Review of Fault Diagnosis Methods for Large Wind Turbines

被引：0
|
作者：
Long X. [1 ]
Yang P. [2 ]
Guo H. [1 ]
Wu X. [3 ]
机构：
[1] School of Electric Power, South China University of Technology, Guangzhou, 510640, Guangdong Province
[2] Guangdong Key Laboratory of Clean Energy Technology, South China university of Technology, Guangzhou, 511548, Guangdong Province
[3] Hunan New Energy Development Co., LTD., Guodian Power, Changsha, 410016, Hunan Province
来源：
Long, Xiafei (304010851@qq.com) | 1600年 / Power System Technology Press卷 / 41期
关键词：
Fault diagnosis; Fault diagnosis system; Qualitative diagnosis; Quantitative diagnosis; Wind turbines;
D O I：
10.13335/j.1000-3673.pst.2016.3326
中图分类号：
学科分类号：
摘要：
Fault diagnosis technology is the key for guaranteeing operation efficiency and reducing operation cost in wind farms. Based on qualitative and quantitative diagnoses, the fault diagnosis technology of wind turbines is reviewed in this paper, and existing fault diagnosis methods and fault diagnosis systems are analyzed. Each type of fault diagnosis methods is further subdivided. Basic ideas, advantages, disadvantages, applicable conditions and applications of these methods are described in detail. Possible future development direction in this area is pointed out. © 2017, Power System Technology Press. All right reserved.
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页码：3480 / 3491
页数：11
相关论文
共 105 条
  • [1] Wymore M.L., Van-Dam J.E., Ceylan H., Et al., A survey of health monitoring systems for wind turbines, Renewable and Sustainable Energy Reviews, 52, pp. 976-990, (2015)
  • [2] Djurovic S., Crabtree C.J., Tavner P.J., Et al., Condition monitoring of wind turbine induction generators with rotor electrical asymmetry, IET Renewable Power Generation, 6, 4, pp. 207-216, (2012)
  • [3] Kandukuri S.T., Klausen A., Karimi H.R., Et al., A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management, Renewable and Sustainable Energy Reviews, 53, pp. 697-708, (2016)
  • [4] Huang L., Cao J., Zhang K., Et al., Status and prospects on operation and maintenance of offshore wind turbines, Proceedings of the CSEE, 36, 3, pp. 729-737, (2016)
  • [5] Hang J., Zhang J., Cheng M., Et al., An overview of condition monitoring and fault diagnostic for wind energy conversion system, Transactions of China Electrotechnical Society, 28, 4, pp. 261-271, (2013)
  • [6] Hahn B., Durstewitz M., Rohrig K., Reliability of Wind Turbines, pp. 329-332, (2007)
  • [7] Li H., Hu Y., Li Y., Et al., Overview of condition monitoring and fault diagnosis for grid-connected high-power wind turbine unit, Electric Power Automation Equipment, 36, 1, pp. 6-16, (2016)
  • [8] Su Z., Tang B., Liu Z., Et al., Multi-fault diagnosis for rotating machinery based on orthogonal supervised linear local tangent space alignment and least square support vector machine, Neurocomputing, 157, pp. 208-222, (2015)
  • [9] Xiao Y., Wang K., He G., Et al., Fuzzy comprehensive evaluation for operating condition of large-scale wind turbines based on trend predication, Proceedings of the CSEE, 34, 13, pp. 103-109, (2014)
  • [10] Fan Z., Li H., A hybrid approach for fault diagnosis of planetary bearings using an internal vibration sensor, Measurement, 64, pp. 71-80, (2015)
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