A New Approach to Detect Stator Fault in Permanent Magnet Synchronous Motors

被引：0
|
作者：
Cira, Ferhat [1 ]
Arkan, Muslum [2 ]
Gumus, Bilal [1 ]
机构：
[1] Dicle Univ, Dept Elect & Elect Engn, Diyarbakir, Turkey
[2] Inonu Univ, Dept Elect & Elect Engn, Malatya, Turkey
来源：
2015 IEEE 10TH INTERNATIONAL SYMPOSIUM ON DIAGNOSTICS FOR ELECTRIC MACHINES, POWER ELECTRONICS AND DRIVES (SDEMPED) | 2015年
关键词：
Permanent Magnet Synchronous Motors; Pattern Recognition System; Fault Detection; Condition Monitoring; Digital Signal Processing; Fault Severity Classification;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, detection of the stator winding inter-turn short circuit fault (SWISCF) in surface-mounted permanent magnet synchronous motors (SPMSMs) and classification of the fault severity via pattern recognition system (PRS) are presented. In order to automatically detect stator winding short circuit fault and to estimate severity of this fault, artificial neural network (ANN) based PRS has been used. It has been observed that the amplitude of the 3rd harmonics of the current is the most distinctive characteristic for detecting the short circuit fault ratio of the SPMSM. To increase the fault clasification accuracy of PRS both fundamental (1st) and 3rd harmonics are used. In order to validate proposed method experimental results are presented.
引用
收藏
页码：316 / 321
页数：6
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