Improved Detection of Inter-turn Short Circuit Faults in PMSM Drives using Principal Component Analysis

Frank Landry Tanenkeu Guefack, A. Kiselev, A. Kuznietsov
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引用次数: 10

Abstract

In this paper, a new online algorithm for detection and location of inter-turn short circuit fault in permanent magnet synchronous motor (PMSM) drives is presented. The developed algorithm is based on the well-know classical Park's Vector Approach (PVA), extended by the Principal Component Analysis (PCA) method. The PCA extension provides a significantly better robustness of the detecting performance against signal noise and allows to locate the fault phase. The detection, location of interturn short circuit fault as well as the noise tolerance is proven by simulation results under real-time conditions.
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基于主成分分析的永磁同步电机匝间短路故障改进检测方法
提出了一种用于永磁同步电机驱动匝间短路故障在线检测与定位的新算法。该算法以经典的帕克矢量法(Park's Vector method, PVA)为基础,通过主成分分析法(PCA)进行扩展。PCA扩展提供了更好的检测性能对信号噪声的鲁棒性,并允许定位故障相位。仿真结果验证了在实时条件下匝间短路故障的检测、定位和噪声容限。
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