• DocumentCode
    3414190
  • Title

    Artificial Intelligence Tracing of Inherence Leakage Current between Power Line and Earth

  • Author

    Li Hua-Song ; Kang Wen-Xiong

  • Author_Institution
    Sch. of Inf. Eng., Wuyi Univ., Jiangmen, China
  • Volume
    2
  • fYear
    2010
  • fDate
    23-24 Oct. 2010
  • Firstpage
    272
  • Lastpage
    275
  • Abstract
    The paper proposes an artificial intelligence method to trace inherence leakage current between power line and Earth, which can be used in history records of only one residual current (RC) detection point. Firstly, it gives the common topology structure of residual current detection in Low voltage power line and defines three ingredients in TLCE (Total Leakage Current to Earth): ILCE (Inherence Leakage Current to Earth), TLCES (Total Leakage Current to Earth after Sub-switch) and BLCE (Burst Leakage Current to Earth). Then the paper analyzes the features of those three ingredients of leakage current. Finally, it gives out an artificial intelligence method to trace inherence leakage current which can be used in leakage current alarm threshold adjustment of electric fire prevention system.
  • Keywords
    alarm systems; artificial intelligence; electrical safety; fires; leakage currents; power cables; power engineering computing; burst leakage current; electric fire prevention system; inherence artificial intelligence tracing; leakage current alarm threshold adjustment; leakage current tracing; low voltage power line; residual current detection; topology structure; Artificial intelligence; Earth; Fires; History; Leakage current; Power systems; Sparks; Electric fire; Inherence leakage current; Residual current;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4244-8432-4
  • Type

    conf

  • DOI
    10.1109/AICI.2010.179
  • Filename
    5656456