• DocumentCode
    2874249
  • Title

    Research on fault diagnosis method of high-voltage circuit breaker based on fuzzy neural network data fusion

  • Author

    Hongxia, Miao ; Honghua, Wang

  • Author_Institution
    Key Lab. of Power Transm., Distrib. & Power Saving Technol., Changzhou, China
  • Volume
    11
  • fYear
    2010
  • fDate
    22-24 Oct. 2010
  • Abstract
    High-voltage circuit breakers are important electrical equipments which play the role of protection and control in the power network. In order to make the power system operate in a stable and reliable way, it is of great significance to make online fault diagnosis. This paper introduced the method of feature level data fusion using fuzzy neural network, and applied it into the fault diagnosis of high-voltage breakers. The results of the diagnosis showed that the model had good fault identification capability, it could deal very well with both the uncertain knowledge and ambiguous data, as well as improve the accuracy of fault diagnosis.
  • Keywords
    circuit breakers; fault diagnosis; fuzzy neural nets; power engineering computing; sensor fusion; electrical equipments; feature level data fusion; fuzzy neural network data fusion; high-voltage breakers; high-voltage circuit breakers; online fault diagnosis; power system; Artificial neural networks; Biological neural networks; Circuit breakers; Circuit faults; Fault diagnosis; Fuzzy neural networks; Training; High-voltage circuit breaker; data fusion; fault diagnosis; fuzzy neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Application and System Modeling (ICCASM), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-7235-2
  • Electronic_ISBN
    978-1-4244-7237-6
  • Type

    conf

  • DOI
    10.1109/ICCASM.2010.5623219
  • Filename
    5623219