A Hybrid Approach for Terminal Fault Detection of Induction Motor

Prevention of Induction Motors against internal and external faults is highly essential for uninterruptable industrial operation. It has an adverse effect on the performance and functionality of Induction Motor. This paper manages the detection and identification of faults at the terminal which descends the capability of Induction Motor in an Industry. A comparative approach among FFT analysis, Wavelet analysis and ANFIS for detection of external fault is presented here. The effect of each approach is described in detail. The faults are examined by wavelet transform in both space and time domain and the Neuro-fuzzy technique is validated by training an ANFIS model at each load to classify the faults most clearly among all the methods. The comparative study and advantage of one method over another are also described.