Sensitive interturn fault diagnosis in induction machine using vibration analysis

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.