, J. Exp. Theor. Artif. Intell. 29(4) 878‒794 (2016).
  23.  N.A. Al-Thanoon, O.S. Qasim, and Z.Y. Algamal, “A new hybrid firefly algorithm and particle swarm optimization for tuning parameter estimation in penalized support vector machine with application in chemometrics”, Chemometrics Intell. Lab. Syst. 184, 142‒152 (2019).
  24.  A.F. Zubair, M. Salman, and A. Mansor, “Embedding firefly algorithm in optimization of CAPP turning machining parameters for cutting tool selections”, Comput. Ind. Eng. 135, 317‒325 (2019).
  25.  T. Sekar, M. Arularasu, and V. Sathiyamoorthy, “Investigations on the effects of Nano-fluid in ECM of die steel”, Measurement 83, 38‒43 (2016).
  26.  E. Nas and B. Öztürk, “Optimization of surface roughness via the Taguchi method and investigation of energy consumption when milling spheroidal graphite cast iron materials”, Mater. Test. 60(5), 519‒525 (2018).
  27.  G. Samtaşand and S. Korucu, “Optimization of Cutting Parameters in Pocket Milling of Tempered and Cryogenically Treated 5754 Aluminum Alloy”, Bull. Pol Ac.: Tech. 67(4), 697‒707 (2019).
  28.  E. Hüner, “Optimization of axial flux permanent magnet generator by Taguchi experimental method”, Bull. Pol Ac.: Tech. 68(3), 409‒419 (2020).
  29.  Ş. Ertürk and G. Samtaş, “Design of grippers for laparoscopic surgery and optimization ofexperimental parameters for maximum tissue weight holding capacity”, Bull. Pol Ac.: Tech. 67(6), 1125‒1132 (2019).
  30.  J.A. Shukor, S. Said, R. Harun, S. Husinand, and Ab. Kadir, “Optimising of machining parameters of plastic material using Taguchi method”, Adv. Mater. Process. Technol. 2(1), 50‒56 (2016).
  31.  S. Shankar, T. Mohanraj, and S.K. Thangarasu, “Multi-response milling process optimization using the Taguchi method coupled to grey relational analysis”, Mater. Test. 58(5), 462‒470 (2016).
  32.  S. Jannet, P.K. Mathews, and R. Raja, “Optimization of process parameters of friction stir welded AA 5083-O aluminum alloy using Response Surface Methodology”, Bull. Pol Ac.: Tech. 63(4), 851‒855 (2015).
  33.  J. Kwiecień and B. Filipowicz, “Firefly algorithm in optimization of queueing systems”, Bull. Pol Ac.: Tech. 60(2), 363‒368 (2012).
  34.  Z. Liu, X. Li, D. Wu, Z. Qian, P. Feng, and Y. Rong, “The development of a hybrid firefly algorithm for multi-pass grinding process optimization”, J. Intell. Manuf. 30(6), 2457‒2472 (2019).
  35.  J. Kwiecień and B. Filipowicz, “Comparison of firefly and cockroach algorithms in selected discreteand combinatorial problems”, Bull. Pol Ac.: Tech. 62(4), 797‒804 (2014).
  36.  M.C. Shaw, Metal Cutting Principles, Second Edition, Oxford University Press, New York (2004).
  37.  A. Elddein, I. Elshwain, M. Handawi, N. Redzuan, M.Y. Noordin, and D. Kurniawan, “Performance Comparison between Dry and Nitrogen Gas Cooling when Turning Hardened Tool Steel with Coated Carbide”, Appl. Mech. Mater. 735, 65‒69 (2015).
  38.  D. Lazarevic, M. Madića, P. Jankovića, and A. Lazarević, “Cutting Parameters Optimization for Surface Roughness in Turning Operation of Polyethylene (PE) Using Taguchi Method”, Tribol. Ind. 34(2), 68‒73, 2012.
  39.  N. Senthilkumar, T. Tamizharasan, and S. Gobikannan, “Application of Response Surface Methodology and Firefly Algorithm for Optimizing Multiple Responses in Turning AISI 1045 Steel”, Arab. J. Sci. Eng. 39, 8015–8030 (2014).
  40.  A.H. Tazehkandi, M. Shabgard, and F. Pilehvarian, “Application of liquid nitrogen and spray mode of biodegradable vegetable cutting fluid with compressed air in order to reduce cutting fluid consumption in turning Inconel 740”, J. Clean Prod. 108 (part A), 90‒103 (2015).
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Autorzy i Afiliacje

P. Prasanth
1
T. Sekar
2
M. Sivapragash
3

  1. Department of Mechanical Engineering, Tagore Institute of Engineering and Technology, Deviyakurichi, Salem – 636112, Tamilnadu, India
  2. Department of Mechanical Engineering, Government College of Technology, Coimbatore – 641013, Tamilnadu, India
  3. Department of Mechanical Engineering, Universal College of Engineering and Technology, Vallioor, Tirunelveli – 627117, Tamilnadu, India
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Abstrakt

This paper discusses the configuration of a space-effective rack cell for storing a given set of heterogeneous items. Rack cells are the primary components of rack storage areas. A rack cell configuration problem (RCCP) for heterogeneous storage is formulated as a combinatorial mathematical model. An effective heuristic for solving the RCCP in practical cases is presented. The proposed heuristic consists of multistage brute force searching of defined sets of feasible solutions and solving linear integer assignment problems by the branch-and-bound method. The developed algorithm was implemented and tested, and the rack cell obtained meets the modularity requirements in the design and operation of heterogeneous storage areas.

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Bibliografia

  1.  M. Kłodawski, K. Lewczuk, I. Jacyna-Gołda, and J. Żak, “Decision making strategies for warehouse operations”, Arch. Transp. 41(1), 43–53 (2017).
  2.  I. Jacyna-Gołda, M. Izdebski, E. Szczepański, and P. Gołda, “The assessment of supply chain effectiveness”, Arch. Transp. 45(1), 43–52 (2018).
  3.  M. Jacyna, M.Wasiak, and A. Bobiński, “SIMMAG3D as a tool for designing of storage facilities in 3D”, Arch. Transp. 42(2), 25–38 (2017).
  4.  K.R. Gue and R.D. Meller, “Aisle configurations for unit-load warehouses”, IIE Trans. 41(3), 171–182 (2009).
  5.  S. Labant, M. Bindzárová Gergel’ová, Š. Rákay, E. Weiss, and J. Zuzik, “Track planarity and verticality of the warehouse racks for the quality assessment of further operation”, Geodesy Cartogr. 68(2), 305–319 (2019).
  6.  G. Dukic and T. Opetuk, “Warehouse layouts”, in Warehousing in the Global Supply Chain. Advanced Models, Tools and Applications for Storage Systems. (Ed.) Manzini, R., pp. 55‒69, Springer-Verlag, London, 2012.
  7.  G. Kovács, “Layout design for efficiency improvement and cost reduction”, Bull. Pol. Ac.: Tech. 67(3), 547‒555 (2019).
  8.  T. Lerher and M. Sraml, “Designing unit load automated storage and retrieval systems”, in Warehousing in the Global Supply Chain. Advanced Models, Tools and Applications for Storage Systems. (Ed.) Manzini, R., pp. 211‒231 Springer-Verlag, London, 2012.
  9.  H.L. Lee, M.H. Lee, and L.S. Hur, “Optimal design of rack structure with modular cell in AS/RS”, Int. J. Prod. Econ. 98(2), 172‒178 (2005).
  10.  A. Ratkiewicz, “A combined bi-level approach for the spatial design of rack storage area”, J. Oper. Res. Soc. 64(8), 1157‒1168 (2013).
  11.  H. Dyckhoff, “Cutting and packing in production and distribution: a typology and bibliography”, Springer-Verlag, Berlin, 1992.
  12.  G. Wäscher, H. Haußner, and H. Schumann, “An improved typology of cutting and packing problems”, Eur. J. Oper. Res. 183(3), 1109‒1130 (2007).
  13.  E. Silva, J.F. Oliveira, and G. Wäscher, “2DCPackGen: A problem generator for two-dimensional rectangular cutting and packing problems”, Eur. J. Oper. Res. 237(3), 846‒856 (2014).
  14.  S. Martello, “Packing problems in one and more dimensions”, in Winter School on Network Optimization, 7th edition, 2018, Estoril, Portugal. [Online]. Available: http://www.or.deis.unibo.it/staff_pages/martello/Slides_Estoril_Martello.pdf (accessed: May 01, 2020].
  15.  G. Scheithauer, “Introduction to cutting and packing optimization”, International Series in Operations Research and Management Science, Springer-Verlag, Berlin, 2018.
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Autorzy i Afiliacje

Andrzej Ratkiewicz
1
ORCID: ORCID
Konrad Lewczuk
1
ORCID: ORCID

  1. Warsaw University of Technology, Faculty of Transport, ul. Koszykowa 75, 00-662 Warsaw, Poland
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Abstrakt

In the paper, a design method of a static anti-windup compensator for systems with input saturations is proposed. First, an anti-windup controller is presented for system with cut-off saturations, and, secondly, the design problem of the compensator is presented to be a non-convex optimization problem easily solved using bilinear matrix inequalities formulation. This approach guarantees stability of the closed-loop system against saturation nonlinearities and optimizes the robust control performance while the saturation is active.
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Bibliografia

  1.  E.F. Mulder, M.V. Kothare, L. Zaccarian, and A.R. Teel, “Multivariable Anti-windup Controller Synthesis using Bilinear Matrix Inequalities”, Eur. J. Control 6(5), 455–464 (2000).
  2.  J.G. VanAntwerp and R.D. Braatz, “A Tutorial on Linear and Bilinear Matrix Inequalities”, J. Process Control 10, 363–385 (2000).
  3.  C. Scherer and S. Weiland, “Linear Matrix Inequalities in Control”, DISC Course on Linear Matrix Inequalities in Control, Technische Universiteit Eindhoven, 2005.
  4.  S. Boyd, L. El Ghaoui, E. Feron, and V. Balakrishnan, “Linear Matrix Inequalities” in System and Control Theory, 2nd ed., SIAM, Philadelphia, 1994.
  5.  E. de Klerk, Aspects of Semidefinite Programming. Interior Point Algorithms and Selected Applications, Kluwer Academic Publishers, Dordrecht, 2002.
  6.  M. Kocvara and M. Stingl, “PENNON – A Generalized Augmented Lagrangian Method for Semidefinite Programming”, in High Performance Algorithms and Software for Nonlinear Optimization, eds. G. Di Pillo, A. Murli, pp. 297–315, Kluwer Academic Publishers, Dordrecht, 2003.
  7.  M. Kocvara and M. Stingl, “PENNON – A Code for Convex Nonlinear and Semidefinite Programming”, Optim. Method Softw. 18(3), 317–333 (2003).
  8.  D. Henrion, J. Löfberg, M. Kocvara, and M. Stingl, “Solving Polynomial Static Output Feedback Problems with PENBMI”, technical report LAAS-CNRS 05165, 2005.
  9.  Tomlab Optimization, [Online]. http://tomopt.com/tomlab/ (accessed 20.03.2020).
  10.  T.D. Quoc, S. Gumussoy, W. Michiels, and M. Diehl, “Combining Convex-Concave Decompositions and Linearization Approaches for solving BMIs, with Application to Static Output Feedback”, technical report, OPTEC K.U. Lueven Optimization in Engineering Center, 2011.
  11.  J. Löfberg, “YALMIP: A Toolbox for Modeling and Optimization in MATLAB”, in Proceedings of the CACSD Conference, Taipei, 2004.
  12.  CVX Research, Inc., CVX: Matlab Software for Disciplined Convex Programming, version 2.0, 2012 [Online]. http://cvxr.com/cvx
  13.  M. Grant and S. Boyd, “Graph implementations for nonsmooth convex programs”, in Recent Advances in Learning and Control, Lecture Notes in Control and Information Sciences, eds. V. Blondel, S. Boyd and H. Kimura, pp. 95–110, Springer-Verlag Limited, 2008.
  14.  A.A. Adegbege and W.P. Heath, “Internal Model Control Design for Input-constrained Multivariable Processes”, AICHE J. 57, 3459–3472 (2011).
  15.  M. Rehan, A. Ahmed, N. Iqbal, and M.S. Nazir, “Experimental Comparison of Different Anti-windup Schemes for an AC Motor Speed Control System”, in Proceedings of 2009 International Conference on Emerging Technologies, Islamabad, 2009.
  16.  N. Wada, M. Saeki, “Synthesis of a Static Anti-windup Compensator for Systems with Magnitude and Rate Limited Actuators”, in 3rd IFAC Symposium on Robust Control Design, Prague, 2000.
  17.  X. Sun, Z. Shi, Z. Yang, S. Wang, B. Su, L. Chen, and K. Li, “Digital Control System Design for bearingless permanent magnet synchronous motor”, Bull. Pol. Ac.: Tech. 66(5), 687–698 (2018).
  18.  M. Ran, Q. Wang, C. Dong, and M. Ni, “Simultaneous antiwindup synthesis for linear systems subject to actuator saturation”, J. Syst. Eng. Electron. 26(1), 119–126 (2015).
  19.  G. Liu, W. Ma, and A. Xue, “Static Anti-windup Control for Unstable Linear Systems with the Actuator Saturation”, Proceedings of the Chinese Automation Congress, Hangzou, 2019, pp. 2734–2739.
  20.  S. Solyom, “A synthesis method for static anti-windup compensators”, Proceedings of the European Control Conference, Cambridge, 2003, pp. 485–488.
  21.  H. Septanto, A. Syaichu-Rohman, and D. Mahayana, “Static Anti-Windup Compensator Design of Linear Sliding Mode Control for Input Saturated Systems”, Proceedings of the International Conference on Electrical Engineering and Informatics, Bandung, 2011, p. C5-2.
  22.  D. Horla, “Interplay of Directional Change in Controls and Windup Phenomena – Analysis and Synthesis of Compensators”, D. Sc. Monography, no. 471, Poznan University of Technology, Poznan, 2012.
  23.  N.Wada and M. Saeki, “Design of a static anti-windup compensator which guarantees robust stability”, Trans. Inst. Syst. Control Inf. Eng. 12(11), 664—670 (1999).
  24.  P.J. Campo and M. Morari, “Robust Control of Processes Subject to Saturation Nonlinearities”, Comput. Chem. Eng. 14(4‒5), 343–358 (1990).
  25.  S. Skogestad and I. Postlethwaite, Multivariable Feedback Control. Analysis and Design, 2nd ed.,Wiley-Blackwell, Chichester, 2005.
  26.  F. Wu and M. Soto, “Extended Anti-windup Control Schemes for LTI and LFT Systems with Actuator Saturations”, Int. J. Robust Nonlinear Control 14(15), 1255–1281 (2004).
  27.  F. Amato, “Robust Control of Linear Systems Subject to Uncertain Time-Varying Parameters”, Lecture Notes in Control and Information Sciences, Springer, Berlin–Heidelberg, 2006.
  28.  F. Uhlig, “A recurring theorem about pairs of quadratic forms and extensions: a survey”, Linear Alg. Appl. 25, 219–237 (1979).
  29.  S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge University Press, Cambridge, 2006.
  30.  D. Horla and A. Królikowski, “Discrete-time LQG Control with Actuator Failure”, in Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics, Noordwijkerhout, 2011, [CD-ROM].
  31.  J.M. Maciejowski, Multivariable Feedback Design, Addison Wesley Publishing Company, Cambridge, 1989.
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Autorzy i Afiliacje

Dariusz Horla
1
ORCID: ORCID

  1. Poznan University of Technology, Faculty of Automatic Control, Robotics and Electrical Engineering, ul. Piotrowo 3a, 60-965 Poznan, Poland
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Abstrakt

In the paper, maximal values xe(τ) of the solutions x(t) of the linear differential equations excited by the Dirac delta function are determined. The analytical solutions of the equations and also the maximal positive values of these solutions are obtained. The analytical formulae enable the design of the system with prescribed properties. The complementary case to the earlier paper is presented. In an earlier paper it was assumed that the roots si are different, and now we consider the case when s1 = s2  = … = sn.

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Bibliografia

  1.  S. Białas, H. Górecki, and M. Zaczyk, “Extremal properties of the linear dynamic systems controlled by Dirac’s impulse”, J. Appl. Math. Comput. Sci. 30(1), 75‒81 (2020).
  2.  L. Farina and S. Rinaldi: Positive Linear Systems. Theory and Application, J. Wiley, New York, 2000.
  3.  H. Górecki and M. Zaczyk: “Design of the oscillatory systems with the extremal dynamic properties”, Bull. Pol. Ac.: Tech. 62(2), 241‒253 (2014).
  4.  T. Kaczorek, Positive 1D and 2D Systems, Springer-Verlag, London, 2002.
  5.  K.L. Moore and S.P. Bhattacharyya, “A technique for choosing zero locations for minimal overshoot”, Proceedings of the 28th IEEE Conference on Decision and Control, Tampa, FL, USA 2, 1989, pp. 1230‒1233.
  6.  H. Górecki and M. Zaczyk, “Positive extremal values and solutions of the exponential equations with application to automatics”, Bull. Pol. Ac.: Tech. 68(3), 585‒591 (2020).
  7.  H. Górecki and M. Zaczyk, “Extremal dynamic errors in linear dynamic systems”, Bull. Pol. Ac.: Tech. 58(1), 99‒105 (2010).
  8.  H. Górecki and S. Białas, “Relations between roots and coefficients of the transcendental equations”, Bull. Pol. Ac.: Tech. 58(4), 631‒634 (2010).
  9.  H. Górecki and M. Zaczyk, “Design of systems with extremal dynamic properties”, Bull. Pol. Ac.: Tech. 61(3), 563‒567 (2013).
  10.  S. Białas and H. Górecki, “Generalization of Vieta’s formulae to the fractional polynomials, and generalizations the method of Graeffe- Lobactievsky”, Bull. Pol. Ac.: Tech. 58(4), 625‒629 (2010).
  11.  T. Kaczorek, “A new method for determination of positive realizations of linear continuous-time systems”, Bull. Pol. Ac.: Tech. 66(5), (2018).
  12.  T. Kaczorek, “Global stability of nonlinear feedback systems with positive descriptor linear part”, Bull. Pol. Ac.: Tech. 67(1), 45‒51 (2019).
  13.  T. Kaczorek, “Stability of interval positive continuous-time linear systems”, Bull. Pol. Ac.: Tech. 66(1), 31‒35 (2018).
  14.  J. Osiowski, An outline of operator calculus. Theory and applications in electrical engineering, WNT, Warszawa, 1965 [in Polish].
  15.  H. Górecki, Optimization and Control of Dynamic Systems, Springer, 2018.
  16.  D.C. Kurtz, “Condition for all the roots of a polynomial to be real”, The American Mathematical Monthly 99(3), 259‒263 (1992).
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Autorzy i Afiliacje

Henryk Górecki
1
Mieczysław Zaczyk
1

  1. AGH University of Science and Technology, Department of Automatics and Robotics, Al. Mickiewicza 30, 30-059 Kraków, Poland
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Abstrakt

In the paper a new, state space, fully discrete, fractional model of a heat transfer process in one dimensional body is addressed. The proposed model derives directly from fractional heat transfer equation. It employes the discrete Grünwald-Letnikov operator to express the fractional order differences along both coordinates: time and space. The practical stability and numerical complexity of the model are analysed. Theoretical results are verified using experimental data.
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Bibliografia

  1.  S. Das, Functional Fractional Calculus for System Identification and Controls, Springer, Berlin, 2010.
  2.  R. Caponetto, G. Dongola, L. Fortuna, and I. Petras, “Fractional order systems: Modeling and Control Applications”, in World Scientific Series on Nonlinear Science, ed. L.O. Chua, pp. 1–178, University of California, Berkeley, 2010.
  3.  A. Dzieliński, D. Sierociuk, and G. Sarwas, “Some applications of fractional order calculus”, Bull. Pol. Ac.: Tech. 58(4), 583– 592 (2010).
  4.  C.G. Gal and M. Warma, “Elliptic and parabolic equations with fractional diffusion and dynamic boundary conditions”, Evol. Equ. Control Theory 5(1), 61–103 (2016).
  5.  E. Popescu, “On the fractional Cauchy problem associated with a feller semigroup”, Math. Rep. 12(2), 81–188 (2010).
  6.  D. Sierociuk et al., “Diffusion process modeling by using fractional-order models”, Appl. Math. Comput. 257(1), 2–11 (2015).
  7.  J.F. Gómez, L. Torres, and R.F. Escobar (eds.), “Fractional derivatives with Mittag-Leffler kernel trends and applications in science and engineering”, in Studies in Systems, Decision and Control, vol. 194, ed. J. Kacprzyk, pp. 1–339. Springer, Switzerland, 2019.
  8.  M. Dlugosz and P. Skruch, “The application of fractional-order models for thermal process modelling inside buildings”, J. Build Phys. 1(1), 1–13 (2015).
  9.  A. Obrączka, Control of heat processes with the use of noninteger models. PhD thesis, AGH University, Krakow, Poland, 2014.
  10.  A. Rauh, L. Senkel, H. Aschemann, V.V. Saurin, and G.V. Kostin, “An integrodifferential approach to modeling, control, state estimation and optimization for heat transfer systems”, Int. J. Appl. Math. Comput. Sci. 26(1), 15–30 (2016).
  11.  T. Kaczorek, “Singular fractional linear systems and electri cal circuits”, Int. J. Appl. Math. Comput. Sci. 21(2), 379–384 (2011).
  12.  T. Kaczorek and K. Rogowski, Fractional Linear Systems and Electrical Circuits, Bialystok University of Technology, Bialystok, 2014.
  13.  I. Podlubny, Fractional Differential Equations, Academic Press, San Diego, 1999.
  14.  B. Bandyopadhyay and S. Kamal, “Solution, stability and realization of fractional order differential equation”, in Stabilization and Control of Fractional Order Systems: A Sliding Mode Approach, Lecture Notes in Electrical Engineering 317, pp. 55–90, Springer, Switzerland, 2015.
  15.  D. Mozyrska, E. Girejko, M. Wyrwas, “Comparison of hdifference fractional operators”, in Advances in the Theory and Applications of Non- integer Order Systems, eds. W. Mitkowski et al., pp. 1–178. Springer, Switzerland, 2013.
  16.  P. Ostalczyk, “Equivalent descriptions of a discrete-time fractional-order linear system and its stability domains”, Int. J. Appl. Math. Comput. Sci. 22(3), 533–538 (2012).
  17.  E.F. Anley and Z. Zheng, “Finite difference approximation method for a space fractional convection–diffusion equation with variable coefficients”, Symmetry 12(485), 1–19 (2020).
  18.  P. Ostalczyk, Discrete Fractional Calculus. Applications in Control and Image Processing, World Scientific, New Jersey, London, Singapore, 2016.
  19.  M. Buslowicz and T. Kaczorek, “Simple conditions for practical stability of positive fractional discrete-time linear systems”, Int. J. Appl. Math. Comput. Sci. 19(2), 263–269 (2009).
  20.  R. Brociek and D. Słota, “Implicit finite difference method for the space fractional heat conduction equation with the mixed boundary condition”, Silesian J. Pure Appl. Math. 6(1), 125–136 (2016).
  21.  D. Mozyrska and E. Pawluszewicz, “Fractional discrete-time linear control systems with initialization”, Int. J. Control 1(1), 1–7 (2011).
  22.  K. Oprzędkiewicz, “The interval parabolic system”, Arch. Control Sci. 13(4), 415–430 (2003).
  23.  K. Oprzędkiewicz, “A controllability problem for a class of uncertain parameters linear dynamic systems”, Arch. Control Sci. 14(1), 85–100 (2004).
  24.  K. Oprzędkiewicz, “An observability problem for a class of uncertain-parameter linear dynamic systems”, Int. J. Appl. Math. Comput. Sci. 15(3), 331–338 (2005).
  25.  A. Dzieliński and D. Sierociuk, “Stability of discrete fractional order state-space systems”, in Proc. of the 2nd IFAC Workshop on Fractional Differentiation and its Applications, Porto, Portugal, 2006, pp. 505–510.
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Autorzy i Afiliacje

Krzysztof Oprzędkiewicz
1
ORCID: ORCID

  1. AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Kraków, Poland
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Abstrakt

The subject of this paper is an assessment of the accuracy of a solution based on the linear theory of elasticity describing the interaction of a cylindrical reinforced concrete tank with the subsoil. The subsoil was modeled in the form of an elastic half-space and Winkler springs. The behavior of the shell structure of the RC cylindrical tank, and particularly of the ground slab interacting with the subsoil, depends largely on the distribution of the reactions on the foundation surface. An analysis of this structure with the shell fixed in a circular ground slab was carried out taking into consideration the elastic half-space model using the Gorbunov-Posadov approach and, for comparison, the two-parameter Winkler model. Although the results for both subsoil models proved to be divergent, the conclusions that follow the accuracy assessment of a solution based on the theory of elasticity are fairly important for engineering practice.

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Bibliografia

  1.  H. Borowicka, “Pressure distribution under elastic plates“, Ing. Arch., X. Band, 113–125 (1939) [in German].
  2.  M.I. Gorbunov-Posadov, T.A. Malikova, and V.I. Solomin, Calculation of Structures on Elastic Foundation, Stroyizdat, Moskva, 1984 [in Russian].
  3.  P.M. Lewiński and M. Rak, “Soil-structure interaction of cylindrical water tanks with linearly varying wall thickness”, PCM-CMM-2015: 3rd Pol. Congr. Mech. & 21st Comp. Meth. Mech., Gdańsk, Poland, 8‒11 September, 2015, vol. 2, pp. 921‒922.
  4.  P.M. Lewiński and M. Rak, “Soil-structure interaction of cylindrical tank of variable wall thickness under the thermal gradient conditions”, IOP Conf. Ser.: Mater. Sci. Eng. 661, 012044 (2019)
  5.  A.R. Kukreti, M.M. Zaman, and A. Issa, “Analysis of fluid storage tanks including foundation-superstructure interaction”, Appl. Math. Model. 17, 618‒631 (1993).
  6.  A.R. Kukreti and Z.A. Siddiqi, “Analysis of fluid storage tanks including foundation-superstructure interaction using differential quadrature method”, Appl. Math. Model. 21, 193‒205 (1997).
  7.  J.A. Hemsley (Ed.), Design Applications of Raft Foundations, Thomas Telford Publishing, London, 2000.
  8.  J.A. Hemsley, Elastic Analysis of Raft Foundations, Thomas Telford Publishing, London, 1998.
  9.  E.S. Melerski, Design Analysis of Beams, Circular Plates and Cylindrical Tanks on Elastic Foundations, Taylor & Francis Group, London, 2006.
  10.  J.S. Horvath and R.J. Colasanti, “Practical subgrade model for improved soil-structure interaction analysis: Model development”, Int. J. Geomech. 11(1), 59‒64 (2011).
  11.  N. el Mezaini, “Effects of soil-structure interaction on the analysis of cylindrical tanks”, Pract. Period. Struct. Des. Constr. 11(1), 50–57 (2006).
  12.  Z. Mistríková and N. Jendželovský, “Static analysis of the cylindrical tank resting on various types of subsoil”, J. Civ. Eng. Manag. 18(5), 744–751 (2012).
  13.  P. Lewiński, Analysis of Interaction of RC Cylindrical Tanks with Subsoil, Prace Naukowe ITB, Rozprawy, Wydawnictwa ITB, Warszawa, 2007 [in Polish].
  14.  Z. Kączkowski, Plates. Static Calculations, Arkady, Warszawa, 2000 [in Polish].
  15.  W. Flügge, Stresses in Shells, 2nd ed., Springer, Berlin, Heidelberg, 1973.
  16.  Z.E. Mazurkiewicz and T. Lewiński (Ed.), Thin Elastic Shells, Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa, 2004 [in Polish].
  17.  E. Szewczak and A. Piekarczuk, “Performance evaluation of the construction products as a research challenge. Small error – big difference in assessment?”, Bull. Pol. Ac.: Tech. Sci. 64(4), 675–686 (2016).
  18.  P.M. Lewiński and S. Dudziak, “Nonlinear interaction analysis of RC cylindrical tank with subsoil by adopting two kinds of constitutive models for ground and structure”, Amer. Inst. Phys., AIP Conf. Proc. 1922, 130007 (2018).
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Autorzy i Afiliacje

Paweł Marek Lewiński
1

  1. Building Research Institute, ul. Filtrowa 1, 00-611 Warszawa, Poland
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Abstrakt

The paper presents the results of analyses concerning a new approach to approximating trajectory of mining-induced horizontal displacements. Analyses aimed at finding the most effective method of fitting data to the trajectory of mining-induced horizontal displacements. Two variants were made. In the first, the direct least square fitting (DLSF) method was applied based on the minimization of the objective function defined in the form of an algebraic distance. In the second, the effectiveness of differential-free optimization methods (DFO) was verified. As part of this study, the following methods were tested: genetic algorithms (GA), differential evolution (DE) and particle swarm optimization (PSO). The data for the analysis were measurements of on the ground surface caused by the mining progressive work at face no. 698 of the German Prospel-Haniel mine. The results obtained were compared in terms of the fitting quality, the stability of the results and the time needed to carry out the calculations. Finally, it was found that the direct least square fitting (DLSF) approach is the most effective for the analyzed registration data base. In the authors’ opinion, this is dictated by the angular range in which the measurements within a given measuring point oscillated.
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Bibliografia

  1.  T. Chmielewski and Z. Zembaty, Podstawy dynamiki budowli, Warsaw: Arkady, 2006 [in Polish].
  2.  J. Rusek, “Influence of the Seismic Intensity of the Area on the Assessment of Dynamic Resistance of Bridge Structures”, in IOP Conf. Ser.: Mater. Sci. Eng. 2017, pp. 245‒252, doi: 10.1088/1757-899X/245/3/032019.
  3.  J. Rusek and W. Kocot, “Proposed Assessment of Dynamic Resistance of the Existing Industrial Portal Frame Building Structures to the Impact of Mining Tremors” in IOP Conf. Ser.: Mater. Sci. Eng. 2017, pp.162‒245, doi: 10.1088/1757-899X/245/3/032020.
  4.  J. Rusek, “A proposal for an assessment method of the dynamic resistance of concrete slab viaducts subjected to impact loads caused by mining tremors”, in JCEEA. 64(1), 469‒486 (2018), doi: 10.7862/rb.2017.43.
  5.  K. Tajduś, “Analysis of Horizontal Displacements Measured over the Mining Operations in Longwall No. 537 at the Girondelle 5 Seam of the Bw Friedrich Heinrich-Rheinland Coal Mine”, Arch. Min. Sci. 61(1), 157‒168 (2016), doi: 10.1515/amsc-2016-0012.
  6.  K. Tajdus, “The nature of mining-induced horizontal displacement of surface on the example of several coal mines”. Arch. Min. Sci. 59(4), 971‒986 (2014), doi: 10.2478/amsc-2014-0067.
  7.  K. Tajduś “Analysis of horizontal displacement distribution caused by single advancing longwall panel excavation”. J. Rock Mech. Geotech. Eng. 7(4), 395‒403 (2015), doi: 10.1016/j.jrmge.2015.03.012.
  8.  Deutsche Montan Technologie GmbH (DMT). BW Prosper Haniel measurements point – Schwarze Heide, 2001 (not published) [in German].
  9.  K. Tajduś, R. Misa, and A. Sroka, “Analysis of the surface horizontal displacement changes due to longwall panel advance”, Int. J. Rock Mech. Min. Sci. 104, 119‒125 (2018), doi: 10.1016/j.ijrmms.2018.02.005.
  10.  Z.L. Szpak, W. Chojnacki, and A. van den Hengel, “Guaranteed Ellipse Fitting with a Confidence Region and an Uncertainty Measure for Centre, Axes, and Orientation”, J. Math. Imaging Vision. 52(2), 173‒199 (2015), doi: 10.1007/s10851-014-0536-x.
  11.  M.A. Kashiha, C. Bahr, S. Ott, C.P.H. Moons, T.A. Niewold, F.O. Ödberg, and D. Berckmans, “Automatic identification of marked pigs in a pen using image pattern recognition”. Comput. Electron. Agric. 93, 111‒120 (2013), doi: 10.1007/978-3-642-38628-2_24.
  12.  L. Li, Y. Wang, X. Liu, Z. Tang, and Z. He, “A fast and robust ellipse detector based on top-down least-square fitting”, in BMVC, 2015, doi: 10.5244/c.29.156.
  13.  A. Xu, Z. Wang, D. Kong, Z. Fu, and Q. Lin, “A new ellipse fitting method of the minimum differential-mode noise in the atom interference gravimeter”, Chin. Phys. B – IOPscience. 27(7), 070203 (2018), doi: 10.1088/1674-1056/27/7/070203.
  14.  K. Kanatani, Y. Sugaya, and Y. Kanazawa, “Ellipse Fitting” in: Guide to 3D Vision Computation. Advances in Computer Vision and Pattern Recognition, pp. 11‒32, Springer, Cham, 2016, doi: 10.1007/978-3-319-48493-8_2.
  15.  R. Halır and J. Flusser, “Numerically stable direct least squares fitting of ellipses” in Proc. 6th International Conference in Central Europe on Computer Graphics and Visualization, vol. 98, pp. 125‒132, WSCG, Citeseer.
  16.  A. Ray and D.C. Srivastava, “Non-linear least squares ellipse fitting using the genetic algorithm with applications to strain analysis”. J. Struct. Geol. 30(12), 1593‒1602 (2008), doi: 10.1016/j.jsg.2008.09.003.
  17.  R. Poli, J. Kennedy, and T. Blackwell, “Particle swarm optimization. An overview”, Swarm Intell. 1(1), 33‒57, (2007), doi: 10.1007/s11721- 007-0002-0.
  18.  F. Ye, “Particle swarm optimization-based automatic parameter selection for deep neural networks and its applications in large-scale and high- dimensional data”, PLos one. 12(12), e0188746 2017, doi: 10.1371/journal.pone.0188746.
  19.  A.J. Mantau, A. Bowolaksono, B. Wiweko, and W. Jatmiko, “Detecting ellipses in embryo images using arc detection method with particle swarm for Blastomere-quality measurement system”, JACIII. 20(7), 1170‒1180 (2016), doi: 10.20965/jaciii.2016.p1170.
  20.  M. Szczepanik and T. Burczyński, “Swarm optimization of stiffeners locations in 2-D structures”, Bull. Pol. Ac.: Tech. 60(2), 241‒246 (2012), doi: 10.2478/v10175-012-0032-7.
  21.  J. Lampinen and R. Storn, Differential evolution. New optimization techniques in engineering, pp. 123–66, Springer, 2004.
  22.  L.M. Rios and N.V. Sahinidis, “Derivative-free optimization: A review of algorithms and comparison of software implementations”. J. Global Optim. Springer. 56(3), 1247‒1293 (2013), doi: 10.1007/s10898-012-9951-y.
  23.  J. Rusek, “Application of support vector machine in the analysis of the technical state of development in the LGOM mining area”, Maint. Reliab. vol.19, 54‒61, 2017, doi: 10.17531/ein.2017.1.8.
  24.  J. Rusek, “Creating a model of technical wear of building in mining area, with utilization of regressive SVM approach”. Arch. Min. Sci. 54(3), 455‒466, (2009).
  25.  D. Rainville, F.-A. Fortin, M.-A. Gardner, M. Parizeau, and C. Gagné, “Deap: A python framework for evolutionary algorithms” in GECCO ‘12, pp. 85–92, 2012.
  26.  F.A. Fortin, F.M.D. Rainville, M.A. Gardner, M. Parizeau, and C. Gagné, “DEAP: Evolutionary algorithms made easy”, J. Mach. Learn. Res. 13(1), 2171‒2175 (2012).
  27.  M.M. McKerns, P. Hung, and M.A.G. Aivazis, “Mystic: a simple model-independent inversion framework”, 2009, [Online] Available: http:// dev.danse.us/trac/mystic.
  28.  M.M. McKerns, L. Strand, T. Sullivan, A. Fang, and M.A.G. Aivazis. „Building a framework for predictive science” arXiv preprint arXiv:1202.1056, 2012.
  29.  B. Hammel and N. Sullivan-Molina, “Bdhammel/least-squares-ellipse-fitting: Initial release (Version v1.0)”, Zenodo, doi: 10.5281/ zenodo.2578663.
  30.  A.W. Fitzgibbon, M. Pilu, and R.B. Fisher, “Direct least squares fitting of ellipses”, IEEE Xplore 1, 253‒257 (1996), doi: 10.1109/ ICPR.1996.546029.
  31.  E. Cuevas, D. Zaldivar, M. Pérez-Cisneros, and M. Ramírez-Ortegón, “Circle detection using discrete differential evolution optimization”, Pattern Anal. Appl. Springer. 14, 93‒107 (2011), doi: 10.1007/s10044-010-0183-9.
  32.  E. Cuevas, M. González, D. Zaldívar, and M. Pérez-Cisneros, “Multi-ellipses detection on images inspired by collective animal behavior”, Neural. Comput. Appl. 24, 1019‒1033 (2014), doi: 10.1007/s00521-012-1332-4.
  33.  T. Witkowski, P. Antczak, and A. Antczak, “Multi-objective decision making and search space for the evaluation of production process scheduling”, Bull. Pol. Ac.: Tech. 3(57), 195‒208 (2012), doi: 10.2478/v10175-010-0121-4.
  34.  J.C. Strikwerda, Finite difference schemes and partial differential equations, SIAM, 2004.
  35.  K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II”, IEEE Trans. Evol. Comput. 6(2), 182‒197 (2002), doi: 10.1109/4235.996017.
  36.  R. Storn and K. Price, “Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces”, J. Global Optim. 11(4), 341‒359 (1997).
  37.  K. Price, R.M. Storn, and J.A Lampinen, Differential evolution: a practical approach to global optimization, Springer-Verlag Berlin Heidelberg, 2006.
  38.  M.M. Ali and A. Törn, “Population set-based global optimization algorithms: some modifications and numerical studies”, Comput Oper Res. 31(10), 1703‒1725 (2004), doi: 10.1016/S0305-0548(03)00116-3.
  39.  Y. Fukuyama, Fundamentals of particle swarm optimization techniques. Modern Heuristic Optimization Techniques: Theory and applications to power systems, pp. 71–87, John Wiley & Sons, 2008.
  40.  C. Blum and X. Li,“Swarm Intelligence in Optimization” in Swarm Intell, pp. 43‒85, ed. Blum C. Merkle D. Natural Computing Series: Springer, Berlin, Heidelberg, 2008, doi: 10.1007/978-3-540-74089-6_2.
  41.  R. Eberhart and J. Kennedy, “A new optimizer using particle swarm theory”, in MHS’95. Proc. Sixth Int. Symp. Micro Mach. Hum. Sci, 1995, pp. 39–43, doi: 10.1109/MHS.1995.494215.
  42.  L.G. de la Fraga, I.V. Silva, and N. Cruz-Cortés, “Euclidean Distance Fit of Conics Using Differential Evolution” in: Evolutionary Image Analysis and Signal Processing, pp. 171‒184, Springer, Berlin, Heidelberg, 2009, doi: 10.1007/978-3-642-01636-3_10.
  43.  C. Robert and G. Casella, Monte Carlo statistical methods, Springer Science and Business Media, 2013.
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Autorzy i Afiliacje

Janusz Rusek
1
ORCID: ORCID
Krzysztof Tajduś
2
ORCID: ORCID

  1. AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krakow, Poland
  2. Strata Mechanics Research Institute, Polish Academy of Sciences, Reymonta 27, 30-059 Krakow, Poland
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Abstrakt

The process of historical building conservation includes the repair of mortars eroded due to material and environmental factors. Identification of old mortar constituents is necessary to enable duplicating the material. Information on the binder and aggregate types and contents can be obtained from microscopic observation used in combination with instrumental methods. This paper presents the results of microstructure and mineral composition tests of mortars collected from the walls of thirteenth century buildings. A combination of techniques was used, which included X-ray diffraction, transmitted light optical microscopy and scanning electron microscopy with micro-area elemental composition analysis. The test results revealed porous lime and sand mortars with a binder-aggregate ratio often beyond the commonly adopted values. The mortars contained sand grains of up to 0.5 mm and larger pieces of limestone, flint, feldspar and brick. Transmitted light optical microscopy and scanning microscopy were found to be essential techniques for mortar characterization in existing buildings and structures.

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Bibliografia

  1.  C.J. Groot, P. Bartos, and J.J. Hughes, “Historic mortars: Characteristic and tests – concluding summary and state-of-the-art”, in Proc. Intern RILEM workshop, Advanced Concrete and Masonry Centre, University of Paisley, Scotland, 1999.
  2.  J. Elsen, “Microscopy of historic mortars – a review”, Cem. Conc. Res. 36, 1416‒1424 (2006).
  3.  L. Czarnecki and D. Van Gemert, “Scientific basis and rules of thumb in civil engineering: conflict or harmony?”, Bull. Pol. Ac.: Tech. 64(4), 665‒673 (2016).
  4.  K.M. Haneefa, S.D. Rani, R. Ramasamy, and M. Santhanam, “Microstructure and geochemistry of lime plaster mortar from a heritage structure”, Constr. Build. Mater. 225, 538–554, (2019).
  5.  G. Borsoi, A. Santos Silva, P. Menezes, A. Candeias, and J. Mirao, “Analytical characterization of ancient mortars from the archaeological roman site of Pisoes (Beja, Portugal)”, Constr. Build. Mater. 204, 597–608 (2019).
  6.  B. Middendorf, G. Baronio, K. Callebaut, and J. Hughes, “Chemical – mineralogical and physical – mechanical investigation of old mortars”, in Proc. Intern. RILEM workshop, Advanced Concrete and Masonry Centre, University of Paisley, Scotland, 1999, pp. 53‒60.
  7.  J.J. Hughes, S. Cuthbert, and P. Bartos, “Alteration textures in historic Scottish lime mortars and the implications for practical mortar analysis”, Proc. of the 7th Euro seminar on Microscopy Applied to Building Materials, Delft, 1999, pp. 417‒426.
  8.  E. Sandström-Malinowski, “Historic mortars revived”, Proc. of the Intern. RILEM-workshop Repair mortars for historic masonry, Delft, 2005.
  9.  L.B. Sickels, “Organics vs. synthetics: their use as additives in mortars”, Proc. of the ICCROM Symposium Mortars, Cements and Grouts used in the Conservation of Historic Buildings, Rome, 1981, pp. 25‒53.
  10.  J. Elsen, A. Brutsaert, M. Deckers, and R. Brulet, “Microscopically study of ancient mortars from Tournai (Belgium)”, Mater. Charact. 53, 289‒295 (2004).
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Autorzy i Afiliacje

Zdzisława Owsiak
1

  1. Kielce University of Technology, Aleja Tysiąclecia Państwa Polskiego 7, 25-314 Kielce, Poland
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Abstrakt

This paper presents a new form of a mathematical estimation of stochastic bio-hydrodynamic lubrication parameters for real human joint surfaces with phospholipid bilayers. In this work, the authors present the analytical and stochastic considerations, which are based on the measurements of human joint surfaces. The gap is restricted between two cooperating biological surfaces. After numerous experimental measurements, it directly follows that the random symmetrical as well as unsymmetrical increments and decrements of the gap height in human joints influence the hydrodynamic pressure, load-carrying capacity, friction forces, and wear of the cooperating cartilage surfaces in human joints. The main focus of the paper was to demonstrate the influence of variations in the expected values and standard deviation of human joint gap height on the hydrodynamic lubrication parameters occurring in the human joint. It is very important to notice that the new form of apparent dynamic viscosity of synovial fluid formulated by the authors depends on ultra-thin gap height variations. Moreover, evident connection was observed between the apparent dynamic viscosity and the properties of cartilage surface coated by phospholipid cells. The above observations indicate an indirect impact of stochastic changes in the height of the gap and the indirect impact of random changes in the properties of the joint surface coated with the phospholipid layers, on the value of hydrodynamic pressure, load carrying capacity and friction forces. In this paper the authors present a synthetic, comprehensive estimation of stochastic bio-hydrodynamic lubrication parameters for the cooperating, rotational cartilage bio-surfaces with phospholipid bilayers occurring in human joints. The new results presented in this paper were obtained taking into account 3D variations in the dynamic viscosity of synovial fluid, particularly random variations crosswise the film thickness for non-Newtonian synovial fluid properties. According to the authors’ knowledge, the obtained results are widely applicable in spatiotemporal models in biology and health science.
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Bibliografia

  1.  J. Cwanek, The usability of the surface geometry parameters for the evaluation of the artificial hip joint wear, Rzeszów University Press, Rzeszów, 2009.
  2.  VC. Mow, A. Ratcliffe, and S. Woo, Biomechanics of Diarthrodial Joints, Springer Verlag, Berlin-Heidelberg-New York, 1990.
  3.  K. Wierzcholski, “Time depended human hip joint lubrication for periodic motion with stochastic asymmetric density function”, Acta Bioeng. Biomech. 16 (1), 83–97 (2014).
  4.  O.S. Andersen and E. Roger, “Bilayer thickness and Membrane Protein Function: An Energetic Perspective”, Annu. Rev. Biophys. Biomolec. Struct. 36 (1), 107–130 (2014).
  5.  B. Bhushan, Handbook of Micro/Nano Tribology, second ed. CRC Press, Boca Raton, London, New York, Washington D.C., 1999.
  6.  B. Bhushan, “Nanotribology and nanomechanics of MEMS/NEMS and BioMEMS/BioNEMS materials and devices”, Microelectron. Eng. 84, 387–412 (2007).
  7.  G. Chagnon, M. Rebouah, and D. Favier, “Hyperelastic Energy Densities for Soft Biological Tissues: A Review”, J. Elast. 120 (2), 129–160 (2015).
  8.  A. Gadomski, P. Bełdowski, J. Miguel Rubi, W. Urbaniak, K. Wayne, W.K. Auge, I.S. Holek, and Z. Pawlak, “Some conceptual thoughts toward nano-scale oriented friction in a model of articular cartilage”, Math. Biosci. 244, 188–200 (2013).
  9.  B.A. Hills, “Oligolamellar lubrication of joint by surface active phospholipid”, J. Reumatol. 16, 82–91 (1989).
  10.  B.A. Hills, “Boundary lubrication in vivo”, Proc. Inst. Mech. Eng. Part H-J. Eng. Med. 214, 83–87 (2000).
  11.  J. Marra and J.N. Israelachvili, “Direct measurements of forces between phosphatidylcholine and phosphatidylethanolamine bilayers in aqueous electrolyte solutions”, Biochemistry 24, 4608– 4618 (1985).
  12.  Z. Pawlak, A. Gadomski, M. Sojka, W. Urbaniak, and P. Bełdowski, “The amphoteric effect on friction between the bovine cartilage/cartilage surfaces under slightly sheared hydration lubrication mode”, Colloids and Surfaces B: Biointerfaces 1, 146, 452–458 (2016).
  13.  Z. Pawlak, W. Urbaniak, and M.W. Hagner–Derengowska, “The Probable Explanation for the Low Friction of Natural Joints”, Cell Biochem. Biophys. 71 (3), 1615–1621 (2015).
  14.  Z. Pawlak, Z.A. Figaszewski, A. Gadomski, W. Urbaniak, and A. Oloyede, “The ultra–low friction of the articular surface is pH-dependent and is built on a hydrophobic underlay including a hypothesis on joint lubrication mechanism”, Tribol. Int. 43, 1719–1725 (2010).
  15.  Z. Pawlak, W. Urbaniak, A. Gadomski, Q. Kehinde, K.Q. Fusuf, I.O. Afara, and A. Oloyede, “The role of lamellate phospholipid bilayers in lubrication of joints”, Acta Bioeng. Biomech. 14 (4), 101–106 (2012).
  16.  Z. Pawlak, W. Urbaniak, and A. Oloyede, “The relationship between friction and wettability in aqueous environment of natural joints”, Wear 271, 1745–1749 (2011).
  17.  Z. Pawlak, A.D. Petelska, W. Urbaniak, K.Q. Fusuf, and A. Oloyede, “Relationship Between Wettability and Lubrication Characteristics of the Surfaces of Contacting PhospholipidsBased Membranes”, Cell Biochem. Biophys. 65 (3), 335–345 (2012).
  18.  A.D. Petelska and Z.A. Figaszewski, “Effect of pH on interfacial tension of bilayer lipid membrane”, Biophys. J. 78, 812–817 (2000).
  19.  I.M. Schwarz and B.A. Hills, “Synovial surfactant: Lamellar bodies in type B synoviocytes and proteolipid in synovial fluid and the articular lining”, Br. J. Rheumatol. 35 (9), 821–827 (1966).
  20.  A. Kucaba-Piętal, “Squeeze flow modelling with the use of micropolar fluid theory”, Bull. Pol. Ac.: Tech. 65 (6), 927–933, (2017).
  21.  K. Murawski and D. Lee, “Numerical methods of solving equations of hydrodynamics from perspectives of the code FLASH”, Bull. Pol. Ac.: Tech. 59 (1), 927–933, (2011).
  22.  K. Wierzcholski and A. Miszczak, “Mathematical principles and methods of biological surface lubrication with phospholipids bilayers”, Biosystems 178, 32–40 (2019).
  23.  K. Wierzcholski and A. Miszczak, “Electro-Magneto-Hydrodynamic Lubrication”, Open Phys. 16 (1), 285–291 (2018).
  24.  K. Wierzcholski, “Topology of calculating pressure and friction coefficients for time-dependent human hip joint lubrication”, Acta Bioeng. Biomech. 13 (1), 41–56 (2011).
  25.  M. Fisz, Probability calculation and mathematical statistics, PWN, Warszawa, 1967, [in Polish].
  26.  Z. Helwig, Elements of probability calculations and mathematical statistics, PWN, Warszawa, 1977, [in Polish].
  27.  C.Q. Yuan, Z. Peng, X.P. Yan, and X.C. Zhou, “Surface roughness evaluation in sliding wear process”, Wear 265, 341–348 (2008).
  28.  K. Wierzcholski, “Joint cartilage lubrication with phospholipids bilayer”, Tribologia 2 (265), 145–157 (2016).
  29.  P. Syrek, Analiza parametrów przestrzennych aplikatorów małogabarytowych, wykorzystywanych w magnetoterapii, Ph.D. thesis, AGH University of Sciences and Technology, Kraków 2011.
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Autorzy i Afiliacje

Krzysztof Wierzcholski
1
ORCID: ORCID
Andrzej Miszczak
2
ORCID: ORCID

  1. WSG University of Economy in Bydgoszcz, ul. Garbary 2, 85-229 Bydgoszcz, Poland
  2. Gdynia Maritime University, ul. Morska 81/87, 81-225 Gdynia, Poland
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Abstrakt

A new method for measurement of sludge blanket height (SBH) based on image analysis is presented. The proposed method uses a histogram back-projection algorithm to distinguish between the settling sludge and supernatant and can be used with sludge possessing different coloring characteristics both in the sludge color and the color of supernatant produced. Individual pixels in the acquired image are compared with a histogram of a representative sludge region. Therefore, the proposed method relies neither on the assumed shape of light intensity profile nor on the dominant sludge or supernatant color. Batch sedimentation tests are presented for different initial sludge concentrations and different background colors to simulate different sludge characteristics. Parameters of a settling velocity function are estimated based on the obtained results. Additionally, an algorithm is proposed that enables the zone settling velocity (ZSV) to be estimated before the batch sedimentation test is completed.

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Bibliografia

  1.  M. Henze, P. Harremoës, J.C. Jansen, and E. Arvin, Wastewater treatment, Springer-Verlag, Berlin, 1995.
  2.  M. Metzger, “Mathematical model of sequentially controlled activated sludge processes”, Arch. of Cont. Sci. 9(3‒4), 111‒133 (1999).
  3.  J.Ph. Chancelier, M. Cohen de Lara, C. Joannis, and F. Pacard, “New insights in dynamic modeling of a secondary settler – I. Flux theory and steady-states analysis”, Wat. Res. 31(8), 1847‒1856 (1997).
  4.  H. Gao and M.K. Stenstrom, “Generalizing the effects of the baffling structures on the buoyancy-induced turbulence in secondary settling tanks with eleven different geometries using CFD models”, Chem. Eng. Res. Design. 143, 215‒225 (2019).
  5.  M. T. Shah et al., “A novel settling tank for produced water treatment: CFD simulations and PIV experiments”, J. Petro. Sci. Eng. 182, 106352 (2019)
  6.  E. Asensi, E. Alemany, P. Duque-Sarango, and D. Aguado, “Assessment and modelling of the effect of precipitated ferric chloride addition on the activated sludge settling properties”, Chem. Eng. Res. Design. 150, 14‒25 (2019).
  7.  X. Kang, Z. Xia, J. Wang, and W. Yang, „A novel approach to model the batch sedimentation and estimate the settling velocity, solid volume fraction, and floc size of kaolinite in concentrated solution”, Colloid Surf. A 579, 123647 (2019).
  8.  J. Wiora, A. Kozyra, and A. Wiora, “Towards automation of measurement process of surface water parameters by remote-controlled catamaran”, Bull. Pol. Ac.: Tech. 65(3), 351‒359 (2017).
  9.  R. Aguilar-López and I. Neria-González, “Controlling continuous bioreactor via nonlinear feedback: modelling an dsimulations approach”, Bull. Pol. Ac.: Tech. 64(1), 235‒241 (2016).
  10.  G.A. Ekama, et al., “Secondary settling tanks: theory, modeling, design and operation. of sludge sedimentation parameters”, IAWQ Scientific and Technical Report No. 6, IAWQ, London. 1997.
  11.  P.A. Vesilind, “Theoretical considerations: Design of prototype thickeners from batch settling tests”, Wat. Sew. Wks. 115(7), 302‒307 (1968).
  12.  I. Takács, G.G. Patry, and D. Nolasco, “A dynamic model of the clarification-thickening process”, Wat. Res. 25(10), 1263‒1271 (1991).
  13.  P. Grassia, S.P. Usher, and P.J. Scales, “Closed-form solution for batch settling height from model settling flux functions”, Chem. Engng. Sci. 66(5), 964‒972 (2011).
  14.  A. Vanderhasselt and P.A. Vanrolleghem, “Estimation of sludge sedimentation parameters from single batch settling curve”, Wat. Res. 34(2), 395‒406 (2000).
  15.  P. Vanrolleghem, et al., “On-line quantification of settling properties with in-sensor-experiments in an automated settlometer”, Wat. Sci. Tech. 33(1), 37‒51 (1996).
  16.  X. Lu, et al. “Automatic monitoring and quantitative characterization of sedimentation dynamics for non-homogenous systems based on image profile analysis”, Powder Technol. 281, 49‒56 (2015).
  17.  W. Suchecki, “Investigation of the sedimentation process using flow visualization methods”, Chem. And Proc. Eng. 40(2), 223‒233 (2019).
  18.  Y.J. Kim, S.J. Choi, H. Bae, and C.W. Kim, “Sludge settleability detection using automated SV30 measurement and its application to a field WWTP”, Wat. Sci. Technol. 64(8), 1743‒1749 (2011).
  19.  N. Derlon, Ch. Thürlimann, D. Dürrenmatt, and K. Villez, “Batch settling curve registration via image data modelling”, Wat. Res. 114, 327‒337 (2017).
  20.  Z-H. Li, D. Han, C-J. Yang, T-Y Zhang, and H-Q. Yu, “Probing operational conditions of mixing and oxygen deficiency using HSV color space”, J. Environ. Manage. 232, 985‒992 (2019)
  21.  Y. Xu, L. Zheng, R. Liu, and X. Dai, “Decyphering color for comprehensive utilization of sludge”, Resour. Conserv. Recycl. 153, 104579 (2020).
  22.  S.M. Pizer, et al., ”Adaptive histogram equalization and its variations”, Comp. Vis. Grap. Img. Proc. 39(3), 355‒368 (1987).
  23.  M.J. Swain and D.H. Ballard, “Color indexing”, Int. J. Comput. Vis. 7, 11‒32 (1991).
  24.  W. Niblack, An introduction to digital image processing, 1st English ed., Prentice Hall, 1986.
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Autorzy i Afiliacje

Witold Nocoń
1
ORCID: ORCID
Jakub Pośpiech
1
ORCID: ORCID
Jacek Kopciński
2

  1. Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, ul. Akademicka 16, 44-100 Gliwice, Poland
  2. MM Automation, ul. E. Bojanowskiego 27a, 40-772 Katowice, Poland
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Abstrakt

This paper presents material and technological studies on lab-on-chip (LOC) devices as a first step towards biocompatible and reliable research on microscopic fungi and soil organisms on a microscale. This approach is intended to respond to the growing need for environmental control and protection, by means of modern, miniaturized, portable and dependable microfluidics instrumentation. The authors have presented herein long-term, successful cultivation of different fungi representatives (with emphasis put on Cladosporium macrocarpum) in specially fabricated all-glass LOCs. Notable differences were noted in the development of these creatures on polymer, polydimethylosiloxane (PDMS) cultivation substrates, revealing the uncommon morphological character of the fungi mycelium. The utility of all-glass LOCs was verified for other fungi representatives as well –  Fusarium culmorum and Pencilium expansum, showing technical correspondence and biocompatibility of the devices. On that basis, other future applications of the solution are possible, covering, e.g. investigation of additional, environmentally relevant fungi species. Further development of the LOC instrumentation is also taken into consideration, which could be used for cultivation of other soil organisms and study of their mutual relationships within the integrated microfluidic device.
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Bibliografia

  1.  C. Wagg, et al., “Fungal-bacterial diversity and microbiome complexity predict ecosystem functioning”, Nat. Commun. 10, 4841 (2019), doi: 10.1038/s41467-019-12798-y.
  2.  M.J. Roossinck, “Evolutionary and ecological links between plant and fungal viruses”, New Phytol. 221(1), 86‒92 (2019), doi: 10.1111/ nph.15364, 2019.
  3.  H. Grossart, et al., “Fungi in aquatic ecosystems”, Nat. Rev. Microbiol. 17, 339–354 (2019), doi: 10.1038/s41579-019-0175-8.
  4.  M. Rai and G. Agarkar, “Plant–fungal interactions: What triggers the fungi to switch among lifestyles?”, Crit. Rev. Microbiol. 42(3), 428‒38 (2016), doi: 10.3109/1040841X.2014.958052.
  5.  A. Frew, J.R. Powell, G. Glauser, A.E. Bennett, and S.N. Johnson, “Mycorrhizal fungi enhance nutrient uptake but disarm defences in plant roots, promoting plant-parasitic nematode populations”, Soil Biol. Biochem. 126, 123‒132 (2018), doi: 10.1016/j.soilbio.2018.08.019.
  6.  M. Dicke, A. Cusumano, and E.H. Poelman, “Microbial Symbionts of Parasitoids”, Annu. Rev. Entomol. 65, 171‒190 (2020).
  7.  B. Kendrick, The fifth kingdom. An Introduction to mycology. Hackett Publishing Company, Inc., Indianapolis, USA, 2017.
  8.  T.A. Richards, G. Leonard, and J.G. Wideman. “What Defines the “Kingdom” Fungi?” in The fungal Kingdom, Washington, DC: ASM Press, American Society for Microbiology, Wiley Online Library, 2018.
  9.  T.S. Kaminski, O. Scheler, and P. Garstecki, “Droplet microfluidics for microbiology: techniques, applications and challenges”, Lab Chip 16, 2168‒2187 (2016).
  10.  A. Burmeister and A. Grünberger, “Microfluidic cultivation and analysis tools for interaction studies of microbial co-cultures”, Curr. Opin. Biotechnol. 62, 106‒115 (2020).
  11.  C.E. Stanley and M.G.A. van der Heijden, “Microbiome-on-a-Chip: New Frontiers in Plant–Microbiota Research”, Trends Microbiol. 25(8), 610‒613, 2017.
  12.  S.R. Lockery, et al., “Artificial Dirt: Microfluidic Substrates for Nematode Neurobiology and Behavior”, J. Neurophysiol 99(6), 3136‒3143, 2008.
  13.  H. Massalha, E. Korenblum, S. Malitsky, O.H. Shapiro, and A. Aharoni, “Live imaging of root–bacteria interactions in a microfluidics setup”, PNAS 114(17), 4549‒4554 (2017).
  14.  C.S. Effenhauser, A. Paulus, A. Manz, and H.M. Widmer, “High-Speed Separation of Antisense Oligonucleotides on a Micromachined Capillary Electrophoresis Device”, Anal. Chem. 66, 1994(18), 2949–2953 (1994).
  15.  L.J. Golonka, “Technology and applications of Low Temperature Cofired Ceramic (LTCC) based sensors and microsystems”, Bull. Pol. Ac.: Tech. 54(2), 221‒231 (2006).
  16.  M. Boyd-Moss, S. Baratchi, M. Di Venere, and K. Khoshmanesh, “Self-contained microfluidic systems: A review”, Lab Chip 16(17), 3177‒3192 (2016).
  17.  G.M. Whitesides, “The origins and the future of microfluidics”, Nature 442, 368–373 (2006).
  18.  B. Zhang, M. Kim, T. Thorsen, and Z. Wang, “A self-contained microfluidic cell culture system”, Biomed. Microdevices 11(6), 1233‒1237 (2009).
  19.  S. Ye and I.N.M. Day, Microarrays & microplates: applications in biomedical sciences, 1st Edition, Garland Science, New York, USA, 2002.
  20.  R.J. Courcol, H. Deleersnyder, M. Roussel-Delvallez, and G.R. Martin, “Automated reading of a microtitre plate: preliminary evaluation in antimicrobial susceptibility tests and Enterobacteriaceae identification”, J. Clin. Pathol. 36(3), 341–344 (1983).
  21.  J.H. Platt, A.B. Shore, A.M. Smithyman, and G.L. Kampfner, “A computerised ELISA system for the determination of total and antigen- specific immunoglobulins in serum and secretions”, J. Immunoassay Immunochem. 2, 59‒74 (2006).
  22.  L. Maresová and H. Sychrova, “Applications of a microplate reader in yeast physiology research”, BioTechniques 43(5), 667‒672, 2007.
  23.  M. Frąc, A. Gryta, K. Oszust and N. Kotowicz, “Fast and accurate microplate method (Biolog MT2) for detection of Fusarium fungicides resistance/sensitivity”, Front. Microbiol. 7, 489 (2016).
  24.  C.E. Stanley, G. Grossmann, X. Casadevall i Solvas, and A.J. deMello, “Soil-on-a-Chip: microfluidic platforms for environmental organismal studies”, Lab Chip 16 (2), 228‒241 (2016).
  25.  A. Sanati Nezhad, “Microfluidic platforms for plant cells studies”, Lab Chip 14(17), 3262‒3274 (2014).
  26.  J.C. Jokerst and J.M. Emory, C.S. Henry, “Advances in microf luidics for environmental analysis”, Analyst 137(1), 24‒34 (2012).
  27.  D.W. Inglis, N. Herman, and G. Vesey, “Highly accurate deterministic lateral displacement device and its application to purification of fungal spores”, Biomicrofluidics 24(2), 024109 (2010).
  28.  Z. Palková, L. Váchová, M. Valer, and T. Preckel, “Single-cell analysis of yeast, mammalian cells, and fungal spores with a microfluidic pressure-driven chip-based system”, Cytometry A 59, 246‒253 (2004).
  29.  M. Held, C. Edwards, and D.V. Nicolau, “Examining the behaviour of fungal cells in microconfined mazelike structures”, in Proc. SPIE 6859, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues VI, 2008.
  30.  M. Held, O. Kašpar, C. Edwards, and D.V. Nicolau, “Intracellular mechanisms of fungal space searching in microenvironments”, PNAS 116, 13543‒13552 (2019).
  31.  E. Berthier, E.W. Young, and D. Beebe, “Engineers are from PDMS-land, Biologists are from Polystyrenia”, Lab Chip 12(7), 1224‒1237 (2012).
  32.  D. Stadnik, M. Chudy, Z. Brzózka, and A. Dybko, “Spectrophotometric analysis using poly (dimethylsiloxane) microfluidic detectors”, Bull. Pol. Ac.: Tech. 53(2), 163‒165 (2005).
  33.  X. Che, J. Boldrey, X. Zhong, S. Unnikandam-Veettil, I. Schneider, D. Jiles, and L. Que, “On-Chip Studies of Magnetic Stimulation Effect on Single Neural Cell Viability and Proliferation on Glass and Nanoporous Surfaces”, ACS Appl. Mater. Interfaces 10 (34), 28269‒28278 (2018).
  34.  C. Iliescu, F. Tay, and J. Miao, “Strategies in deep wet etching of Pyrex glass”, Sens. Actuator A Phys. 133, 395‒400 (2007).
  35.  R. Ma, Q. Chen, Y. Fan, Q. Wang, S. Chen, X. Liu, L. Cai, and B. Yao, “Six new soil–inhabiting Cladosporium species from plateaus in China”, Mycologia 109(2), 244‒260 (2017).
  36.  I. Ghiaie Asl, M. Motamedi, G.R. Shokuhi, N. Jalalizand, A. Farhang, and H. Mirhendi, “Molecular characterization of environmental Cladosporium species isolated from Iran.” Curr. Med. Mycol 3(1), 1–5 (2017).
  37.  T. Watanabe, Pictorial Atlas of Soil and Seed Fungi: Morphologies of Cultured Fungi and Key to Species, CRC Press, Washington, USA (2011).
  38.  K.H. Domsch, W. Gams, and T.H. Anderson. Compendium of Soil Fungi, T: 1, Academic Press, London, UK, 1980.
  39.  J.C. Gilman, A manual of soil fungi, Ed. 2, Iowa State College Press, Ames, USA, 1957.
  40.  W. Pusz, K. Patejuk, and A. Kaczmarek, “Fungi colonizing of small balsam seeds (Impatiens parviflora DC.) seeds in Wigry National Park”, Prog. Plant Prot. 60, 33‒40 (2020).
  41.  B. Jacewski, J. Urbaniak, P. Kwiatkowski, and W. Pusz, “Microfungal diversity of Juncus trifidus L. and Salix herbacea L. at isolated locations in the Sudetes and Carpathian Mountains”, Acta Mycol. 54(1), 1118 (2019).
  42.  E. Levetin and K. Dorseys, “Contribution to leaf surface fungi to the air spora.” Aerobiologia 22, 3‒12 (2006).
  43.  S.N. Stohr and J. Dighton, “Effects of species diversity on establishment and coexistence: A phylloplane fungal community model system”, Microb. Ecol. 48, 431‒438 (2004).
  44.  E.M. El-Morsy, “Fungi isolated from the endorhizosphere of halophytic plants from the Red Sea Coast of Egypt”, Fungal Divers. 5, 43‒54 (2000).
  45.  K. Bensch, U. Braun, J.Z. Groenewald, and P.W. Crous, “The genus Cladosporium”, Stud. Mycol. 72, 1‒401 (2012).
  46.  M.B. Ellis, Dematiaceous Hyphomycetes, Commonwealth Mycological Institute, Kew, Surrey, UK, 1971.
  47.  R. Ogórek, A. Lejman, W. Pusz, A. Miłuch, and P. Miodyńska, “Characteristics and taxonomy of Cladosporium fungi”, Med. Mycol. J. 19(2), 80‒85 (2012).
  48.  S. Sharma, R.C. Sharma, and R. Malhotra, “Effect of the Saprophytic Fungi Alternaria alternata and Cladosporium oxysporum on Germination, Parasitism and Viability of Melampsora ciliata Urediniospores”, J. Plant. Dis. Prot. 109(3), 291‒300 (2002).
  49.  W. Pusz, R. Weber, A. Dancewicz, and W. Kita, “Analysis of selected fungi variation and its dependence on season and mountain range in southern Poland – key factors in drawing up trial guidelines for aeromycological monitoring”, Environ. Monit. Assess. 189(10), 526 (2017).
  50.  W. Pusz, W. Kita, A. Dancewicz, and R. Weber, “Airborne fungal spores of subalpine zone of the Karkonosze and Izerskie Mountains (Poland)”, J. Mt. Sci. 10(10), 940–952 (2013).
  51.  W. Pusz, M. Król, and T. Zwijacz-Kozica, “Airborne fungi as indicators of ecosystem disturbance: an example from selected Tatra Mountains caves (Poland)”, Aerobiologia 34, 111‒118 (2018).
  52.  E. Porca, V. Jurado, P.M. Martin-Sanchez, B. Hermosin, F. Bastian, C. Alabouvette, and C. Saiz-Jimenez, “Aerobiology: An ecological indicator for early detection and control of fungal outbreaks in caves”, Ecol. Indic. 11(6), 1594‒1598 (2011).
  53.  P. Gutarowska, “Moulds in biodeterioration of technical materials”, Folia Biologica et Oecologica 10, 27‒39 (2014).
  54.  B. Zyska and Z. Żakowska. Mikrobiologia materiałów, Politechnika Łódzka, Łódź, 2005.
  55.  T.J. Berryman. “Fuel Quality and demand – an overview” in Microbiology of fuels, Ed. R.N. Smith, Institute of Petroleum, London, UK, 1987.
  56.  K. Schubert, J.Z. Groenewald, U. Braun, J. Dijksterhuis, M. Starink, C.F. Hill, P. Zalar, G.S. de Hoog, and P.W. Crous, “Biodiversity in the Cladosporium herbarum complex (Davidiellaceae, Capnodiales), with standardisation of methods for Cladosporium taxonomy and diagnostics”, Stud. Mycol. 58, 105‒156 (2007).
  57.  J. Israel Martínez-López, M. Mojica, C.A. Rodríguez, and H.R. Siller, “Xurography as a Rapid Fabrication Alternative for Point-of-Care Devices: Assessment of Passive Micromixers”, Sensors (Basel) 16(5), 705 (2016).
  58.  D. Witkowski, W. Kubicki, J.A. Dziuban, D. Jašíková, and A. Karczemska, “Micro-particle image velocimetry for imaging flows in passive microfluidic mixers”, Bull. Pol. Ac.: Tech. 25(3), 441–450 (2018).
  59.  A. Lamberti, S.L. Marasso, and M. Cocuzza, “PDMS membranes with tunable gas permeability for microfluidic applications”, RSC Adv. 4, 61415–61419 (2014).
  60.  K. Kamei, Y. Mashimo, and Y. Koyama, “3D printing of soft lithography mold for rapid production of polydimethylsiloxane-based microfluidic devices for cell stimulation with concentration gradients”, Biomed. Microdev. 17(2), 36 (2015).
  61.  P. Thurgood, S. Baratchi, C. Szydzik, A. Mitchella, and K. Khoshmanesh, “Porous PDMS structures for the storage and release of aqueous solutions into fluidic environments”, Lab Chip 17, 2517‒2527 (2017).
  62.  A. Podwin, R. Walczak, and J.A. Dziuban, “A 3D printed membrane-based gas microflow regulator for on-chip cell culture”, Appl. Sci. 8(4), 579 (2018).
  63.  A. Podwin and J.A. Dziuban, “Modular 3D printed lab-on-a-chip bio-reactor for the biochemical energy cascade of microorganisms”, J. Micromech. Microeng. 27(10), 104004 (2017).
  64.  A. Podwin, W. Kubicki, K. Adamski, R. Walczak, and J.A. Dziuban, “A step towards on-chip biochemical energy cascade of microorganisms: Carbon dioxide generation induced by ethanol fermentation in 3D printed modular lab-on-a-chip”, J. Phys.: Conf. Ser. 773(1), 012052 (2016).
  65.  K. Ozasa, J. Lee, S. Song, M. Hara, and M. Maeda, “Gas/liquid sensing via chemotaxis of euglena cells confined in an isolated micro- aquarium”, Lab Chip 13, 4033‒4039 (2013).
  66.  F.J.H. Hol and C. Dekker, “Zooming in to see the bigger picture: Microfluidic and nanofabrication tools to study bacteria”, Science 346 (6208), 1251821 (2014).
  67.  K. Nagy, Á. Ábrahám, J.E. Keymer, and P. Galajda, “Application of Microfluidics in Experimental Ecology: The Importance of Being Spatial”, Front. Microbiol. 9, 496 (2018)
  68.  A. Podwin, W. Kubicki, and J.A. Dziuban, “Study of the behavior of Euglena viridis, Euglena gracilis and Lepadella patella cultured in all-glass microaquarium”, Biomed. Microdev. 19(3), 63 (2017).
  69.  R. Walczak, P. Śniadek, J.A. Dziuban, J. Kluger, and A. Chełmońska-Soyta, “Supravital fluorometric apoptosis detection in a single mouse embryo using lab-on-a-chip”, Lab Chip 11, 3263‒3268 (2011).
  70.  A. Podwin, D. Lizanets, D. Przystupski, W. Kubicki, P. Śniadek, J. Kulbacka, A. Wymysłowski, R. Walczak, and J.A. Dziuban, “Lab-on- Chip Platform for Culturing and Dynamic Evaluation of Cells Development”, Micromachines 11(2), 196 (2020).
  71.  W. Wei, et al., “A numerical model for air concentration distribution in self-aerated open channel flows”, J. Hydrodynam. B. 27(3), 394‒402 (2015).
  72.  S. Agaoglu, et al., “The effect of pre-polymer/cross-linker storage on the elasticity and reliability of PDMS microfluidic devices”, Microfluid. Nanofluidics 21, 117 (2017).
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Autorzy i Afiliacje

Agnieszka Podwin
1
Tymon Janisz
1
ORCID: ORCID
Katarzyna Patejuk
2
Piotr Szyszka
1
Rafał Walczak
1
Jan Dziuban
1

  1. Wrocław University of Science and Technology, Faculty of Microsystem Electronics and Photonics, ul. Janiszewskiego 11/17, 50-372 Wrocław, Poland
  2. Wrocław University of Environmental and Life Sciences, Department of Plant Protection, Grunwaldzki Sq. 24a, 50-363 Wroclaw, Poland
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Abstrakt

The longitudinal automatic carrier landing system (ACLS) control law is designed based on nonlinear dynamic inversion (NDI), which can reject air wake, decouple lateral states, and track the dynamic desired touchdown point (DTP). First of all, the nonlinear landing model of F/A−18 aircraft in the final approach is established, in which the parameters of the aerodynamic, control surfaces, and limited states are acquired. Second, the strategy of tracking the desired longitudinal trajectory through pitch angle control is adopted. The automatic power compensation system (APCS), pitch angle rate, pitch angle, and vertical position control loops are developed based on the adaptive NDI. The stable analysis and the principal description are derived in detail. Deck motion compensation (DMC) algorithm is designed by frequency response method. Third, the control parameters are optimized through the genetic algorithm. A fitness function integrated with velocity, angle of attack (AOA), pitch rate, pitch angle, and vertical position of the aircraft are proposed. Finally, integrated simulations are conducted on a semi-physical simulation platform. The results indicate that the adopted automatic landing control law can achieve both excellent performance and the ability to reject the air wake and lateral coupling.
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Bibliografia

  1.  M. Ryota and S. Shinji, “Modeling of pilot landing approach control using stochastic switched linear regression model”, J. Aircr. 47(5), 1554–1558 (2010).
  2.  J. Tian, Y. Dai, H. Rong, and T.D. Zhao, “Hybrid safety analysis method based on SVM and RST: An application to carrier landing of aircraft”, Saf. Sci. 80, 56–65 (2015).
  3.  L.P. Wang, Q.D. Zhu, Z. Zhang, and R. Dong. “Modeling pilot behaviors based on discrete–time series during carrier-based aircraft landing”, J. Aircr. 53(6), 1922–1931 (2016).
  4.  J.M. Urnes and R.K. Hess, “Development of the F/A 18A automatic carrier landing system”, J. Guid. 8(3), 289-295 (1985).
  5.  Z.Y. Guan, Y.P. Ma, and Z.W. Zheng, “Prescribed performance control for automatic carrier landing with disturbance”, Nonlinear Dyn. 94(2), 1335–1349 (2018).
  6.  Z.Y. Zhen, S.Y. Jiang, and K. Ma, “Automatic carrier landing control for unmanned aerial vehicles based on preview control and particle filtering”, Aerosp. Sci. Technol. 81, 99–107 (2018).
  7.  Z.Y. Zhen, S.Y. Jiang, and J. Jiang, “Preview control and particle filtering for automatic carrier landing”, IEEE Trans. Aerosp. Electron. Syst. 54(6), 2662–2674 (2018).
  8.  R. Lungu and M. Lungu, “Design of automatic landing systems using the H-inf control and the dynamic inversion”, J. Dyn. Syst. Meas. Control- Trans. ASME. 138(2), 1–5 (2016).
  9.  R. Lungu and M. Lungu, “Automatic Landing system using neural networks and radio-technical subsystems”, Chin. J. Aeronaut. 30(1), 399–411 (2017).
  10.  M. Lungu and R. Lungu, “Automatic control of aircraft lateraldirectional motion during landing using neural networks and radio-technical subsystems”, Neurocomputing. 171, 471–481 (2016).
  11.  Q. Bian, B. Nener, T. Li, and X.M. Wang, “Multimodal control parameter optimization for aircraft longitudinal automatic landing via the hybrid particle swarm-BFGS algorithm”, Proc. Inst. Mech. Eng. Part G-J. Aerosp. Eng. 233(12), 4482–4491 (2019).
  12.  F.Y. Zheng, Z.Y. Zhen, and H.J. Gong, “Observer-based backstepping longitudinal control for carrier-based UAV with actuator faults”, J. Syst. Eng. Electron. 28(2), 322–337 (2017).
  13.  Z.Y. Zhen, C.J. Yu, and S.Y. Jiang, “Adaptive super-twisting control for automatic carrier landing of aircraft”, IEEE Trans. Aerosp. Electron. Syst. 56(2), 987–994 (2020).
  14.  Z.Y. Zhen, G. Tao, and C.J. Yu, “A multivariable adaptive control scheme for automatic carrier landing of UAV”, Aerosp. Sci. Technol. 92, 714–721 (2019).
  15.  L.P. Wang, Z. Zhang, Q.D. Zhu, and R. Dong, “Longitudinal automatic carrier landing system guidance law using model predictive control with an additional landing risk term”, Proc. Inst. Mech. Eng. Part G-J. Aerosp. Eng. 233(3), 1–17 (2019).
  16.  L.P. Wang, Z. Zhang, and Q.D. Zhu, “Automatic Flight Control Design Considering Objective and Subjective Risks during Carrier Landing”, Proc. Inst. Mech. Eng. Part I-J Syst Control Eng. 234(4), 446–461 (2020).
  17.  L.P. Wang, Z. Zhang, Q.D. Zhu, X.W. Jiang, “Lateral autonomous carrier-landing control with high-dimension landing risks consideration”, Aircr. Eng. Aerosp. Technol. 92(6), 837– 850 (2020).
  18.  T. Woodbury and J. Valasek, “Synthesis and flight test of an automatic landing controller using quantitative feedback theory”, J. Guid. Control Dyn. 39(9), 1994–2010 (2016).
  19.  B. Xu, D.W. Wang, Y.M. Zhang, and Z.K. Shi, “DOB-based neural control of flexible hypersonic flight vehicle considering wind effects”, IEEE Trans. Ind. Electron. 64(11), 8676–8685 (2017).
  20.  D. Gawel, M. Nowak, H. Hausa, and R. Roszak, “New biomimetic approach to the aircraft wing structural design based on aeroelastic analysis”, Bull. Pol. Ac.: Tech. 65(5), 741–750 (2017).
  21.  J.N. Li and H.B. Duan, “Simplified brain storm optimization approach to control parameter optimization in F/A 18 automatic carrier landing system”, Aerosp. Sci. Technol. 42, 187–195 (2015).
  22.  R. Dou and H.B. Duan, “Levy flight based pigeon-inspired optimization for control parameters optimization in automatic carrier landing system”, Aerosp. Sci. Technol. 61, 11–20 (2017).
  23.  K. Lu and C.S. Liu, “A L-1 adaptive control scheme for UAV carrier landing using nonlinear dynamic inversion”, Int. J. Aerosp. Eng. 1–9 (2019).
  24.  M. Brodecki and K. Subbarao. Autonomous formation flight control system using in-flight sweet-spot estimation. J. Guid. Control Dyn. 38(6), 1083–1096 (2015).
  25.  H. Bouadi, F.M. Camino, and D. Choukroun, “Space–Indexed Control for Aircraft Vertical Guidance with Time Constraint”, J. Guid. Control Dyn. 37(4), 1103–1113 (2014).
  26.  P.K. Menon, S.S. Vaddi, and P. Sengupta, “Robust landingguidance law for impaired aircraft”, J. Guid. Control Dyn. 35(6), 1865−1877 (2012).
  27.  W.H. Chen, “Nonlinear Disturbance observer-enhanced dynamic inversion control of missiles”, J. Guid. Control Dyn. 26(1), 161–166 (2003).
  28.  I. Hameduddin and A.H. Bajodah, “Nonlinear generalised dynamic inversion for aircraft manoeuvring control”, Int. J. Control. 85(4), 437–450 (2012).
  29.  R. Lungu and M. Lungu, “Design of automatic landing systems using the H-inf control and the dynamic inversion”, J. Dyn. Syst. Meas. Control- Trans. ASME. 138(2), 1–5 (2016).
  30.  M. Lungu and R. Lungu, “Landing auto-pilots for aircraft motion in longitudinal plane using adaptive control laws based on neural networks and dynamic inversion”, Asian J. Control. 19(1), 302–315 (2017).
  31.  R. Lungu and M. Lungu, “Automatic control of aircraft in lateral-directional plane during landing”, Asian J. Control. 18(2), 433–446 (2016).
  32.  A. Chakraborty, P. Seiler, and G. J. Balasz, “Applications of linear and nonlinear robustness analysis techniques to the F/A-18 flight control laws”, AIAA Guidance, Navigation, and Control conference. Chicago, USA, 2009, pp.10–13.
  33.  A. Chakraborty, P. Seiler, and G. J. Balas, “Susceptibility of F/A 18 flight controllers to the falling-leaf mode: nonlinear analysis”, J. Guid. Control Dyn. 34(1), 57–72 (2011).
  34.  J.M. Urnes, and R.K. Hess, “Development of the F/A-18A Automatic Carrier Landing System”, J. Guid. 8(3), 289–295 (1985).
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Autorzy i Afiliacje

Lipeng Wang
1
ORCID: ORCID
Zhi Zhang
1
Qidan Zhu
1
Zixia Wen
2

  1. College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, 150001, China
  2. AVIC Xi’an Flight Automatic Control Research Institute, Xi’an, 710065, China
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Abstrakt

The unmanned underwater tracked bulldozer (UUTB) is an indispensable equipment for dredging and cleaning obstacles on the river bed in the flood season. The investigation on the interaction properties between the UUTB tracks and sediments provides foundation for the evaluation of operation performance when it works on the inland river bed. Based on the current worldwide research, the sediments mixed by sand, bentonite and water with sand content 0%, 10% and 20% were configured in this study to replace the real sediments on the inland river bed in China. The current pressure-sinkage model and shear stress-shear displacement model were discussed. Three different tracks were tested for the pressure-sinkage and the shear stress-shear displacement on the platform. The relationship between pressure and sinkage under sand content 0%, 10% and 20% are revealed based on the experimental results. The modulus of cohesive deformation and friction deformation of the sediments under said sand content are presented. The curves of shear stress and shear displacement are also obtained, which demonstrates the properties between the tracks and configured sediments under sand content 0%, 10% and 20%. The relationship between the tractive force and slip ratio with three different tracks under said sand content is also presented based on the quantitative analysis, which provides reference for the dynamics control and performance evaluation of UUTB on the inland river bed.

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Bibliografia

  1.  C.B. Yang, M. Dong, L. Gu, Q. Li, X.D. Gao, “Study on soil thrust of crawler plate considering the shape of shoe thorn”, J. Beijing Inst. Technol. 35(11), 1118‒1121 (2015).
  2.  C.B. Yang, Research on the adhesion characteristics and optimization of high-speed track and soft ground, Beijing Institute of Technology, 2015.
  3.  X. Lü, Q. Zhou, and B. Fang, “Hydrodynamic performance of distributed pump-jet propulsion system for underwater vehicle,” J. Hydrodyn. 26(4), 523–530 (2014).
  4.  A. Yasui, K.Sunobe, and T. Murata “Development of underwater bulldozer systems”, J. Terramech. 10(4), 13‒20 (1973).
  5.  G. Yamauchi, K. Nagatani, T. Hashimoto, and K. Fujino, “Slip-compensated odometry for tracked vehicle on loose and weak slope”, J. Hydrodyn. 4(2), 2197‒4225 (2017).
  6.  F. Xu, Q.H. Rao, and W.B. Ma, “Predicting the sinkage of a moving tracked mining vehicle using a new rheological formulation for soft deep-sea sediment”, J. Hydrodyn. 36, 230‒237 (2018).
  7.  S. Hong, J.S. Choi, H.W. Kim, M.C. Won, S.C. Shin, J.S. Rhee, and H.N. Par, “A path tracking control algorithm for underwater mining vehicles”, J. Mech. Sci. Technol. 23(8), 2030‒2037 (2009).
  8.  S.M. Yoon, S. Hong, S.J. Park, J.S. Choi, H.W. Kim, and T.K. Yeu, “Track velocity control of crawler type underwater mining robot through shallow-water test”, J. Mech. Sci. Technol. 26(10), 3291‒3298 (2012).
  9.  K. Herzog, E. Schulte, M.A. Atmanand, and W. Schwarz, “Slip Control System for a Deep-Sea Mining Machine”, IEEE Trans. Autom. Sci. Eng. 4(2), 282‒286 (2007).
  10.  H. Grebe and E.S. Schulte, Determination of soil parameters based on the operational data of a ground operated tracked vehicle, pp. 149‒156, International Society of Offshore and Polar Engineers, 2005.
  11.  E. Schulte and W. Schwarz, “Simulation of Tracked Vehicle Performance on Deep Sea Soil Based on Soil Mechanical Laboratory Measurements in Bentonite Soil”, in Proceedings of The Eighth ISOPE Ocean Mining Symposium, 2009, pp. 276‒284.
  12.  L.Q. Song, “Geotechnical Properties of Oceanic Sediments in Polymetallic Nodules Belts”, Acta Oceanol. Sin., 19(2), 57‒67 (2000).
  13.  X.L. Chen, J.Z. Lu, T.W. Cui, L.Q. Tian, L.Q. Chen, and W.J. Zhao, “Coupling remote sensing retrieval with numerical simulation for SPM study—Taking Bohai Sea in China as a case”, Int. J. Appl. Earth Obs. Geoinf. 12(2), 203‒211 (2010).
  14.  S.J. Liu, C. Liu, and Y. Dai, “Research and development of deep-sea mining equipment”, Chin. J. Mech. Eng. 50(2), 8‒18 (2014).
  15.  Y. Dai and S.J. Liu, “Dynamic analysis of integrated linkage operation mode of deep-sea mining system”, J. Huazhong Univ. Sci. Tech.- Natural Sci. 40(S2), 39‒43 (2012).
  16.  Y. Dai and S.J. Liu, “Theoretical design and dynamic simulation of new mining paths of tracked miner on deep seafloor”, J. Cent. South Univ. 20(04), 918‒923 (2013).
  17.  Y. Dai and S.J. Liu, “Dynamic Analysis of the Seafloor Pilot Miner Based on Single-Body Vehicle Model and Discretized Track-Terrain Interaction Model”, China Ocean Eng. 24(01), 145‒160 (2010).
  18.  Y. Dai, H. Liu, T. Zhang, and S.J. Liu, “A study on the driving performance of seabed crawler mining vehicle”, Chinese Sci. Technol. Paper 10(10), 1203‒1208 (2015).
  19.  L. Li and S.L. Li, “Simulation of deep-sea surface Marine mud and study on surface mechanical properties”, Eng. Mech. 27(11), 213‒220 (2010).
  20.  M. Wang, X. Wang, and Y. Sun, “Tractive performance evaluation of seafloor tracked trencher based on laboratory mechanical measurements”, Int. J. Nav. Archit. Ocean Eng. 8(2), 177‒187 (2016).
  21.  M. Wang, X. Wang, and Y. Sun, “Traction Potential Analysis of Self-Propelled Seafloor Trencher Based on Mechanical Measurements in Bentonite Soil”, J. Harbin Inst. Technol. 24(1), 71‒80 (2017).
  22.  C. Yang, G. Yang, and Z. Liu, “A method for deducing pressure–sinkage of tracked vehicle in rough terrain considering moisture and sinkage speed”, J. Terramech. 79, 99‒113 (2018).
  23.  P. Siemaszko and Z. Meyer, “Static load test cure analysis based on soil field investigations”, Bull. Pol. Ac.: Tech. 67(2), 329‒337 (2019).
  24.  A. Sawicki, J. Mierczynski, and W. Swidzinski, “Basic set of experiments for determination of mechanical properties of sand”, Bull. Pol. Ac.: Tech. 62(1), 129‒137 (2014).
  25.  C. Janarthanan, K.Gopkumar, V.Sundaramoorthi, N.R. Ramesh, and G.A. Ramadass, “Influence of Grouser Geometrical Parameters of Deep-Sea Crawler Vehicle on Soft Clays”, J. Hydrodyn. 47:899‒912 (2018).
  26.  H. Mao, F. Kumi, and Q. Li, “Combining X-ray computed tomography with relevant techniques for analysing soil-root dynamics-an overview”, Acta Agric. Scand. Sect. B – Soil Plant Sci. 66(1), 1‒19 (2015).
  27.  T. Kato and M. Kamichika, “Determination of a crop coefficient for evapotranspiration in a sparse sorghum field”, Irrig. Drain., 55(2), 165‒175 (2010).
  28.  S. Hong, H.W. Kim, T. Yue, J.S. Choi, T.H. Lee, and J.K. Lee, “Technologies for Safe and Sustainable Mining of Deep-Seabed Minerals”, J. Hydrodyn. 65:95‒143 (2019).
  29.  Z.Y. Zuo, X.G. Li, C. Xu, “Responses of barley Albina and Xantha mutants deficient in magnesium chelatase to soil salinity”, Plant Soil Environ. 63(8), 348‒354 (2017).
  30.  C.L. Qi, Q.H. Rao, Q. Liu, and W.B. Ma, “Traction rheological properties of simulative soil for deep-sea sediment”, J. Hydrodyn. 37:61‒71 (2019).
  31.  B. Ali Abubaker, H.F. Yan, and L. Hong, “Enhancement of Depleted Loam Soil as Well as Cucumber Productivity Utilizing Biochar Under Water Stress”, Commun. Soil Sci. Plant Anal. 50(1), 49‒64 (2019).
  32.  W. Wei, Y. Xu, and S. Li, “Developing suppressive soil for root diseases of soybean with continuous long-term cropping of soybean in black soil of Northeast China”, Acta Agric. Scand. Sect. B – Soil Plant Sci. 65(3), 7 (2015).
  33.  J.Z. Li, S.J. Liu, and Y. Dai, “Effect of grouser height on tractive performance of tracked mining vehicle”, J. Hydrodyn. 39:2459‒2466 (2017).
  34.  D. Knez and A. Calicki, “Looking for a new source of natural proppants in Poland”, Bull. Pol. Ac.: Tech. 66(1), 3‒8 (2018).
  35.  M. Mitew-Czajewska, “Parametric study of deep excavation in clays”, Bull. Pol. Ac.: Tech. 66(5), 747‒754 (2018).
  36.  J. Liu, X.M. Liu, and J.M. Xie, “Influence of copper on transport and dissipation of lambda-cyhalothrin and cypermethrin in soils”, Pedosphere 23(3), 395‒401 (2013).
  37.  L.L. Chu, Y.H. Kang, and S.Q. Wan, “Effect of different water application intensity and irrigation amount treatments of microirrigation on soil-leaching coastal saline soils of North China”, J. Integr. Agric. 15(9), 2123‒2131 (2016).
  38.  J.Y. Wong, Theory of Ground Vehicles. John Wiley & Sons Inc, 2001.
  39.  J.Y. Wong, Terramechanics and Off-road Engineering. Elsevier, 2010.
  40.  J.Y. Wong, M. Garber, and J. Preston-Thomas, “Theoretical prediction and experimental substantiation of the ground pressure distribution and tractive performance of tracked vehicles”, Proc. Inst. Mech. Eng. Part D-J. Automob. Eng. (4), 265‒285 (1988).
  41.  E. Schulte, R. Handschuh, and W. Schwarz, “Transferability of soil mechanical parameters to traction potential calculation of a tracked vehicle”, in Proceedings of the Fifth Ocean Mining Symposium, 2003, pp. 123‒131.
  42.  Z. Janosi and B. Hanamoto, “Analytical determination of drawbar pull as a function of slip on tracked vehicles in deformable soils”, 1st Intern. Conference on Terrain-Vehicles Systems, 1961, pp. 1131‒1152.
  43.  M. Wang, C. Wu, and T. Ge, “Calibration and validation of tractive performance for seafloor tracked trencher”, J. Terramech. 66, 13‒25 (2016).
  44.  M. Wang, X.Y. Wang, Y.H. Sun, and Z.M. Gu, “Tractive performance evaluation of seafloor tracked trencher based on laboratory mechanical measurements”, Int. J. Nav. Archit. Ocean Eng. 8, 177‒187 (2016).
  45.  M.G. Bekker, Theory of land locomotion: the mechanics of vehicle mobility, pp. 221‒262, The University of Michigan Press, 1956.
  46.  M.G. Bekker, Theory of Land Locomotion, University of Michigan Press, 1962.
  47.  M.G. Bekker, Introduction to Terrain-vehicle Systems, University of Michigan Press, 1969.
  48.  A.R. Reece, “Principles of soil-vehicle mechanics”, Proc. Inst. Mech. Eng. Automob. Div. 180(1), 45‒66 (1965).
  49.  Y. Xu, H.Y. Wu, and L.B. Zuo, “Influence of shale tooth height of tracked vehicle on traction performance and its parameter determination”, Trans. Chinese Soc. Agric. Eng. 28(11), 68‒74 (2012).
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Autorzy i Afiliacje

Yong Li
1
Dingchang He
1
Qiaorui Si
2

  1. Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, 212013, P. R. China
  2. Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang, 212013, P. R. China
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Abstrakt

This article presents a system of precise navigation for a visually impaired person which uses GPS navigation and an infrared sensor in the form of an infrared matrix. The presented system allows determining the orientation and distance of a blind person relative to a selected object, e.g. a wall or road edge. The application of the above solution facilitates a significant increase in the accuracy of determining the position of a blind person compared to the accuracy offered by commonly used ground satellite devices. The system uses thermal energy accumulated in the environment without the need to generate additional signals. The main parts of the system are a simple infrared matrix, data processing system and vibrating wristband. Messages and navigation warnings are sent to a blind person in the form of a vibration code. The article describes the method of determining the path of a specified width and distance from the wall of a building, curb, etc., along which a blind person should move. The article additionally describes the method of determining the orientation of a blind person depending on the selected object. Such a method facilitates verifying whether the visually impaired person is moving according to the indicated direction. The method can also be used to navigate mobile robots. Due to the use of natural energy for data registration and processing, the mobile navigation system can be operated for a long time without the need to recharge the battery.

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Bibliografia

  1.  R.R.A. Bourne et al., “Vision Loss Expert Group (2017). Magnitude, temporal trends, and projections of the global prevalence of blindness and distance and near vision impairment: a systematic review and meta-analysis”, Lancet Glob. Health 5(9), e888-e897 (2017), doi: 10.1016/S2214-109X(17)30293-0.
  2.  K. Bryant, “Seeing what the future holds”, Sightings SEE International, April, 2018
  3.  P. Barański and P. Strumiłło, “Enhancing positioning accuracy in urban terrain by fusing data from a GPS receiver, inertial sensors, stereo- camera and digital maps for pedestrian navigation”, Sensors 12(6), 6764–6801 (2012).
  4.  R. Sammouda and A. Alrjoub, “Mobile blind navigation system using RFID”, in 2015 Global Summit on Computer & Information Technology (GSCIT), Sousse, 2015, pp. 1‒4, doi: 10.1109/GSCIT.2015.7353325.
  5.  J. Villanueva and R. Farcy, “Optical Device Indicating a Safe Free Path to Blind People”, IEEE Trans. Instrum. Meas. 61(1), 170‒177 (2012), doi: 10.1109/TIM.2011.2160910.
  6.  A. Sen, K. Sen, and J. Das, “Ultrasonic Blind Stick for Completely Blind People to Avoid Any Kind of Obstacles”, 2018 IEEE SENSORS, New Delhi, India, 2018, pp. 1‒4, doi: 10.1109/ICSENS.2018.8589680.
  7.  N. Mahmud, R.K. Saha, R.B. Zafar, M.B.H. Bhuian, and S.S. Sarwar, “Vibration and voice operated navigation system for visually impaired person”, in 2014 International Conference on Informatics, Electronics & Vision (ICIEV), Dhaka, 2014, pp. 1‒5, doi: 10.1109/ ICIEV.2014.6850740.
  8.  P. Barański, M. Polańczyk, and P. Strumiłło, “A remote guidance system for the blind”, in Proceedings of the 12th International Conference on e-Health Networking, Application & Services (Healthcom2010), Lyon, France, 2010, pp. 386–390.
  9.  W. Gelmuda and A. Kos, “Multichannel ultrasonic range finder for blind people navigation”, Bull. Pol. Ac.: Tech. 61(3), 633‒637 (2013).
  10.  P. Marzec and A. Kos, “Low energy precise navigation system for the blind with infrared sensors”, in 2019 MIXDES – 26th International Conference “Mixed Design of Integrated Circuits and Systems”, Rzeszów, 2019.
  11.  Kiruthika and Sheela, “Developing mobile application to navigate blind people using sensors”, 2016 International Conference on Computation of Power, Energy Information and Commuincation (ICCPEIC), Chennai, 2016, pp. 080‒084, doi: 10.1109/ICCPEIC.2016.7557228.
  12.  “The ultimate infrared handbook for R&D professionals”, FLIR AB. [Online]. https://www.flirmedia.com/MMC/THG/Brochures/T559243/ T559243_EN.pdf
  13.  S. Sichelschmidt, A. Haselhoff, A. Kummert, M. Roehder, B. Elias, and K. Berns, “Pedestrian crossing detecting as a part of an urban pedestrian safety system”, 2010 IEEE Intelligent Vehicles Symposium, San Diego, CA, 2010, pp. 840‒844, doi: 10.1109/IVS.2010.5548032.
  14.  A. Kos, K. Boroń, and I. Brzozowski, “Thermal tablet for the blind”, Microelectron. Int. 33(1), 1‒8 (2016), doi: 10.1108/MI-02-2015- 0016.
  15.  R. Sarkar, S. Das, and D. Rudrapal, “A low cost microelectromechanical Braille for blind people to communicate with blind or deaf blind people through SMS subsystem”, 2013 3rd IEEE International Advance Computing Conference (IACC), Ghaziabad, 2013, pp. 1529‒1532, doi: 10.1109/IAdCC.2013.6514454.
  16.  R. Uzun, G.K. Yaman, A. Tekkanat, and Y. İşler, “Wristband design to support blind people”, 2017 Medical Technologies National Congress (TIPTEKNO), Trabzon, 2017, pp. 1‒4, doi: 10.1109/TIPTEKNO.2017.8238038.
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Autorzy i Afiliacje

Paweł Marzec
1
Andrzej Kos
1

  1. AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, al. Mickiewicza 30, 30-059 Krakow, Poland

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