Bearing damage detection via wavelet packet decomposition of the stator current

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.

[1]  Victor Wowk,et al.  Machinery Vibration: Measurement and Analysis , 1991 .

[2]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[3]  Martin Vetterli,et al.  Wavelets and filter banks: theory and design , 1992, IEEE Trans. Signal Process..

[4]  T.G. Habetler,et al.  Motor bearing damage detection using stator current monitoring , 1994, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting.

[5]  M. Victor Wickerhauser,et al.  Adapted wavelet analysis from theory to software , 1994 .

[6]  Rashid Ansari IIR Filter Banks and Wavelets , 1996 .

[7]  S. Santoso,et al.  Power quality assessment via wavelet transform analysis , 1996 .

[8]  Michael J. Devaney,et al.  Power measurement using the wavelet transform , 1998, IEEE Trans. Instrum. Meas..

[9]  Alireza Sadeghian,et al.  Signature analysis of induction motor mechanical faults by wavelet packet decomposition , 2001, APEC 2001. Sixteenth Annual IEEE Applied Power Electronics Conference and Exposition (Cat. No.01CH37181).

[10]  Alireza Sadeghian,et al.  Current signature analysis of induction motor mechanical faults by wavelet packet decomposition , 2003, IEEE Trans. Ind. Electron..