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Neural network based motor bearing fault detection

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3 Author(s)
Eren, L. ; Dept. of Electr. & Electron. Eng., Univ. of Bahcesehir, Turkey ; Karahoca, A. ; Devaney, M.J.

Bearing faults are the biggest single cause of motor failures. The bearing defects induce vibration resulting in the modulation of the stator current. The stator current can be analyzed via wavelet packet decomposition to detect bearing defects. This method enables the analysis of frequency bands that can accommodate the rotational speed dependence of the bearing defect frequencies. In this study, radial basis function neural networks are used to improve bearing fault detection procedure.

Published in:

Instrumentation and Measurement Technology Conference, 2004. IMTC 04. Proceedings of the 21st IEEE  (Volume:3 )

Date of Conference:

18-20 May 2004