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Impulse testing for detection of insulation failure of motor winding and diagnosis based on Hidden Markov Model

机译:基于隐马尔可夫模型的电机绕组绝缘故障脉冲测试与诊断

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摘要

Short circuit fault of a motor, due to breakdown of an insulating material of winding, is one of the most probable faults in motor drive systems. Establishment of an easy and effective fault diagnosis method has been strongly required to assure operation with high reliability. This paper proposes a novel diagnosis method for insulation failure of motor windings by a combination of impulse testing and pattern recognition based on Hidden Markov Model (HMM). A voltage waveform across two winding terminals is recorded under application of an impulse voltage. HMM is exploited to distinguish a small difference in voltage waveforms between healthy and faulty winding insulations. Usefulness of the proposed diagnostic method is verified through voltage waveforms experimentally obtained for motors with several kinds of turn-to-turn insulation failures.
机译:由于绕组的绝缘材料击穿而引起的电动机短路故障是电动机驱动系统中最可能的故障之一。强烈要求建立一种简单有效的故障诊断方法,以确保操作具有高可靠性。提出了一种基于隐马尔可夫模型(HMM)的脉冲测试与模式识别相结合的电机绕组绝缘故障诊断方法。在施加脉冲电压的情况下记录两个绕组端子之间的电压波形。利用HMM可以区分正常和故障绕组绝缘之间的电压波形的微小差异。通过对几种匝间绝缘故障的电动机进行实验获得的电压波形,可以验证所提出的诊断方法的实用性。

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