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

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 f...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement 2020-12, Vol.69 (12), p.9496-9504
Main Authors: Singh, Megha, Shaik, Abdul Gafoor
Format: Article
Language:English
Subjects:
Classification
Coils (windings)
Fault detection
Fault diagnosis
Feature extraction
Frequencies
Induction motors
Motor stators
Stator fault diagnosis
Stator windings
Stators
Stockwell transform (ST)
support vector machine (SVM)
Support vector machines
three phase induction motor~(IM)
Transforms
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Summary: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.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2020.3002444