USING DISCRETE WAVELET ANALYSIS OF VIBRATION SIGNAL FOR DETECTION OF ELECTRICAL MACHINES’ DEFECTS

Authors

  • VALERII HRANIAK Vinnytsia National Agrarian University, Vinnytsia, Ukraine Author

DOI:

https://doi.org/10.59277/RRST-EE.2023.4.6

Keywords:

Technical condition, Diagnostics, Electric machine, Defect, Wavelet transform

Abstract

The paper proposes a method for establishing the presence of several of the most common defects of rotating electric machines of alternating current using discrete wavelet transform of their vibration signal. It is shown that discrete wavelet transform is one of the most effective methods of pre-processing vibration signals formed from the operation of rotating electric machines. The choice of optimal maternal wavelet functions for each of the considered defects according to the sensitivity parameter is theoretically substantiated, and frequency bands are determined, which should be analyzed for their detection analysis of wavelet transform coefficients. The adequacy of the theoretical conclusions is experimentally confirmed.

References

Y. Yang, M. M. Haque, D. Bai, W. Tang, Fault Diagnosis of Electric Motors Using Deep Learning, Algorithms and Its Application. Energies, vol. 14, pp. 1-26 (2021). DOI:10.3390/en14217017

O. V. Gubarevich Reliability and diagnostics of electrical equipment, SNU after V. Dalia, Severodonetsk, 248 p. (2016).

V. F. Hraniak, V. V. Kukharchuk, V. V. Bogachuk, Y. G. Vedmitskyi at all, Phase noncontact method and procedure for measurement of axial displacement of electric machine's rotor, Proc. SPIE 10808, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments, 7 p. (2018). DOI:10.1117/12.2501611

F. Duan Diagnostic of Rotor and Stator Problems in Industrial Induction Motors, Adelaide University, Adelaide, 139 p. (2010).

V. F. Hraniak, V. V. Kukharchuk, V. V. Bilichenko, V. V. Bogachuk at all, Correlation method for calculation of weight coefficients of artificial neural-like networking hydraulic units' diagnostic systems, Proc. SPIE 1117663, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments, 7 p. (2019). DOI:10.1117/12.2537215

V. F. Hraniak, V. V. Kukharchuk, V. Y. Kucheruk, A. K. Khassenov, Using instantaneous cross-correlation coefficients of vibration signals for technical condition monitoring in rotating electric power machine, Bulletin of the Karaganda University. «Physics» series, vol. 1, pp. 72-80 (2018).

A. R. Shirman, A. B. Soloviev, Practical vibration diagnostics and monitoring of the state of mechanical equipment, Mechanical Engineering, Moscow, 276 p. (1996).

M. Weeks, M. Bayoumi, Discrete wavelet transform: architectures, design and performance issues, Journal of VLSI signal processing systems for signal, image and video technology, vol 35, pp. 155-178 (2003). DOI:10.1023/A:1023648531542

V. I. Vorob'ev, V. G. Gribunin, Theory and practice of wavelet transform, VSU, St. Petersburg, 204 p. (1999).

ITG Energomash. Determination of malfunction of an induction motor, http://energo.ucoz.ua/publ/5-1-0-10 [accessed: February 19, 2023].

Y. V. Kiselev, D. Y. Kiselev, S. N. Titz, Vibration diagnostics of systems and structures of aviation technology, SSAU Publishing House, Samara, 207 p. (2012).

S. A. Broughton, K. Bryan, Discrete fourier analysis and wavelets: applications to signal and image processing, John Wiley & Sons, Inc., New Jersey, 355 p. (2008).

R. Polikar, The Wavelet tutorial, Rowan University, College of Engineering Web Servers, Roma, 79 p. (2001).

V. F. Hraniak, S. Sh. Katsiv, V. V. Kukharchuk, The use of discrete wavelet analysis of vibro-acoustic signal to detect the imbalance of the rotor of rotating electric machines, Scientific works of DonNTU. Series «Computer Science, Cybernetics and Computer Science», vol. 1 (32), pp. 32-40 (2021).

P. S. Addison, The Illustrated Wavelet Transform Handbook. Introductory Theory and Applications in Science, Engineering, Medicine and Finance, Napier University, Edinburgh, 359 p. (2002).

J. Patrick, Discrete Wavelet Transformations: An Elementary Approach with Applications, 2nd Edition, Wiley, New York, 624 p. (2019).

I. Daubechies, Ten lectures on wavelets, Research Center «Regular and Chaotic Dynamics», Izhevsk, 464 p. (2001).

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Published

23.12.2023

Issue

Section

Électrotechnique et électroénergétique | Electrical and Power Engineering

How to Cite

USING DISCRETE WAVELET ANALYSIS OF VIBRATION SIGNAL FOR DETECTION OF ELECTRICAL MACHINES’ DEFECTS. (2023). REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE, 68(4), 357-362. https://doi.org/10.59277/RRST-EE.2023.4.6