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Fault Diagnosis of Three-Phase Induction Motor: A Review

Published in Optics (Volume 4, Issue 1-1)
Received: 20 September 2014     Accepted: 25 September 2014     Published: 29 November 2014
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Abstract

Now a days the use of Condition Monitoring of electrical machines are increasing due to its potential to reduce operating costs, enhance the reliability of operation and improve service to customers. Different alternatives to detect and diagnose faults in induction machines have been proposed and implemented in the last years. These new alternatives are characterized by an on-line and non-invasive feature, that is to say, the capacity to detect faults while the machine is working and the capacity to work sensor less. These characteristics, obtained by the new techniques, distinguish them from the traditional ones, which, in most cases, need that the machine which is being analyzed is not working to do the diagnosis. The main purpose of this article is to revise the main alternatives in the detection of faults in induction machines and compare their contributions according to the information they require for the diagnosis, the number and relevance of the faults that can be detected, the speed to anticipate a fault and the accuracy in the diagnosis. and to identify various such diagnosis techniques that can be applied for automatic condition monitoring of induction motors and can be extended easily to other electrical machines also.

Published in Optics (Volume 4, Issue 1-1)

This article belongs to the Special Issue Applied Optics and Signal Processing

DOI 10.11648/j.optics.s.2015040101.11
Page(s) 1-8
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2014. Published by Science Publishing Group

Keywords

Induction Machines, Fault Detection and Fault Diagnosis

References
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[2] Benbouzid, M.E.H., “A Review of Induction Motors Signature Analysis as a Medium for FaultsDetection”, IEEE Transactions on Industrial Electronics, 47, 984-993 (2000).
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[4] Are bearing currents causing your motor failures? Greenheck, (FA/117-03), Jan-2004.
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[6] P.Vas, “Parameter estimation condition monitoring and diagnosis of electrical machines.” Oxford, U.K. Claredon, 1996.
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[8] R.R. Schoen, T.G. Habetler, F. Kamran, and R.G. Bartfield,” Motor bearing damage detection using stator current monitoring”, IEEE transaction. Ind. Appl. Vol 31, Dec 1995.
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[19] Y. Han and Y. H. Song, “Condition Monitoring Techniques for Electrical Equipment- A Literature Survey” , IEEE, 2003.
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[21] Arfat Siddique, G. S. Yadava, and Bhim Singh, “A Review of Stator Fault Monitoring Techniques of Induction Motors”, IEEE, 2005.
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Cite This Article
  • APA Style

    Malik Abadulrazzaq Alsaedi. (2014). Fault Diagnosis of Three-Phase Induction Motor: A Review. Optics, 4(1-1), 1-8. https://doi.org/10.11648/j.optics.s.2015040101.11

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    ACS Style

    Malik Abadulrazzaq Alsaedi. Fault Diagnosis of Three-Phase Induction Motor: A Review. Optics. 2014, 4(1-1), 1-8. doi: 10.11648/j.optics.s.2015040101.11

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    AMA Style

    Malik Abadulrazzaq Alsaedi. Fault Diagnosis of Three-Phase Induction Motor: A Review. Optics. 2014;4(1-1):1-8. doi: 10.11648/j.optics.s.2015040101.11

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  • @article{10.11648/j.optics.s.2015040101.11,
      author = {Malik Abadulrazzaq Alsaedi},
      title = {Fault Diagnosis of Three-Phase Induction Motor: A Review},
      journal = {Optics},
      volume = {4},
      number = {1-1},
      pages = {1-8},
      doi = {10.11648/j.optics.s.2015040101.11},
      url = {https://doi.org/10.11648/j.optics.s.2015040101.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.optics.s.2015040101.11},
      abstract = {Now a days the use of Condition Monitoring of electrical machines are increasing due to its potential to reduce operating costs, enhance the reliability of operation and improve service to customers. Different alternatives to detect and diagnose faults in induction machines have been proposed and implemented in the last years. These new alternatives are characterized by an on-line and non-invasive feature, that is to say, the capacity to detect faults while the machine is working and the capacity to work sensor less. These characteristics, obtained by the new techniques, distinguish them from the traditional ones, which, in most cases, need that the machine which is being analyzed is not working to do the diagnosis. The main purpose of this article is to revise the main alternatives in the detection of faults in induction machines and compare their contributions according to the information they require for the diagnosis, the number and relevance of the faults that can be detected, the speed to anticipate a fault and the accuracy in the diagnosis. and to identify various such diagnosis techniques that can be applied for automatic condition monitoring of induction motors and can be extended easily to other electrical machines also.},
     year = {2014}
    }
    

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    T1  - Fault Diagnosis of Three-Phase Induction Motor: A Review
    AU  - Malik Abadulrazzaq Alsaedi
    Y1  - 2014/11/29
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    UR  - https://doi.org/10.11648/j.optics.s.2015040101.11
    AB  - Now a days the use of Condition Monitoring of electrical machines are increasing due to its potential to reduce operating costs, enhance the reliability of operation and improve service to customers. Different alternatives to detect and diagnose faults in induction machines have been proposed and implemented in the last years. These new alternatives are characterized by an on-line and non-invasive feature, that is to say, the capacity to detect faults while the machine is working and the capacity to work sensor less. These characteristics, obtained by the new techniques, distinguish them from the traditional ones, which, in most cases, need that the machine which is being analyzed is not working to do the diagnosis. The main purpose of this article is to revise the main alternatives in the detection of faults in induction machines and compare their contributions according to the information they require for the diagnosis, the number and relevance of the faults that can be detected, the speed to anticipate a fault and the accuracy in the diagnosis. and to identify various such diagnosis techniques that can be applied for automatic condition monitoring of induction motors and can be extended easily to other electrical machines also.
    VL  - 4
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Author Information
  • Dept. of Electrical, Faculty of Engineering, University of Misan, Amarah, Iraq

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