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Information Journal Paper

Title

SIMULATION OF ELECTRICAL FAULT IN STATOR WINDING OF PERMANENT MAGNET SYNCHRONOUS MOTOR AND DISCRIMINATING IT FROM OTHER POSSIBLE ELECTRICAL FAULTS USING PROBABILISTIC NEURAL NETWORK

Pages

  1-12

Abstract

 One of the most common electrical faults in PERMANENT MAGNET SYNCHRONOUS MOTOR (PMSM) is INTER-TURN FAULT in stator winding. At the incipient steps it seems not dangerous and so light, but spreading this fault can leads to irreparable Consequences. In this paper, the intelligent system is presented to protect PMSMs from this kind fault. At the first, intelligent protection system determine the condition of the motor (which can be: Normal, Phase-phase short circuit, Open circuit and INTER-TURN FAULT conditions). If the system determines the faults then send an alarm to operator and also if the fault is inter-turn, it can determine the damaged phase. Obtaining results show that PROBABILISTIC NEURAL NETWORK can be the most reliable and robust protection system for PMSMs against internal faults, especially INTER-TURN FAULTs.

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    APA: Copy

    TAGHIPOUR GORJIKOLAIE, M., RAZAVI, S.M., & SHAMSI NEJAD, M.A.. (2015). SIMULATION OF ELECTRICAL FAULT IN STATOR WINDING OF PERMANENT MAGNET SYNCHRONOUS MOTOR AND DISCRIMINATING IT FROM OTHER POSSIBLE ELECTRICAL FAULTS USING PROBABILISTIC NEURAL NETWORK. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, A- MUHANDISI -I BARQ, 13(1), 1-12. SID. https://sid.ir/paper/228149/en

    Vancouver: Copy

    TAGHIPOUR GORJIKOLAIE M., RAZAVI S.M., SHAMSI NEJAD M.A.. SIMULATION OF ELECTRICAL FAULT IN STATOR WINDING OF PERMANENT MAGNET SYNCHRONOUS MOTOR AND DISCRIMINATING IT FROM OTHER POSSIBLE ELECTRICAL FAULTS USING PROBABILISTIC NEURAL NETWORK. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, A- MUHANDISI -I BARQ[Internet]. 2015;13(1):1-12. Available from: https://sid.ir/paper/228149/en

    IEEE: Copy

    M. TAGHIPOUR GORJIKOLAIE, S.M. RAZAVI, and M.A. SHAMSI NEJAD, “SIMULATION OF ELECTRICAL FAULT IN STATOR WINDING OF PERMANENT MAGNET SYNCHRONOUS MOTOR AND DISCRIMINATING IT FROM OTHER POSSIBLE ELECTRICAL FAULTS USING PROBABILISTIC NEURAL NETWORK,” NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, A- MUHANDISI -I BARQ, vol. 13, no. 1, pp. 1–12, 2015, [Online]. Available: https://sid.ir/paper/228149/en

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