A Review of Research on Wind Turbine Bearings' Failure Analysis and Fault Diagnosis

被引：41

作者：

Peng, Han ^{[1
]}

Zhang, Hai ^{[1
]}

Fan, Yisa ^{[1
]}

Shangguan, Linjian ^{[1
]}

Yang, Yang ^{[2
]}

机构：

[1] North China Univ Water Resources & Elect Power, Sch Mech Engn, Zhengzhou 450000, Peoples R China

[2] Peter Great St Petersburg Polytech Univ, Inst Mech Engn Mat & Transportat, St Petersburg 195251, Russia

来源：

LUBRICANTS | 2023年 / 11卷 / 01期

关键词：

wind power bearings; bearing failure; fault diagnosis technology; bearing life; ROLLING-CONTACT FATIGUE; ARTIFICIAL NEURAL-NETWORK; WHITE ETCHING CRACKS; MODE DECOMPOSITION; WEAR; GEARBOX; ENERGY; MAINTENANCE; RELIABILITY; SPECTRUM;

D O I：

10.3390/lubricants11010014

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Bearings are crucial components that decide whether or not a wind turbine can work smoothly and that have a significant impact on the transmission efficiency and stability of the entire wind turbine's life. However, wind power equipment operates in complex environments and under complex working conditions over long time periods. Thus, it is extremely prone to bearing wear failures, and this can cause the whole generator set to fail to work smoothly. This paper takes wind turbine bearings as the research object and provides an overview and analysis for realizing fault warnings, avoiding bearing failure, and prolonging bearing life. Firstly, a study of the typical failure modes of wind turbine bearings was conducted to provide a comprehensive overview of the tribological problems and the effects of the bearings. Secondly, the failure characteristics and diagnosis procedure for wind power bearings were examined, as well as the mechanism and procedure for failure diagnosis being explored. Finally, we summarize the application of fault diagnosis methods based on spectrum analysis, wavelet analysis, and artificial intelligence in wind turbine bearing fault diagnosis. In addition, the directions and challenges of wind turbine bearing failure analysis and fault diagnosis research are discussed.

引用

页数：33

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