Fault Monitoring Method of Wind Turbine Main Bearing

doi:10.16450/j.cnki.issn.1004-6801.2021.02.019

CORC > 兰州理工大学 > 兰州理工大学

	Fault Monitoring Method of Wind Turbine Main Bearing
	Zheng, Yuqiao; Wei, Jianfeng; Zhu, Kai; Dong, Bo
刊名	Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis
	2021-04-01
卷号	41 期号:2 页码:341-347 and 415
关键词	Bearings (machine parts) Forecasting Linear regression Monitoring Sliding mode control Statistics Support vector machines Support vector regression Wind turbines Change of temperatures Combination forecasting models Determination coefficients Mean and standard deviations Multiple linear regression models Multivariate linear regression model Sliding window methods Support vector machine regressions
ISSN号	10046801
DOI	10.16450/j.cnki.issn.1004-6801.2021.02.019
英文摘要	Aiming to the problem that high cost and error of traditional fault monitoring method, a fault monitoring method is proposed based on the temperature model for fault monitoring of the wind turbine main bearings. The multiple linear regression model, grey model, support vector machine regression model and their combination forecasting model of main bearing temperature under normal operation are established respectively. Based on the combined prediction model, the sliding window method is introduced to analyse the change of temperature residual mean and standard deviation in the faulty condition of the main bearing. The failure of the main bearing is judged by comparing the confidence interval of the mean value or standard deviation of temperature residual with the set critical value. The results indicate that, the determination coefficient of the main bearing temperature combination forecasting model value is 0.049 3, 0.002 7 and 0.000 2 higher than that of the multivariate linear regression model, the grey prediction model and the support vector machine regression model, the combination forecasting model by introducing a sliding window method can reflect the abnormal situation of main bearing temperature in time, which provides high-precision monitoring of the main bearing fault state and formulating scientific and healthy maintenance strategy. © 2021, Editorial Department of JVMD. All right reserved.
语种	英语
出版者	Nanjing University of Aeronautics an Astronautics
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/150726]
专题	兰州理工大学
作者单位	School of Mechanical and Electronical Engineering, Lanzhou University of Technology, Lanzhou; 730050, China
推荐引用方式 GB/T 7714	Zheng, Yuqiao,Wei, Jianfeng,Zhu, Kai,et al. Fault Monitoring Method of Wind Turbine Main Bearing[J]. Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis,2021,41(2):341-347 and 415.
APA	Zheng, Yuqiao,Wei, Jianfeng,Zhu, Kai,&Dong, Bo.(2021).Fault Monitoring Method of Wind Turbine Main Bearing.Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis,41(2),341-347 and 415.
MLA	Zheng, Yuqiao,et al."Fault Monitoring Method of Wind Turbine Main Bearing".Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis 41.2(2021):341-347 and 415.