Title :
Bearing damage detection via wavelet packet decomposition of the stator current
Author :
Eren, Levent ; Devaney, Michael J.
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Bahcesehir, Istanbul, Turkey
fDate :
4/1/2004 12:00:00 AM
Abstract :
Bearing faults are one of the major causes of motor failures. The bearing defects induce vibration, resulting in the modulation of the stator current. In this paper, the stator current is analyzed via wavelet packet decomposition to detect bearing defects. The proposed method enables the analysis of frequency bands that can accommodate the rotational speed dependence of the bearing defect frequencies. The wavelet packet decomposition also provides a better treatment of nonstationary stator current than currently used Fourier techniques.
Keywords :
cepstral analysis; computerised monitoring; fault location; induction motor drives; machine bearings; machine testing; stators; wavelet transforms; MCSA; bearing damage detection; bearing defect detection; bearing defect frequencies; bearing defects; bearing fault detection; bearing faults; condition monitoring; frequency band analysis; induction motors; motor current signature analysis; motor failures; nonstationary stator current; rotational speed dependence; stator current modulation; vibration; wavelet packet decomposition; Discrete wavelet transforms; Fault detection; Frequency; Geometry; Induction motors; Signal analysis; Stators; Steady-state; Wavelet analysis; Wavelet packets;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2004.823323