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A Review of Fault Diagnosis, Status Prediction, and Evaluation Technology for Wind Turbines

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  • Fanghong Zhang

    (The National Center for Applied Mathematics in Chongqing, Chongqing Normal University, Chongqing 401331, China)

  • Mingsong Chen

    (The National Center for Applied Mathematics in Chongqing, Chongqing Normal University, Chongqing 401331, China)

  • Yuze Zhu

    (The National Center for Applied Mathematics in Chongqing, Chongqing Normal University, Chongqing 401331, China)

  • Kai Zhang

    (CSIC Haizhuang Windpower Co., Ltd., Chongqing 401122, China)

  • Qingan Li

    (University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

With the rapid development and increasing energy production capacity of high-power wind turbines, a corresponding increase in maintenance requirements has been observed. Reducing the failure rate of wind turbines is a critical objective, alongside decreasing affiliated operation and maintenance costs. This review focuses on the status monitoring, fault diagnosis, fault prediction, and status evaluation of wind turbines. The early fault diagnosis of wind turbines is explored with regard to existing condition monitoring technology. Moreover, the current mathematics-based fault diagnosis and smart fault diagnosis technologies are further explored. Through comprehensive investigation, this paper summarizes the research status of wind turbine fault prediction and complete machine status evaluation, conclusively presenting relevant research points and trends in the fault diagnosis, fault prediction, and status assessment of high-power wind turbines.

Suggested Citation

  • Fanghong Zhang & Mingsong Chen & Yuze Zhu & Kai Zhang & Qingan Li, 2023. "A Review of Fault Diagnosis, Status Prediction, and Evaluation Technology for Wind Turbines," Energies, MDPI, vol. 16(3), pages 1-15, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1125-:d:1041464
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    References listed on IDEAS

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    1. Amirat, Y. & Benbouzid, M.E.H. & Al-Ahmar, E. & Bensaker, B. & Turri, S., 2009. "A brief status on condition monitoring and fault diagnosis in wind energy conversion systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2629-2636, December.
    2. Si, Xiao-Sheng & Wang, Wenbin & Hu, Chang-Hua & Zhou, Dong-Hua, 2011. "Remaining useful life estimation - A review on the statistical data driven approaches," European Journal of Operational Research, Elsevier, vol. 213(1), pages 1-14, August.
    3. Zheng Xiang, 2017. "Note from the Editor," Information Technology & Tourism, Springer, vol. 17(2), pages 143-144, June.
    4. Hameed, Z. & Hong, Y.S. & Cho, Y.M. & Ahn, S.H. & Song, C.K., 2009. "Condition monitoring and fault detection of wind turbines and related algorithms: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(1), pages 1-39, January.
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