Abstract：When performing rolling bearing fault diagnosis under time-varying rotating speed condition, the determination of phase function in the generalized demodulation algorithm depends upon tachometer and other auxiliary equipment. Aiming at this problem, a rolling element bearing fault diagnosis method based on the chirplet path pursuit (CPP) and stepwise demodulation filtering was proposed. The instantaneous fault characteristic frequency (IFCF) in envelope signals has the amplitude advantage. Adopting this feature, CPP algorithm was used to extract the trend curve of IFCF from down-sampled envelope signals and construct IFCF’s phase function. Aiming at the problem of bearing instantaneous rotating frequency (IRF) being difficult to extract in signals, the method of repeated estimation of IRF was used to calculate phase functions of potential IRFs. According to phase functions of IFCF and IRF, the stepwise demodulation filtering algorithm was constructed to recover the periodicity of time-varying frequency, reduce noise interference and avoid IRFs with smaller amplitude being submerged. According to the ratio of IFCF to IRF in the demodulated frequency spectrum, the bearing fault location was judged. The effectiveness of the proposed method was verified with the processing results of simulated signals and test ones.
刘东东，程卫东，温伟刚. 基于线调频小波路径追踪和逐步解调滤波的滚动轴承故障诊断[J]. 振动与冲击, 2019, 38(11): 88-94.
LIU Dongdong, CHENG Weidong, WEN Weigang. Rolling element bearing fault diagnosis based on CPP and stepwise demodulation filtering. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(11): 88-94.
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