Demagnetization Diagnosing in PMSM Based on SIDDTW Under Nonstationary Conditions

Demagnetization, as one of the most frequent faults, has great influence on the performance of (permanent magnet synchronous motor) PMSM. However, the motor usually runs in nonstationary conditions, that brings great challenge to the effective diagnosis of demagnetization fault. This paper presents a new methodology of Shift-invariant Dictionary of Dynamic Time Warping (SIDDTW) to diagnose the demagnetization fault under nonstationary conditions. Firstly, according to the characteristics of current signal under demagnetization fault, the shift-invariant dictionary is constructed. Then, Matching Pursuit (MP) is used to represent the current signals that collected from the running process of PMSM, and then the sparse coefficient series are obtained. Finally, the Dynamic Time Warping (DTW) method is used to calculate the sparse coefficient series distance between the test data and the database which build in the training process. In this step, the nearest distance is matched, and corresponding operation state is recognized as the final diagnosis result. The results show that the presented method has good adaptability when dealing with nonstationary conditions both on the Simulink platform and the real-time simulation platform.