Journal ArticleDOI
Incipient Fault Detection in Stator Windings of an Induction Motor Using Stockwell Transform and SVM
Megha Singh,Abdul Gafoor Shaik +1 more
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TLDR
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.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.read more
Citations
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Journal ArticleDOI
Detection of Stator Interturn Short-Circuit Faults in Inverter-Fed Induction Motors by Online Common-Mode Impedance Monitoring
TL;DR: In this paper, the stator interturn short-circuit (ITSC) faults of an inverter-fed induction motor can be detected with good confidence by monitoring the online common-mode (CM) impedance of an IM through an inductive coupling technique at a specific frequency of interest (FOI).
Journal ArticleDOI
Inter-Turn Short-Circuit Faults Diagnosis in Synchronous Reluctance Machines, Using the Luenberger State Observer and Current's Second-Order Harmonic
TL;DR: In this article , the authors proposed an interturn fault diagnostic technique for synchronous reluctance machines based on the Luenberger state observer and current's second-order harmonic, which can evaluate the severity of the fault in early stages and under various operating conditions.
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Transformer Fault Diagnosis Based on Multi-Class AdaBoost Algorithm
TL;DR: Wang et al. as mentioned in this paper proposed a transformer fault diagnosis method based on Multi-class AdaBoost Algorithms in response to low fault diagnosis accuracy, where the AdaBoost algorithm is combined with Support Vector Machines (SVM), and the SVM is enhanced through the Adaboost algorithm, and the transformer fault data is deeply explored.
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Research on Rolling Bearing Fault Diagnosis Method Based on Generative Adversarial and Transfer Learning
TL;DR: A rolling bearing fault diagnosis method suitable for different working conditions based on simulating the real industrial scene and the experimental results show that the average fault diagnosis accuracy can reach 96.58%.
Journal ArticleDOI
Hypergraph regularized semi-supervised support vector machine
TL;DR: Wang et al. as discussed by the authors exploited the multivariate manifold structure by hypergraph, and proposed a hypergraph regularized semi-supervised support vector machine (HGSVM) algorithm.
References
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TL;DR: The fundamental theory, main results, and practical applications of motor signature analysis for the detection and the localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of induction motors are introduced.
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A review of stator fault monitoring techniques of induction motors
TL;DR: In this article, a comprehensive review of various stator faults, their causes, detection parameters/techniques, and latest trends in the condition monitoring technology is presented. And a broad perspective on the status of stator fault monitoring to researchers and application engineers using induction motors is provided.
Journal ArticleDOI
A Survey on Testing and Monitoring Methods for Stator Insulation Systems of Low-Voltage Induction Machines Focusing on Turn Insulation Problems
TL;DR: An in-depth literature review of testing and monitoring methods that diagnose the condition of the turn-to-turn insulation of low-voltage machines, which is a rapidly expanding area for both research and product development efforts.
Proceedings ArticleDOI
A survey of faults on induction motors in offshore oil industry, petrochemical industry, gas terminals and oil refineries
O.V. Thorsen,M. Dalva +1 more
TL;DR: A survey of the reliability of squirrel cage motors on board drilling, production, and other platforms offshore, together with cage motors in the petrochemical industry, gas terminals, and refineries onshore is presented in this article.