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Condition Monitoring and Fault Diagnosis of Electrical Motors—A Review

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TLDR
A review paper describing different types of faults and the signatures they generate and their diagnostics' schemes will not be entirely out of place to avoid repetition of past work and gives a bird's eye view to a new researcher in this area.
Abstract
Recently, research has picked up a fervent pace in the area of fault diagnosis of electrical machines. The manufacturers and users of these drives are now keen to include diagnostic features in the software to improve salability and reliability. Apart from locating specific harmonic components in the line current (popularly known as motor current signature analysis), other signals, such as speed, torque, noise, vibration etc., are also explored for their frequency contents. Sometimes, altogether different techniques, such as thermal measurements, chemical analysis, etc., are also employed to find out the nature and the degree of the fault. In addition, human involvement in the actual fault detection decision making is slowly being replaced by automated tools, such as expert systems, neural networks, fuzzy-logic-based systems; to name a few. It is indeed evident that this area is vast in scope. Hence, keeping in mind the need for future research, a review paper describing different types of faults and the signatures they generate and their diagnostics' schemes will not be entirely out of place. In particular, such a review helps to avoid repetition of past work and gives a bird's eye view to a new researcher in this area.

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Journal ArticleDOI

A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

TL;DR: The three-part survey paper aims to give a comprehensive review of real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade.
Journal ArticleDOI

Advances in Diagnostic Techniques for Induction Machines

TL;DR: This paper investigates diagnostic techniques for electrical machines with special reference to induction machines and to papers published in the last ten years, and research activities are classified into four main topics.
Journal ArticleDOI

Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals

TL;DR: In this article, a mathematical analysis to select the most significant intrinsic mode functions (IMFs) is presented, and the chosen features are used to train an artificial neural network (ANN) to classify bearing defects.
Journal ArticleDOI

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 of Condition Monitoring and Protection Methods for Medium-Voltage Induction Motors

TL;DR: A comprehensive survey of the existing condition monitoring and protection methods in the following five areas: thermal protection and temperature estimation, stator insulation monitoring, bearing fault detection, broken rotor bar/end-ring detection, and air gap eccentricity detection is presented in this article.
References
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Journal ArticleDOI

A review of induction motors signature analysis as a medium for faults detection

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.
Proceedings ArticleDOI

Motor bearing damage detection using stator current monitoring

TL;DR: In this article, the authors used motor current spectral analysis to detect rolling-element bearing damage in induction machines, where the bearing failure modes were reviewed and bearing frequencies associated with the physical construction of the bearings were defined.
Book

Parameter Estimation, Condition Monitoring, and Diagnosis of Electrical Machines

Peter Vas
TL;DR: In this article, the effects of time harmonics on various space-phasor loci, harmonic amplitude estimation Monitoring of the rotor speed and the rotor angle Monitoring various machine parameters Diagnosis, condition monitoring Bibliography Index
Journal ArticleDOI

Noninvasive detection of broken rotor bars in operating induction motors

TL;DR: In this paper, a computer-based noninvasive broken bar fault detector for squirrel-cage rotors of induction motors is presented, which can be applied to existing motors without disassembly or shutdown and has the sensitivity to diagnose the presence of a single broken bar or an open end ring.
Journal ArticleDOI

Vibration and current monitoring for detecting airgap eccentricity in large induction motors

TL;DR: In this paper, a study carried out to detect air gap eccentricity in large 3-phase induction motors was carried out and the philosophy of using a unified online monitoring strategy was presented and the reasons for selecting line current and frame vibration as the monitored parameters are discussed.
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