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Accurate identification of cross-sectional bending stiffness in large-scale wind turbine blades through static loading test

Authors :
Yi Ma
Aiguo Zhou
Jinlei Shi
Yutian Zhu
Lili Ren
Source :
AIP Advances, Vol 13, Iss 9, Pp 095214-095214-12 (2023)
Publication Year :
2023
Publisher :
AIP Publishing LLC, 2023.

Abstract

To ensure the safe and stable operation of wind turbines, it is essential that the blades have sufficient bending stiffness to prevent excessive deflection and tower impact. A method combining static loading test and numerical analysis is proposed to solve the problem of identifying the cross-sectional bending stiffness of actual blades. Two working conditions, namely multi-point static test and single-point static calibration, are considered. A mathematical model of a cantilever beam with an initial small curvature and variable cross section is established. By fitting the deflection measurement data obtained from the static loading test, the deflection differential equation is solved by the finite difference method to obtain expressions for the cross-sectional bending stiffness under large and small deflection. The analysis results of several blade models show that the bending stiffness identification error for most blade sections is less than 10%, confirming the effectiveness of this method. This provides a practical and theoretical basis for the design, analysis, and refinement of test parameters for large-scale blades.

Subjects

Subjects :
Physics
QC1-999

Details

Language :
English
ISSN :
21583226
Volume :
13
Issue :
9
Database :
Directory of Open Access Journals
Journal :
AIP Advances
Publication Type :
Academic Journal
Accession number :
edsdoj.66a20df4f6b448edb9f9938abb3f4f89
Document Type :
article
Full Text :
https://doi.org/10.1063/5.0171042