Fault Diagnosis Method of Rotor Magnetic Field Local Demagnetization in Permanent Magnet Synchronous Motor Model Predictive Current Control System

Abstract

In order to realize the reliable diagnosis of the rotor magnetic field local demagnetization fault of permanent magnet synchronous motor (PMSM) model predictive current control system, based on the establishment of the mathematical model of PMSM considering local demagnetization of rotor magnetic field and the simulation model of its model predictive current control system, a diagnosis method combining the adaptive signal extraction algorithm and Hilbert transform is proposed in this study. This method is first based on the adaptive signal extraction algorithm to extract the fault characteristic harmonics of rotor magnetic field local demagnetization fault in PMSM model predictive current control system under stationary and nonstationary operating conditions, and then, we use Hilbert transform to realize the time-frequency transformation of the extracted fault characteristic harmonics. Based on solving the problem that the weak fault characteristic signal near the fundamental wave component existing in the Hilbert–Huang transform is difficult to effectively decompose, the reliable diagnosis of the rotor magnetic field local demagnetization fault of the PMSM model predictive current control system is realized with the calculation amount less than Hilbert–Huang transform. The simulation and experimental results show that the proposed method is accurate and useful.