Bearing fault feature extraction method: improved weighted envelope spectrum

Abstract

Abstract Many existing cyclic spectrum analysis methods are ineffective in solving bearing fault diagnosis in multi-information frequency bands. Based on this, an improved weighted envelope spectrum (IWES) method is proposed. Firstly, IWES uses the fault information intensity index to quantify bearing fault information and evaluate bearing fault information of spectral frequency bands in spectral coherence. Secondly, the threshold function is constructed to determine the threshold adaptively, so as to identify the spectrum frequency components with rich fault information in the spectral coherence. Meanwhile, a weight function is designed based on threshold function to eliminate the interference noise components and keep the fault information. Finally, the spectral coherence and weight function are used to generate IWES with multi-band information. The bearing experiments show that the IWES has excellent noise robustness and can accurately extract the bearing fault characteristic frequency.