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<p>Inter-turn short circuit (ITSC) and static eccentricity (SE) faults are common and critical faults in permanent magnet synchronous motor (PMSM). This paper proposes a fault classification method based on the characteristics of stator phase current fluctuation to address the misclassification issues caused by the coupling effects between the SE and ITSC faults. Firstly, the mathematical models of PMSM under SE and ITSC conditions are established, and the impacts of these two faults on stator current signatures are analyzed respectively. Secondly, the fault indicators are designed to extract the distinct fault features. Finally, both simulation and experimental studies are carried out, which validate that the proposed diagnosis method can effectively classify the fault type and exhibit strong robustness against variations in speed, load, and parameters. The proposed method is simple and economical, and provides practical significance for enhancing motor reliability and facilitating predictive maintenance.</p>

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Classification Diagnosis of Static Eccentricity and Inter-Turn Short-Circuit Faults in PMSM Based on Current Signature Analysis

  • 期刊论文

  • 发表日期：

    2026年2月25日

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  • Yao Zhao,
  • Kang Yang,
  • Dongdong Li,
  • Mengqi Zhu,
  • Tongtong Zhao

摘要

Inter-turn short circuit (ITSC) and static eccentricity (SE) faults are common and critical faults in permanent magnet synchronous motor (PMSM). This paper proposes a fault classification method based on the characteristics of stator phase current fluctuation to address the misclassification issues caused by the coupling effects between the SE and ITSC faults. Firstly, the mathematical models of PMSM under SE and ITSC conditions are established, and the impacts of these two faults on stator current signatures are analyzed respectively. Secondly, the fault indicators are designed to extract the distinct fault features. Finally, both simulation and experimental studies are carried out, which validate that the proposed diagnosis method can effectively classify the fault type and exhibit strong robustness against variations in speed, load, and parameters. The proposed method is simple and economical, and provides practical significance for enhancing motor reliability and facilitating predictive maintenance.