Synchronous odd symmetric transform for rolling bearing fault diagnosis

Abstract

Time-frequency analysis (TFA) is an important tool to process non-stationary signals and detect bearing faults. For considering energy concentration, computational efficiency, and computational accuracy, a novel TFA technique, termed synchronous odd symmetric transform (SOST) is proposed in this paper. In the SOST, the odd symmetry extraction operator (OSEO) is defined according to the odd symmetric window based short-time Fourier transform (OSTFT). The main idea of OSEO is to obtain accurate instantaneous frequency (IF) ridges in a satisfactory computation time. Meanwhile, the STFT result is retained at the IF ridges, and the time–frequency representation (TFR) with high energy concentration is calculated. The performance of the developed technique is verified by a multi-component signal with strong frequency-modulated and amplitude-modulated (FM-AM) laws. Experimental analysis results show that the proposed SOST can display bearing fault-related time–frequency trajectories with high time–frequency resolution.