Title :
Bearing Fault Detection via Wavelet Packet Decomposition with Spectral Post Processing
Author :
Eren, Levent ; Teotrakool, Kaptan ; Devaney, Michael J.
Author_Institution :
Bahcesehir Univ. Besiktas, Bahcesehir
Abstract :
We present a method for detecting motor bearing fault conditions via wavelet packet decomposition (WPD) of induction motor current. This method involves the decomposition of motor current into equally spaced frequency bands by using all-pass implementation of Elliptic IIR half-band filters in the filter bank structure to obtain wavelet packet coefficients (WPC). Then, the bias in WPCs for each frequency band is removed to suppress leakage from adjacent frequency bands. Fourier analysis is applied to wavelet packet coefficients to provide higher frequency resolution within each frequency band. The changes in the energy levels of frequency bands in which motor fault related current frequencies lie are monitored to detect motor fault conditions.
Keywords :
Fourier analysis; IIR filters; all-pass filters; elliptic filters; fault diagnosis; induction motors; machine bearings; spectral analysis; wavelet transforms; Fourier analysis; WPD; all-pass implementation; bearing fault detection; elliptic IIR half-band filters; induction motor current; motor current decomposition; motor fault; spaced frequency bands; spectral post processing; wavelet packet decomposition; Condition monitoring; Energy resolution; Energy states; Fault detection; Filter bank; Frequency; IIR filters; Induction motors; Wavelet analysis; Wavelet packets; Bearing Faults; Motor Current Signature Analysis; Wavelet Packet Decomposition;
Conference_Titel :
Instrumentation and Measurement Technology Conference Proceedings, 2007. IMTC 2007. IEEE
Conference_Location :
Warsaw
Print_ISBN :
1-4244-0588-2
DOI :
10.1109/IMTC.2007.379444