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ANN based fault diagnosis of permanent magnet synchronous motor under stator winding shorted turn

机译:基于ANN的定子绕组短路匝间永磁同步电动机故障诊断。

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摘要

The fault detection and diagnosis in electrical motors is a topic of increasing interest in the field of highly reliable and fault-tolerant measurement and control systems. This paper focuses on inter-turn short circuit fault diagnosis in stator windings of a Permanent magnet synchronous motor (PMSM). A multilayer artificial neural network (MANN) has been used for diagnosis and classification of different levels of short circuit. The analytical and finite element method (FEM) based results have been validated by experimental results. Experimental data have been employed to train ANN. (C) 2015 Elsevier B.V. All rights reserved.
机译:在高度可靠和容错的测量和控制系统领域,电动机的故障检测和诊断是一个越来越引起人们关注的话题。本文着重于永磁同步电动机(PMSM)的定子绕组匝间短路故障诊断。多层人工神经网络(MANN)已用于诊断和分类不同级别的短路。基于分析和有限元方法(FEM)的结果已通过实验结果验证。实验数据已被用来训练人工神经网络。 (C)2015 Elsevier B.V.保留所有权利。

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