Biaxial Dynamic Fatigue Tests of Wind Turbine Blades

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Bürkner, Falko: Biaxial dynamic fatigue tests of wind turbine blades. Stuttgart : Fraunhofer Verlag, 2021, xvi, 167 S. ISBN 978-3-8396-1710-6

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/10903

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Sum total of downloads: 529




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Abstract: 
Testing rotor blades of wind turbines is essential to mitigate financial risks caused by serial damages. Present day uniaxialdynamic tests are time consuming and often inaccurate regarding the applied loading. This thesis proposes a fasterfatigue test method by loading the two primary directions at the same time. In addition, a more realistic test, comparedto uniaxial tests, is accomplished by loading larger areas of the blade cross-sections. To achieve this, an elliptical biaxialdynamic excitation is used. To fulfill the industry requirement for cost effective tests, a relatively simple test setup wasdeveloped, still achieving an elliptical dynamic excitation of the rotor blade. Two methods for an accurate determinationof the applied loadings for dynamic fatigue tests are described. These calibration tests use easily measured values andsimple analysis to achieve accurate test load measurements in a cost-effective way.
License of this version: CC BY 3.0 DE
Document Type: DoctoralThesis
Publishing status: publishedVersion
Issue Date: 2020
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie
Dissertationen

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downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 271 51.23%
2 image of flag of China China 78 14.74%
3 image of flag of United States United States 68 12.85%
4 image of flag of United Kingdom United Kingdom 19 3.59%
5 image of flag of Denmark Denmark 14 2.65%
6 image of flag of Israel Israel 13 2.46%
7 image of flag of Spain Spain 13 2.46%
8 image of flag of No geo information available No geo information available 11 2.08%
9 image of flag of Japan Japan 5 0.95%
10 image of flag of Hong Kong Hong Kong 4 0.76%
    other countries 33 6.24%

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