• DocumentCode
    3393553
  • Title

    Intelligent multi-agent approach to fault location and diagnosis on railway 10kv automatic blocking and continuous power lines

  • Author

    Zhengyou, He ; Qian, Wang ; Qingquan, Qian

  • Author_Institution
    Inst. of Electrification & Autom., Southwest Jiaotong Univ., Chengdu, China
  • fYear
    2002
  • fDate
    6-7 Nov. 2002
  • Firstpage
    336
  • Lastpage
    341
  • Abstract
    This paper discusses the intelligent multi-agent technology, and proposes an intelligent multi-agent based accurate fault location detection and fault diagnosis system applied in 10kv automatic blocking and continuous power transmission lines along the railway. Agents are software processes capable of searching for information in the networks, interacting with pieces of equipment and performing tasks on behalf of their owner(device). Moreover, they are autonomous and cooperative. Intelligent agents also have the capability to learn as the power supply network topology or environment changed. The system architecture is proposed, the features of each agents are described. Analysis brings forth the merits of this fault location and diagnosis system.
  • Keywords
    fault diagnosis; fault location; learning (artificial intelligence); multi-agent systems; power engineering computing; power transmission faults; power transmission lines; railways; automatic blocking; continuous power transmission lines; cooperative agents; fault diagnosis; fault location; intelligent multi-agent approach; learning; power supply network topology; railway; system architecture; Electrical fault detection; Fault detection; Fault diagnosis; Fault location; Intelligent agent; Network topology; Power supplies; Power transmission lines; Rail transportation; Software performance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Autonomous Decentralized System, 2002. The 2nd International Workshop on
  • Print_ISBN
    0-7803-7624-2
  • Type

    conf

  • DOI
    10.1109/IWADS.2002.1194694
  • Filename
    1194694