کنفرانس بین المللی ماشین و محرکه های الکتریکی

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صفحه اصلی / icemd2023

Fault diagnosis modeling of permanent magnet motors: inter-turn short circuit (ITSC) faults

نویسندگان :

Reza Heibati¹ Ramin Alipour-Sarabi² Seyed Mohammad Taghi Bathaee³

1- دانشگاه صنعتی خواجه نصیرالدین طوسی 2- دانشگاه صنعتی خواجه نصیرالدین طوسی 3- دانشگاه صنعتی خواجه نصیرالدین طوسی

کلمات کلیدی :

Permanent Magnet Synchronous Motor،inter-turn short circuit fault،Deep Learning،Dynamic Modeling

چکیده :

This study addresses the critical issue of inter-turn short circuits in permanent magnet synchronous machines (PMSMs) within the realm of power engineering. It encompasses a thorough investigation, from examining prevalent fault detection methods to employing advanced computational tools for accurate machine modeling and simulation. The novel approach combines precise magnetic field modeling with established electrical and mechanical equations, yielding significantly higher accuracy compared to conventional methods. The computational models not only detect inter-turn faults but also allow for the analysis of ground faults, open circuit faults, and dynamic and static eccentricities. Results from simulations closely align with real-world values, affirming the efficacy of the proposed modeling approach. The study also demonstrates the feasibility of identifying non-axisymmetric faults through dynamic machine behavior analysis. Torque oscillations, resultant from imbalanced phase currents, emerge as a potential diagnostic tool for inter-turn faults. Additionally, phase current asymmetry opens avenues for fault detection based on sequence analysis. This research provides a robust framework for accurate inter-turn short circuit detection in PMSMs. By integrating advanced computational modeling with established electrical engineering principles, it offers a approach to fault diagnosis in these machines, addressing a critical concern in power engineering.

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