Continuous strain prediction for fatigue assessment of an offshore wind turbine using Kalman filtering techniques
Maes, K.; De Roeck, G.; Lombaert, G.; Iliopoulos, A.; Van Hemelrijck, D.; Devriendt, C.; Guillaume, P. (2015). Continuous strain prediction for fatigue assessment of an offshore wind turbine using Kalman filtering techniques, in: 2015 IEEE workshop on environmental, energy and structural monitoring systems: proceedings. pp. 44-49
In: (2015). 2015 IEEE workshop on environmental, energy and structural monitoring systems: proceedings. IEEE: USA. ISBN 978-1-4799-8214-1. xiii, 264 pp., more
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Document type: Conference paper
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| Authors | | Top |
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- Van Hemelrijck, D., more
- Devriendt, C., more
- Guillaume, P., more
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| Abstract |
Offshore wind turbines are exposed to continuous wind and wave excitation. The continuous monitoring of high periodic strains at critical locations is important to assess the remaining lifetime of the structure. Some of the critical locations are not accessible for direct strain measurements, e.g. at the mud-line, 30 meter below the water level. Response estimation techniques can then be used to estimate the response at unmeasured locations from a limited set of response measurements and a system model. This paper shows the application of a Kalman filtering algorithm for the estimation of strains in the tower of an offshore monopile wind turbine in the Belgian North Sea. The algorithm makes use of a model of the structure and a limited number of response measurements for the prediction of the strain responses. It is shown that the Kalman filter algorithm is able to account for the different types of excitation acting on the structure in operational conditions, in this way yielding accurate strain estimates that can be used for continuous fatigue assessment of the wind turbine. |
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