Empirical wavelet transform‑synchroextracting transform and its applications in fault diagnosis of rolling bearing

In order to accurately diagnose bearing faults and explore the time-varying characteristics of the fault signal, a bearing fault diagnosis method based on Synchroextracting Transform and Empirical Wavelet Transform (EWT-SET) is proposed. In the proposed method, the fault signal is decomposed by EWT, and the obtained empirical modes are used by SET. The SET of all modes are superimposed to obtain the time-frequency distributions of fault signal. The simulation shows that the proposed method is superior to the traditional SET method, and can solve the problem of the ambiguity of the instantaneous frequency trajectory occurred in the SET when the frequencies of the modal signals are very close to each other. The proposed method is applied to the fault diagnosis of rolling bearing with different degrees of damage. The experiments show that the proposed method can effectively diagnose the type of rolling bearing faults and the degree of damage, and can clearly represent the time-varying characteristics of fault signals. © 2021, Editorial Board of Journal of Vibration Engineering. All right reserved.