Physics-based data analysis for wind turbine condition monitoring

被引:6
|
作者
Luo H. [1 ,2 ]
机构
[1] National Institute of Clean-and-Low-Carbon Energy, Future Science City, Changping District, Beijing
[2] Department of Applied Mechanics, University of Science and Technology Beijing, 30 Xueyuan Road, Haidian District, Beijing
来源
Clean Energy | 2017年 / 1卷 / 01期
关键词
Bearing damage detection; Condition monitoring; Drivetrain; Gear damage detection; Gearbox kinematics; Physics-based data analytics; Vibration analysis; Wind turbine;
D O I
10.1093/ce/zkx005
中图分类号
学科分类号
摘要
This article presents methodologies for improving wind turbine condition monitoring using physics-based data analysis techniques. The unique operating conditions of the wind turbine drivetrain are described, and the complex kinematics of the gearbox is analyzed in detail. The pros and cons of the current wind turbine condition monitoring system (CMS) are evaluated. To improve the wind turbine CMS capability, it is suggested to use linear models with unsteady excitations, instead of using nonlinear and nonstationary process models, when dealing the wind turbine dynamics response model. An analysis is undertaken of the damage excitation mechanisms cause for various components in a gearbox, especially for those associated with lower-speed shafts. Physics (mechanics)-based data analysis methods are presented for different component damage excitation mechanisms. Validation results, using the wind farm and manufacturing floor data, are reported. © The Author 2017. Published by Oxford University Press on behalf of National Institute of Clean-and-Low-Carbon Energy.
引用
收藏
页码:4 / 22
页数:18
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