Fuzzy logic based Fault Diagnosis in Induction Motor (original) (raw)

Abstract

Induction motors are one of the commonly used electrical machines in industry because of many technical and economical reasons. They face various stresses during operating conditions leading to some modes of faults. Hence, condition monitoring becomes necessary in order to avoid catastrophic failures. Different fault monitoring techniques for induction motors can be broadly categorized as model based, signal processing based and soft computing techniques. It is difficult to obtain the accurate models of faulty machines and also to apply model based techniques. Soft computing techniques give good analysis of a faulty system even if accurate models are unavailable. These techniques are easy to extend and modify and also give improved performance. Here the different soft computing techniques for fault diagnosis are discussed. A methodology based on Park's Vector approach employing Fuzzy logic and Adaptive Neuro-Fuzzy Inference System (ANFIS) is used to diagnose electrical faults. D...

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