• DocumentCode
    2116307
  • Title

    Study on the Transformer Solid Insulation Aging Diagnosis Method

  • Author

    Mu Xueyun ; Yang Qiping ; Wang Jun ; Xu Danfeng

  • Author_Institution
    Sch. of Electr. Power & Autom. Eng., Shanghai Univ. of Electr. Power, Shanghai, China
  • fYear
    2010
  • fDate
    28-31 March 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper state that several different methods of oil transformer solid insulation aging are described and the dissolved gas in oil contents (including CO, CO2 and furfural) are analyzed. The appreciation of ANN in transformers diagnosis solid insulation aging is introduced. The feasibility and effectiveness of ANN for transformer insulation aging diagnosis are explained by some examples.
  • Keywords
    ageing; neural nets; power engineering computing; transformer insulation; artificial neural nets; dissolved gas; oil contents; transformer solid insulation aging diagnosis; Aging; Dielectrics and electrical insulation; Gas insulation; Oil insulation; Petroleum; Plastic insulation; Polymers; Power transformer insulation; Power transformers; Solids;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-4812-8
  • Electronic_ISBN
    978-1-4244-4813-5
  • Type

    conf

  • DOI
    10.1109/APPEEC.2010.5449352
  • Filename
    5449352
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2116307