A multi-agent fault detection system for wind turbine defect recognition and diagnosis

Ammar Samir Abd Elazim Zaher, S.D.J. McArthur

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

60 Citations (Scopus)


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.
Original languageEnglish
Title of host publication2007 IEEE Lausanne Powertech Proceedings
Place of PublicationNew York
Number of pages6
ISBN (Print)9781424421893
Publication statusPublished - 2007
EventIEEE Lausanne Powertech - Lausanne, Switzerland
Duration: 1 Jul 20075 Jul 2007


ConferenceIEEE Lausanne Powertech


  • power generation economics , Power system economics
  • wind turbines
  • wind farms
  • sensor systems
  • artificial intelligence
  • degradation
  • fault detection
  • fault diagnosis
  • intelligent sensors
  • multi-agent
  • fault detection system
  • wind turbine
  • defect recognition
  • diagnosis


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