• DocumentCode
    1708253
  • Title

    Power transformer fault diagnosis based on immune evolutionary clustering algorithm

  • Author

    Hong-xia, Xie ; Li-ping, Shi

  • Volume
    2
  • fYear
    2010
  • Abstract
    In this paper, Fuzzy C-Means (FCM) algorithm is combined with the immune evolutionary algorithm to propose a new method which can be applied to transformer fault diagnosis. First, the paper makes attributes reduction in decision table with the use of rough set, then the continuous attributes in the decision table use immune evolutionary clustering algorithm for discrete processing, and then builds transformer fault diagnosis system. Experiments show that the transformer fault diagnosis system has the feasibility and high accuracy.
  • Keywords
    evolutionary computation; fault diagnosis; fuzzy set theory; pattern clustering; power engineering computing; power transformers; rough set theory; decision table; discrete processing; fuzzy C-Means algorithm; immune evolutionary clustering algorithm; power transformer fault diagnosis; rough set theory; Clustering algorithms; Discharges; Fault diagnosis; Immune system; Power transformers; Set theory; Signal processing algorithms; Fault Diagnosis; Fuzzy Cluster; Immune Evolutionary; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Systems (ICSPS), 2010 2nd International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4244-6892-8
  • Electronic_ISBN
    978-1-4244-6893-5
  • Type

    conf

  • DOI
    10.1109/ICSPS.2010.5555225
  • Filename
    5555225