부산대학교 도서관

Static eccentricity fault (SEF) is mainly caused by incorrect fabrication of the motor and external mechanical stress from the outside, while permanent magnet irreversible demagnetization fault (IDF) is mainly caused by an increase in the temperature of the motor when instantaneous overcurrent is applied. These faults are generally diagnosed through a vibration sensor and an additional hardware device. However, the hardware for vibration measurement is expensive, and the reliability of the vibration sensor is also low due to the influence of electrical noise generated by the high switching frequency of the inverter. Therefore, in order to solve this problem, this article proposes a fault diagnosis method for a six-phase interior permanent magnet synchronous motor (IPMSM) using the voltage angle calculated by the inverter in real-time without additional hardware configuration. First, an analysis of voltage angle and electrical parameter changes due to fault is performed using the finite element method (FEM). Next, fault diagnosis using the proposed voltage angle is verified through experiment. Finally, we compare the fault diagnosis accuracy of the multivariate regression analysis (MRA) model and the artificial neural network (ANN) model using the voltage angle.