应用人工神经网络诊断三相异步电动机定子绕组匝间短路

P. J. Broniera, W. S. Gongora, A. Goedtel, W. Godoy
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引用次数: 11

摘要

感应电动机在工业上的应用是广泛的。因此,一些研究提出了诊断和预测这些电机故障的策略。所使用的一种技术是基于最近使用的用于检测电动机故障的智能系统。因此,本文提出了一种替代传统技术的工具,用于定子绕组匝间短路故障检测,使用人工神经网络在时域分析定子电流信号。实验结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diagnosis of stator winding inter-turn short circuit in three-phase induction motors by using artificial neural networks
The application of induction motors in industry is widespread. Thus, several studies have presented strategies for the diagnosis and prediction of failures in these motors. One technique used is based on the recent utilization of intelligent systems for detecting faults in electric motors. Thus, this paper proposes an alternative tool to traditional techniques for fault detection of a short circuit between the inter-turns of the stator winding using artificial neural networks to analyze stator current signals in the time domain. Experimental results are presented to validate the proposed approach.
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