• DocumentCode
    2913645
  • Title

    ANN approach for condition monitoring of power transformers using DGA

  • Author

    Sarma, D. V S S Siva ; Kalyani, G.N.S.

  • Author_Institution
    Dept. of Electr. Eng., Nat. Inst. of Technol., India
  • Volume
    C
  • fYear
    2004
  • fDate
    21-24 Nov. 2004
  • Firstpage
    444
  • Abstract
    Power transformer being a major apparatus in a power system, monitoring of its in-service behavior is necessary to avoid catastrophic failures, costly outages. Dissolved gas analysis (DGA) is an important tool for transformer fault diagnosis. The ratio methods used in the DGA have an advantage that they are independent of volume of gases involved. But the main draw back of the ratio methods is that they fail to cover all ranges of data. ANN approach is adopted as a remedy for the drawback of ratio methods in this paper.
  • Keywords
    condition monitoring; fault diagnosis; neural nets; power engineering computing; power transformers; ANN; DGA; condition monitoring; dissolved gas analysis; fault diagnosis; power transformers; Breakdown voltage; Condition monitoring; Dissolved gas analysis; Fault diagnosis; Gases; Petroleum; Power system reliability; Power transformers; Testing; Thermal stresses;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 2004. 2004 IEEE Region 10 Conference
  • Print_ISBN
    0-7803-8560-8
  • Type

    conf

  • DOI
    10.1109/TENCON.2004.1414803
  • Filename
    1414803