التفاصيل البيبلوغرافية
| العنوان: |
Fault diagnosis of electrical faults of three-phase induction motors using acoustic analysis. |
| المؤلفون: |
GLOWACZ, Adam1 adglow@agh.edu.pl, SULOWICZ, Maciej1, KOZIK, Jaroslaw2, PIECH, Krzysztof2, GLOWACZ, Witold3, LI, Zhixiong4,5, BRUMERCIK, Frantisek6, GUTTEN, Miroslav7, KORENCIAK, Daniel7, KUMAR, Anil8, LUCAS, Guilherme Beraldi9, IRFAN, Muhammad10, CAESARENDRA, Wahyu4,11, LIU, Hui12 |
| المصدر: |
Bulletin of the Polish Academy of Sciences: Technical Sciences. 2024, Vol. 72 Issue 1, p1-7. 7p. |
| مصطلحات موضوعية: |
*INDUCTION motors, *FAULT diagnosis, *INDUCTION machinery, *ARTIFICIAL neural networks, *ELECTRIC faults, *FAST Fourier transforms, *ELECTRIC motors |
| مستخلص: |
Fault diagnosis techniques of electrical motors can prevent unplanned downtime and loss of money, production, and health. Various parts of the induction motor can be diagnosed: rotor, stator, rolling bearings, fan, insulation damage, and shaft. Acoustic analysis is non-invasive. Acoustic sensors are low-cost. Changes in the acoustic signal are often observed for faults in induction motors. In this paper, the authors present a fault diagnosis technique for three-phase induction motors (TPIM) using acoustic analysis. The authors analyzed acoustic signals for three conditions of the TPIM: healthy TPIM, TPIM with two broken bars, and TPIM with a faulty ring of the squirrel cage. Acoustic analysis was performed using fast Fourier transform (FFT), a new feature extraction method called MoD-7 (maxima of differences between the conditions), and deep neural networks: GoogLeNet, and ResNet-50. The results of the analysis of acoustic signals were equal to 100% for the three analyzed conditions. The proposed technique is excellent for acoustic signals. The described technique can be used for electric motor fault diagnosis applications. [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
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