• DocumentCode
    3102631
  • Title

    Transformer fault diagnosis based on the improved D-S evidence theory

  • Author

    Hou, Yan-dong ; Wang, Xiao-jun ; Wen, Cheng-lin ; Xu, Wei-xing

  • Author_Institution
    Dept. of Electr. Autom., Shanghai Maritime Univ. Shanghai, Shanghai, China
  • Volume
    6
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    3413
  • Lastpage
    3417
  • Abstract
    To overcome the bad performance of marine transformer fault diagnosis, which induced by the reliability of symptom and the correlation with each other. Based on improved D-S evidence theory, a novel marine transformer fault diagnosis method is proposed in this paper. Firstly, the fault diagnosis model is established based on traditional D-S evidence theory. Secondly, the effective measuring for the reliability of symptom and the correlation with each other is sloved by information entropy and information energy. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
  • Keywords
    entropy; fault diagnosis; reliability; transformers; D-S evidence theory; information energy; information entropy; marine transformer fault diagnosis model; reliability; Automation; Cybernetics; Fault diagnosis; Information entropy; Machine learning; Oil insulation; Power system reliability; Power transformer insulation; Power transformers; Uncertainty; Correlation; D-S evidence theory; Fault diagnosis; Information entropy; Reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2009 International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3702-3
  • Electronic_ISBN
    978-1-4244-3703-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2009.5212787
  • Filename
    5212787