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      KCI등재 SCIE SCOPUS

      Electromagnetic Signal Analysis for Electrical and Mechanical Fault Diagnosis in Synchronous Motor

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      https://www.riss.kr/link?id=A110100010

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      This paper presents a comprehensive approach to fault diagnosis in synchronous motors by integrating noninvasive electromagnetic signal analysis with the Finite Element Method (FEM). The study encompasses a wide range of electrical and mechanical faults, including stator and rotor winding issues, ground faults, phase short circuits, eccentricity faults, and broken damper bars. By analyzing stator current harmonics and stray magnetic flux, the proposed method significantly enhances the accuracy of fault detection. The diagnostic process is validated through simulation results, demonstrating its effectiveness in real-time monitoring and predictive maintenance. These findings contribute to the development of more reliable and cost-efficient diagnostic systems, reducing operational disruptions and extending the lifespan of electrical machinery in industrial applications.
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      This paper presents a comprehensive approach to fault diagnosis in synchronous motors by integrating noninvasive electromagnetic signal analysis with the Finite Element Method (FEM). The study encompasses a wide range of electrical and mechanical faul...

      This paper presents a comprehensive approach to fault diagnosis in synchronous motors by integrating noninvasive electromagnetic signal analysis with the Finite Element Method (FEM). The study encompasses a wide range of electrical and mechanical faults, including stator and rotor winding issues, ground faults, phase short circuits, eccentricity faults, and broken damper bars. By analyzing stator current harmonics and stray magnetic flux, the proposed method significantly enhances the accuracy of fault detection. The diagnostic process is validated through simulation results, demonstrating its effectiveness in real-time monitoring and predictive maintenance. These findings contribute to the development of more reliable and cost-efficient diagnostic systems, reducing operational disruptions and extending the lifespan of electrical machinery in industrial applications.

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