SUMMARYInduction motors condition monitoring is a very important process for immediate detection of the incipient faults. This prevents the spread of the faults up to risky degrees and avoids catastrophic stop of the motor and relevant production line. The stator winding fault is one of the most commonly occurring faults in alternating current machines. This paper is a comprehensive survey on the stator winding faults causes, diagnosis methods, indexes, and modeling and simulation methods. An efficient method is used to model and simulate the squirrel‐cage induction motor performance under inter‐turn fault. The results are used to obtain the performance of some common indexes of the fault and recognize the most proper index. Finally, some simulation results are compared with the corresponding experimental results and good agreements are achieved. Copyright © 2013 John Wiley & Sons, Ltd.

In spite of numerous research activities performed so far, determination of type and exact degree of the eccentricity faults in induction motors is challenging yet. This study presents a model-based fault diagnosis technique for identifying all the three eccentricity fault types, including static, dynamic and mixed eccentricities, with their exact degrees in the mentioned motors. This technique uses a special analytic model prepared for simulating squirrel-cage induction motors under healthy and all eccentricity fault conditions as well as the particle swarm optimisation method. Correct performance and effectiveness of the proposed technique is verified by using simulation and experiments. Finally, an algorithm is introduced for the eccentricity fault treatment using the identified degrees of the fault components and their time trends.

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Winding function method (WFM) provides a detailed and rather simple analytical modeling and simulation technique for analyzing performance of faulty squirrel-cage induction motors (SCIMs). Such analysis is mainly applicable for designing on-line fault diagnosis techniques. In this paper, WFM is extended to include variable degrees of magnetic saturation by applying an appropriate air gap function and novel techniques for estimating required saturation factor and angular position of the air gap flux density. The resultant saturable winding function method (SWFM) is properly applied to analyze SCIMs with broken rotor bars and to identify the saturation effect on the related fault indexes. Comparing simulation results to the corresponding experimental ones show higher accuracy of the SWFM. This means that more precise fault diagnosis techniques can be designed by using the proposed saturable modeling technique.