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2020 , Vol. 25 >Issue 6: 755 - 761

DOI: https://doi.org/10.1007/s12204-020-2174-3

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

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  • (School of Mechanical and Electronical Engineering, Lanzhou University of Technology, Lanzhou 730050, China)
     

Online published: 2020-11-26

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Abstract

 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.

Key words： composite wind turbine blade; accelerated degradation testing (ADT); accelerated model (AM);
full-scale fatigue testing; blade stiffness; lifetime prediction

Cite this article

KOU Haixia, AN Zongwen, MA Qiang, GUO Xu . Lifetime Prediction of Wind Turbine Blade Based on Full-Scale Fatigue Testing  [J]. Journal of Shanghai Jiaotong University(Science), 2020 , 25(6) : 755 -761 . DOI: 10.1007/s12204-020-2174-3

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