A diagnostic knowledge model of wind turbine fault

Hongwei Wang, Wei Liu, Zhanli Liu

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


    With the development of the wind power industry, wind power has become one of the main green generation energy. At the same time, with the wind power installed capacity increasing, the failure rate gradually growth. As wind turbine is a complex electromechanical equipment, the fault diagnosis for this kind of equipment is also a complicated process. Focused on the current shortage of fault diagnosis knowledge representation, this paper proposes a diagnostic knowledge model for wind turbine and also elaborates the model structure definition with a target to ensure the accuracy of fault diagnosis. Besides, this model can also offer assistance reference model for researchers in related fields to develop advanced methods for sharing and reuse of diagnostic knowledge.
    Original languageEnglish
    Title of host publicationIntelligent Robotics and Applications
    Subtitle of host publication10th International Conference, ICIRA 2017, Wuhan, China, August 16–18, 2017, Proceedings, Part III
    EditorsY. Huang, H. Wu, H. Liu, Z. Yin
    Number of pages11
    ISBN (Electronic)978-3319652986
    ISBN (Print)978-3319652979
    Publication statusPublished - Sept 2017
    EventInternational Conference on Intelligent Robotics and Applications (ICIRA) - Wuhan, China
    Duration: 16 Aug 201718 Aug 2017

    Publication series

    NameLecture Notes in Computer Science
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    ConferenceInternational Conference on Intelligent Robotics and Applications (ICIRA)


    • wind turbine
    • fault diagnosis
    • knowledge model


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