Enhanced feature detection in bearing health diagnosis using wavelet packet transform with spectral post processing

Abstract

A hybrid method for detecting motor bearing fault conditions via discrete wavelet packet decomposition (DWPD) of induction motor current with spectral post processing is presented in this paper. This method involves the decomposition of motor current into equally spaced frequency bands by using an all-pass implementation of elliptic IIR half-band filters in the filter bank structure to obtain wavelet packet coefficients (WPC) in a computationally efficient way. Then, the bias in WPCs for each frequency band is removed to suppress both power system harmonics and leakage from adjacent frequency bands. Finally, Fourier analysis is applied to WPCs to provide higher frequency resolution within each frequency band. The hybrid approach provides better results in early detection of bearing faults. © 2009 Praise Worthy Prize S.r.l. - All rights reserved. © 2022 Elsevier B.V., All rights reserved.