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Single-Turn Fault Detection in Induction Machine Using Complex-Wavelet-Based Method

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3 Author(s)
Seshadrinath, J. ; Dept. of Electr. Eng., Indian Inst. of Technol. Delhi, New Delhi, India ; Singh, B. ; Panigrahi, B.K.

Interturn short circuit is often confused with voltage imbalance in induction machines. Therefore, detection and classification of single-turn fault (TF) are becoming important in the presence of voltage imbalances, under various loading conditions. Substantial studies are conducted on the interturn fault detection, but a comprehensive method for classifying the faults at different operating points of the machine, under varying supply conditions, is still a challenge. This is a critical problem in industries since the induction motors form the major workhorses. The artificial-intelligence-based techniques are advanced methods in fault monitoring. This, when combined with optimization techniques, is expected to give improved and accurate results with minimum false alarms. In this paper, a technique is developed, based on recent developments in the wavelet-based analysis, particularly in the complex wavelet domain. The support vector machines are adopted for comparing the classification accuracy obtained using complex-wavelet- and standard discrete-wavelet-based methods. The receiver operating characteristic curves indicate that the fault detection, down to single turn, is feasible using a single current sensor.

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Industry Applications, IEEE Transactions on  (Volume:48 ,  Issue: 6 )