• DocumentCode
    1711403
  • Title

    A Multi-Agent Fault Detection System for Wind Turbine Defect Recognition and Diagnosis

  • Author

    Zaher, A.S. ; McArthur, S.D.J.

  • Author_Institution
    Inst. for Energy & Environ., Univ. of Strathclyde, Glasgow
  • fYear
    2007
  • Firstpage
    22
  • Lastpage
    27
  • Abstract
    This paper describes the use of a combination of anomaly detection and data-trending techniques encapsulated in a multi-agent framework for the development of a fault detection system for wind turbines. Its purpose is to provide early error or degradation detection and diagnosis for the internal mechanical components of the turbine with the aim of minimising overall maintenance costs for wind farm owners. The software is to be distributed and run partly on an embedded microprocessor mounted physically on the turbine and on a PC offsite. The software will corroborate events detected from the data sources on both platforms and provide information regarding incipient faults to the user through a convenient and easy to use interface.
  • Keywords
    fault diagnosis; multi-agent systems; power engineering computing; wind turbines; data-trending techniques; degradation detection; embedded microprocessor; multiagent fault detection system; wind turbine defect recognition-diagnosis; Artificial intelligence; Degradation; Fault detection; Fault diagnosis; Intelligent sensors; Power generation economics; Power system economics; Sensor systems; Wind farms; Wind turbines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Tech, 2007 IEEE Lausanne
  • Conference_Location
    Lausanne
  • Print_ISBN
    978-1-4244-2189-3
  • Electronic_ISBN
    978-1-4244-2190-9
  • Type

    conf

  • DOI
    10.1109/PCT.2007.4538286
  • Filename
    4538286