A new motor fault detection method using multiple window S-method time-frequency analysis

Abstract

Fault signals of motors is non-stationary typically. Conventional Fourier transform method can't meet the demand of fault signals extraction. Time-frequency analysis (TFA) based motor fault diagnosis methods, which can identify rotor faults by detecting time-varying frequency components of stator current signals, have been very important signal processing techniques. This paper proposes a new motor fault detection method based on multiple window S-method TFA. Slepian sequences are applied as window functions. Compared with common short-time Fourier transform (STFT) and Wigner-Ville distribution (WVD), multiple window S-method TFA provides better time-frequency concentration and cross-term suppression performances, thus improving accuracy rate of motor rotor fault detection. Taking rotor dynamic eccentricity fault as an example, the validity of method is demonstrated.