An order tracking-free method for variable speed fault diagnosis based on adaptive chirp mode decomposition

Various time-frequency analysis based tacholess methods have been developed for fault detection under variable rotational speed conditions. However, most of them rely on order tracking (OT) which must transform a vibration signal from time domain to angular domain. In this paper, an order tracking-free method based on adaptive chirp mode decomposition (ACMD) is proposed to break through the boundedness. As pre-processing, synchroextracting transform (SET) is employed to calculate time-frequency distribution (TFD) of the raw signal with high concentration energy. Afterwards, multiple instantaneous frequencies (IFs) are simultaneously extracted by ACMD, which decomposes multimode non-stationary signal with an adaptive bandwidth updating rule. Finally, select the relevant IFs to calculate the fault characteristic coefficient (FCC) and then the fault state of bearing can be identified. Numerical simulation and experimental investigations with varying speeds verify the effectiveness of the new method. The results of comparison tests further to demonstrate the proposed method is high-efficiency.

Automated summary

This paper proposes a tacholess method based on ACMD and SET, extracting multiple instantaneous frequencies to solve the limitation of order tracking, which is successfully applied in fault characteristic extraction and state identification of bearings.