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Study on Transformer Fault Diagnosis Based on Dynamic Fault Tree

Received: 22 November 2015     Published: 24 November 2015
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Abstract

In this paper, according to theoretical diagnosis of fault tree, the author builds a diagnosis model based on dynamic fault tree and illustrates the model’s construction method and diagnosis logic in detail. According to case analysis, compared with conventional fault tree diagnosis, the above-mentioned method is advanced in fault-tolerant ability. Plus, the diagnosis results record some intermediate processes of the diagnosis, with relevant information being returned to the researchers as ideas facilitating further analysis in the event of incomplete information.

Published in Journal of Electrical and Electronic Engineering (Volume 3, Issue 5)
DOI 10.11648/j.jeee.20150305.16
Page(s) 133-138
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), 2015. Published by Science Publishing Group

Keywords

Transformer, Dynamic Fault Tree, Fault-Tolerant Ability, Fault Diagnosis

References
[1] FU Qiang, CHEN Tefang, ZHU Jiaojiao. Transformer Fault Diag-nosis Using Self-adaptive RBF Neural Network Algorithm[J]. High Voltage Engineering, 2012, 38(6): 1368-1375.
[2] CHEN Xiaoqing, LIU Juemin,HUANG Yingwei,FU Bo. Transformer Fault Diagnosis Using Improved Artificial Fish Swarm with Rough Set Algorithm[J]. High Voltage Engineering, 2012, 38(6): 1403-1408.
[3] BAI Cuifen, GAO Wensheng, JIN Lei, YU Wenxuan, ZHU Wenjun. Integrated Diagnosis of Transformer Faults Based on Three-layer Bayesian Network[J]. High Voltage Engineering, 2013, 39(2): 330-335.
[4] Wang Jianyuan, Ji Yanchao. Appliacation of fuzzy petri nets knowledge representation in electric power transformer fault diag-nosis[J]. Proceedings of the CSEE, 2003, 23(3): 121-125.
[5] ZHAO Wenqing, ZHANG Shenglong, NIU Dongxiao. Transformer fault diagnosis based on multi-Agent[J]. Electric Power Automation Equipment, 2011, 31(3): 23-26.
[6] Lei Yaguo. Research on hybrid intelligent technique and its applications in fault diagnosis[D]. Xi’an, China: Xi’an Jiaotong University, 2007.
[7] Xie Jijian, Liu Chengping. Fuzzy mathematics method and its application[M]. Wuhan, China: Huazhong University of Science and Technology Press, 2000.
[8] Lan Jibin, Xu Yang, Huo Liangan, Liu Jiazhong. Research on the Priorities of Fuzzy Analytical Hierarchy Process [J]. Systems Engineering – Theory & Practice, 2006, 26(9):107-112.
[9] SATTY T.L. The analytic hierarchy process.New York, NY, USA: McGraw-Hill Inc, 1980.
[10] Wang Yingluo. Systems engineering[M]. Beijing, China: Machinery Industry Press, 2001.
Cite This Article
  • APA Style

    Fei Peng, Lin Cheng, Kaikai Gu, Zhenbo Du, Jiang Guo. (2015). Study on Transformer Fault Diagnosis Based on Dynamic Fault Tree. Journal of Electrical and Electronic Engineering, 3(5), 133-138. https://doi.org/10.11648/j.jeee.20150305.16

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    ACS Style

    Fei Peng; Lin Cheng; Kaikai Gu; Zhenbo Du; Jiang Guo. Study on Transformer Fault Diagnosis Based on Dynamic Fault Tree. J. Electr. Electron. Eng. 2015, 3(5), 133-138. doi: 10.11648/j.jeee.20150305.16

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    AMA Style

    Fei Peng, Lin Cheng, Kaikai Gu, Zhenbo Du, Jiang Guo. Study on Transformer Fault Diagnosis Based on Dynamic Fault Tree. J Electr Electron Eng. 2015;3(5):133-138. doi: 10.11648/j.jeee.20150305.16

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  • @article{10.11648/j.jeee.20150305.16,
      author = {Fei Peng and Lin Cheng and Kaikai Gu and Zhenbo Du and Jiang Guo},
      title = {Study on Transformer Fault Diagnosis Based on Dynamic Fault Tree},
      journal = {Journal of Electrical and Electronic Engineering},
      volume = {3},
      number = {5},
      pages = {133-138},
      doi = {10.11648/j.jeee.20150305.16},
      url = {https://doi.org/10.11648/j.jeee.20150305.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20150305.16},
      abstract = {In this paper, according to theoretical diagnosis of fault tree, the author builds a diagnosis model based on dynamic fault tree and illustrates the model’s construction method and diagnosis logic in detail. According to case analysis, compared with conventional fault tree diagnosis, the above-mentioned method is advanced in fault-tolerant ability. Plus, the diagnosis results record some intermediate processes of the diagnosis, with relevant information being returned to the researchers as ideas facilitating further analysis in the event of incomplete information.},
     year = {2015}
    }
    

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  • TY  - JOUR
    T1  - Study on Transformer Fault Diagnosis Based on Dynamic Fault Tree
    AU  - Fei Peng
    AU  - Lin Cheng
    AU  - Kaikai Gu
    AU  - Zhenbo Du
    AU  - Jiang Guo
    Y1  - 2015/11/24
    PY  - 2015
    N1  - https://doi.org/10.11648/j.jeee.20150305.16
    DO  - 10.11648/j.jeee.20150305.16
    T2  - Journal of Electrical and Electronic Engineering
    JF  - Journal of Electrical and Electronic Engineering
    JO  - Journal of Electrical and Electronic Engineering
    SP  - 133
    EP  - 138
    PB  - Science Publishing Group
    SN  - 2329-1605
    UR  - https://doi.org/10.11648/j.jeee.20150305.16
    AB  - In this paper, according to theoretical diagnosis of fault tree, the author builds a diagnosis model based on dynamic fault tree and illustrates the model’s construction method and diagnosis logic in detail. According to case analysis, compared with conventional fault tree diagnosis, the above-mentioned method is advanced in fault-tolerant ability. Plus, the diagnosis results record some intermediate processes of the diagnosis, with relevant information being returned to the researchers as ideas facilitating further analysis in the event of incomplete information.
    VL  - 3
    IS  - 5
    ER  - 

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Author Information
  • School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, China

  • School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, China

  • Wuhan Nari Group Corporation of State Grid Electric Power Research Institute, Wuhan, Hubei, China

  • Wuhan Nari Group Corporation of State Grid Electric Power Research Institute, Wuhan, Hubei, China

  • School of Power and Mechanical Engineering, Wuhan University, Wuhan, Hubei, China

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