Lifetime Prediction of Wind Turbine Blade Based on Full-Scale Fatigue Testing

doi:10.1007/s12204-020-2174-3

CORC > 兰州理工大学 > 兰州理工大学 > 机电工程学院

	Lifetime Prediction of Wind Turbine Blade Based on Full-Scale Fatigue Testing
	Kou, Haixia; An, Zongwen; Ma, Qiang; Guo, Xu
刊名	Journal of Shanghai Jiaotong University (Science)
	2020-12-01
卷号	25 期号:6 页码:755-761
关键词	Fatigue testing Forecasting Stiffness Turbine components Turbomachine blades Wind turbinesAccelerated degradation testing (ADT) Accelerated models Blade stiffness Composite wind turbine blade Full scale fatigue testing Lifetime prediction TK 83
ISSN号	10071172
DOI	10.1007/s12204-020-2174-3
英文摘要	In order to predict the lifetime of products appropriately with long lifetime and high reliability, the accelerated degradation testing (ADT) has been proposed. Composite wind turbine blade is one of the most important components in wind turbine system. Its fatigue cycle is very long in practice. A full-scale fatigue testing is usually used to verify the design of a new blade. In general, the full-scale fatigue testing of blade is accelerated on the basis of the damage equivalent principle. During the full-scale fatigue testing, blade is subjected to higher testing load than normal operating conditions; consequently, the performance degradation of the blade is hastened over time. The full-scale fatigue testing of blade is regarded as a special ADT. According to the fatigue failure criterion, we choose blade stiffness as the characteristic quantity of the blade performance, and propose an accelerated model (AM) for blade on the basis of the theories of ADT. Then, degradation path of the blade stiffness is modeled by using Gamma process. Finally, the lifetime prediction of full-scale megawatt (MW) blade is conducted by combining the proposed AM and blade stiffness degradation model. The prediction results prove the reasonability and validity of this study. This can supply a new approach to predict the lifetime of the full-scale MW blade. © 2020, Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature.
语种	英语
出版者	Shanghai Jiaotong University
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/132364]
专题	机电工程学院
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	Kou, Haixia,An, Zongwen,Ma, Qiang,et al. Lifetime Prediction of Wind Turbine Blade Based on Full-Scale Fatigue Testing[J]. Journal of Shanghai Jiaotong University (Science),2020,25(6):755-761.
APA	Kou, Haixia,An, Zongwen,Ma, Qiang,&Guo, Xu.(2020).Lifetime Prediction of Wind Turbine Blade Based on Full-Scale Fatigue Testing.Journal of Shanghai Jiaotong University (Science),25(6),755-761.
MLA	Kou, Haixia,et al."Lifetime Prediction of Wind Turbine Blade Based on Full-Scale Fatigue Testing".Journal of Shanghai Jiaotong University (Science) 25.6(2020):755-761.