Abstract: A rotating machinery fault diagnosis method based on differential local mean decomposition (DLMD) is proposed. The differential and integral operations are integrated into the traditional local mean decomposition (LMD). The original signal is processed with k-order differential, and then the signal obtained is decomposed using LMD. The production function (PF) components obtained are circularly processed with an integral and first-order the LMD decomposition until k times, and it can get m PF components and the residual component. The whole time-frequency distribution of the original signal can be obtained by the combination of the instantaneous amplitude and instantaneous frequency of all the PF components. The method is applied to rotating machinery fault diagnosis study which is analyzed by simulation and experimental study. The results show that, the fault diagnosis method of rotating machinery based on DLMD can effectively suppress the false interference frequency, and improve the accuracy of rotating machinery fault diagnosis.

Key words: differential local mean decomposition;rotating machinery;fault diagnosis