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Dynamic strain estimation for fatigue assessment of an offshore monopile wind turbine using filtering and modal expansion algorithms
Maes, K.; Iliopoulos, A.; Weijtjens, W.; Devriendt, C.; Lombaert, G. (2016). Dynamic strain estimation for fatigue assessment of an offshore monopile wind turbine using filtering and modal expansion algorithms. Mechanical Systems and Signal Processing 76-77: 592-611. https://dx.doi.org/10.1016/j.ymssp.2016.01.004
In: Mechanical Systems and Signal Processing. Elsevier: Amsterdam. ISSN 0888-3270; e-ISSN 1096-1216, more
Peer reviewed article  

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Keyword
    Marine/Coastal
Author keywords
    Response estimation; Kalman filter; Joint input-state estimation; Modalexpansion; System identification; Offshore wind turbine

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Abstract
    Offshore wind turbines are exposed to continuous wind and wave excitation. The monitoring of high periodic strains at critical locations is important to assess the remaining lifetime of the structure. At some critical locations below the water level, direct measurements of the strains are not feasible. Response estimation techniques can then be used to estimate the strains from a limited set of response measurements and a system model. This paper compares a Kalman filtering algorithm, a joint input-state estimation algorithm, and a modal expansion algorithm, for the estimation of dynamic strains in the tower of an offshore monopile wind turbine. The algorithms make use of a model of the structure and a limited number of response measurements for the prediction of the strain responses. The strain signals obtained from the response estimation algorithms are compared to the actual measured strains in the tower.

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