Applied sciences

Archives of Acoustics

Content

Archives of Acoustics | 2021 | vol. 46 | No 3

Download PDF Download RIS Download Bibtex

Abstract

Nonlinear excitation of the entropy perturbations by magnetosonic waves in a uniform and infinite plasma model is considered. The wave vector of slow or fast mode forms an arbitrary angle θ (0≤θ≤π) with the equilibrium straight magnetic field, and all perturbations are functions of the time and longitudinal coordinate. Thermal conduction is the only factor which destroys isentropicity of wave perturbations and causes the nonlinear excitation of the entropy mode. A dynamic equation is derived which describes excitation of perturbation in the entropy mode in the field of dominant magnetosonic mode. Effects associatiated with temperature dependent and anisotropic thermal conduction are considered and discussed.
Go to article

Bibliography

1. Afanasyev A.N., Nakariakov V.M. (2014), Nonlinear slow magnetoacoustic waves in coronal plasma structures, Astronomy and Astrophysics, 573: A32, doi: 10.1051/0004-6361/201424516.
2. Ballai I. (2006), Nonlinear waves in solar plasmas – a review, Journal of Physics: Conference Series, 44(20): 20–29, doi: 10.1088/1742-6596/44/1/003.
3. Braginskii S.I. (1965), Transport processes in plasma, Reviews of Plasma Physics, M.A. Leontovich [Ed.], Vol. 1, p. 205, Consultants Bureau, New York.
4. Callen J.D. (2003), Fundamentals of Plasma Physics, Lecture Notes, University of Wisconsin, Madison.
5. Chin R., Verwichte E., Rowlands G., Nakariakov V.M. (2010), Self-organization of magnetoacoustic waves in a thermal unstable environment, Physics of Plasmas, 17(32): 107–118, doi: 10.1063/1.3314721.
6. Dahlburg R.B., Mariska J.T. (1988), Influence of heating rate on the condensational instability, Solar Physics, 117(1): 51–56, doi: 10.1007/BF00148571.
7. Field G.B. (1965), Thermal instability, The Astrophysical Journal, 142: 531–567, doi: 10.1086/148317.
8. Heyvaerts J. (1974), The thermal instability in a magnetohydrodynamic medium, Astronomy and Astrophysics, 37(1): 65–73.
9. Hollweg J.V. (1985), Viscosity in a magnetized plasma: Physical interpretation, Journal of Geophysical Research, 90(A8): 7620–7622, doi: 10.1029/JA090iA08p07620.
10. Ibáñez S.M.H., Parravano A. (1994), On the thermal structure and stability of configurations with heat diffusion and a gain-loss function. 3: Molecular gas, The Astrophysical Journal, 424(2): 763–771, doi: 10.1086/173929.
11. Krall N.A., Trivelpiece A.W. (1973), Principles of Plasma Physics, McGraw Hill, New York.
12. Kumar N., Kumar P., Singh S. (2006), Coronal heating by MHD waves, Astronomy and Astrophysics, 453: 1067–1078, doi: 10.1051/0004-6361:20054141.
13. Leble S., Perelomova A. (2018), The Dynamical Projectors Method: Hydro and Electrodynamics, CRC Press.
14. De Moortel I., Hood A.W. (2004), The damping of slow MHD waves in solar coronal magnetic fields, Astronomy and Astrophysics, 415: 705–715, doi: 10.1051/0004-6361:20034233.
15. Nakariakov V.M., Mendoza-Briceño C.A., Ibáñez M.H. (2000), Magnetoacoustic waves of small amplitude in optically thin quasi-isentropic plasmas, The Astrophysical Journal, 528(2, Part 1): 767–775, doi: 10.1086/308195.
16. Ofman L., Wang T. (2002), Hot coronal loop oscillations observed by SUMER: slow magnetosonic wave damping by thermal conduction, The Astrophysical Journal, 580(1): L85–L88, doi: 10.1086/345548.
17. Parker E.N. (1953), Instability of thermal fields, The Astrophysical Journal, 117: 431–436, doi: 10.1086/145707.
18. Perelomova A. (2006), Development of linear projecting in studies of non-linear flow. Acoustic heating induced by non-periodic sound, Physics Letters A, 357: 42–47, doi: 10.1016/j.physleta.2006.04.014.
19. Perelomova A. (2008), Modelling of acoustic heating induced by different types of sound, Archives of Acoustics, 33(2): 151–160.
20. Perelomova A. (2018a), Magnetoacoustic heating in a quasi-isentropic magnetic gas, Physics of Plasmas, 25: 042116, doi: 10.1063/1.5025030.
21. Perelomova A. (2018b), Magnetoacoustic heating in nonisentropic plasma caused by different kinds of heating-cooling function, Advances in Mathematical Physics, 2018: Article ID 8253210, 12 pages, doi: 10.1155/2018/8253210.
22. Perelomova A. (2020), Hysteresis curves for some periodic and aperiodic perturbations in magnetosonic flow, Physics of Plasmas, 27(10): 102101, doi: 10.1063/5.0015944.
23. Ruderman M.S., Verwichte E., Erdélyi R., Goossens M. (1996), Dissipative instability of the MHD tangential discontinuity in magnetized plasmas with an isotropic viscosity and thermal conductivity, Journal of Plasma Physics, 56(2): 285–306, doi: 10.1017/S0022377800019279.
24. Sabri S., Poedts S., Ebadi H. (2019), Plasma heating by magnetoacoustic wave propagation in the vicinity of a 2.5D magnetic null-point, Astronomy and Astrophysics, 623, doi: 10.1051/0004-6361/201834286.
25. Soler R., Ballester J.L., Parenti S. (2012), Stability of thermal modes in cool prominence plasmas, Astronomy and Astrophysics, 540: A7, doi: 10.1051/0004-6361/201118492.
26. Spitzer L. (1962), Physics of Fully Ionized Gases, 2nd ed., New York, Interscience.
27. Vesecky J.F., Antiochos S.K., Underwood J.H. (1979), Numerical modeling of quasi-static coronal loops. I – Uniform energy input, The Astrophysical Journal, 233(3): 987–997, doi: 10.1086/157462.
28. Wang T. (2011), Standing slow-mode waves in hot coronal loops: observations, modeling, and coronal seismology, Space Science Reviews, 158: 397–419, doi: 10.1007/s11214-010-9716-1.
29. Zavershinskii D.I., Molevich N.E., Riashchikov D.S., Belov S.A. (2020), Nonlinear magnetoacoustic waves in plasma with isentropic thermal instability, Physical Review E, 101(4): 043204, doi: 10.1103/PhysRevE.101.043204.
Go to article

Authors and Affiliations

Anna Perelomova
1

  1. Gdansk University of Technology, Faculty of Applied Physics and Mathematics, Gdansk, Poland
Download PDF Download RIS Download Bibtex

Abstract

Thanks to their excellent strength and durability, composite materials are used to manufacture many important structural elements. In the face of their extensive use, it is crucial to seek suitable methods for monitoring damages and locating their origins. The purpose of the article was to verify the possibility of applying the acoustic emissions (AE) method in the detection of damages in the structures of composite materials. The experimental part comprised static tensile tests carried out on various sandwich composites, including simultaneous registration of elastic waves with increasing loads, carried out with the use of an acousticelectrical sensor connected. The signal obtained from the sensor was then further processed and used to draw up diagrams of the AE hits, amplitude, root mean square of the AE source signal (RMS) and duration in the function of time. These diagrams were then applied on their corresponding stretching curves, the obtained charts were analysed. The results obtained point to a conclusion that the acoustic emissions method can be successfully used to detect and locate composite material damages.
Go to article

Bibliography

1. Aggelis D., Barkoula N.-M., Matikas T., Paipetis A. (2012), Acoustic structural health monitoring of composite materials: Damage identification and evaluation in cross ply laminates using acoustic emission and ultrasonics, Composities Science and Technology, 72(10): 1127–1133, doi: 10.1016/ j.compscitech.2011.10.011.
2. Al-Jumaili S.K., Pearson M.R., Holford K.M., Eaton M.J., Pullin R. (2016), Acoustic emission source location in complex structures using full automatic delta T mapping technique, Mechanical Systems and Signal Processing, 72–73: 513–524, doi: 10.1016/j.ymssp.2015.11.026.
3. Caesarendra W., Kosasih B., Tieu A.K., Zhu H., Moodie C.A.S., Zhu Q. (2016), Acoustic emissionbased condition monitoring methods: Review and application for low speed slew bearing, Mechanical Systems and Signal Processing, 72–73: 134–159, doi: 10.1016/j.ymssp.2015.10.020.
4. De Rosa I., Santulli C., Sarasini F. (2009), Acoustic emission for monitoring the mechanical behaviour of natural fibre composites: A literature review, Composites Part A: Applied Science and Manufacturing, 40(9): 1456–1469, doi: 10.1016/j.composite sa.2009.04.030.
5. Dudzik K., Labuda W. (2020), The possibility of applying acoustic emission and dynamometric methods for monitoring the turning process, Materials (Basel), 13(13): 2926, doi: 10.3390/ma13132926.
6. Gołaski L. (1994), Acoustic emission in composite materials [in Polish: Emisja akustyczna w materiałach kompozytowych], [in]: Małecki J., Ranachowski Z. [Eds], Acoustic emission. Sources. Methods. Usage [in Polish: Emisja akustyczna. Zródła. Metody. Zastosowania], Warszawa: PASCAL.
7. Gutkin R., Green C.J., Vangrattanachai S., Pinho S.T., Robinson P., Curtis P.T. (2011), On acoustic emission for failure investigation in CFRP: Pattern recognition and peak frequency analyses, Mechanical Systems and Signal Processing, 25(4): 1393– 1407, doi: 10.1016/j.ymssp.2010.11.014.
8. Hoła J. (1999), Acoustic-emission investigation of failure of high strength concrete, Archives of Acoustics, 24(2): 233–244.
9. Juskowiak E., Małdachowska A., Panek M. (2013), Acoustic emission of composite sandwich panels during three-point bending [in Polish: Emisja akustyczna kompozytowych płyt przekładkowych podczas trójpunktowego zginania], Przetwórstwo Tworzyw, 19(4): 351– 354.
10. Kurzydłowski K., Boczkowska A.S.J., Konopka K., Spychalski W. (2005), Monitoring of failures in the composites by non-destructive methods [in Polish: Monitorowanie uszkodzen w kompozytach metodami nieniszczacymi], Polymers, 50(4): 255–261.
11. Kyzioł L., Panasiuk K., Barcikowski M., Hajdukiewicz G. (2020), The influence of manufacturing technology on the properties of layered composites with polyester–glass recyclate additive, Progress in Rubber, Plastics and Recycling Technology, 36(1): 18–30, doi: 10.1177/1477760619895003.
12. Marec A., Thomas J., Guerjouma R.E. (2008), Damage characterization of polymer-based composite materials: Multivariable analysis and wavelet transform for clustering acoustic emission data, Mechanical Systems and Signal Processing, 22(6): 1441–1448, doi: 10.1016/j.ymssp.2007.11.029.
13. McCrory J.P. et al. (2005), Damage classification in carbon fibre composites using acoustic emission: A comparison of three techniques, Composites: Part B, 68: 424–430, doi: 10.1016/j.compositesb.2014.08.046.
14. Mohammadi R., Najafabadi M.A., Saeedifar M., Yousefi J., Minak G. (2017), Correlation of acoustic emission with finite element predicted damages in open-hole tensile laminated composites, Composites Part B: Engineering, 118: 427–435, doi: 10.1016/j.compositesb.2016.09.101.
15. Monti A., El Mahi A., Jendli Z., Guillaumat L. (2016), Mechanical behaviour and damage mechanisms analysis of a flax-fibre reinforced composite by acoustic emission, Composites Part A: Applied Science and Manufacturing, 90: 100–110, doi: 10.1016/j.compositesa.2016.07.002.
16. Nikbakht M., Yousefi J., Hosseini-Toudeshky H., Minak G. (2017), Delamination evaluation of composite laminates with different interface fiber orientations using acoustic emission features and micro visualization, Composites Part B: Engineering, 113: 185–196, doi: 10.1016/j.compositesb.2016.11.047.
17. Panasiuk K., Hajdukiewicz G. (2017), Production of composites with added waste polyester-glass with their initial mechanical properties, Scientific Journals of the Maritime University of Szczecin, 52(124): 30–36, doi: 10.17402/242.
18. Panasiuk K., Kyzioł L., Dudzik K. (2019), The use of acoustic emission signal (AE) in mechanical tests, Przeglad Elektrotechniczny, 95(11): 8–11, doi: 10.15199/48.2019.11.03.
19. PN-EN ISO 527-4:2000, Plastics – Determination of mechanical properties under static stretching – Test conditions for isotropic and orthotropic fiber-reinforced plastic composites.
20. PN-EN 1330-9:2017-09, Non-destructive testing – Terminology – Part 9: Terms used in acoustic emission testing.
21. PN-EN 13554: 2011E, Non-destructive testing – Acoustic emission – General rules. 22. PN-EN 15857: 2010E, Non-destructive testing – Acoustic emission – Testing of fiber-reinforced polymers – Specified methodology and general evaluation criteria.
23. Ranachowski Z., Józwiak-Niedzwiedzka D., Brandt A., Debowski T. (2012), Application of acoustic emission method to determine critical stress in fibre reinforced mortar beams, Archives of Acoustics, 37(3): 261–268, doi: 10.2478/v10168-012-0034-3.
24. Saeedifar M., Fotouhi M., Ahmadi Najafabadi M., Hosseini Toudeshky H., Minak G. (2016), Prediction of quasi-static delamination onset and growth in laminated composites by acoustic emission, Composites Part B: Engineering, 85: 113–122, doi: 10.1016/j.compositesb.2015.09.037.
25. Shafiq B., Quispitupa A., Just F., Banos M. (2005), Sandwich Structures 7: Advancing with Sandwich Structures and Materials: Proceedings of the 7th International Conference on Sandwich Structures, Aalborg University, Aalborg, Denmark, August 29– 31, 2005, Springer Science & Business Media, doi: 10.1007/1-4020-3848-8.
26. Xiao Y., Qiao W., Fukuda H., Hatta H. (2016), The effect of embedded devices on structural integrity of composite laminates, Composite Structures, 153: 21–29, doi: 10.1016/j.compstruct.2016.06.007.
27. Xingmin Z., Xiong Y.I. (2006), Investigation of damage mechanisms in self-reinforced polyethylene composites by acoustic emission, Composite Science and Technology, 66(3–4): 444–449, doi: 10.1016/j.compsci tech.2005.07.013.
28. Yu Y.-H., Cho J.-H., Kweon J.-H., Kim D.-H. (2006), A study on the failure detection of composite materials using an acoustic emission, Composite Structures, 75(1–4): 163–169, doi: 10.1016/j.compstruct.2006.04.070.
29. Zaki A., Chai H., Aggelis D., Alver N. (2015), Non-destructive evaluation for corrosion monitoring in concrete: a review and capability of acoustic emission technique, Sensors, 15(8): 19069–19101, doi: 10.3390/s150819069.
30. Zakłady Chemiczne „Organika Sarzyna” S.A., http://www.krisko.lublin.pl/chemia/zywice-poliestrowepolimal/konstrukcyjne-ogolnego-stosowania-polimal-1094-awtp-1/polimal-1094-awtp-1/polimal-1094-awtp-1-a-5-kg-1.html (access: 20.07.2020).
Go to article

Authors and Affiliations

Katarzyna Panasiuk
1
Krzysztof Dudzik
2
Grzegorz Hajdukiewicz
1

  1. Gdynia Maritime University, Faculty of Marine Engineering, Department of Engineering Sciences, Gdynia, Poland
  2. Gdynia Maritime University, Faculty of Marine Engineering, Marine Maintenance Department, Gdynia, Poland
Download PDF Download RIS Download Bibtex

Abstract

The paper presents the results of the application of the hierarchical clustering methods for the classification of the acoustic emission (AE) signals generated by eight basic forms of partial discharges (PD), which can occur in paper-oil insulation of power transformers. Based on the registered AE signals from the particular PD forms, using a frequency descriptor in the form of the power spectral density (PSD) of the signal, their representation in the form of the set of points on plane XY was created. Next, these sets were subjected to analysis using research algorithms consisting of selected clustering methods. Based on the suggested numeric performance indicators, the analysis of the degree of reproduction of the actual distribution of points showing the particular time waveforms of the AE signals from eight adopted PD forms (PD classes) in the obtained clusters was carried out. As a result of the analyses carried out, the clustering algorithms of the highest effectiveness in the identification of all eight PD classes, classified simultaneously, where indicated. Within the research carried out, an attempt to draw general conclusions as to the selection of the most effective hierarchical clustering method studied and the similarity function to be used for classification of the selected basic PD forms.
Go to article

Bibliography

1. Akbari A., Setayeshmehr A., Borsi H., Gockenbach E. (2010), Intelligent agent-based system using dissolved gas analysis to detect incipient faults in power transformers, IEEE Electrical Insulation Magazine, 26(6): 27–40, doi: 10.1109/MEI.2010.5599977.
2. Boczar T. (2001), Identification of a specific type of PD form acoustics emission frequency spectra, IEEE Transaction on Dielectric and Electrical Insulation, 8(4): 598–606, doi: 10.1109/94.946712.
3. Boczar T., Borucki S., Cichon A., Zmarzły D. (2009), Application Possibilities of Artificial Neural Networks for Recognizing Partial Discharges Measured by the Acoustic Emission Method, IEEE Transaction on Dielectric and Electrical Insulation, 16(1): 214–223, doi: 10.1109/TDEI.2009.4784570.
4. Boczar T., Cichon A., Borucki S. (2014), Diagnostic expert system of transformer insulation systems using the acoustic emission method, IEEE Transaction on Dielectric and Electrical Insulation, 21(2): 854–865, doi: 10.1109/TDEI.2013.004126.
5. Borucki S., Boczar T., Cichon A., Lorenc M. (2007), The evaluation of neural networks application for recognizing single-source PD forms generated in paper-oil insulation systems based on the AE signal analysis, European Physical Journal Special Topics, 154: 23–29, doi: 10.1140/epjst/e2008-00512-7.
6. Borucki S., Łuczak J. (2017), Assessment of the impact of an acoustic signal power spectral density frequency selection on partial discharges basic forms classification efficiency with the use of data clustering method [in Polish: Ocena wpływu doboru czestotliwosci widmowej gestosci mocy sygnału akustycznego na efektywnosc klasyfikacji podstawowych form wyładowan niezupełnych z uzyciem metody klasteryzacji], Energetyka, 7: 448–452.
7. Borucki S., Łuczak J., Zmarzły D. (2018), Using Clustering Methods for the Identification of Acoustic Emission Signals Generated by the Selected Form of Partial Discharge in Oil-Paper Insulation, Archives of Acoustics, 43(2): 207–215, doi: 10.24425/122368.
8. Castro Heredia L.C., Rodrigo Mor A. (2019), Density-based clustering methods for unsupervised separation of partial discharge sources, International Journal of Electrical Power & Energy Systems, 107: 224–230, doi: 10.1016/j.ijepes.2018.11.015.
9. Chia-Hung L., Chien-Hsien W., Ping-Zan H. (2009), Grey clustering analysis for incipient fault diagnosis in oil-immersed transformers, Expert Systems with Applications, 36(2, part 1): 1371–1379, doi: 10.1016/j.eswa.2007.11.019.
10. Cichon A. (2013), Assessment of technical condition of on-load tap-changers by the method of acoustic emission, [in Polish: Ocena stanu technicznego podobciazeniowych przełaczników zaczepów metoda emisji akustycznej], Studia i Monografie, No. 352, Ofic. Wyd. Politechniki Opolskiej.
11. Fuhr J. (2005), Procedure for identification and localization of dangerous partial discharge sources in power transformers, IEEE Transaction on Dielectric and Electrical Insulation, 12(5): 1005–1014, doi: 10.1109/TDEI.2005.1522193.
12. Han J., Kamber M., Pei J. (2012), Data Mining. Concepts and Techniques, 3rd ed., Morgan Kaufmann Publishers, Waltham.
13. Kapinos J., Glinka T., Drak B. (2014), Typical causes of operational failures in power transformers working in National Grid [in Polish: Typowe przyczyny uszkodzen eksploatacyjnych transformatorów energetycznych], Przeglad Elektrotechniczny, 90(1): 186–189, doi: 10.12915/pe.2014.01.45.
14. Kazmierski M., Olech W. (2013), Technical Diagnostics and Monitoring of Transformers [in Polish: Diagnostyka techniczna i monitoring transformatorów], Printing house of ZPBE Energopomiar-Elektryka Sp. z o.o., Gliwice.
15. Krzysko M., Wołynski W., Górecki T. Skorzybut M. (2008), Learning Systems – Pattern Recognition, Cluster Analysis and Dimensional Reduction [in Polish: Systemy uczace sie – rozpoznawanie wzorców, analiza skupien i redukcja wymiarowosci], Wydawnictwa Naukowo-Techniczne, Warszawa.
16. Kurtasz P. (2011), Application of a multi-comparative algorithm to classify acoustic emission signals generated by partial discharges [in Polish: Zastosowanie algorytmu multikomparacyjnego do klasyfikacji sygnałów emisji akustycznej generowanych przez wyładowania niezupełne], Ph.D. Dissertation, Opole University of Technology.
17. Lalitha E.M., Satish L. (2002),Wavelet analysis for classification of multi-source PD patterns, IEEE Transaction on Dielectric and Electrical Insulation, 7(1): 40– 47, doi: 10.1109/94.839339.
18. Ming-Shou S., Chung-Chu C., Chien-Yi C., Jiann-Fuh C. (2014), Classification of partial discharge events in GILBS using probabilistic neural networks and the fuzzy c-means clustering approach, International Journal of Electrical Power & Energy Systems, 61: 173–179, doi: 10.1016/j.ijepes.2014.03.054.
19. Mohan Rao U., Sood Y.R., Jarial R.K. (2015), Subtractive Clustering Fuzzy Expert System for Engineering Applications, Procedia Computer Science, 48: 77–83, doi: 10.1016/j.procs.2015.04.153.
20. Morzy T. (2013), Data mining. Methods and Algorithms [in Polish: Eksploracja danych. Metody i algorytmy], Wydawnictwo Naukowe PWN, Warszawa.
21. Olszewska A., Witos F. (2012), Location of partial discharge sources and analysis of signals in chosen power oil transformers by means of acoustic emission method, Acta Physica Polonica A, 122(5): 921–926.
22. Radionov A.A., Evdokimov S.A., Sarlybaev A.A., Karandaeva O.I. (2015), Application of Subtractive Clustering for Power Transformer Fault Diagnostics, Procedia Engineering, 129: 22–28, doi: 10.1016/j.proeng.2015.12.003.
23. Rodrigo Mor A., Castro Heredia L.C., Muñoz F.A. (2017), Effect of acquisition parameters on equivalent time and equivalent bandwidth algorithms for partial discharge clustering, International Journal of Electrical Power & Energy Systems, 88: 141–149, doi: 10.1016/j.ijepes.2016.12.017.
24. Rubio-Serrano J., Rojas-Moreno M., Posada J., Martienez-Tarifa J., Robles G., Garcia-Souto J. (2012), Electro-acoustic detection, identification and location of PD sources in oil-paper insulation systems, IEEE Transaction on Dielectric and Electrical Insulation, 19(5): 1569–1578, doi: 10.1109/TDEI. 2012.6311502.
25. Soltani A.A., Haghjoo F., Shahrtash S.M. (2012), Compensation of the effects of electrical sensors in measuring PD signals, IET Science, Measurement &Technology, 6(6): 494–501, doi: 10.1049/iet-smt.2012.0001.
Go to article

Authors and Affiliations

Sebastian Borucki
1
Jacek Łuczak
1
Marcin Lorenc
1

  1. Opole University of Technology, Opole, Poland
Download PDF Download RIS Download Bibtex

Abstract

A SAW gas sensor based on Zinc Oxide (ZnO) piezoelectric substrate is simulated and evaluated for the detection of the dichloromethane (DCM) volatile organic compound (VOC). The study is performed based on the finite element method (FEM) using COMSOL Multiphysics software. The obtained device response using the ZnO substrate is compared to the one using the typical lithium niobate (LiNbO3) piezoelectric substrate. A thin film of polyisobutylene (PIB) membrane is selected to act as the sensing layer. The obtained results reveal a linear behaviour of the resonance frequency downshift (i.e., the sensor sensitivity) versus the investigated gas concentrations varying from 10 ppm to 100 ppm of DCM gas. Additionally, the sensor response is investigated by applying several thicknesses of PIB ranging from 0.3 μm to 1.0 μm. The observed sensor response shows less dependence on the PIB thickness using the ZnO substrate than the LiNbO3 one.
Go to article

Bibliography

1. Aslam M.Z., Jeoti V., Karuppanan S., Malik A., Iqbal A. (2018), FEM analysis of Sezawa Mode SAW sensor for VOC based on CMOS compatible AlN/ SiO2/Si, Multilayer Structure. Sensors, 18(6): 1687, doi: 10.3390/s18061687.
2. Beauchet R., Magnoux P., Mijoin J. (2007), Catalytic oxidation of volatile organic compounds (VOCs) mixture (isopropanol/O-xylene) on zeolite catalysts, Catalysis Today, 124(3–4): 118–123, doi: 10.1016/ j.cattod.2007.03.030.
3. Caliendo C., Laidoudi F. (2020), Experimental and theoretical study of multifrequency surface acoustic wave devices in a single Si/SiO2/ZnO piezoelectric structure, Sensors, 20(5): 1380, doi: 10.3390/s20051380.
4. Carlotti G., Socino G., Petri A., Verona E. (1987), Elastic constants of sputtered ZnO films, Proceedings of IEEE 1987 Ultrasonics Symposium, pp. 295–300, doi: 10.1109/ULTSYM.1987.198972.
5. Deng Q., Yang X., Zhang J.S. (2012), Key factor analysis of VOC sorption and its impact on indoor concentrations: the role of ventilation, Building and Environment, 47: 182–187, doi: 10.1016/j.buildenv.2011.07.026.
6. El-Shennawy K., Orabi M.S, Taha T.E. (2000), Simulation of high sensitivity and stability surface acoustic wave NO2 gas sensor based on amplitude variations as measurand, 22nd International Conference on Microelectronics, Vol. 2, pp. 611–614.
7. Gowini M., Moussa W. (2010), A Finite Element Model of a MEMS-based Surface Acoustic Wave hydrogen sensor, Sensors, 10(2): 1232–1250, doi: 10.3390/s100201232.
8. Gualtieri J.G., Kosinski J.A., Ballato A. (1994), Piezoelectric materials for acoustic wave applications, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 41(1): 53–59, doi: 10.1109/58.265820.
9. Guo Y.J. et al. (2015), Ultraviolet sensing based on nanostructured ZnO/Si surface acoustic wave devices, Smart Materials and Structures, 24(12): 125015, doi: 10.1088/0964-1726/24/12/125015.
10. Hands P.J.W., Laughlin P.J., Bloor D. (2012), Metal–polymer composite sensors for volatile organic compounds. Part 1. Flow-through chemi-resistors, Sensors and Actuators B: Chemical, 162(1): 400–408, doi: 10.1016/j.snb.2011.12.016.
11. Hernandez G., Wallis S.L., Graves I., Narain S., Birchmore R., Berry T-A. (2020), The effect of ventilation on volatile organic compounds produced by new furnishings in residential buildings, Atmospheric Environment: X, 6: 10069, doi: 10.1016/j.aeaoa.2020.100069.
12. Hofer M. et al. (2006), Finite-element simulation of wave propagation in periodic piezoelectric SAW structures, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 53(6): 1192–1201, doi: 10.1109/tuffc.2006.1642518
13. Horrillo M.C. et al. (2006), Optimization of SAW sensors with a structure ZnO-SiO2-Si to detect volatile organic compounds, Sensors and Actuators B: Chemical, 118(1–2): 356–361, doi: 10.1016/j.snb.2006.04.050.
14. Huang H., Chiang H., Wu C., Lin Y., Shen Y. (2019), Analysis on characteristics of ZnO surface acoustic wave with and without micro-structures, Micromachines (Basel), 10(7): 434, doi: 10.3390/mi10070434.
15. Jang S.W. et al. (2006), Refractive index change by photoinduction of a UV-sensitive SMF-to-PWG coupler. IEEE Photonics Technology Letters, 18(1): 220– 222, doi: 10.1109/LPT.2005.861624.
16. Jiang Q., Yang X.M, Zhou H.G, Yang J.S. (2005), Analysis of surface acoustic wave pressure sensors, Sensors and Actuators A: Physical, 118(1): 1–5, doi: 10.1016/j.sna.2004.07.007.
17. Joo B.-S., Lee J.-H., Lee E.-W., Song K.-D., Lee D.-D. (2005), Polymer film SAW sensors for chemical agent detection, [in:] Proceedings of the 1st Conference on Sensing Technology, Palmerston North, New Zealand, pp. 307–310.
18. Karpina V.A. et al. (2004), Zinc oxide – analogue of GaN with new perspective possibilities, Crystal Research and Technology, 39(11): 980–992, doi: 10.1002/crat.200310283.
19. Koistinen K. et al. (2008), The INDEX project: executive summary of a European Union project on indoor air pollutants, Allergy, 63(7): 810–819, doi: 10.1111/j.1398-9995.2008.01740.x.
20. Kumar S., Kim G.H., Sreenivas K., Tandon R.P. (2009), ZnO based surface acoustic wave ultraviolet photo sensor, Journal of Electroceramics, 22(1): 198– 202, doi: 10.1007/s10832-007-9409-7.
21. Lin H., Jang M., Suslick K.S. (2011), Preoxidation for colorimetric sensor array detection of VOCs, Journal of the American Chemical Society, 133(42): 16786–16789, doi: 10.1021/ja207718t.
22. Le Brizoual L., Elmazria O., Sarry F., El Hakiki M., Talbi A., Alno P. (2006), High frequency SAW devices based on third harmonic generation, Ultrasonics, 45(1–4): 100–103, doi: 10.1016/j.ultras.2006.07.013.
23. Leonhard M., Ismail M. (2004), Wireless measurement of temperature using surface acoustic waves sensors, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 51(11): 1457–1463, doi: 10.1109/TUFFC.2004.1367486.
24. Lerch R. (1990), Simulation of piezoelectric devices by two- and three-dimensional finite elements, IEEE transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 37(3): 233–247, doi: 10.1109/58.55314.
25. Liu X., Cheng S., Liu H., Hu S., Zhang D., Ning H. (2012), A survey on gas sensing technology, Sensors (Basel), 12(7): 9635–9665, doi: 10.3390/s120709635.
26. Ma W., Yang H., Wang W., Gao P., Yao J. (2011), Ethanol vapor sensing properties of triangular silver nanostructures based on localized surface plasmon resonance, Sensors, 11(9): 8643–8653, doi: 10.3390/s110908643.
27. Mombello D. et al. (2009), Porous anodic alumina for the adsorption of volatile organic compounds, Sensrs and Actuators B: Chemical, 137(1): 76–82, doi: 10.1016/j.snb.2008.11.046.
28. Ondo-Ndong R., Ferblantier G., Al Kalfioui M., Boyer A., Foucaran A. (2002), Properties of RF magnetron sputtered zinc oxide thin films, Journal of Crystal Growth, 255(1–2): 130–135, doi: 10.1016/S0022-0248(03)01243-0.
29. Ondo J., Blampain E., Mbourou G., Mc Murtry S., Hage-Ali S., Elmazria O. (2020), FEM modeling of the temperature influence on the performance of SAW sensors operating at gigahertz frequency range and at high temperature up to 500XC, Sensors (Basel), 20(15): 4166, doi: 10.3390/s20154166.
30. Özgür Ü. et al. (2005), A comprehensive review of ZnO materials and devices, Journal of Applied Physics, 98(4): 041301, doi: 10.1063/1.1992666.
31. Raj V.B., Singh H., Nimal A.T., Sharma M.U., Tomar M., Gupta V. (2017), Distinct detection of liquor ammonia by ZnO/SAW sensor: Study of complete sensing mechanism, Sensors and Actuators B: Chemical, 238: 83–90, doi: 10.1016/j.snb.2016.07.040.
32. Roesch C., Kohajda T., Roeder S., von Bergen M., Schlink U. (2014), Relationship between sources and patterns of VOCs in indoor air, Atmospheric Pollution Research, 5(1): 129–137, doi: 10.5094/APR.2014.016.
33. Sua F.-C., Mukherjeeb B., Battermana S. (2013), Determinants of personal, indoor and outdoor VOC concentrations: An analysis of the RIOPA data, Environmental Research, 126: 192–203, doi: 10.1016/j.envres.2013.08.005.
34. Tang I.-T., Chen H.-J., Hwang W.C., Wang Y.C., Houng M.-P., Wang Y.-H. (2004), Applications of piezoelectric ZnO film deposited on diamond-like carbon coated onto Si substrate under fabricated diamond SAW filter, Journal of Crystal Growth, 262(1–4): 461– 466, doi: 10.1016/j.jcrysgro.2003.10.081.
35. Tonami S., Nishikata A., Shimizu Y. (1995), Characteristic of leaky surface acoustic wave propagating on LiNbO3 and LiTaO3 substrates, Japanese Journal of Applied Physics, 34(Part 1, No. 5B): 2664–2667, doi: 10.1143/jjap.34.2664.
36. Wang Z.L. (2004), Zinc oxide nanostructures: growth, properties and applications, Journal of Physics: Condensed Matter, 16(25): R829–R858, doi: 10.1088/0953- 8984/16/25/R01.
37. Wongchoosuk C., Wisitsoraat A., Tuantranont A., Kerdcharoen T. (2010), Portable electronic nose based on carbon nanotube-SnO2 gas sensors and its application for detection of methanol contamination in whiskeys, Sensors and Actuators B: Chemical, 147(2): 392–399, doi: 10.1016/j.snb.2010.03.072.
38. Yoon J.K., Seo G.W., Cho K.M., Kim E.S., Kim S.H., Kang S.W. (2003), Controllable in-line UV sensor using a side-polished fiber coupler with photofunctional polymer, IEEE Photonics Technology Letters, 15(6): 837–839, doi: 10.1109/LPT.2003.811341.
Go to article

Authors and Affiliations

Mohamed Moustafa
1
Ghaylen Laouini
2
Tariq Alzoubi
2

  1. Department of Physics, School of Sciences and Engineering, The American University in Cairo, Egypt
  2. College of Engineering and Technology, American University of the Middle East, Kuwait
Download PDF Download RIS Download Bibtex

Abstract

The ultrasonic ring array, designed for examining the female breast with the use of ultrasonic transmission tomography (UTT), has been adapted for reflection method trials. By altering the activation time of ultrasonic elementary transducers, the parameters of the focus were changed with the aim at improving the quality of the obtained ultrasound image. For this purpose, a phantom consisting of rods having varying thicknesses was analyzed when moving the position of the focus with the use of dynamic focusing along the symmetry axis of the ring array ranging from 30 to 130 mm from central transducers. In previous trials, which applied an algorithm using the sum of all the acoustic fields, a series of simulations was performed in conditions identical to the phantom trial. This paper documents attempts at improving the parameters of the acoustic field distribution during unconventional focusing. The research here presented is a continuation of examinations focusing on the acoustic field distribution inside the ultrasonic ring array with the aim at finding the best possible cross-section of the female breast using the reflection method.
Go to article

Bibliography

1. Birk M., Kretzek E., Figuli P., Weber M., Becker J., Ruiter N.V. (2016), High-speed medical imaging in 3D ultrasound computer tomography, IEEE Transactions on Parallel and Distributed Systems, 27(2): 455–467, doi: 10.1109/TPDS.2015.2405508.
2. Costaridou L. (2005), Medical Image Analysis Method, CRC Press Taylor & Fracis, New York.
3. Duric N. et al. (2007), Detection of breast cancer with ultrasound tomography: First results with the Computed Ultrasound Risk Evaluation (CURE) prototype, Medical Physics, 34(2) 773–785, doi: 10.1118/1.2432161.
4. Duric N. et al. (2013), Breast imaging with the Soft- Vue imaging system: first results, [in:] Medical Imaging 2013: Ultrasonic Imaging, Tomography, and Therapy. Proceedings of SPIE.SPIE, Bosch J.G., Doyley M.M. [Eds], Vol. 8675, pp. 164–171, doi: 10.1117/12.2002513.
5. Entrekin R., Jackson P., Jago J.R., Porter B.A. (1999), Real time spatial compound imaging in breast ultrasound: Technology and early clinical experience, Medicamundi, 43(3): 35–43.
6. Gudra T., Opielinski K. (2006), The ultrasonic probe for investigating of internal object structure by ultrasound transmission tomography, Ultrasonics, 44(Suppl. 1): e679–e683, doi: 10.1016/j.ultras.2006.05.126.
7. Gudra T., Opielinski K. (2016), The multi-element probes for ultrasound transmission tomography, Journal de Physique IV, 137: 79–86, doi: 10.1051/jp4: 2006137015.
8. Gudra T., Opielinski K.J. (2009), A method of visualizing the internal structure of the center and a device for implementing this method [in Polish: Sposób wizualizacji struktury wewnetrznej osrodka i urzadzenie do realizacji tego sposobu], Patent No 210202, Poland.
9. Jirik R. et al. (2012), Sound-speed image reconstruction insparse-aperture 3-D ultrasound transmission tomography, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 59(2): 254–264, doi: 10.1109/TUFFC.2012.2185.
10. Kak A.C., Slaney M. (2001), Principles Computerized Tomographic Imaging, IEEE Press, New York.
11. Marmarelis V., Jeong J., Shin D., Do S. (2007), High-resolution 3-D imaging and tissue differentiation with transmission tomography, [in:] Acoustical Imaging, André M.P. et al. [Eds], Vol. 28, 195–206, Springer, Dordrecht, doi: 10.1007/1-4020-5721-0_21.
12. Narodowy Instytut Onkologii im. Marii Skłodowskiej- Curie (n.d.), National Cancer Registry [in Polish: Krajowy Rejestr Nowotworów], available at https://www.pib-nio.pl/krajowy-rejestr-nowotworow/.
13. Opielinski K.J. (2011), Application of Transmission of Ultrasonic Waves for Characterization and Imaging of Biological Media Structures [in Polish], Printing House of Wroclaw University of Science and Technology, Wroclaw.
14. Opielinski K.J. et al. (2015), Imaging results of multi-modalultrasound computerized tomography system designed for breast diagnosis, Computerized Medical Imaging and Graphics, 46(2): 83–94, doi: 10.1016/j.compmedimag.2017.06.009.
15. Opielinski K.J. et al. (2016), Breast ultrasound tomography: preliminary in vivo results, [in:] Information Technologies in Medicine, Pietka E., Badura P., Kawa J., Wieclawek W. [Eds], Vol. 1, pp. 193–2015, Springer International Publishing, doi: 10.1007/978-3- 319-39796-2_16.
16. Opielinski K.J. et al. (2018), Multimodal ultrasound computer-assisted tomography: An approach to the recognition of breast lesion, Computerized Medical Imaging and Graphics, 65: 102–114, doi: 10.1016/j.compmedimag.2017.06.009.
17. Opielinski K.J., Pruchnicki P., Gudra T., Majewski J. (2014), Full angle ultrasound spatial compound imaging, [In:] Proceedings of 7th Forum Acusticum 2014 Joined with 61st Open Seminar on Acoustics and Polish Acoustical Society – Acoustical Society of Japan Special Session Stream [CD-ROM], Krakow: European Acoustics Association.
18. Pratap R. (2013), MATLAB for scientists and engineers [in Polish: MATLAB dla naukowców i inzynierów], Warszawa: WN PWN.
19. Staszewski W., Gudra T. (2019), The effect of dynamic focusing of the beam on the acoustic field distribution inside the ultrasonic ring array, Vibrations in Physical Systems, 30(1): 2019106, 8 pages.
20. Staszewski W., Gudra T., Opielinski K.J. (2018), The acoustic field distribution inside the ultrasonic ring array, Archives of Acoustic, 43(3): 455–463, doi: 10.24425/123917.
21. Staszewski W., Gudra T., Opielinski K.J. (2019), The Effect of dynamic beam deflection and Focus shift on the acoustics field distribution inside the ultrasonic ring array, Archives of Acoustics, 44(4): 625–636, doi: 10.24425/aoa.2019.129721.
22. Wiskin J. et al. (2013), Three-dimensional nonlinear inverse scattering: quantitative transmission algorithms, refraction corrected reflection, scanner design and clinical results, Proceedings of Meetings on Acoustics, 19(1): 075001, doi: 10.1121/1.4800267.
Go to article

Authors and Affiliations

Wiktor Staszewski
1 2
Tadeusz Gudra
1
Krzysztof J. Opieliński
1

  1. Department of Acoustics and Multimedia, Faculty of Electronics, Wrocław University of Science and Technology, Wrocław, Poland
  2. T. Marciniak Lower Silesian Specjalist Hospital – Emergency Medicine Centre, Wrocław, Poland
Download PDF Download RIS Download Bibtex

Abstract

The design of neonatal intensive care units (NICU) influences both patient safety and clinical outcomes as well as the acoustic conditions. In NICU exposure to sound pressure levels above the recommended can affect both neonates and healthcare staff.
This study aimed to evaluate the sound pressure levels and to assess noise perception of professionals in a NICU before and after structural modifications and layout redesign.
The measurements were performed with a sound level meter. A questionnaire was given to staff before and after the intervention. The opinion of healthcare staff regarding noise in NICU was better after the intervention, when compared with the responses previously given.
The results showed that noise levels were excessive in the NICU (before and after), exceeding the international recommendations, with the levels ranging between 46.6 dBA to 57.8 dBA before and 52.0 dBA to 54.0 dBA after intervention. Overall, there is a need for more research in order to verify the effectiveness of some actions and strategies to reduce the impact of noise in NICU.
Go to article

Bibliography

1. Ahamed M.F., Campbell D., Horan S., Rosen O. (2017), Noise reduction in the neonatal intensive care unit: a quality improvement initiative, American Journal of Medical Quality, 33(2): 177–184, doi: 10.1177/1062860617711563.
2. American Academy of Pediatrics: Committee on Environmental Health (1997), Noise: a hazard for the fetus and newborn, Pediatrics, 100(4): 724–727, doi: 10.1542/peds.100.4.724.
3. Basner M. et al. (2014), Auditory and non-auditory effects of noise on health, The Lancet, 383(9925): 1325– 1332, doi: 10.1016/S0140-6736(13)61613-X.
4. Berglund B., Lindvall T., Schwela H.D. (1999), Guidelines for community noise, [in:] Guidelines for Community Noise, retrieved on July 22, 2017, from http://www.who.int/docstore/peh/noise/guidelines2.html.
5. Carvalhais C., da Silva M.V., Xavier A., Santos J. (2019), Good practices to reduce noise levels in the neonatal intensive care unit, [in:] Occupational and Environmental Safety and Health. Studies in Systems, Decision and Control, P.M. Arezes et al. [Eds], Vol. 202, pp. 297–302, Springer, Cham, doi: 10.1007/978-3-030-14730-3_32.
6. Carvalhais C., Santos J., Vieira da Silva M., Xavier A. (2015), Is there sufficient training of healthcare staff on noise reduction in neonatal intensive care units? A pilot study from NeoNoise Project, Journal of Toxicology and Environmental Health, Part A, 78(13– 14): 897–903, doi: 10.1080/15287394.2015.1051204.
7. Carvalhais C., Silva M., Xavier A., Santos J. (2017), Newborns safety at neonatal intensive care units: are they exposed to excessive noise during routine health care procedures?, Global Environment Health and Safety, 1(1): 1–3.
8. Domanico R., Davis D.K., Coleman F., Davis B.O. (2011), Documenting the NICU design dilemma: comparative patient progress in open-ward and single family room units, Journal of Perinatology: Official Journal of the California Perinatal Association, 31(4): 281– 288, doi: 10.1038/jp.2010.120.
9. Gray L., Philbin M.K. (2000), Measuring sound in hospital nurseries, Journal of Perinatology, 20(8 Pt 2): S100–S104, doi: 10.1038/sj.jp.7200440.
10. Joshi R., Straaten H., van Mortel H., van de Long X., Andriessen P., van Pul C. (2018), Does the architectural layout of a NICU affect alarm pressure? A comparative clinical audit of a single-family room and an open bay area NICU using a retrospective study design, BMJ Open, 8(6): e022813, doi: 10.1136/bmjopen-2018-022813.
11. Kellam B., Bhatia J. (2008), Sound spectral analysis in the intensive care nursery: measuring highfrequency sound, Journal of Pediatric Nursing, 23(4): 317–323, doi: 10.1016/j.pedn.2007.09.009.
12. Kent W.T., Tan A.W., Clarke M.C., Bardell T. (2002), Excessive noise levels in the neonatal ICU: potential effects on auditory system development, The Journal of Otolaryngology, 31(6): 355–360, doi: 10.2310/7070.2002.34358.
13. Kol E., Aydin P., Dursun O. (2015), The effectiveness of environmental strategies on noise reduction in a pediatric intensive care unit: Creation of singlepatient bedrooms and reducing noise sources, Journal for Specialists in Pediatric Nursing, 20(3); 210–217, doi: 10.1111/jspn.12116.
14. Krueger C., Schue S., Parker L. (2007), Neonatal intensive care unit sound levels before and after structural reconstruction, MCN The American Journal of Maternal/Child Nursing, 32(6), 358–362, doi: 10.1097/01.NMC.0000298131.55032.76.
15. Lahav A. (2015), Questionable sound exposure outside of the womb: Frequency analysis of environmental noise in the neonatal intensive care unit, Acta Paediatrica, International Journal of Paediatrics, 104(1): e14–e19, doi: 10.1111/apa.12816.
16. Lester B.M. et al. (2014), Single-family room care and neurobehavioral and medical outcomes in preterm infants, Pediatrics, 134(4): 754–760, doi: 10.1542/peds.2013-4252.
17. Livera M.D. et al. (2008), Spectral analysis of noise in the neonatal intensive care unit, The Indian Journal of Pediatrics, 75(3): 217–222, doi: 10.1007/s12098-008-0048-z.
18. Meredith J.L., Jnah A., Newberry D. (2017), The NICU Environment: Infusing Single-Family Room Benefits into the Open-Bay Setting, Neonatal Network, 36(2): 69–76, doi: 10.1891/0730-0832.36.2.69.
19. Parra J., de Suremain A., Berne Audeoud F., Ego A., Debillon T. (2017), Sound levels in a neonatal intensive care unit significantly exceeded recommendations, especially inside incubators, Acta Paediatrica, 106(12): 1909–1914, doi: 10.1111/apa.13906.
20. Philbin M.K. (2004), Planning the acoustic environment of neonatal intensive care units, Clinical Perinatology, 31(2): 331–352, doi: 10.1016/j.clp.2004.04.014.
21. Philbin M.K., Gray L. (2002), Changing levels of quiet in an intensive care nursery, Journal of Perinatology , 22(6): 455–460, doi: 10.1038/sj.jp.7210756.
22. Ramm K., Mannix T., Parry Y., Gaffney M.P.C. (2017), A comparison of sound levels in open plan versus pods in a neonatal intensive care unit, Health Environments Research and Design Journal, 10(3): 30–39, doi: 10.1177/1937586716668636.
23. Robertson A., Kohn J., Vos P., Cooper-Peel C. (1998), Establishing a noise measurement protocol for neonatal intensive care units, Journal of Perinatology, 18(2): 126–130, http://www.ncbi.nlm.nih.gov/pubmed/9605303.
24. Romeu J., Cotrina L., Perapoch J., Linés M. (2016), Assessment of environmental noise and its effect on neonates in a Neonatal Intensive Care Unit, Applied Acoustics, 111: 161–169, doi: 10.1016/j.apacoust.2016.04.014.
25. Santos J., Carvalhais C., Xavier A., Silva M.V. (2018), Assessment and characterization of sound pressure levels in Portuguese neonatal intensive care units, Archives of Environmental and Occupational Health, 73(2): 121–127, doi: 10.1080/19338244.2017.1304883.
26. Smith S.W., Ortmann A.J., Clark W.W. (2018), Noise in the neonatal intensive care unit: a new approach to examining acoustic events, Noise & Health, 20(95): 121–130, doi: 10.4103/nah.NAH_53_17.
27. Szymczak S.E., Shellhaas R.A. (2014), Impact of NICU design on environmental noise, Journal of Neonatal Nursing, 20(2): 77–81, doi: 10.1016/j.jnn.2013.07.003.
28. United States Environmental Protection Agency (1974), Information on Levels of Environmental Noise Requisite to Protect Public Health and Welfare with an Adequate Margin of Safety (EPA/ONAC 550/9-74- 004).
29. Wachman E.M., Lahav A. (2011), The effects of noise on preterm infants in the NICU, Archives of Disease in Childhood-Fetal and Neonatal Edition, 96(4): F305–F309, doi: 10.1136/adc.2009.182014.
30. Wiese C.H., Wang L.M., Ronsse L.M. (2009), Comparison of noise levels between four hospital wings with different material treatments, The Journal of the Acoustical Society of America, 126(4): 2217, doi: 10.1121/1.3248811.
Go to article

Authors and Affiliations

Carlos Carvalhais
1 2
Célia Rodrigues
3
Ana Xavier
1
Manuela V. Silva
1
Joana Santos
1 4 5

  1. Scientific Area of Environmental Health, Health and Environment Research Center (CISA), School of Health of Polytechnic Institute of Porto (ESS P.Porto), Porto, Portugal
  2. Epidemiology Research Unit (EPIUnit), Institute of Public Health, University of Porto, Porto, Portugal
  3. PROA/LABIOMEP, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal
  4. Institute of Science and Innovation in Mechanical and Industrial Engineering, Associated Laboratory for Energy, Transports and Aeronautics (INEGI/LAETA), Faculdade de Engenharia, Universidade do Porto, Porto, Portugal
  5. Center for Rehabilitation Research (CIR), School of Health of Polytechnic Institute of Porto (ESS P.Porto), Porto, Portugal
Download PDF Download RIS Download Bibtex

Abstract

Mosques are Islamic places of worship where speech and music rituals are performed. Since two different languages are spoken there, mosques are described as bilingual spaces. Among studies on the complex acoustic structure of mosques there are only few studies on speech intelligibility and none on the bilingual characteristics of the mosque. Therefore, a comprehensive study has been carried out to evaluate the acoustic comfort of the contemporary Turkish mosques (CTM) over speech intelligibility of Turkish and Arabic languages. In the study the CTM model providing optimum acoustic conditions recommended in the literature is examined on speech intelligibility by applying acoustic simulation and auralisation techniques, as well as word recognition tests. As a result, the acoustic condition in the model is found insufficient in terms of speech intelligibility of both languages. Also, with the decrease of Signal-to-Noise Ratio (SNR), the Turkish intelligibility ratio is observed to decrease at least two times faster than the Arabic ones.
This study is viewed as an outline for researchers to further study mosque acoustics in terms of speech intelligibility, and thus support the standardisation process of the acoustic comfort criteria for the mosques.
Go to article

Bibliography

1. Abdou A.A. (2003), Measurement of acoustical characteristics of mosques in Saudi Arabia, The Journal of the Acoustical Society of America, 113(3): 1505–1517, doi: 10.1121/1.1531982.
2. Ahmad Y., Din N.C., Othman R. (2013), Mihrab design and its basic acoustical characteristics of traditional vernacular mosques in Malaysia, Journal of Building Performance, 4(1): 44–51, http://spaj.ukm.my/ jsb/index.php/jbp/article/view/79.
3. Akın A. (2016), An essay about the function of mosques throughout the history [in Turkish: Tarihi Süreç Içinde Cami ve Fonksiyonlari Üzerine Bir Deneme], Hitit Üniversitesi Ilahiyat Fakültesi Dergisi, 15(29): 179–211.
4. Alic E. (2019), A study on speech intelligibility of mosque over Turkish and Arabic language [in Turkish: Camilerde Konusma Anlasilabilirliginin Türkçe ve Arapça Dilleri Üzerinden Incelenmesi], Master Thesis, Eskisehir Technical University.
5. Alic E., Ozcevik Bilen A. (2019), Determination of the characteristics of contemporary Turkish mosque and its acoustical properties, Proceedings of the 23rd International Congress on Acoustics, pp. 3989–3990, Aachen, Germany.
6. Alusi H.A., Hinchcliffe R., Ingham B., Knight J.J., North C. (1974), Arabic speech audiometry, International Journal of Audiology, 13(3): 212–230.
7. ANSI/ASA S3.2. (2009), Method for measuring the intelligibility of speech over communication systems, American National Standards Institute.
8. Audio Check (n.d.), Online audiogram hearing test, retrieved April 4, 2019, from https://www.audio check.net/testtones_hearingtestaudiogram.php.
9. Aydın T. (2010), The letters in Arabic and Turkish – contrastive analysi [in Turkish: Arapça ve Türkçe’de Sesler – Karsıtsal Çözümleme], EKEV Akademi Dergisi, pp. 321–334.
10. Baktır M. (n.d.), Khutbah [in Turkish: Hutbe], detrieved March 11, 2019, from Turkiye Diyanet Foundation, Encyclopaedia of Islam, https://islamansiklopedisi.org.tr/hutbe.
11. Bilingualism (n.d.), [in:] Cambridge Dictionary, retrieved November 15, 2019, from https://dictionary.cambridge.org/dictionary/english/bilingualism.
12. Bobran H.W. (1973), ABC of sound and heat protection technolog [in German: ABC der Schallund Wärmeschutztechnik: Eine Zusammenstellung der wichtigsten Begriffe des Schallschutzes, der Raumakustik und der Bauphysik. Mit Stoffwerten Konstruktionsdetails, Markennamen-Erläuterung gen sowie umfassendem Firmenverzeichnis], ABC-Redaktion.
13. Bradley J.S. (1986), Predictors of speech ıntelligibility in rooms, The Journal of the Acoustical Society of America, 80(3): 837–845, doi: 10.1121/1.393907.
14. BS 8233 (1999), Sound insulation and noise reduction for buildings – Code of Practice, London, UK.: British Standards Institution.
15. BS EN 60268-16 (2011), Sound system equipment – Part 16: Objective rating of speech intelligibility by speech transmission index, London, UK: British Standard Institute.
16. BS EN ISO 9921 (2003), Ergonomics – Assessment of Speech Communication, British Standards Institution, London, UK.
17. Carvalho A., Freitas C. (2011), Acoustical characterization of the central mosque of Lisbon, Forum Acusticum 2011.
18. ÇGDYY (2010), Environmental Noise Assessment and Management Regulation [in Turkish: Çevresel Gürültünün Degerlendirilmesi ve Yonetimi Yonetmeligi (2002/49/EC)], TC Çevre ve Orman Bakanlıgı, Resmi Gazete.
19. Cirit H. (n.d.), Sermon, [in Turkish: Vaaz], retrieved October 1, 2018, from Turkiye Diyanet Foundation, Encyclopaedia of Islam, https://islamansiklope disi.org.tr/vaaz#.
20. Elkhateeb A., Adas A., Atilla M., Balia Y. (2016), The acoustics of Masjids, looking for future design criteria, [in:] The 23rd International Congress on Sound and Vibration, pp. 10–14, Greece.
21. Erdem A. (1992), A Study on the acoustic characteristics of the Muradiye mosque [in Turkish: Muradiye camii’nin akustik karakteristikleri üzerine bir arastırma], Edirne: Doctoral Thesis, Trakya University.
22. Ez-Züvey A., Hanay N. (2013), The founder of the sound science El-Halil B. AHMED [in Turkish: Ses Bilimin Kurucusu El-Halil B. AHMED], Recep Tayyip Erdogan Üniversitesi Ilahiyat Fakültesi Dergisi, 4: 195– 227.
23. Fischer S.R. (2015), History of language [in Turkish: Dilin tarihi], trans. M. Güvenç, Kültür yayınevi. 24. Güler E., Hengirmen M. (2005), Sound science and diction [in Turkish: Ses bilimi ve diksiyon], Engin yayin evi.
25. Hafizah D., Putra A., Noor M.J., Py M.S. (2015), Double layered micro perforated panel as acoustic absorber in mosque, Proceedings of Mechanical Engineering Research Day, pp. 103–104.
26. Harris C.M. (1991), Handbook of Acoustical Measurements and Noise Control, McGraw-Hill.
27. Houtgast T., Steeneken H. (1984), A multilanguage evaluation of the RASTI-method for estimating speech intelligibility in auditoria, Acta Acustica united with Acustica, 54(4): 185–199.
28. Ismail M.R. (2013), A parametric investigation of the acoustical performance of contemporary mosques, Frontiers of Architectural Research, 2(1): 30–41, doi: 10.1016/j.foar.2012.11.002.
29. Karabiber Z. (2000), New Approach to an Ancient Subject: CAHRISMA Project, Proceedings of the 7th ICSV Conference.
30. Karabiber Z., Erdogan S. (2002), Comparison of the acoustical properties of an ancient and recent mosque, Forum Acusticum.
31. Kavraz M. (2014), The acoustic characteristics of the Çarsı Mosque in Trabzon, Turkey, Indoor and Built Environment, 25(1): 128–136, doi: 10.1177/1420 326X14541138.
32. Kayılı M. (1988), Evaluation of acoustic data in Mimar Sinan’s Mosques, Chief Architect Koca Sinan: His Age and Works [in Turkish: Mimar Sinan’ın Camilerindeki Akustik Verilerin Degerlendirilmesi, Mimarbası Koca Sinan: Yasadıgı Çag ve Eserleri], T.C. Basbakanlık Vakıflar Genel Müdürlügü, Istanbul, pp. 545–555.
33. Kayili M. (2005), Acoustic Solutions in classic Ottoman architecture, Foundation for Science, Technology and Civilisation, Publication ID: 4087.
34. Kılıncarslan A.S. (1986), Standardization of phonetically balanced monosyllabic word lists developed for the Turkish language [in Turkish: Türk Diliiçin Gelistirilmis Fonetik Dengeli Tek Heceli Kelime Listelerinin Standardizasyonu], Master Thesis, Hacettepe University, Ankara.
35. Kitapçı K. (2016), Speech ıntelligibility in multilingual spaces, Doctoral Thesis, Heriot-Watt University. 36. Kitapçi K., Galbrun L. (2014), Comparison of speech intelligibility between English, Polish, Arabic and Mandarin, Proceeding of Forum Acusticum, Krakow, Poland.
37. Kuttruff H. (2009), Room Acoustics, 5th ed., CRC Press.
38. Long M. (2006), Architectural Acoustics, Elsevier Academic Press.
39. ODEON, (2015), Odeon Application Note – Auralisation and how to calibrate the sound level for presentations, JHR.
40. Orfali W.A. (2007), Sound parameters in mosque, Proceedings of Meeting on Acoustics, 1(1): 035001, doi: 10.1121/1.2829306.
41. Parkin P.H., Cowell J.R., Humphreys H.R. (1979), Acoustics, Noise, and Buildings, 4th ed., Faber and Faber: Boston MA.
42. Pilancı H. (2011), Turkish phonetics [in Turkish: Türkçe ses bilgisi], Anadolu Üniversitesi basımevi.
43. Presidency of Religious Affairs (2016), 2016 4-B Contracted Islamic Preacher Recruitment (SÖZPER-2016- III) [in Turkish: 2016 Yılı 4-B Sözlesmeli Imam-Hatip Alımı (SÖZPER-2016-III)], Retrieved November 15, 2019, from https://insankaynaklari.diyanet.gov.tr/De tay/315/2016-y%C4%B1l%C4%B1-4-b-s%C3%B6zle %C5%9Fmeli-imam-hatip-al%C4%B1m%C4%B1-(s% C3%B6zper-2016-%C4%B1%C4%B1%C4%B1.
44. Prodi N., Marsilio M. (2003), On the effect of domed ceiling in worship spaces: a scale model study of a mosque, Building Acoustics, 10(2): 117–134, doi: 10.1260/135101003768965979.
Go to article

Authors and Affiliations

Elma Alic
1
Asli Ozcevik Bilen
1

  1. Department of Architecture, Eskisehir Technical University, Eskisehir, Turkey
Download PDF Download RIS Download Bibtex

Abstract

The lower limit of pitch (LLP) perception was explored for pure tones, sinusoidally amplitude-modulated (SAM) tones with a carrier frequency of 125 Hz, and trains of 125-Hz tone pips, using an adaptive procedure to estimate the lowest repetition rate for which a tonal/humming quality was heard. The LLP was similar for the three stimulus types, averaging 19 Hz. There were marked individual differences, which were correlated to some extent across stimulus types. The pure-tone stimuli contained a single resolved harmonic, whereas the SAM tones and tone-pip trains contained only unresolved components, whose frequencies did not necessarily form a harmonic series. The similarity of the LLP across stimulus types suggests that the LLP is determined by the repetition period of the sound for pure tones, and the envelope repetition period for complex stimuli. The results are consistent with the idea that the LLP is determined by a periodicity analysis in the auditory system, and that the longest time interval between waveform or envelope peaks for which this analysis can be performed is approximately 53 ms.
Go to article

Bibliography

1. Atal B.S. (1972), Automatic speaker recognition based on pitch contours, The Journal of the Acoustical Society of America, 52(6B): 1687–1697, doi: 10.1121/1.1913303.
2. Bernstein J.G., Oxenham A.J. (2005), An autocorrelation model with place dependence to account for the effect of harmonic number on fundamental frequency discrimination, The Journal of the Acoustical Society of America, 117(6): 3816–3831, doi: 10.1121/1.1904268.
3. British Society of Audiology (2018), Recommended Procedure: Pure-tone air-conduction and bone conduction threshold audiometry with and without masking, British Society of Audiology, Reading, UK.
4. Burke S. (1998), Missing values, outliers, robust statistics & non-parametric methods, Valid Analytical Measurement Bulletin, 19: 22–27.
5. Carney L.H., Yin T.C.T. (1988), Temporal coding of resonances by low-frequency auditory nerve fibers: Single-fiber responses and a population model, Journal of Neurophysiology, 60(5): 1653–1677, doi: 10.1152/jn.1988.60.5.1653.
6. de Cheveigné A. (1997), Concurrent vowel identification III: A neural model of harmonic interference cancellation, The Journal of the Acoustical Society of America, 101(5): 2857–2865, doi: 10.1121/1.419480.
7. de Cheveigné A., Pressnitzer D. (2006), The case of the missing delay lines: Synthetic delays obtained by cross-channel phase interaction, The Journal of the Acoustical Society of America, 119(6): 3908–3918, doi: 10.1121/1.2195291.
8. Cullen J.K., Long G.R. (1986), Rate discrimination of high-pass-filtered pulse trains, The Journal of the Acoustical Society of America, 79(1): 114–119, doi: 10.1121/1.393762.
9. Dau T. (2003), The importance of cochlear processing for the formation of auditory brainstem and frequency following responses, The Journal of the Acoustical Society of America, 113(2): 936–950, doi: 10.1121/1.1534833.
10. Drugman T., Huybrechts G., Klimkov, V., Moinet A. (2018), Traditional machine learning for pitch detection, IEEE Signal Processing Letters, 25(11): 1745–1749, doi: 10.1109/LSP.2018.2874155.
11. Drullman R., Festen J.M., Plomp R. (1994), Effect of reducing slow temporal modulations on speech reception, The Journal of the Acoustical Society of America, 95(5): 2670–2680, doi: 10.1121/1.409836.
12. Elliott T.M., Theunissen F.E. (2009), The modulation transfer function for speech intelligibility, PLOS Computational Biology, 5: e1000302, doi: 10.1371/journal.pcbi.1000302.
13. Fastl H. (1983), Fluctuation strength of modulated tones and broadband noise, [in:] Hearing – Physiological Bases and Psychophysics, Klinke R., Hartmann R. [Eds], pp. 282–288, Springer, Berlin, Heidelberg, doi: 10.1007/978-3-642-69257-4_41.
14. Fukushima M., Doyle A.M., Mullarkey M.P., Mishkin M., Averbeck B.B. (2015), Distributed acoustic cues for caller identity in macaque vocalization, Royal Society Open Science, 2(12): 150432, doi: 10.1098/rsos.150432.
15. Gerson A., Goldstein J.L. (1978), Evidence for a general template in central optimal processing for pitch of complex tones, The Journal of the Acoustical Society of America, 63(2): 498–510, doi: 10.1121/1.381750.
16. Glasberg B.R., Moore B.C.J. (1990), Derivation of auditory filter shapes from notched-noise data, Hearing Research, 47(1–2): 103–138, doi: 10.1016/0378-5955(90)90170-t.
17. Guttman N., Pruzansky S. (1962), Lower limits of pitch and musical pitch, Journal of Speech, Language, and Hearing Research, 5(3): 207–214, doi: 10.1044/jshr.0503.207.
18. Han K., Wang D. (2014), Neural networks for supervised pitch tracking in noise, [in:] Proceedings of the International Conference on Acoustic, Speech and Signal Processing (ICASSP), Florence, Italy, pp. 1488–1492, doi: 10.1109/ICASSP.2014.6853845.
19. He C., Trainor L.J. (2009), Finding the pitch of the missing fundamental in infants, Journal of Neuroscience, 29(24): 7718–7722, doi: 10.1523/JNEUROSCI.0157-09.2009.
20. Hoeschele M. (2017), Animal pitch perception: melodies and harmonies, Comparative Cognition and Behavior Reviews, 12: 5–18, doi: 10.3819/CCBR.2017.120002.
21. Hoke M., Ross B., Wickesberg R., Lütkenhöner B. (1984), Weighted averaging – theory and application to electric response audiometry, Electroencephalography and Clinical Neurophysiology, 57(5): 484–489, doi: 10.1016/0013-4694(84)90078-6.
22. ISO-226 (2003), Acoustics – normal equal-loudness contours, International Organization for Standardization, Geneva, Switzerland.
23. Jackson H.M., Moore B.C.J. (2013), The dominant region for the pitch of complex tones with low fundamental frequencies, The Journal of the Acoustical Society of America, 134(2): 1193–1204, doi: 10.1121/1.4812754.
24. Joly O., Baumann S., Poirier C., Patterson R.D., Thiele A., Griffiths T.D. (2014), A perceptual pitch boundary in a non-human primate, Frontiers in Psychology, 5, Article 998, doi: 10.3389/fpsyg.2014.00998.
25. Jurado C., Gallegos P., Gordillo D., Moore B.C.J. (2017), The detailed shapes of equal-loudness-level contours at low frequencies, The Journal of the Acoustical Society of America, 142(6): 3821–3832, doi: 10.1121/1.5018428.
26. Jurado C., Larrea M., Patel H., Marquardt T. (2020), Dependency of threshold and loudness on sound duration at low and infrasonic frequencies, The Journal of the Acoustical Society of America, 148(2): 1030–1038, doi: 10.1121/10.0001760 .
27. Jurado C., Marquardt T. (2016), The effect of the helicotrema on low-frequency loudness perception, The Journal of the Acoustical Society of America, 140(5): 3799–3809, doi: 10.1121/1.4967295.
28. Jurado C., Marquardt T. (2020), Brain’s frequency following responses to low-frequency and infrasound, Archives of Acoustics, 45(2): 313–319, doi: 10.24425/aoa.2020.133151.
29. Jurado C., Moore B.C.J. (2010), Frequency selectivity for frequencies below 100 Hz: Comparisons with mid-frequencies, The Journal of the Acoustical Society of America, 128(6): 3585–3596, doi: 10.1121/1.3504657.
30. Jurado C., Pedersen C.S., Moore B.C.J. (2011), Psychophysical tuning curves for frequencies below 100 Hz, The Journal of the Acoustical Society of America, 129(5): 3166–3180, doi: 10.1121/1.3560535.
31. Kanedera N., Arai T., Hermansky H., Pavel M. (1999), On the relative importance of various components of the modulation spectrum for automatic speech recognition, Speech Communication, 28(1): 43–55, doi: 10.1016/S0167-6393(99)00002-3.
32. Kinsler L.E., Frey A.R., Coppens A.B., Sanders J.V. (1999), Fundamentals of Acoustics, 4th ed., New York: Wiley-VCH.
33. Koumura T., Terashima H., Furukawa S. (2019), Cascaded tuning to amplitude modulation for natural sound recognition, Journal of Neuroscience, 39(28): 5517–5533, doi: 10.1523/JNEUROSCI.2914-18.2019.
34. Krumbholz K., Patterson R.D., Pressnitzer D. (2000), The lower limit of pitch as determined by rate discrimination, The Journal of the Acoustical Society of America, 108(3): 1170–1180, doi: 10.1121/1.1287843.
35. Kühler R., Fedtke T., Hensel J. (2015), Infrasonic and low-frequency insert earphone hearing threshold, The Journal of the Acoustical Society of America, 137(4): EL347–EL353, doi: 10.1121/1.4916795.
36. Logos Foundation (2016), Instrument frequencies and ranges, https://www.logosfoundation.org/kursus/frequen cy_table.html (date last viewed: 05-Oct-20).
37. Marquardt T., Hensel J., Mrowinski D., Scholz G. (2007), Low-frequency characteristics of human and guinea pig cochleae, The Journal of the Acoustical Society of America, 121(6): 3628–3638, doi: 10.1121/1.2722506.
38. Meddis R., O’Mard L. (1997), A unitary model of pitch perception, The Journal of the Acoustical Society of America, 102(3): 1811–1820, doi: 10.1121/1.420088.
39. Mehta A.H., Oxenham A.J. (2020), Effect of lowest harmonic rank on fundamental-frequency difference limens varies with fundamental frequency, The Journal of the Acoustical Society of America, 147(4): 2314– 2322, doi: 10.1121/10.0001092.
40. Mrller H., Pedersen C.S. (2004), Hearing at low and infrasonic frequencies, Noise and Health, 6(23): 37–57.
41. Moore B.C.J. (1982), An Introduction to the Psychology of Hearing, 2nd ed., London: Academic Press.
42. Moore B.C.J. (2008), The role of temporal fine structure processing in pitch perception, masking, and speech perception for normal-hearing and hearingimpaired people, Journal of the Association for Research in Otolaryngology, 9(4): 399–406, doi: 10.1007/s10162-008-0143-x.
43. Moore B.C.J. (2019), The roles of temporal envelope and fine structure information in auditory perception, Acoustical Science and Technology, 40(2): 61–83, doi: 10.1250/ast.40.61.
44. Moore B.C.J., Glasberg B.R., Flanagan H.J., Adams J. (2006), Frequency discrimination of complex tones; assessing the role of component resolvability and temporal fine structure, The Journal of the Acoustical Society of America, 119(1): 480–490, doi: 10.1121/1.2139070.
45. Moore B.C.J., Glasberg B.R., Low K.E., Cope T., Cope W. (2006), Effects of level and frequency on the audibility of partials in inharmonic complex tones, The Journal of the Acoustical Society of America, 120(2): 934–944, doi: 10.1121/1.2216906.
46. Moore B.C.J., Gockel H.E. (2011), Resolvability of components in complex tones and implications for theories of pitch perception, Hearing Research, 276(1–2): 88–97, doi: 10.1016/j.heares.2011.01.003.
47. Moore B.C.J., Hopkins K., Cuthbertson S. (2009), Discrimination of complex tones with unresolved components using temporal fine structure information, The Journal of the Acoustical Society of America, 125(5): 3214–3222, doi: 10.1121/1.3106135.
48. Moore B.C.J., Ohgushi K. (1993), Audibility of partials in inharmonic complex tones, The Journal of the Acoustical Society of America, 93(1): 452–461, doi: 10.1121/1.405625.
49. Moore G.A., Moore B.C.J. (2003), Perception of the low pitch of frequency-shifted complexes, The Journal of the Acoustical Society of America, 113(2): 977– 985, doi: 10.1121/1.1536631.
50. Oxenham A.J. (2008), Pitch perception and auditory stream segregation: implications for hearing loss and cochlear implants, Trends in Amplification, 12(4): 316– 331, doi: 10.1177/1084713808325881.
51. Patterson R.D. (1987), A pulse ribbon model of monaural phase perception, The Journal of the Acoustical Society of America, 82(5): 1560–1586, doi: 10.1121/1.395146.
52. Plomp R. (1964), The ear as a frequency analyzer, The Journal of the Acoustical Society of America, 36(9): 1628–1636, doi: 10.1121/1.1919256.
53. Plomp R. (1967), Pitch of complex tones, The Journal of the Acoustical Society of America, 41(6): 1526–1533, doi: 10.1121/1.1910515.
54. Plomp R. (1983), The role of modulation in hearing, [in:] Hearing – Physiological Bases and Psychophysics, Klinke R., Hartmann R. [Eds], Springer, Berlin, pp. 270–276.
55. Pressnitzer D., Patterson R.D., Krumbholz K. (2001), The lower limit of melodic pitch, The Journal of the Acoustical Society of America, 109(5): 2074–2084, doi: 10.1121/1.1359797.
56. Ritsma R.J. (1962), Existence region of the tonal residue – I, The Journal of the Acoustical Society of America, 34(9A): 1224–1229, doi: 10.1121/1.1918307.
57. Santurette S., Dau T. (2011), The role of temporal fine structure information for the low pitch of highfrequency complex tones, The Journal of the Acoustical Society of America, 129(1): 282–292, doi: 10.1121/1.3518718.
58. Seebeck A. (1841), Observations on some conditions of tone formation [in German: Beobachtungen über einige Bedingungen der Entstehung von Tönen], Annalen der Physik, 129(7): 417–436, doi: 10.1002/andp.18411290702.
59. Shackleton T.M., Carlyon R.P. (1994), The role of resolved and unresolved harmonics in pitch perception and frequency modulation discrimination, The Journal of the Acoustical Society of America, 95(6): 3529–3540, doi: 10.1121/1.409970.
60. Shamma S., Dutta K. (2019), Spectro-temporal templates unify the pitch percepts of resolved and unresolved harmonics, The Journal of the Acoustical Society of America, 145(2): 615–629, doi: 10.1121/1.5088504.
61. Singh N.C., Theunissen F.E. (2003), Modulation spectra of natural sounds and ethological theories of auditory processing, The Journal of the Acoustical Society of America, 114(6): 3394–3411, doi: 10.1121/1.1624067.
62. Spetner N.B., Olsho L.W. (1990), Auditory frequency resolution in human infancy, Child Development, 61(3): 632–652, doi: 10.1111/j.1467-8624.1990.tb02808.x.
63. Terhardt E. (1974), Pitch, consonance, and harmony, The Journal of the Acoustical Society of America, 55(5): 1061–1069, doi: 10.1121/1.1914648.
64. Tichko P., Skoe E. (2017), Frequency-dependent fine structure in the frequency-following response: The byproduct of multiple generators, Hearing Research, 348: 1–15, doi: 10.1016/j.heares.2017.01.014.
65. Tukey J.W. (1977), Exploratory Data Analysis, Reading, Mass: Addison-Wesley Pub.
66. Varnet L., Ortiz-Barajas M.C., Erra R.G., Gervain J., Lorenzi C. (2017), A cross-linguistic study of speech modulation spectra, The Journal of the Acoustical Society of America, 142(4): 1976–1989, doi: 10.1121/1.5006179.
67. Walker K.M.M., Schnupp J.W.H., Hart-Schnupp S.M.B., King A.J., Bizley J.K. (2009), Pitch discrimination by ferrets for simple and complex sounds, The Journal of the Acoustical Society of America, 126(3): 1321–1335, doi: 10.1121/1.3179676.
68. Warren R.M., Bashford J.A. (1981), Perception of acoustic iterance: Pitch and infrapitch, Perception and Psychophysics, 29(4): 395–402, doi: 10.3758/ BF03207350.
69. Yrttiaho S., Tiitinen H., May P.J.C., Leino S., Alku P. (2008), Cortical sensitivity to periodicity of speech sounds, The Journal of the Acoustical Society of America, 123(4): 2191–2199, doi: 10.1121/1.2888489.
Go to article

Authors and Affiliations

Carlos Jurado
1
Marcelo Larrea
1
Brian C.J. Moore
2

  1. Escuela de Ingeniería en Sonido y Acústica, Universidad de Las Américas, Avenue Granados and Colimes, EC170125, Ecuador
  2. Cambridge Hearing Group, Department of Experimental Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, England
Download PDF Download RIS Download Bibtex

Abstract

This research determines an identification system for the types of Beiguan music – a historical, nonclassical music genre – by combining artificial neural network (ANN), social tagging, and music information retrieval (MIR). Based on the strategy of social tagging, the procedure of this research includes: evaluating the qualifying features of 48 Beiguan music recordings, quantifying 11 music indexes representing tempo and instrumental features, feeding these sets of quantized data into a three-layered ANN, and executing three rounds of testing, with each round containing 30 times of identification. The result of ANN testing reaches a satisfying correctness (97% overall) on classifying three types of Beiguan music. The purpose of this research is to provide a general attesting method, which can identify diversities within the selected non-classical music genre, Beiguan. The research also quantifies significant musical indexes, which can be effectively identified. The advantages of this method include improving data processing efficiency, fast MIR, and evoking possible musical connections from the high-relation result of statistical analyses.
Go to article

Bibliography

1. Briot J.-P., Hadjeres G., Pachet F.-D. (2019), Deep Learning Techniques for Music Generation, Computational Synthesis and Creative Systems, Springer, arXiv: 1709.01620.
2. Hagan M.T., Demuth H.B., Beale M. (2002), Neural Network Design, CITIC Publishing House, Beijing.
3. Lamere P. (2008), Social tagging and music information retrieval, Journal of New Music Research, 37(2): 101–114, doi: 10.1080/09298210802479284.
4. Lu C.-K. (2011), Beiguan Music, Taichung, Taiwan: Morningstar.
5. Pan J.-T. (2019), The transmission of Beiguan in higher education in Taiwan: A case study of the teaching of Beiguan in the department of traditional music of Taipei National University of the Arts [in Chinese], Journal of Chinese Ritual, Theatre and Folklore, 2019.3(203): 111–162.
6. Rosner A., Schuller B., Kostek B. (2014), Classification of music genres based on music separation into harmonic and drum components, Archives of Acoustics, 39(4): 629–638, doi: 10.2478/aoa-2014-0068.
7. Tzanetakis G., Kapur A., Scholoss W.A., Wright M. (2007), Computational ethnomusicology, Journal of Interdisciplinary Music Studies, 1(2): 1–24.
8. Wiering F., de Nooijer J., Volk A., Tabachneck- Schijf H.J.M. (2009), Cognition-based segmentation for music information retrieval systems, Journal of New Music Research, 38(2): 139–154, doi: 10.1080/09298210903171145.
9. Yao S.-N., Collins T., Liang C. (2017), Head-related transfer function selection using neural networks, Archives of Acoustics, 42(3): 365–373, doi: 10.1515/aoa-2017-0038.
10. Yeh N. (1988), Nanguan music repertoire: categories, notation, and performance practice, Asian Music, 19(2): 31–70, doi: 10.2307/833866.
Go to article

Authors and Affiliations

Yu-Hsin Chang
1
Shu-Nung Yao
2

  1. Department of Music, Tainan National University of the Arts, No. 66, Daqi, Guantian Dist., Tainan City 72045, Taiwan
  2. Department of Electrical Engineering, National Taipei University, No. 151, University Rd., Sanxia District, New Taipei City 237303, Taiwan
Download PDF Download RIS Download Bibtex

Abstract

Gears are essential machine elements used to transmit power and motion from one unit to another under desired angular velocity ratio. Various types of gears have been developed to fulfill power transmission requirements in industrial applications. Under normal or fluctuating operating conditions, increase in fatigue load cycles, transition in lubrication regimes, fluctuating loads and speeds, etc., result in various surface fatigue wear modes which affect the performance of geared system. The severity of wear anomalies developed on gear tooth surfaces can be assessed by using vibration signals acquired from the gear box. On the other hand, reliable wear assessment is very important to perform maintenance action which depends on the sensors, data acquisition procedure, vibration signal analysis and interpretation. This paper presents results of the experimental investigations carried out to assess initiation and propagation of surface fatigue failure wear modes developed on gear tooth contact surfaces. A FZG back to back power recirculation type spur gearbox was used to conduct fatigue test experiments on spur gears under accelerated test conditions. Accelerated test conditions resulted in a rapid transition of lubrication regimes, i.e., hydrodynamic lubrication regime to boundary lubrication regime which triggered surface fatigue faults on gear tooth surfaces. A cepstral analysis method was used to assess fault severity in the geared system. The results obtained from the cepstral features were correlated to various surface fatigue faults and reduction in gear tooth stiffness. Results obtained from the experimental investigations highlighted the suitability of cepstral features to assess incipient faults developed on spur gear tooth surfaces.
Go to article

Bibliography

1. Amarnath M., Chandramohan S., Seetharaman S. (2012), Experimental investigations of surface wear assessment of spur gear teeth, Journal of Vibration and Control, 18(7): 1009–1024, doi: 10.1177/1077546311399947.
2. Amarnath M., Lee S.K. (2015), Assessment of surface contact fatigue failure in a spur geared system based on the tribological and vibration parameter analysis, Measurement, 76: 32–44, doi: 10.1016/ j.measurement.2015.08.020.
3. Amarnath M., Sujatha C., Swarnamani S. (2009), Experimental studies on the effects of reduction in gear tooth stiffness and lubricant film thickness in a spur geared system, Tribology International, 42(2): 340–352, doi: 10.1016/j.triboint.2008.07.008.
4. Dalpiaz G., Rivola A., Rubini R. (2000), Effectiveness and sensitivity of vibration processing techniques for local fault detection in gears, Mechanical Systems and Signal Processing, 14(3): 387–412, doi: 10.1006/mssp.1999.1294.
5. El Badaoui M., Antoni J., Guillet F., Daniere J., Velex P. (2001), Use of the moving cepstrum integral to detect and localise tooth spalls in gears, Mechanical Systems and Signal Processing, 15(5): 873–885, doi: 10.1006/mssp.2001.1413.
6. Fakhfakh T., Chaari F., Haddar M. (2005), Numerical and experimental analysis of a gear system with teeth defects, The International Journal of Advanced Manufacturing Technology, 25(5–6): 542–550, doi: 10.1007/s00170-003-1830-8.
7. Fernandes P.J.L. (1996), Tooth bending fatigue failures in gears, Engineering Failure Analysis, 3(3): 219– 225, doi: 10.1016/1350-6307(96)00008-8.
8. Fernandes P.J.L., McDuling C. (1997), Surface contact fatigue failures in gears, Engineering Failure Analysis, 4(2): 99–107, doi: 10.1016/S1350-6307(97)00006-X.
9. Jacobson B. (2003), The Stribeck memorial lecture, Tribology International, 36(11): 781–789, doi: 10.1016/S0301-679X(03)00094-X.
10. Lee S.K., Amarnath M. (2016), Experimental investigations to establish correlation between stribeck curve, specific film thickness and statistical parameters of vibration and sound signals in a spur gear system, Journal of Vibration and Control, 22(6): 1667–1681, doi: 10.1177/1077546314544164.
11. Liang B., Iwnicki S.D., Zhao Y. (2013), Application of power spectrum, cepstrum, higher order spectrum and neural network analyses for induction motor fault diagnosis, Mechanical Systems and Signal Processing, 39(1–2): 342–360, doi: 10.1016/j.ymssp.2013.02.016.
12. Łazarz B., Wojnar G., Czech P. (2011), Early fault detection of toothed gear in exploitation conditions, Maintenance and Reliability, 2011(1): 68–77.
13. Łazarz B., Wojnar G., Figlus T. (2007), Comparison of the efficiency of selected vibration measures used in the diagnosis of complex cases of tooth gear damage, Diagnostyka, 44: 19–24.
14. Madej H., Łazarz B., Wojnar G. (2005), Geartooth pitting detection through use of the wavelet transform. Tribosysteme in der Fahrzeugtechnik, Symposium 2005 der Osterreichischen Tribologischen Gesellschaft, Wien, 10 November 2005, pp. 241–248.
15. McFadden P.D. (1986), Detecting fatigue cracks in gears by amplitude and phase demodulation of the meshing vibration, Journal of Vibration, Acoustics, Stress, and Reliability in Design, 108(2): 165–170, doi: 10.1115/1.3269317.
16. Ozturk H., Yesilyurt I., Sabuncu M. (2010), Detection and advancement monitoring of distributed pitting failure in gears, Journal of Nondestructive Evaluation, 29(2): 63–73, doi: 10.1007/s10921-010-0066-4.
17. Park C.S., Choi Y.C., Kim Y.H. (2013), Early fault detection in automotive ball bearings using the minimum variance cepstrum, Mechanical Systems and Signal Processing, 38(2): 534–548, doi: 10.1016/ j.ymssp.2013.02.017.
18. Randall R.B. (1982), A new method of modeling gear faults, Journal of Mechanical Design, 104(2): 259–267, doi: 10.1115/1.3256334.
19. Sung C.K., Tai H.M., Chen C.W. (2000), Locating defects of a gear system by the technique of wavelet transform, Mechanism and Machine Theory, 35(8): 1169–1182, doi: 10.1016/S0094-114X(99)00045-2.
20. Wojnar G., Łazarz B. (2007), Averaging of the vibration signal with the synchronizing impulse location correction in tooth gear diagnostics, Diagnostyka, 44: 19–24.
21. Yesilyurt I., Gu F., Ball A.D. (2003), Gear tooth stiffness reduction measurement using modal analysis and its use in wear fault severity assessment of spur gears, NDT & E International, 36(5): 357–372, doi: 10.1016/S0963-8695(03)00011-2.
22. Ziaran S., Darula R. (2013), Determination of the state of wear of high contact ratio gear sets by means of spectrum and cepstrum analysis, Journal of Vibration and Acoustics, 135(2): 021008, doi: 10.1115/1.4023208.
Go to article

Authors and Affiliations

Muniyappa Amarnath
1
I.R. Praveen Krishna
2
Ramalingam Krishnamurthy
3

  1. Tribology and Machine Dynamics Laboratory, Department of Mechanical Engineering, Indian Institute of Information Technology Design and Manufacturing, Jabalpur,Jabalpur 482001, India
  2. Department of Aerospace Engineering, Indian Institute of Space Science and Technology, Thiruvananthapuram – 695547, India
  3. Department of Mechanical Engineering, Indian Institute of Technology, Madras 600025, Tamilnadu, India
Download PDF Download RIS Download Bibtex

Abstract

The core goal of this paper is to put forward a feasible scheme of noise reduction for a target forklift on the basis of solving the problem of vibration and acoustic radiation from complex structures in infinite domain. Based on the previous report and vibration acceleration tests, the acoustic virtual wind tunnel model of forklift power compartment was established using finite element method and boundary element method, in which the perfectly matched layer was first applied to simulate the attenuation propagation of sound waves in air. In addition, according to the distribution characteristics of sound pressure field with different frequencies, the acoustic energy mainly radiated through the bottom and right side, and concentrated in the low frequency. Consequently, the acoustic packaging design for the whole forklift power compartment was presented, and a satisfying noise reduction effect was achieved.
Go to article

Bibliography

1. Bermudez A., Hervella-Nieto L., Prieto A., Rodriguez R. (2014), An optimal perfectly matched layer with unbounded absorbing function for timeharmonic acoustic scattering problems, Journal of Computational Physics, 223(2): 469–488, doi: 10.1016/j.jcp.2006.09.018
2. Bi C.X., Zhang Y., Zhang X.Z., Zhang Y.B. (2018), Stability analysis of inverse time domain boundary element method for near-field acoustic holography, The Journal of the Acoustical Society of America, 143(3): 1308–1317, doi: 10.1121/1.5026024.
3. Cai H,S., Li X.X., Zhang W.B. (2010), Analysis and experimental study on sound absorption and noise reduction performance of some composite materials, Noise and Vibration Control, 4: 54–57, doi: 10.3969/j.issn.1006-1355.2010.04.015.
4. Chen L.H., Schweikert D.G. (1963), Sound radiation from an arbitrary body, The Journal of the Acoustical Society of America, 35(10): 1626–1632, doi: 10.1121/1.1918770.
5. Chen L.L., Liu L.C., Zhao W.C., Chen H.B. (2016), 2D acoustic design sensitivity analysis based on adjoint variable method using different types of boundary elements, Acoustics Australia, 44(2): 343–357, doi: 10.1007/s40857-016-0065-4.
6. Chen L.L., Zhao W.C., Liu C., Chen H.B. (2017), 2D structural acoustic analysis using the FEM/FMBEM with Different Coupled Element Types, Archives of Acoustics, 42(1): 37–48, doi: 10.1515/aoa-2017-0005.
7. Chen L.L., Zhao W.C., Liu C., Chen H.B., Marburg S. (2019), Isogeometric Fast Multipole Boundary Element Method based on Burton-Miller formulation for 3D acoustic problems, Archives of Acoustics, 44(3): 475–492, doi: 10.24425/aoa.2019.129263.
8. Dammak K., Koubaa S., EI Hami A., Walha L., Haddar M. (2019), Numerical modelling of vibroacoustic problem in presence of uncertainty: Application to a vehicle cabin, Applied Acoustics, 144: 113– 123, doi: 10.1016/j.apacoust.2017.06.001.
9. Dogan H., Eisenmenger C., Ochmann M. (2018), A LBIE-RBF solution to the convected wave equation for flow acoustics, Engineering Analysis with Boundary Elements, 92: 196–206, doi: 10.1016/j.enganabound.2017.11.016.
10. Duru K., Kreiss G. (2014), Efficient and stable perfectly matched layer for CEM, Applied Numerical Mathematics, 76: 34–47, doi: 10.1016/j.apnum.2013.09.005.
11. Gao K., Fu S.B., Chung E.T. (2018), A high-order multiscale finite-element method for time-domain acoustic-wave modeling, Journal of Computational Physics, 360: 120–136, doi: 10.1016/j.jcp.2018.01.032.
12. Gao R.X., Zhang Y.H., Kennedy D. (2019), Topology optimization of sound absorbing layer for the midfrequency vibration of vibro-acoustic systems, Structural and Multidisciplinary Optimization, 59(5): 1733– 1746, doi: 10.1007/s00158-018-2156-3.
13. Hashimoto N. (2001), Measurement of sound radiation efficiency by the discrete calculation method, Applied Acoustics, 62(4): 429–446, doi: 10.1016/S0003- 682X(00)00025-6.
14. Jang H.W., Ih J.G. (2013), On the instability of time-domain acoustic boundary element method due to the static mode in interior problems, Journal of Sound and Vibration, 332(24): 6463–6471, doi: 10.1016/j.jsv.2013.07.018.
15. Kolber K., Snakowska A., Kozupa M. (2014), The effect of plate discretizationon accuracy of the sound radiation efficiency measurements, Archives of Acoustics, 39(4): 511–518, doi: 10.2478/aoa-2014-0055.
16. Komatisch D., Tromp J. (2003), A perfectly matched layer absorbing boundary condition for the secondorder seismic wave equation, Geophysical Journal International, 154(1):146–153, doi: 10.1046/j.1365- 246X.2003.01950.x.
17. Kozien M.S. (2005), Hybrid method of evaluation of sounds radiated by vibrating surface elements, Journal of Theoretical and Applied Mechanics, 43(1): 119–133.
18. Kozien M.S. (2009), Acoustic intensity vector generated by vibrating set of small areas with random amplitudes, Journal of Theoretical and Applied Mechanics, 47(2): 411–420.
19. Liu X.J., Wu H.J., Jiang W.K. (2017), A boundary element method based on the hierarchical matrices and multipole expansion theory for acoustic problems, International Journal of Computational Methods, 15: 1850009, doi: 10.1142/S0219876218500093.
20. Lock A., Holloway D. (2016), Boundary element modelling of a novel simple enhanced bandwidth schroeder diffuser offering comparable performance to a fractal design, Acoustics Australia, 44(1): 137–147, doi: 10.1007/s40857-016-0049-4.
21. Loeffler C.F., Mansur W.J., Barcelos H.D., Bulcao A. (2015), Solving Helmholtz problems with boundary element method using direct radial basis function interpolation, Engineering Analysis with Boundary Elements, 61: 218–225, doi: 10.1016/j.enganabound.2015.07.013.
22. Mott P.H., Michael R.C., Corsaro R.D. (2002), Acoustic and dynamic mechanical properties of a polyurethane rubber, The Journal of the Acoustical Society of America, 111(4): 1782–1790, doi: 10.1121/1.1459465.
23. Qu W.Z., Fan C.M., Gu Y., Wang F.J. (2019), Analysis of three-dimensional interior acoustic fields by using the localized method of fundamental solutions, Applied Mathematical Modelling, 76: 122–132, doi: 10.1016/j.apm.2019.06.014.
24. Tian W.Y., Yao L.Y., Li L. (2017), A Coupled Smoothed Finite Element-Boundary Element Method for structural-acoustic analysis of shell, Archives of Acoustics, 42(1): 49–59, doi: 10.1515/aoa-2017-0006.
25. Yang H.B. (2013), Low-frequency acoustic absorption mechanism of a viscoelastic layer with resonant cylindrical scatterers, Acta Physica Sinca, 62(15): 223–229, doi: 10.7498/aps.62.154301.
26. Zhang E.L., Hou L., Yang W.P. (2015), Noise source identification and experimental research of engine compartment of a Forklift based on fast independent component analysis and Scan & Paint, Proceedings of the ASME 2015 International Mechanical Engineering Congress and Exposition, Vol. 13: Vibration, Acoustics and Wave Propagation, Houston, Texas, USA, November 13–19, 2015, doi: 10.1115/IMECE2015-51380.
27. Zhang E.L., Zhang Q.M., Xiao J.J., Hou L., Guo T. (2018), Acoustic comfort evaluation modeling and improvement test of a forklift based on rank score comparison and multiple linear regression, Applied Acoustics, 135: 29–36, doi: 10.1016/j.apacoust.2018.01.026.
28. Zhang E.L., Zhuo J.M., Hou L., Fu C.H., Guo T. (2021), Comprehensive annoyance modeling of forklift sound quality based on rank score comparison and multi-fuzzy analytic hierarchy process, Applied Acoustics, 173: 107705, doi: 10.1016/j.apacoust.2020.107705
Go to article

Authors and Affiliations

Enlai Zhang
1 2
Zhiqi Liu
2
Jingjing Zhang
3
Jiahe Lin
4

  1. School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen, China
  2. Chengyi University College, Jimei University, Xiamen, China
  3. College of Applied Science and Technology, Hainan University, Danzhou, China
  4. Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen, China
Download PDF Download RIS Download Bibtex

Abstract

M-estimators are widely used in active noise control (ANC) systems in order to update the adaptive FIR filter taps. ANC systems reduce the noise level by generating anti-noise signals. Up to now, the evaluation of M-estimators capabilities has shown that there exists a need for further improvements in this area. In this paper, a new improved M-estimator is proposed. The sensitivity of the proposed algorithm to the variations of its constant parameter is checked in feedforward control. The effectiveness of the algorithm in both types is proved by comparing it with previous studies. Simulation results show the steady performance and fast initial convergence of the proposed algorithm.
Go to article

Bibliography

1. Akhtar M.T., Mitsuhashi W. (2010), A modified normalized FxLMS algorithm for active control of impulsive noise, Proceedings of 18th European Signal Processing Conference (EUSIPCO), IEEE, pp. 1–5, Aalborg.
2. Ang L.Y.L., Koh Y.K., Lee H.P. (2017), The performance of active noise-canceling headphones in different noise environments, Applied Acoustics, 122: 16– 22, doi: 10.1016/j.apacoust.2017.02.005.
3. Behera S. K., Das D.P., Subudhi B. (2017), Adaptive nonlinear active noise control algorithm for active headrest with moving error microphones, Applied Acoustics, 123: 9–19, doi: 10.1016/j.apacoust.2017.03.002.
4. Darvish M., Frank S., Paschereit C.O. (2015), Numerical and experimental study on the tonal noise generation of a radial fan, Journal of Turbomachinery, 137(10): 101005, doi: 10.1115/1.4030498.
5. Elliott S. (2001), Signal Processing for Active Control, Academic Press, Elsevier.
6. Ertas H., Kaçıranlar S., Güler H. (2017), Robust Liu-type estimator for regression based on M-estimator, Communications in Statistics-Simulation and Computation, 46(5): 3907–3932, doi: 10.1080/03610918.2015.1045077.
7. Khan W.U., Ye Z., Altaf F., Chaudhary N.I., Raja M.A.Z. (2019), A novel application of fireworks heuristic paradigms for reliable treatment of nonlinear active noise control, Applied Acoustics, 146: 246–260, doi: 10.1016/j.apacoust.2018.11.024.
8. Kuo S.M., Morgan D.R. (1999), Active noise control: a tutorial review, Proceedings of the IEEE, 87(6): 943–973, doi: 10.1109/5.763310.
9. Lee J.W., Lee J.C., Pandey J., Ahn S.H., Kang Y.J. (2010), Mechanical properties and sound insulation effect of ABS/carbon-black composites, Journal of Composite Materials, 44(14): 1701–1716, doi: 10.1177/0021998309357673
10. Li J., Chen W. (2018), Singular boundary method based on time-dependent fundamental solutions for active noise control, Numerical Methods for Partial Differential Equations, 34(4): 1401–1421, doi: 10.1002/num.22263.
11. Lu L., Zhao H. (2017), Active impulsive noise control using maximum correntropy with adaptive kernel size, Mechanical Systems and Signal Processing, 87(part A) 180–191, doi: 10.1016/j.ymssp.2016.10.020.
12. Nelson P.A., Elliott S.J. (1991), Active Control of Sound, Academic Press, Elsevier. 13. Nunez I.J., Miranda J.G., Duarte M.V. (2019), Active noise control in acoustic shutters, Applied Acoustics, 152: 41–46, doi: 10.1016/j.apacoust.2019.03.024.
14. Patel V., George N.V. (2015), Nonlinear active noise control using spline adaptive filters, Applied Acoustics, 93: 38–43, doi: 10.1016/j.apacoust.2015.01.009.
15. Paul L. (1934), Process of silencing sound oscillations, Google patents. 16. Sabet S.M., Keshavarz R., Ohadi A. (2018), Sound isolation properties of polycarbonate/clay and polycarbonate/silica nanocomposites, Iranian Polymer Journal, 27(1): 57–66, doi: 10.1007/s13726-017-0585-2.
17. Sabzevari S.A.H., Moavenian M. (2017), Application of reinforcement learning for active noise control, Turkish Journal of Electrical Engineering & Computer Sciences, 25(4): 2606–2613.
18. Sen K.M., Morgan D.R. (1996), Active Noise Control Systems: Algorithms and DSP Implementations, John Wiley and Sons.
19. Suhail M., Chand S., Kibria B.G. (2019), Quantile-based robust ridge m-estimator for linear regression model in presence of multicollinearity and outliers, Communications in Statistics-Simulation and Computation, 1–13, doi: 10.1080/03610918.2019.1621339.
20. Sun G., Li M., Lim T.C. (2015), Enhanced filteredx least mean M-estimate algorithm for active impulsive noise control, Applied Acoustics, 90: 31–41, doi: 10.1016/j.apacoust.2014.10.012.
21. Tan L., Jiang J. (2015), Active control of impulsive noise using a nonlinear companding function, Mechanical Systems and Signal Processing, 58: 29–40, doi: 10.1016/j.ymssp.2015.01.010.
22. Thanigai P., Kuo S.M., Yenduri R. (2007), Nonlinear active noise control for infant incubators in neonatal intensive care units, Proceedings of 2007 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, pp. 1–109, Honolulu, doi: 10.1109/ICASSP.2007.366628.
23. Vu H.-S., Chen K.H. (2017), A high-performance feedback FxLMS active noise cancellation VLSI circuit design for in-ear headphones, Circuits, Systems and Signal Processing, 36(7): 2767–2785, doi: 10.1007/s00034-016-0436-y.
24. Wu L., Qiu X. (2013), An M-estimator based algorithm for active impulse-like noise control, Applied Acoustics, 74(3: 407–412, doi: 10.1016/j.apacoust.2012.06.019.
Go to article

Authors and Affiliations

Seyed Amir Hoseini Sabzevari
1
Seyed Iman Hoseini Sabzevari
2

  1. Department of Mechanical Engineering, University of Gonabad, Gonabad, 9691957678, Iran
  2. Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, 9177948974, Iran
Download PDF Download RIS Download Bibtex

Abstract

This paper describes boundary element method (BEM), experimental and optimization studies conducted to understand the potential of expansion tube coupled micro-perforated cylindrical panel (MPCP) to enhance the acoustic attenuation for in-duct noise control issues. Due to complex structure of the MPCP and for the correct prediction of acoustic attenuation, BEM is adopted on the basis of PLM Simcenter 3D software to compute the sound transmission loss (TL). As the MPCP is cylindrical in-shape with numbers of sub-milimeter holes, additive manufacturing based 3D printing was utilized for the model prototyping to reduce current design limitation and enabled fast fabrication. The TL measurement based two-load method is adopted for modal validation. Subsequently, a parametric studies of the MPCP concerning the perforation hole diameter, perforation ratio and depth of air space are carried out to investigate the acoustical performance. Optimization via response surface method (RSM) is used as it allows evaluating the effects of multiple parameters as required in this study. The model validation result shows that the error between the BEM and and measured values is relatively small and show a good agreement. The R-square value is 0.89. The finding from parametric study shows that a widen peak attenuation can be achieve by reducing the perforation hole diameter and one way to increase the transmission loss amplitude is by increasing the air cavity depth. Finally, the optimized MPCP model was adopted to the commercial vacuum cleaner for the verification. The sound pressure level (SPL) of the vacuum cleaner is significantly attenuated within the objective frequency of 1.7 kHz and its A-weighted SPL is reduced by 1.8 dB.
Go to article

Bibliography

1. Andersen K.S. (2008), Analyzing muffler performance using the transfer matrix method, Comsol Conference, https://www.comsol.com/paper/analyzing-muffler-per formance-using-the-transfer-matrix-method-5079.
2. Aziz M.S.A., Abdullah M.Z., Khor C.Y., Azid I.A. (2015), Optimization of pin through hole connector in thermal fluid–structure interaction analysis of wave soldering process using response surface methodology, Simulation Modelling Practice and Theory, 57: 45–57, doi: 10.1016/j.simpat.2015.06.001.
3. Citarella R., Landi M. (2011), Acoustic analysis of an exhaust manifold by Indirect Boundary Element Method, The Open Mechanical Engineering Journal, 5: 138–151, doi: 10.2174/1874155X01105010138.
4. Delany M.E., Bazley E.N. (1970), Acoustical properties of fibrous absorbent materials, Applied Acoustics, 3(2): 105–116, doi: 10.1016/0003-682X(70)90031-9.
5. Fu J., Chen W., Tang Y., Yuan W., Li G., Li Y. (2015), Modification of exhaust muffler of a diesel engine based on finite element method acoustic analysis, Advances in Mechanical Engineering, 7(4): 1-11, doi: 10.1177/1687814015575954.
6. Gaeta R.J., Ahuja K.K. (2016), Effect of orifice shape on acoustic impedance, International Journal of Aeroacoustics, 15(4–5): 474–495, doi: 10.1177/1475 472X16642133.
7. Ganguli R. (2002), Optimum design of a helicopter rotor for low vibration using aeroelastic analysis and response surface methods, Journal of Sound and Vibration, 258(2): 327–344, doi: 10.1006/jsvi.2002.5179.
8. Ishak M.H.H., Ismail F., Aziz M.S.A., Abdullah M.Z., Abas A. (2019), Optimization of 3D IC stacking chip on molded encapsulation process: a response surface methodology approach, The International Journal of Advanced Manufacturing Technology, 103(1–4): 1139– 1153, doi: 10.1007/s00170-019-03525-4.
9. Ji Z.L., Selamet A. (2000), Boundary element analysis of three-pass perforated duct mufflers, Noise Control Engineering Journal, 48(5): 151–156, doi: 10.3397/1.2827962.
10. Kallias A.N., Imran Rafiq M. (2013), Performance assessment of corroding RC beams using response surface methodology, Engineering Structures, 49: 671– 685, doi: 10.1016/j.engstruct.2012.11.015.
11. Leong W.C., Abdullah M.Z., Khor C.Y. (2013), Optimization of flexible printed circuit board electronics in the flow environment using response surface methodology, Microelectronics Reliability, 53(12): 1996–2004, doi: 10.1016/j.microrel.2013.06.008.
12. Li Z., Liang X. (2007), Vibro-acoustic analysis and optimization of damping structure with Response Surface Method, Materials & Design, 28(7): 1999–2007, doi: 10.1016/j.matdes.2006.07.006.
13. Liu Z., Zhan J., Fard M., Davy J.L. (2017), Acoustic properties of multilayer sound absorbers with a 3D printed micro-perforated panel, Applied Acoustics, 121: 25–32, doi: 10.1016/j.apacoust.2017.01.032.
14. Lu C., Chen W., Liu Z., Du S., Zhu Y. (2019), Pilot study on compact wideband micro-perforated muffler with a serial-parallel coupling mode, Applied Acoustics, 148: 141–150, doi: 10.1016/j.apacoust.2018.12.001.
15. Maa D.Y. (1975), Theory and design of microperforated panel sound-absorbing constructions, Scientia Sinica, 18(1): 55–71, doi: 10.1360/ya1975-18-1-55.
16. Munjal M.L. (1987), Acoustics of Ducts and Mufflers with Application to Exhaust and Ventilation System Design, John Wiley & Sons.
17. Na Y., Lancaster J., Casali J., Cho G. (2007), Sound absorption coefficients of micro-fiber fabrics by reverberation room method, Textile Research Journal, 77(5): 330–335, doi: 10.1177/0040517507078743.
18. Qian Y.J., Kong D.Y., Liu S.M., Sun S.M., Zhao Z. (2013), Investigation on micro-perforated panel absorber with ultra-micro perforations, Applied Acoustics, 74(7): 931–935, doi: 10.1016/j.apacoust.2013.01.009.
19. Qin X., Wang Y., Lu C., Huang S., Zheng H., Shen C. (2016), Structural acoustics analysis and optimization of an enclosed box-damped structure based on response surface methodology, Materials & Design, 103: 236–243, doi: 10.1016/j.matdes.2016.04.063.
20. C S.W. et al. (2019), Improvement of the sound absorption of flexible micro-perforated panels by local resonances, Mechanical Systems and Signal Processing, 117: 138–156, doi: 10.1016/j.ymssp.2018.07.046.
21. Selamet A., Ji Z.L. (1999), Acoustic attenuation performance of circular expansion chambers with extended inlet/outlet, Journal of Sound and Vibration, 223(2): 197–212, doi: 10.1006/jsvi.1998.2138.
22. Selamet A., Ji Z.L., Radavich P.M. (1998), Acoustic attenuation performance of circular expansion chambers with offset inlet/outlet: II. Comparison with experimental and computational studies, Journal of Sound and Vibration, 213(4): 619–641, doi: 10.1006/jsvi.1998.1515.
23. Tan W.-H., Ripin Z.M. (2013), Analysis of exhaust muffler with micro-perforated panel, Journal of Vibroengineering, 15(2): 558–573.
24. Tan W.-H., Ripin Z.M. (2016), Optimization of double-layered micro-perforated panels with vibroacoustic effect, Journal of the Brazilian Society of Mechanical Sciences and Engineering, 38(3): 745–760, doi: 10.1007/s40430-014-0274-4.
25. Vasile O. (2010), Transmission loss assessment for a muffler by boundary element method approach, Analele Universitaµii “Eftimie Murgu”, 17(1): 233–242, http://anale-ing.uem.ro/2010/26_C.pdf.
26. Wang Y., Qin X., Huang S., Lu L., Zhang Q., Feng J. (2017), Structural-borne acoustics analysis and multi-objective optimization by using panel acoustic participation and response surface methodology, Applied Acoustics, 116: 139–151, doi: 10.1016/ j.apacoust.2016.09.013.
27. Wu M.Q. (1997), Micro-perforated panels for duct silencing, Noise Control Engineering Journal, 45(2): 69– 77.
28. Yuksel E., Kamci G., Basdogan I. (2012), Vibroacoustic design optimization study to improve the sound pressure level inside the passenger cabin, Journal of Vibration and Acoustics, 134(6): 061017-1–061017- 9, doi: 10.1115/1.4007678.
29. Zhenlin J., Qiang M., Zhihua Z. (1994), Application of the boundary element method to predicting acoustic performance of expansion chamber mufflers with mean flow, Journal of Sound and Vibration, 173(1): 57–71, doi: 10.1006/jsvi.1994.1217.
Go to article

Authors and Affiliations

Mohamad Izudin Alisah
1
Lu-Ean Ooi
1
Zaidi Mohd Ripin
1
Ahmad Fadzli Yahaya
2
Kelvin Ho
2

  1. The Vibration Lab, School of Mechanical Engineering, Engineering Campus, Universiti Sains Malaysia,14300 Nibong Tebal, Pulau Pinang, Malaysia
  2. Dyson Manufacturing, 81400 Senai, Johor, Malaysia
Download PDF Download RIS Download Bibtex

Abstract

Cylindrical shells made of composite material form one of the major structural parts in aerospace structures. Many of them are acoustically thick, in which the ring frequencies are much higher than their critical frequencies. In this work, sound radiation behaviour of acoustically thick composite cylinders is presented. Based on the structural and acoustic wave number diagrams, the modal average radiation resistances in the frequency band of interest are theoretically determined. The structural wavenumbers are determined considering transverse shear deformation. The results show lesser sound radiation between the critical and ring frequencies, and significant sound radiation near the ring frequency and beyond. In the absence of the present results the radiation efficiency is considered to be unity at all frequencies beyond the critical frequency, including near the ring frequency. The radiation resistances of the same cylinder are determined experimentally and they are in very good agreement with the theoretical estimates. As part of this investigation, an expression for determining the ring frequency of composite cylinder is also presented.
Go to article

Bibliography

1. Bordoni P.G., Gross W. (1948), Sound radiation from a finite cylinder, Journal of Mathematics and Physics, 27(1–4): 242–252, doi: 10.1002/sapm1948271241.
2. Burroughs C.B. (1984), Acoustic radiation from fluid-loaded infinite circular cylinders with doubly periodic ring supports, The Journal of the Acoustical Society of the America, 75(3): 715–722, doi: 10.1121/1.390582.
3. Cao X., Hua H., Ma C. (2012), Acoustic radiation from shear deformable stiffened laminated cylindrical shells, Journal of Sound and Vibration, 331(3): 651–670, doi: 10.1016/j.jsv.2011.10.006.
4. Cox T.J., D’Antonio P. (2004), Acoustic Absorbers and Diffusers: Theory, Design and Application, New York: CRC Press.
5. Fahy F.J. (1969), Vibration of containing structure by sound in the contained fluid, Journal of Sound and Vibration, 10(3): 490–512, doi: 10.1016/0022-460x(69)90228-4.
6. Fahy F.J. (1970), Response of a cylinder to random sound in the contained fluid, Journal of Sound and Vibration, 13(2): 171–194, doi: 10.1016/s0022-460x(70)81172-5.
7. Fyfe K.R., Ismail F. (1989), An investigation of the acoustic properties of vibrating finite cylinders, Journal of Sound and Vibration, 128(3): 361–375, doi: 10.1016/0022-460x(89)90780-3.
8. Ghinet S., Atalla N., Osman H. (2006), Diffuse field transmission into infinite sandwich composite and laminate composite cylinders, Journal of Sound and Vibration, 289(4–5): 745–778, doi: 10.1016/j.jsv.2005.02.028.
9. Josephine Kelvina Florence S., Renji K., Subramanian K. (2018), Modal density of honeycomb sandwich composite cylindrical shells considering transverse shear deformation, International Journal of Acoustics and Vibration, 23(3): 83–92, doi: 10.20855/ijav.2018.23.11241 .
10. Laulagnet B., Guyader J.L. (1989), Modal analysis of a shell’s acoustic radiation in light and heavy fluids, Journal of Sound and Vibration, 131(3): 397–415, doi: 10.1016/0022-460x(89)91001-8.
11. Le Bot A., Cotoni V. (2010), Validity diagrams of statistical energy analysis, Journal of Sound and Vibration, 329(2): 221–235, doi: 10.1016/j.jsv.2009.09.008.
12. Lin T.R., Mechefske C., O’Shea P. (2011), Characteristics of modal sound radiation of finite cylindrical shells, Journal of Vibration and Acoustics, 133(5): 051011–051016, doi: 10.1115/1.4003944.
13. Lyon R.H. (1975), Statistical Energy Analysis of Dynamical Systems: Theory and Applications, Cambridge, MA: MIT Press.
14. Manning J.E., Maidanik G. (1964), Radiation properties of cylindrical shells, The Journal of the Acoustical Society of the America, 36(9): 1691–1698, doi: 10.1121/1.1919266.
15. Miller V.J., Faulkner L.L. (1983), Prediction of aircraft interior noise using the statistical energy analysis method, Journal of Vibration,Acoustics,Stress and Reliability in Design, 105(4): 512–518, doi: 10.1115/1.3269136.
16. Norton M.P. (1989), Fundamentals of Noise and Vibration Analysis for Engineers, England: Cambridge University Press.
17. Qiao Y., Chen H.B., Luo J.L. (2013), Estimation of shell radiation efficiency using a FEM-SmEdA algorithm, Journal of Vibroengineering, 15(3): 1130–1146.
18. Ramachandran P., Narayanan S. (2007), Evaluation of modal density, radiation efficiency and acoustic response of longitudinally stiffened cylindrical shell, Journal of Sound and Vibration, 304(1–2): 154–174, doi: 10.1016/j.jsv.2007.02.020.
19. Renji K., Josephine Kelvina Florence S. (2020), Critical frequencies of composite cylindrical Shells, International Journal of Acoustics and Vibration, 25(1): 79–87, doi: 10.20855/ijav.2020.25.11572.
20. Renji K., Josephine Kelvina Florence S., Sameer Deshpande (2019), Characteristics of in-plane waves in composite plates, International Journal of Acoustics and Vibration, 24(3): 458–466, doi: 10.20855/ijav.2019.24.31290.
21. Renji K., Josephine Kelvina Florence S., Sameer Deshpande (2020), An Experimental investigation of modal densities of composite honeycomb sandwich cylindrical shells, International Journal of Acoustics and Vibration, 25(1): 112–120, doi: 10.20855/ijav.2020.25.11626.
22. Renji K., Nair P.S., Narayanan S. (1998), On acoustic radiation resistance of plates, Journal of Sound and Vibration, 212(4): 583–598, doi: 10.1006/jsvi.1997.1438.
23. Reynolds D.D. (1981), Engineering Principles of Acoustics Noise and Vibration, Boston, MA: Allyn and Bacon.
24. Runkle C.J., Hart F.D. (1969), The Radiation Resistance of Cylindrical Shells, NASA CR-1437.
25. Squicciarini G., Putra A., Thompson D.J., Zhang X., Salim M.A. (2015), Use of a reciprocity technique to measure the radiation efficiency of a vibrating structure, Applied Acoustics, 89: 107–121, doi: 10.1016/j.apacoust.2014.09.013.
26. Stephanishen P.R. (1978), Radiated power and radiation loading of cylindrical surfaces with non-uniform velocity distribution, The Journal of the Acoustical Society of the America, 63(2): 328–338, doi: 10.1121/1.381743.
27. Sun Y., Yang T., Chen Y. (2018), Sound radiation modes of cylindrical surfaces and their application to vibro-acoustics analysis of cylindrical shells, Journal of Sound and Vibration, 424: 64–77, doi: 10.1016/ j.jsv.2018.03.004.
28. Szechenyi E. (1971), Modal densities and radiation efficiencies of unstiffened cylinders using statistical methods, Journal of Sound and Vibration, 19(1): 65– 81, doi: 10.1016/0022-460x(71)90423-8.
29. Wang C., Lai J.C.S. (2000), The sound radiation efficiency of finite length acoustically thick circular cylindrical shells under mechanical excitation. I: Theoretical analysis, Journal of Sound and Vibration, 232(2): 431–447, doi: 10.1006/jsvi.1999.2749.
30. Wang C., Lai J.C.S. (2001), The sound radiation efficiency of finite length circular cylindrical shells under mechanical excitation II: Limitations of the infinite length model, Journal of Sound and Vibration, 241(5): 825–838, doi: 10.1006/jsvi.2000.3338.
31. Yin X.W., Liu L.J., Hua H.X., Shen R.Y. (2009), Acoustic radiation from an infinite laminate composite cylindrical shells with doubly periodic rings, Journal of Vibration and Acoustics, 131(1): 011005–011009, doi: 10.1115/1.2980376.
32. Zhao X., Zhang B., Li Y. (2015), Vibration and acoustic radiation of an orthotropic composite cylindrical shell in a hygroscopic environment, Journal of Vibration and Control, 23(4): 673–692, doi: 10.1177/1077546315581943.
Go to article

Authors and Affiliations

S. Josephine Kelvina Florence
1
K. Renji
2

  1. Structures Group, U. R. Rao Satellite Centre, Bangalore, India-560017
  2. Advanced Technology Development Group, U. R. Rao Satellite Centre Bangalore, India-560017
Download PDF Download RIS Download Bibtex

Abstract

Noise pollution is a major problem nowadays. In urban context, road traffic is the main source of noise pollution. People directly exposed to road traffic noise suffer from moderate to severe annoyance, headache, stress, feeling of exhaustion, and reduced work performance efficiency. As the sources and severity of noise pollution continue to grow, new approaches are needed to reduce the exposure. In this research, noise abatement has been investigated using a computer simulation model (SoundPLAN essential 4.0). Noise maps were developed using SoundPLAN essential 4.0 software. Noise maps are very beneficial to identify the impact of noise pollution. Data required for mapping are noise data (LAeq), road inventory data, geometric features of mapping area, category wise traffic counts, category wise vehicle speed, meteorological data such as wind velocity, humidity, temperature, air pressure. LAeq observed on all locations of the Central zone of Surat city was greater than the prescribed central pollution control board (CPCB) limits during day time and night time. This paper is focused on using acoustic software for the simulation and calculation methods of controlling the traffic noise. According to the characteristics of traffic noise and the techniques of noise reduction, road traffic noise maps were developed using SoundPLAN essential 4.0 software to predict the scope of road traffic noise. On this basis, four reasonable noise control schemes were used to control noise, and the feasibility and application effect of these control schemes can be verified by using the method of simulation modelling. The simulation results show that LAeq is reduced by up to 5 dB(A). The excess noise can be efficiently reduced by using the corresponding noise reduction methods.
Go to article

Bibliography

1. Arana M.R.S., Nagore I., Pérez D. (2013), Main results of strategic noise maps and action plans in Navarre (Spain), Environmental Monitoring and Assessment, 185(6): 4951–4957, doi: 10.1007/s10661-012-2916-2.
2. Central Pollution Control Board (2000), Noise pollution regulation in India.
3. Cerdá S., Lacatis R., Gimenez A. (2013), On absorption and scattering coefficient effects in modellisation software, Acoustics Australia, 41(2): 151–155.
4. Golmohammadi R., Abbaspour M., Nassiri P., Mahjub H. (2007), Road traffic noise model, Journal of Research in Health Sciences, 7(1): 13–7, http://www.ncbi.nlm.nih.gov/pubmed/23343866.
5. Jhanwar D. (2016), Noise pollution: a review, Journal of Environment Pollution and Human Health, 4(3): 72– 77, doi: 10.12691/jephh-4-3-3.
6. Lavanya C., Dhankar R., Chhikara S. (2014), Noise Pollution: an Overview, International Journal of Current Research, 6(5): 6536–6543.
7. Manojkumar N., Basha K., Srimuruganandam B. (2019), Assessment, prediction and mapping of noise levels in Vellore City, India, Noise Mapping, 6(1): 38– 51, doi: 10.1515/noise-2019-0004
8. Oguntunde P.E., Okagbue H.I., Oguntunde O.A., Odetunmibi O.O. (2019), Public health in Ota Metropolis, Access Macedonian Journal of Medical Sciences, 7(8): 1391, doi: 10.3889/oamjms.2019.234
9. Paszkowski W., Sobiech M. (2019), The modeling of the acoustic condition of urban environment using noise annoyance assessment, Environmental Modeling and Assessment, 24(3): 319–330, doi: 10.1007/s10666-018-9643-1.
10. Prajapati P., Devani A.N. (2017), Review paper on noise reduction using different techniques, International Research Journal of Engineering and Technology (IRJET), 4(3): 522–524, https://irjet.net/archives/V4/i3/IRJET-V4I3145.pdf.
11. Sonaviya D.R., Tandel B.N. (2019a), 2-D noise maps for tier-2 city urban Indian roads, Noise Mapping, 6(1): 1–7, doi: 10.1515/noise-2019-0001.
12. Sonaviya D.R., Tandel B.N. (2019b), A review on GIS based approach for road traffic noise mapping, Indian Journal of Science and Technology, 12(14): 1–6, doi: 10.17485/ijst/2019/v12i14/132481.
13. Sonaviya D.R., Tandel B.N. (2020), Integrated road traffic noise mapping in urban Indian context, Noise Mapping, 7(1): 99–113, doi: 10.1515/noise-2020-0009.
14. Tandel B.N., Macwan J.E.M. (2017), Road traffic noise exposure and hearing impairment among traffic policemen in Surat, Western India, Journal of The Institution of Engineers (India): Series A, 98(1–2): 101–105, doi: 10.1007/s40030-017-0210-6.
15. Wolniewicz K., Zagubien A. (2015), Verifying traffic noise analysis calculation models, Polish Journal of Environmental Studies, 24(6): 2767–2772, doi: 10.15244/pjoes/58962.
Go to article

Authors and Affiliations

Dipeshkumar Ratilal Sonaviya
1
Bhaven N. Tandel
1

  1. Civil Engineering Department, SVNIT Surat, India
Download PDF Download RIS Download Bibtex

Abstract

The article presents the main results of research on plaster samples with different physical parameters of their structure. The basic physical parameter taken into account in the research is plaster aeration. Other physical parameters were also considered, but they play a minor part. The acoustic properties of the modified plaster were measured by the sound absorption coefficient; the results were compared with the absorption coefficient of standard plaster. The influence of other physical, mechanical and thermal properties of plaster was not analyzed. The effect of modified plasters on indoor acoustics was also determined. To this end, an acoustic problem with impedance boundary conditions was solved. The results were achieved by the Meshless Method (MLM) and compared with exact results. It was shown that the increase in plaster aeration translated into an increase in the sound absorption coefficient, followed by a slight decrease in the noise level in the room. Numerical calculations confirmed this conclusion.
Go to article

Bibliography

1. Bonfiglio P., Pompoli F. (2007), Acoustical and physical characterization of a new porous absorbing plaster, ICA, 19-th International Congress on Acoustics, Madrid, 2–7 September 2007.
2. Branski A. (2013), Numerical methods to the solution of boundary problems, classification and survey [in Polish], Rzeszow University of Technology Press, Rzeszow.
3. Branski A., Kocan-Krawczyk A., Predka E. (2017), An influence of the wall acoustic impedance on the room acoustics. The exact solution, Archives of Acoustics, 42(4): 677–687, doi: 10.1515/aoa-2017-0070.
4. Branski A., Predka E. (2018), Nonsingular meshless method in an acoustic indoor problem, Archives of Acoustics, 43(1): 75–82, doi: 10.24425/118082.
5. Branski A., Predka E., Wierzbinska M., Hordij P. (2013), Influence of the plaster physical structure on its acoustic properties, 60th Open Seminar on Acoustics, Rzeszów–Polanczyk (abstract: Archives of Acoustics, 38(3): 437–437).
6. Chen L., Zhao W., Liu C., Chen H., Marburg S. (2019), Isogeometric fast multipole boundary element method based on Burton-Miller formulation for 3D acoustic problems, Archives of Acoustics, 44(3): 475– 492, doi: 10.24425/aoa.2019.129263.
7. Chen L., Li X. (2020), An efficient meshless boundary point interpolation method for acoustic radiation and scattering, Computers & Structures, 229: 106182, doi: 10.1016/j.compstruc.2019.106182.
8. Cucharero J., Hänninen T., Lokki T. (2019), Influence of sound-absorbing material placement on room acoustical parameters, Acoustics, 1(3): 644–660; doi: 10.3390/acoustics1030038.
9. ISO 10354-2:1998 (1998), Acoustics – determination of sound absorption coefficient in impedance tube. Part 2: Transfer-function method.
10. Kulhav P., Samkov A., Petru M., Pechociakova M. (2018), Improvement of the acoustic attenuation of plaster composites by the addition of shortfibre reinforcement, Advances in Materials Science and Engineering, 2018: Article ID 7356721, 15 pages, doi: 10.1155/2018/7356721.
11. Li W., Zhang Q., Gui Q., Chai Y. (2020), A coupled FE-Meshfree triangular element for acoustic radiation problems, International Journal of Computational Methods, 18(3): 2041002, doi: 10.1142/S0219876220410029.
12. McLachlan N.W. (1955), Bessel Functions for Engineers, Clarendon Press, Oxford.
13. Meissner M. (2012), Acoustic energy density distribution and sound intensity vector field inside coupled spaces, The Journal of the Acoustical Society of America, 132(1): 228−238, doi: 10.1121/1.4726030.
14. Meissner M. (2013), Analytical and numerical study of acoustic intensity field in irregularly shaped room, Applied Acoustics, 74(5): 661–668, doi: 10.1016/j.apacoust.2012.11.009.
15. Meissner M. (2016), Improving acoustics of hardwalled rectangular room by ceiling treatment with absorbing material, Progress of Acoustics, Polish Acoustical Society, Warsaw Division, Warszawa, pp. 413–423.
16. Mondet B., Brunskog J., Jeong C.-H., Rindel J.H. (2020), From absorption to impedance: Enhancing boundary conditions in room acoustic simulations, Applied Acoustics, 157: 106884, doi: 10.1016/j.apacoust.2019.04.034.
17. Piechowicz J., Czajka I. (2012), Estimation of acoustic impedance for surfaces delimiting the volume of an enclosed space, Archives of Acoustics, 37(1): 97– 102, doi: 10.2478/v10168-012-0013-8.
18. Piechowicz J., Czajka I. (2013), Determination of acoustic impedance of walls based on acoustic field parameter values measured in the room, Acta Physica Polonica, 123(6): 1068–1071, doi: 10.12693/Aphyspola.123.1068.
19. Predka E., Branski A. (2020), Analysis of the room acoustics with impedance boundary conditions in the full range of acoustic frequencies, Archives of Acoustics, 45(1): 85–92, doi: 10.24425/aoa.2020.132484.
20. Predka E., Kocan-Krawczyk A., Branski A. (2020), Selected aspects of meshless method optimization in the room acoustics with impedance boundary conditions, Archives of Acoustics, 45(4): 647–654, doi: 10.24425/aoa.2020.135252
21. Qu W. (2019), A high accuracy method for longtime evolution of acoustic wave equation, Applied Mathematics Letters, 98: 135–141, doi: 10.1016/j.aml.2019.06.010.
22. Qu W., Fan C.-M., Gu Y., Wang F. (2019), Analysis of three-dimensional interior acoustic field by using the localized method of fundamental solutions, Applied Mathematical Modelling, 76: 122–132, doi: 10.1016/j.apm.2019.06.014.
23. Qu W., He H. (2020), A spatial–temporal GFDM with an additional condition for transient heat conduction analysis of FGMs, Applied Mathematics Letters, 110: 106579, doi: 10.1016/j.aml.2020.106579.
24. Shebl S.S., Seddeq H.S., Aglan H.A. (2011), Effect of micro-silica loading on the mechanical and acoustic properties of cement pastes, Construction and Building Materials, 25(10): 3903–3908, doi: 10.1016/j.conbuildmat.2011.04.021.
25. Stankevicius V., Skripki¯unas G., Grinys A., Miškinis K. (2007), Acoustical characteristics and physical-mechanical properties of plaster with rubber waste additives, Materials Science (Medžiagotyra), 13(4): 304–309.
26. You X., Li W., Chai Y. (2020), A truly meshfree method for solving acoustic problems using local weak form and radial basis functions, Applied Mathematics and Computation, 365: 124694, doi: 10.1016/j.amc.2019.124694.
Go to article

Authors and Affiliations

Edyta Prędka
1
Adam Brański
1
ORCID: ORCID
Małgorzata Wierzbińska
2

  1. Department of Electrical and Computer Engineering Fundamentals, Technical University of Rzeszow, Rzeszów, Poland
  2. Department of Materials Science, Technical University of Rzeszow, Rzeszów, Poland
Download PDF Download RIS Download Bibtex

Abstract

Indoor noise can greatly affect the health and comfort of users, so the significance of the right assessment of the compliance with the requirements is obvious. But noise level testing is carried out using different methods, which may not ensure consistency in assessments.
The paper presents the influence of test methods on measurement results determined based on an analysis of inter-laboratory comparative studies. The analyses presented in the paper apply to an equivalent sound pressure level determined for a permanent source of sound – an air-conditioning device. The test methods were characterised according to their precision. In order to compare them, their compatibility was analysed based on the methodology described in the literature, alongside a single-factor analysis of variance. It was determined that there were no grounds for rejecting the hypothesis about lack of statistical differences between the results obtained via different methods. Each of the methods is characterised by different precision, so consequently the same result obtained with each method carries a different risk in regards to noise assessment.
The reason for taking up this kind of research was the decision of the Polish Technical Committee in 2018 about introducing new acoustic requirements in Poland concerning the admissible indoor sound pressure levels. It was decided to implement new international methods of testing indoor sound pressure levels emanating from the service equipment in the building. It was necessary to show the differences between the current method and its new counterparts.
Go to article

Bibliography

1. Batko W.M., Stepien B. (2014), Type a standard uncertainty of long-term noise indicators, Archives of Acoustics, 39(1): 25–36, doi: 10.2478/aoa-2014-0004.
2. Berardi U. (2012), A comparison of measurement standard methods for the sound insulation of building façades, Building Acoustics, 19: 267–282, doi: 10.1260/1351-010X.19.4.267.
3. Czichos H., Saito T., Smith L. (2011), Springer Handbook of Metrology and Testing, Springer Berlin– Heidelberg, doi: 10.1007/978-3-642-16641-9.
4. Daszykowski M., Kaczmarek K., Vander Heyden Y., Walczak B. (2007), Robust statistics in data analysis – A review: basic concepts, Chemometrics and Intelligent Laboratory Systems, 85: 203–219, doi: 10.1016/J.CHEMOLAB.2006.06.016.
5. Di Bella A., Pontarollo C.M., Granzotto N., Remigi F. (2013), Interlaboratory test for field evaluation of noise from equipment in residential buildings, [in:] AIA-DAGA 2013 Merano, Merano, pp. 1880–1883.
6. EA-4/16 G:2003 (2003), EA guidelines on the expression of uncertainty in quantitative testing, EA, https://european-accreditation.org/publications/ea-4- 16-g/ (retrieved 18.01.2021).
7. Flores M., Fernández-Casal R., Naya S., Tarrío- Saavedra J., Bossano R. (2018), ILS: An R package for statistical analysis in interlaboratory studies, Chemometrics and Intelligent Laboratory Systems, 181: 11–20, doi: 10.1016/j.chemolab.2018.07.013.
8. ISO-10052 (2004), Acoustics – Field measurements of airborne and impact sound insulation and of service equipment sound – Survey method.
9. ISO-16032 (2004), Acoustics – Measurement of sound pressure level from service equipment in buildings – Engineering method.
10. ISO 13528 (2015), Statistical methods for use in proficiency testing by interlaboratory comparison.
11. ISO 5725-2 (1994), Accuracy (trueness and precision) of measurement methods and results – Part 2: Basic method for the determination of repeatability and reproducibility of a standard measurement method.
12. Jagan K., Forbes A.B. (2019), Assessing interlaboratory comparison data adjustment procedures, International Journal of Metrology and Quality Engineering, 10: 1–8, doi: 10.1051/ijmqe/2019003.
13. JCGM 100:2008 (2008), Evaluation of measurement data – Guide to the expression of uncertainty in measurement, JCGM. 14. JCGM 106:2012 (2012), Evaluation of measurement data: The role of measurement uncertainty in conformity assessment, JCGM.
15. JCGM 200:2012 (2008), International vocabulary of metrology – Basic and general concepts and associated terms (VIM), 3rd ed., JCGM.
16. Kacker R.N., Kessel R., Sommer K.D. (2010), Assessing differences between results determined according to the guide to the expression of uncertainty in measurement, Journal of Resarch of the National Institute of Standards and Technology, 115: 453–459, doi: 10.6028/jres.115.031
17. Kessel R., Kacker R.N., Sommer K.D. (2011), Combining results from multiple evaluations of the same measurand, Journal of Resarch of the National Institute of Standards and Technology, 116: 809–820, doi: 10.6028/jres.116.023
18. Molenaar J., Cofino W.P., Torfs P.J.J.F. (2018), Efficient and robust analysis of interlaboratory studies, Chemometrics and Intelligent Laboratory Systems, 175: 65–73, doi: 10.1016/j.chemolab.2018.01.003
19. NIST/SEMATECH (2013), e-Handbook of Statistical Methods, Ch. 1.3.5.10, http://www.itl.nist.gov/div898/handbook/ (retrieved 12.08.2020).
20. PN-B-02151-02 (1987), Building acoustics – Noise protection of apartments in buildings – Permissible values of sound level in apartments [in Polish: Akustyka budowlana – Ochrona przed hałasem pomieszczen w budynkach – Dopuszczalne wartosci poziomu dzwieku w pomieszczeniach].
21. PN-B-02156 (1987), Building acoustics – Methods for measurement of sound power of A-level in buildings [in Polish: Akustyka budowlana – Metody pomiaru poziomu dzwieku A w budynkach].
22. Pozzer T., Wunderlich P., Monteneiro C., de Frias J. (2019), Interlaboratory and proficiency tests for field measurements in Brazil, [in:] INTER-NOISE and NOISE-CON Congress and Conference Proceedings, Vol. 259, No. 1, pp. 8120–8130, Institute of Noise Control Engineering, http://www.sea-acustica.es/filead min/INTERNOISE_2019/Fchrs/Proceedings/2200.pdf.
23. Prezelj J., Murovec J. (2017), Traffic noise modelling and measurement: Inter-laboratory comparison, Applied Acoustics, 127: 160–168, doi: 10.1016/j.apacoust.2017.06.010.
24. Przysucha B., Batko W., Szelag A. (2015), Analysis of the accuracy of uncertainty noise measurement, Archives of Acoustics, 40(2): 183–189, doi: 10.1515/aoa-2015-0020.
25. Przysucha B., Szelag A., Pawlik P. (2020), Probability distributions of one-day noise indicators in the process of the type A uncertainty evaluation of longterm noise indicators, Applied Acoustics, 161: 107158, doi: 10.1016/j.apacoust.2019.107158.
26. Scamoni F. et al. (2009), Repeatability and reproducibility of field measurements in buildings, [in:] Proceedings of 8th European Conference on Noise Control 2009, EuroNoise09, Edinburgh, Scotland, UK, 26–28 October, 2009.
27. Scrosati C. et al. (2015), Uncertainty of faqade sound insulation measurements obtained by a round robin test: The influence of the low frequencies extension, [in:] Proceedings of the 22nd International Congress on Sound and Vibration (ICSV22), Florence, Italy, pp. 12– 16.
28. Scrosati C. et al. (2020), Towards more reliable measurements of sound absorption coefficient in reverberation rooms: An Inter-Laboratory Test, Applied Acoustics, 165: 107298, doi: 10.1016/j.apacoust.2020.107298
29. Seddeq H.S., Medhat A.A. (2011), Indoor noise measurements evaluations for HVAC-Unit using interlaboratory comparisons, International Journal of Metrology and Quality Engineering, 2(2): 75–81, doi: 10.1051/ijmqe/2011104
30. Szewczak E., Bondarzewski A. (2016), Is the assessment of interlaboratory comparison results for a small number of tests and limited number of participants reliable and rational?, Accreditation and Quality Assurance, 21(2): 91–100, doi: 10.1007/s00769-016-1195-y.
31. Trzpiot G. (2015), Some remarks of type III error for directional two-tailed test, Studia Ekonomiczne. Zeszyty Naukowe Uniwersytetu Ekonomicznego w Katowicach, 219: 5–16.
32. Walker W.E. et al. (2003), Defining uncertainty: a conceptual basis for uncertainty management in model-based decision support, Integrated Assessment, 4(3): 5–17, doi: 10.1076/iaij.4.1.5.16466
33. Wszolek T. (2006), Effect of traffic noise statistical distribution on LAeq;T measurement uncertainty, Archives of Acoustics, 31(3): 311–318.
Go to article

Authors and Affiliations

Elżbieta Nowicka
1
Ewa Szewczak
1

  1. Building Research Institute, Warsaw, Poland
Download PDF Download RIS Download Bibtex

Abstract

Using perforated tube in exhaust mufflers is known to improve transmission loss (TL) by improving their sound pressure level (SPL) at the orifice. The perforated tube should affect the muffler performance analogous to a shell-and-tube heat exchanger. To the authors’ knowledge, there are few previous assessments reported in literature of the effects that the perforated tube configuration has on acoustic response and pressure drop predicted. The effects of (i) the perforated tube length, (ii) the diameter of tube holes, and (iii) flow through perforated tube were investigated. To assess the perforated tube effect on flow, the SOLIDWORKS 2017 based on Computational Fluid Dynamics (CFD) tool was utilized using real walls approach model with a surface roughness of 0.5 micrometres (AISI 316 cold rolled stainless steel sheet (ss) Ra = 0:5 μm). Perforated tube was found to cause back pressure which may increase SPL about 10%.
Go to article

Bibliography

1. Cui F., Wang Y., Cai R.C. (2014), Improving muffler performance using simulation-based design, [in:] INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 249(7): 1190–1194.
2. Demir A., Çinar Ö.Y. (2009), Propagation of sound in an infinite two-part duct carrying mean flow inserted axially into a larger infinite duct with wall impedance discontinuity, ZAMM – Journal of Applied Mathematics and Mechanics, 89(6): 454–465, doi: 10.1002/zamm.200800145.
3. Elsayed A., Bastien C., Jones S., Christensen J., Medina H., Kassem H. (2017), Investigation of baffle configuration effect on the performance of exhaust mufflers, Case Studies in Thermal Engineering, 10: 86–94, doi: 10.1016/j.csite.2017.03.006.
4. Ferziger J.H., Peric M. (2002), Computational Methods for Fluid Dynamics, 3rd ed., Springer, doi: 10.1007/978-3-642-56026-2.
5. Lee I., Selamet A. (2006), Impact of perforation impedance on the transmission loss of reactive and dissipative silencers, The Journal of the Acoustical Society of America, 120(6): 3706–3713, doi: 10.1121/1.2359703.
6. Mohamad B. (2019), Design and optimization of vehicle muffler using the Ffowcs Williams and Hawkings model, Machine Design, 11(3): 101–106, doi: 10.24867/MD.11.2019.3.101-106.
7. Mohamad B., Karoly J., Zelentsov A., Amroune S. (2020), A hybrid method technique for design and optimization of Formula race car exhaust muffler, International Review of Applied Sciences and Engineering, 11(2): 174–180, doi: 10.1556/1848.2020.20048.
8. Siano D. (2010), Three-dimensional/one-dimensional numerical correlation study of a three-pass perforated tube, Simulation Modelling Practice and Theory, 19(4): 1143–1153, doi: 10.1016/j.simpat.2010.04.005.
9. Sim H.J., Park S.G., Joe Y.G., Oh J.E. (2008), Design of the intake system for reducing the noise in the automobile using support vector regression, Journal of Mechanical Science and Technology, 22(6): 1121–1131, doi: 10.1007/s12206-008-0306-z.
10. Tiryakioglu B. (2020), Radiation of sound waves by a semi-infinite duct with outer lining and perforated end, Archives of Acoustics, 45(1): 77–84, doi: 10.24425/aoa.2020.132483.
Go to article

Authors and Affiliations

Barhm Mohamad
1
Jalics Karoly
1
Andrei Zelentsov
2
Salah Amroune
3

  1. Faculty of Mechanical Engineering and Informatics, University of Miskolc, Miskolc, Hungary
  2. Piston Engine Department, Bauman Moscow State Technical University, Moscow, Russia
  3. Université Mohamed Boudiaf, M’sila, Algérie

Instructions for authors

Author Guidelines
• Manuscripts intended for publication in Archives of Acoustics should be submitted in pdf format by an on-line procedure.
• Manuscript should be original, and should not be submitted either previously or simultaneously elsewhere, neither in whole, nor in part.
• Submitted papers must be written in good English and proofread by a native speaker.
• Basically, the papers should not exceed 40 000 typographic signs.
• Postal addresses, affiliations and email addresses for each author are required.
• Detailed information see Article Requirements.
• Manuscript should be accompanied by a cover letter containing the information:
o why the paper is submitted to ARCHIVES OF ACOUSTICS,
o suggestion on the field of acoustics related to the topic of the submitted paper,
o the statement that the manuscript is original, the submission has not been previously published, nor was sent to another journal for consideration,
o 3–5 names of suggested reviewers together with their affiliations, full postal and e-mail addresses; at least 3 suggested reviewers should be affiliated with other scientific institutions than the affiliations of the authors,
o author’s suggestion to classification of the paper as the research paper, review paper or technical note.

Article Requirements
1. At submission time only a PDF file is required. After acceptance, authors must submit all source material (see information about Figures). Authors can use their preferred manuscript-preparation software. The journal itself is produced in LaTeX, so accepted articles will be converted to LaTeX at production time.
2. The title of the paper should be as short as possible.
3. Full names and surnames should be given.
4. The full postal address of each affiliation, including the country name should be provided. Affiliations should contain the full postal address, as well as an e-mail address of one author designated as corresponding author.
5. The text should be preceded by a concise abstract (less than 200 words).
6. Keywords should be given.
7. The formulae to be numbered are those referred to in the paper, as well as the final formulae.
8. All notations should be written very distinctly.
9. References in the text (author(s) and year of publication) are to be cited between parentheses.
Items appearing in the reference list should be complete, including surname and the initials of the first name of the author, the full title of the paper/book in English followed by the information on the original paper language. In case of a book, the publisher's name, the place and year of publication should be given. In case of a periodical, the full title of the periodical, consecutive volume number, current issue number, pages, and year of publication should be given. All references in the bibliography should be cited in the text, and arranged in alphabetical order by authors' last name.
For more information on references see http://acoustics.ippt.gov.pl/public/Instructions.pdf.
10. Figures must be of publication quality. Each figure should be saved in separate file and captioned and numbered so that it can float. After acceptance, Authors will need to submit the original source files for all photos, diagrams and graphs in manuscript.
For diagrams and graphs vector EPS or vector PDF files are the most useful. Make sure that what you're saving is vector graphics and not a bitmap. Please also include the original data for any plots. This is particularly important if you are unable to save Excel-generated plots in vector format. Saving them as bitmaps is not useful; please send the Excel (.xls) spreadsheets instead.
Photographs should be high-quality – with resolution no lower than 300 dpi.
Pack all figure files into a single archive (zip, tar, rar or other format) and then upload on the magazine web site.

This page uses 'cookies'. Learn more