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Incipient Fault Detection in Stator Windings of an Induction Motor Using Stockwell Transform and SVM

Megha Singh, Abdul Gafoor Shaik

2020IEEE Transactions on Instrumentation and Measurement88 citationsDOI

Abstract

In this article, Stockwell transform (ST) is used to analyze the stator current signals for diagnosis of various motor conditions such as healthy, stator winding interturn shorts, and phase to ground faults. ST decomposes the current signals into complex ST matrix whose magnitude has been utilized for the fault detection. The nature of the fault, that is, ground or interturn is identified using the zero sequence currents followed by postfault detection. Two separate frequency bands are defined to extract the features which are fed to two different support vector machine (SVM) models for faulty phase detection for both types of faults. Under both cases, a heuristic feature selection approach is utilized to find the optimal features for classification purposes. Average classification accuracy of 96% has been achieved for both types of faults.

Topics & Concepts

StatorSupport vector machineInduction motorElectromagnetic coilPattern recognition (psychology)Fault detection and isolationFault (geology)EngineeringArtificial intelligenceFeature vectorHeuristicComputer scienceControl theory (sociology)VoltageElectrical engineeringGeologySeismologyActuatorControl (management)Machine Fault Diagnosis TechniquesOil and Gas Production TechniquesNon-Destructive Testing Techniques