Details

Title

Comparison of Intelligent Control Methods for the Ore Jigging Process

Journal title

International Journal of Electronics and Telecommunications

Yearbook

2021

Volume

vol. 67

Issue

No 3

Affiliation

Kulakova, Yelena : Satbaev University, Almaty, Kazakhstan ; Wójcik, Waldemar : Lublin University of Technology, Lublin, Poland ; Suleimenov, Batyrbek : Satbaev University, Almaty, Kazakhstan ; Smolarz, Andrzej : Lublin University of Technology, Lublin, Poland

Authors

Keywords

neural network ; Ore jiggling ; control algorithm ; fuzzy logic

Divisions of PAS

Nauki Techniczne

Coverage

363-368

Publisher

Polish Academy of Sciences Committee of Electronics and Telecommunications

Bibliography

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[2] W.M. Ambrósa, C.H. Sampaioa, Bogdan G. Cazacliub, Paulo N.Conceiçãoa and Glaydson S.dos Reisab, “Some observations on the influence of particle size and size distribution on stratification in pneumatic jigs”, Powder Technology, Vol. 342, pp. 594-606, 2019. https://doi.org/10.1016/j.powtec.2018.10.029.
[3] M.V. Verkhoturov, “Gravitational enrichment methods”. Moscow: MAX Press, 2006, pp.160- 180. ISBN 5-317-01710-6.
[4] Ya-li Kuang, Jin-Wu Zhuo, Li Wang, Chao Yang, “Laws of motion of particles in a jigging process”, Journal of China University of Mining and Technology, Vol. 18, no 4, pp. 575-579, December 2008. https://doi.org/10.1016/S1006-1266(08)60297-7.
[5] S.Cierpisz. “A dynamic model of coal products discharge in a jig”, Minerals Engineering, Vol. 105, pp. 1-6, 1 May 2017. https://doi.org/10.1016/j.mineng.2016.12.010.
[6] B.A. Suleimenov and Ye.A. Kulakova, “The prospects for the use of intelligent systems in the processes of gravitational enrichment”, Informatyka, Automatyka, Pomiary w Gospodarcei Ochronie Środowiska, Vol. 9, no 2, pp. 46-49, 2019. https://doi.org/10.5604/01.3001.0013.2547.
[7] Y.R. Murthy, S.K. Tripathy, C.R. Kumar, “Chrome ore beneficiation challenges & opportunities – A review”, Minerals Engineering, Vol. 24, no 5, pp. 375-380, 2011, DOI: https://doi.org/10.1016/j.mineng.2010.12.001.
[8] L. Panda, S.K. Tripathy, “Performance prediction of gravity concentrator by using artificial neural network – A case study”. International Journal of Mining Science and Technology, Vol. 24, no 4, pp. 461-465, 2014. https://doi.org/10.1016/j.ijmst.2014.05.007.
[9] Y.R. Murthy, S.K. Tripathy, C.R. Kumar, “Chrome ore beneficiation challenges & opportunities-a review”, Minerals Engineering, Vol. 36, no 5, pp. 375-380, 2014, https://doi.org/10.1016/j.ijmst.2014.05.007.
[10] T. J. Stich, and J.K. Spoerre and T.Velasco, “The application of artificial neutral networks to monitoring and control of an induction hardening process”, Journal of Industrial Technology, Vol. 16, no 1, pp.168-174, 2015.
[11] L.Panda, A.K. Sahoo, S.K Tripathy and others, “Application of artificial neural network to study the performance of jig for beneficiation of noncoking coal”, Fuel, Vol. 97, pp. 151-156, 2012. https://doi.org/10.1016/j.fuel.2012.02.018.
[12] K. Shravan and R. Venugopal, “Performance analyses of jig for coal cleaning using 3D response surface methodology”, International Journal of Mining Science and Technology, Vol. 27, no 2, pp 333-337, March 2017.
[13] B.A. Suleimenov and E.A. Kulakova, “Development of intelligent system for optimal process control”, Resource–saving technologies of raw–material base development in mineral mining and processing: Multy–authored monograph, Universitas Publishing, Romania, Petrosani: 2020, pp.198-217. URI: ep3.nuwm.edu.ua/id/eprint/18359.
[14] V. Mashkov, A. Smolarz, V. Lytvynenko, and K. Gromaszek, “The problem of system fault-tolerance”, Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, vol. 4, no. 4, pp. 41-44, 2014, https://doi.org/10.5604/20830157.1130182
[15] M. S. Islam, P. Nepal and others. “A knowledge-based expert system to assess power plant project cost overrun risks”, Expert Systems With Applications, Vol. 136, pp. 12-32, 2019. https://doi.org/10.1016/j.eswa.2019.06.030.
[16] B.A.Suleimenov and E.A Kulakova, “Creation the knowledge base of the intelligent control system for gravitational enrichment processes using expert information processing methods”, Vestnik KazNRTU, Vol. 5, no 141, pp. 590-597, October 2020.
[17] Ye.A. Kulakova and B.A. Suleimenov, “Development and Research of Intelligent Algorithms for Controlling the Process of Ore Jigging”, International Journal of Emerging Trends in Engineering Research, Vol. 8, no 9, pp. 6240-6246, September 2020. https://doi.org/10.30534/ijeter/2020/21589202.
[18] N. Siddique. “Intelligent Control”, Springer International Publishing, Switzerland, 2014, pp.54-78. https://doi.org/10.1007/978-3-319-02135-5.
[19] P.V. de Campos Souza, “Fuzzy neural networks and neuro-fuzzy networks: A review the main techniques and applications used in the literature” Applied Soft Computing. Vol. 92, pp. 106275, July 2020. https://doi.org/10.1016/j.asoc.2020.106275.
[20] A.Tripathy, L.Panda, A.K Sahoo, S.K. Biswal, R.K Dwari, A.K. Sahu, “Statistical optimization study of jigging process on beneficiation of fine size high ash Indian non-coking coal”, Advanced Powder Technology, Vol. 27, no 4, pp. 1219-1224, 2016. https://doi.org/10.1016/j.apt.2016.04.006.
[21] A.K. Mukherjeea and B.K. Mishrab, “An integral assessment of the role of critical process parameters on jigging”, International Journal of Mineral Processing Vol. 81, no 3, pp. 187-200, December 2006. https://doi.org/10.1016/j.minpro.2006.08.005.
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Date

2021.09.23

Type

Article

Identifier

DOI: 10.24425/ijet.2021.137821
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