Electromagnetic Field Analysis and Diagnosis of Rotor Demagnetization and Eccentricity Faults in SPMSM

被引:0
|
作者
Li, Xian [1 ]
Wang, Xiuhe [1 ]
Zhao, Wenliang [1 ]
机构
[1] Shandong Univ, Sch Elect Engn, Jinan 250061, Peoples R China
关键词
Deep neural network (DNN); fault diagnosis; local irreversible demagnetization fault (LIDF); permanent magnet (PM) synchronous motor; rotor eccentricity (RE); PERMANENT-MAGNET MACHINES; SUBDOMAIN MODEL; COGGING TORQUE; MOTORS; PERFORMANCE; POLE;
D O I
10.1109/TMAG.2024.3524638
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Aiming at the common faults of demagnetization and rotor eccentricity (RE) in permanent magnet (PM) synchronous motor, the electromagnetic field analysis under the faults and a nonintrusive fault diagnosis and localization technique are investigated in this article. Initially, a PM segmentation model is developed, and a general solution is derived for surface-mounted PM motor with local irreversible demagnetization fault (LIDF) accounting for core saturation, which can precisely simulate LIDF in arbitrary regions. Additionally, an equivalent transformation method is introduced to emulate the nonuniform magnetic field arising from RE. The validity and correctness of the proposed models are confirmed by finite element analysis and experiments. Furthermore, the effects caused by the faults on the no-load electromagnetic performance are analyzed, based on which a diagnosis technique for rotor faults using coil BEMF (CBEMF) is proposed. The localization of the LIDF is achieved by integration with the least square method, and the eccentric angle and ratio are determined by combining with a deep neural network (DNN). Overall, the proposed model can provide an important reference for rotor failure risk assessment, fault-tolerant optimization, and maintenance strategy.
引用
收藏
页数:13
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