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Journal ArticleDOI

Sensorless, online motor diagnostics

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TLDR
In this paper, the authors present recent developments in providing tools for the diagnosis of faults or incipient faults in electric motor drives, including: sensorless torque measurement; direct detection of turn-to-turn short circuits; detection of cracked or broken rotor bars; and detection of bearing deterioration.
Abstract
Early detection of abnormalities in electric motors helps to avoid expensive failures. Motor current signature analysis (MCSA) implemented in a computer-based motor monitor can contribute to such condition-based maintenance functions. Such a system may also detect an abnormality in the process as well as the motor. Extensive online monitoring of the motors can lead to greater plant availability, extended plant life, higher quality product, and smoother plant operation. With advances in digital technology over the last several years, adequate data processing capability is now available on cost-effective, microprocessor-based, protective-relay platforms to monitor motors for a variety of abnormalities in addition to the normal protection functions. Such multifunction monitors, are displacing the multiplicity of electromechanical devices commonly applied for many years. Following some background information on motor monitoring, this article features recent developments in providing tools for the diagnosis of faults or incipient faults in electric motor drives, including: sensorless torque measurement; direct detection of turn-to-turn short circuits; detection of cracked or broken rotor bars; and detection of bearing deterioration.

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Citations
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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.
Journal ArticleDOI

Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks

TL;DR: A fast and accurate motor condition monitoring and early fault-detection system using 1-D convolutional neural networks that has an inherent adaptive design to fuse the feature extraction and classification phases of the motor fault detection into a single learning body is proposed.
Proceedings ArticleDOI

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

TL;DR: In this article, the authors present a tutorial overview of induction motors signature analysis as a medium for fault detection, and introduce 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 inductive motors.
Journal ArticleDOI

What stator current processing-based technique to use for induction motor rotor faults diagnosis?

TL;DR: In this article, a comparison of signal processing-based techniques for the detection of broken bars and bearing deterioration in induction motors is presented, which are then analyzed and compared to deduce the most appropriate technique for induction motor rotor rotor fault detection.
Journal ArticleDOI

The detection of inter-turn short circuits in the stator windings of operating motors

TL;DR: A winding-function-based method for modeling polyphase cage induction motors with inter-turn short circuits in the machine stator winding is developed and it is shown that, as a result of the nature of the cage rotor, no new frequency components of the line current spectra can appear as a consequence of the fault.
References
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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.
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.
Proceedings ArticleDOI

A new approach to on-line turn fault detection in AC motors

TL;DR: Turn-to-turn fault detection is based on the principal that symmetrical motors powered by symmetrical multiphase voltage sources will have no negative sequence currents flowing in the leads as mentioned in this paper.
Journal ArticleDOI

Analysis of Cage Induction Motors with Stator Winding Faults

TL;DR: In this article, a generalised method of harmonic analysis is proposed to predict the performance of a cage motor with a stator winding fault, for the particular instances of a phase-to-neutral fault and a phaseto-phase fault.
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