• DocumentCode
    3416099
  • Title

    Application of rough set and genetic algorithm to transformer fault diagnosis

  • Author

    Zhu, Ji ; Yu, Ying

  • Author_Institution
    Dept. of Autom., Shanghai Univ., Shanghai, China
  • fYear
    2011
  • fDate
    19-21 Oct. 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A genetic algorithm combined with theories of rough set is proposed in the process of fault diagnosis of power transformer. Then by the process of value reducing, the fault diagnosis rules are extracted from the minimal decision table obtained from the algorithm. Besides, the feasibility of the generalized rules for power transformer fault diagnosis and the efficiency of the algorithm are illustrated with two specific examples.
  • Keywords
    fault diagnosis; genetic algorithms; power transformers; rough set theory; decision table; fault diagnosis process; genetic algorithm; power transformer; rough set theories; transformer fault diagnosis; Fault diagnosis; Gases; Genetic algorithms; Hydrocarbons; Information systems; Oil insulation; Power transformers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computational Intelligence (IWACI), 2011 Fourth International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-61284-374-2
  • Type

    conf

  • DOI
    10.1109/IWACI.2011.6159963
  • Filename
    6159963
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3416099