Multielectrical Signal Fusion-Based Method for Bearing Fault Diagnosis in Permanent Magnet Synchronous Machines Under Dynamic Conditions

Abstract

In this article, a multielectrical signal fusion method based on the rotor speed and stator current is investigated for bearing fault diagnosis of permanent magnet synchronous machines (PMSMs) under variable speed conditions. This method can achieve low-cost and real-time fault diagnosis by using directly measured rotor speed and stator current signals from the drive machine of the mechatronics system. First, the fault feature harmonic can be extracted from the rotor speed signal, and the instantaneous phase is estimated using the stator current of PMSMs. The time-domain fault feature harmonic is then resampled on the angle domain using a high-precision accumulative angle calculated by the instantaneous phase. Finally, the fault type can be diagnosed by the fault indicator in the envelope spectrum of the resampled signal. Furthermore, experimental validations are conducted on the PMSM-drive-system-based bearing fault diagnosis platform. The results indicate that the proposed method can accurately extract fault features to diagnose the bearing faults under variable speed conditions without extra sensors.