IDENTIFICATION OF A BACKLASH ZONE IN AN ELECTROMECHANICAL SYSTEM CONTAINING CHANGES OF A MASS INERTIA MOMENT BASED ON A WAVELET–NEURAL METHOD

Marcin TOMCZYK

tomczykmarcin@poczta.fm
Electrical School No. 1 in Krakow them. Silesian Insurgents, Kamieńskiego 49 Street, 30-644 Kraków (Poland)

Barbara BOROWIK


Cracow Univeristy of Technology, Faculty of Physics, Mathematics and Computer Science, Institute of Computer Science, Warszawska 24 Street, 31-155 Kraków, P (Poland)

Mariusz MIKULSKI


State University of Applied Sciences in Nowy Sącz, Institute of Technology, Zamenhofa 1a Street, 33-300 Nowy Sącz, (Poland)

Abstract

In this article a new method of identification of a backlash zone width in a structure of an electromechanical system has been presented. The results of many simulations in a tested model of a complex electromechanical system have been taken while changing a value of a reduced masses inertia moment on a shaft of an induction motor drive. A wavelet analysis of tested signals and analysis of weights that have been obtained during a neural network supervised learning - have been applied in a diagnostic algorithm. The proposed algorithm of detection of backlash zone width, represents effective diagnostic method of a system at changing dynamic conditions, occurring also as a result of mass inertia moment changes.


Keywords:

inertia moment, induction motor, wavelet transformation, backlash zone, neural network weights

Annamalai, B., & Swaminathan, S. T. (2016). Diagnostics of faults in induction motor via wavelet packet transform. IOSR Journal of VLSI and Signal Processing (IOSR-JVSP), 01–06.
  Google Scholar

Chandralekha, R., & Yayanthi, D. (2016). Diagnosis of faults in three phase induction motor using Neuro Fuzzy Logic. Journal of Applied Engineering Research, 11(8), 5735–5740.
  Google Scholar

Da Costa, C., Kashiwagi, M., & Mathias, M. H. (2015). Rotor failure detection of induction motors by wavelet and Fourier transform in non-stationary condition. Case Studies in Mechanical Systems and Signal Processing, 1, 15–26. https://doi.org/10.1016/j.csmssp.2015.05.001
DOI: https://doi.org/10.1016/j.csmssp.2015.05.001   Google Scholar

Douglas, H., Pillay, P., & Ziarani, A. (2003). Detection of broken rotor bars in induction motors using wavelet analysis. In IEEE International Electric Machines and Drives Conference, 2003. IEMDC'03 (pp. 923–928). Madison, USA: IEEE. https://doi.org/10.1109/IEMDC.2003.1210345
DOI: https://doi.org/10.1109/IEMDC.2003.1210345   Google Scholar

Kowalski, Cz. (2005). Monitorowanie i diagnostyka uszkodzeń silników indukcyjnych z wykorzystaniem sieci neuronowych. Prace Naukowe Instytutu Maszyn, Napędów i Pomiarów Elektrycznych Politechniki Wrocławskiej, 57(18), 226.
  Google Scholar

Orlowska-Kowalska, T., & Szabat, K. (2007). Neural-Network Application for Mechanical Variables Estimation of a Two-Mass Drive System. IEEE Transactions on Industrial Electronics, 54(3), 1352–1364. doi:10.1109/TIE.2007.892637
DOI: https://doi.org/10.1109/TIE.2007.892637   Google Scholar

Osowski, S. (1996). Sieci neuronowe – w ujęciu algorytmicznym. Warszawa: WNT.
  Google Scholar

Sridhar, S., Uma Rao, K., & Jade, S. (2016). Detection and classification of power quality disturbances in the supply to induction motor using wavelet transform and neural networks. Balkan Journal of Electrical & Computer Engineering, 4(1), 37–44. https://doi.org/10.17694/bajece.62699
DOI: https://doi.org/10.17694/bajece.62699   Google Scholar

Zając, M. (2009). Metody falkowe w monitoringu i diagnostyce układów elektromechanicznych. Kraków: Wydawnictwo Politechniki Krakowskiej im. Tadeusza Kościuszki.
  Google Scholar

Download


Published
2018-12-30

Cited by

TOMCZYK, M., BOROWIK, B., & MIKULSKI, M. (2018). IDENTIFICATION OF A BACKLASH ZONE IN AN ELECTROMECHANICAL SYSTEM CONTAINING CHANGES OF A MASS INERTIA MOMENT BASED ON A WAVELET–NEURAL METHOD. Applied Computer Science, 14(4), 54–69. https://doi.org/10.23743/acs-2018-29

Authors

Marcin TOMCZYK 
tomczykmarcin@poczta.fm
Electrical School No. 1 in Krakow them. Silesian Insurgents, Kamieńskiego 49 Street, 30-644 Kraków Poland

Authors

Barbara BOROWIK 

Cracow Univeristy of Technology, Faculty of Physics, Mathematics and Computer Science, Institute of Computer Science, Warszawska 24 Street, 31-155 Kraków, P Poland

Authors

Mariusz MIKULSKI 

State University of Applied Sciences in Nowy Sącz, Institute of Technology, Zamenhofa 1a Street, 33-300 Nowy Sącz, Poland

Statistics

Abstract views: 112
PDF downloads: 16


License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.


Similar Articles

1 2 3 4 5 6 7 > >> 

You may also start an advanced similarity search for this article.