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Sensitive interturn fault diagnosis in induction machine using vibration analysis

机译:基于振动分析的感应电机匝间故障诊断

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Vibration analysis based interturn fault diagnosis and condition monitoring, using minimum computations is explored in this paper. The voltage imbalance is often confused with turn fault (TF), and has therefore been a challenge to diagnose the fault under varying supply-frequency and load conditions. The application of analytical wavelets in incipient fault diagnosis using vibration analysis, under such grid perturbations is highlighted in this paper. Once the feature extraction is performed using analytical wavelets, it is classified effortlessly using simple algorithm like KNN. The performance metrics brings out the benefit of using an efficient feature extraction for processing machine signatures. The turn fault can be identified at its very inception using this technique under varying conditions.
机译:本文探索了基于振动分析的匝间故障诊断和状态监测,并使用最少的计算方法。电压不平衡经常与转向故障(TF)混淆,因此在电源频率和负载条件变化的情况下诊断故障一直是一个挑战。在这种网格扰动下,分析小波在利用振动分析的早期故障诊断中的应用得到了强调。一旦使用解析小波执行了特征提取,就可以使用诸如KNN的简单算法轻松地对其进行分类。性能指标带来了使用高效的特征提取来处理计算机签名的好处。使用这种技术,可以在变化的条件下从一开始就识别出转向故障。

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