Load analysis of wind turbine blade model based on digital image correlation method

Yaoyao Qing; Qiancheng Zhao; Chao Shu

doi:10.1117/12.2548706

13 November 2019 Load analysis of wind turbine blade model based on digital image correlation method

Yaoyao Qing, Qiancheng Zhao, Chao Shu

Proceedings Volume 11343, Ninth International Symposium on Precision Mechanical Measurements; 113431C (2019) https://doi.org/10.1117/12.2548706
Event: International Symposium on Precision Mechanical Measurements 2019, 2019, Chongqing, China

Abstract

In this paper, an optical measurement method based on three-dimensional digital image correlation (3D-DIC) is described for load analysis of wind turbine blades. Author measured full-field strain and displacement fields of wind turbine blade model under different loads by the method and studied the deformation of the wind turbine blade model under different loads. In addition, the author evaluated the displacement accuracy of 3D-DIC method. Results show that 3D-DIC method can directly analyze the deformation of wind turbine blade model, and the displacement accuracy meets standards. At the same time, the results of load analysis will provide a theoretical basis for the load study of wind turbine blade in the future.

Citation Download Citation

Yaoyao Qing, Qiancheng Zhao, and Chao Shu "Load analysis of wind turbine blade model based on digital image correlation method", Proc. SPIE 11343, Ninth International Symposium on Precision Mechanical Measurements, 113431C (13 November 2019); https://doi.org/10.1117/12.2548706

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available