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Proceedings ArticleDOI

Induction motor broken bar fault detection based on MCSA, MSCSA and PCA: A comparative study

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TLDR
In this paper, a comparative study of three methods based on the electrical signal analysis is presented, and the performance of the three methods is tested under different fault and load conditions, and experimental results are presented in order to compare the performance between them.
Abstract
The early failure detection of induction motors is considered very important in order to ensure their stability and high performance. Thus, condition monitoring of these motors are essential to ensure that. However, the effectiveness of the fault diagnosis depends on the quality of the fault features selection that is used in the adopted method. In this way, this paper will present a comparative study of three methods based on the electrical signal analysis. The first one is the most known method, motor current signature analysis (MCSA). Another method based on the analysis of spectral current, is the motor square current signature analysis (MSCSA), will also be used. Finally a third method based on principal component analysis (PCA) is also used. The performance of the methods is tested under different fault and load conditions. Experimental results are presented in order to compare the performance between the three methods.

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Citations
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Proceedings ArticleDOI

New vision about the overlap frequencies in the MCSA-FFT technique to diagnose the eccentricity fault in the induction motors

TL;DR: This study proposes a development of the new formulas which precisely shows the overlap between the frequencies in this method under static and dynamic eccentricity fault (SE and DE).
Proceedings ArticleDOI

Determination of faults in 3–Ø Induction Motor By Motor Current Signature Analysis

TL;DR: Detailed analysis is presented of how fault frequency is inducing as byproduct of unique rotating flux components and how fault Frequency is modulated in stator current which was not done so far.
Proceedings ArticleDOI

Improved Park's Vector Method and its Application in Planetary Gearbox Fault Diagnosis

TL;DR: The simulation result shows that, compared with traditional planetary gearbox signal analysis method, the proposed Park's vector method has better effect on characteristic frequency extracting of a three-phase current signal.
Journal ArticleDOI

Detectability of rotor failure for induction motors through stator current based on advanced signal processing approaches

TL;DR: In this paper, the authors investigated the ability of the diagnosis techniques and detectability of induction motor faults through a stator current and proposed techniques are based on advanced signal processing tools.
Proceedings ArticleDOI

Fault diagnosis of an induction motor through motor current signature analysis, FFT & DWT analysis

TL;DR: In the present work, the two different fault conditions namely Broken Rotor Bar and Stator Winding Fault are jointly analyzed, as a novel approach, and the results have been compared with the fault diagnosis of healthy machine.
References
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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

Online Diagnosis of Induction Motors Using MCSA

TL;DR: An online induction motor diagnosis system using motor current signature analysis (MCSA) with advanced signal-and-data-processing algorithms is proposed, able to ascertain four kinds of motor faults and diagnose the fault status of an induction motor.
Journal ArticleDOI

Monitoring and diagnosis of induction motors electrical faults using a current Park's vector pattern learning approach

TL;DR: In this article, Park's vector-based approach is used to diagnose electrical faults in induction motors, and the proposed methodology has been experimentally tested on a 4 kW squirrel-cage induction motor.
Journal ArticleDOI

Unsupervised Neural-Network-Based Algorithm for an On-Line Diagnosis of Three-Phase Induction Motor Stator Fault

TL;DR: An automatic algorithm based an unsupervised neural network for an on-line diagnostics of three-phase induction motor stator fault is presented and the obtained experimental results show the effectiveness of the proposed method.
Journal ArticleDOI

Rotor Cage Fault Diagnosis in Three-Phase Induction Motors by Extended Park's Vector Approach

TL;DR: In this article, a new approach based on the spectral analysis of the motor current Park's vector modulus was proposed for detecting rotor cage faults in operating three-phase induction machines.
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