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Evaluation of different automated operational modal analysis techniques for the continuous monitoring of offshore wind turbines
Devriendt, C.; El-Kafafy, M.; Weijtjens, W.; De Sitter, G.; Guillaume, P. (2014). Evaluation of different automated operational modal analysis techniques for the continuous monitoring of offshore wind turbines, in: Cunha, A. et al. (Ed.) Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 2014. pp. 2239-2246
In: Cunha, A. et al. (Ed.) (2014). Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 2014. European Association for Structural Dynamics (EASD): Portugal. ISBN 978-972-752-165-4. 3889 pp., more

Available in Authors 
Document type: Conference paper

Keyword
    Marine
Author keywords
    monitoring, offshore wind turbine, operational modal analysis, modal parameters estimators, automated

Authors  Top 
  • Devriendt, C., more
  • El-Kafafy, M., more
  • Weijtjens, W., more
  • De Sitter, G., more
  • Guillaume, P., more

Abstract
    This paper will evaluate different automated operational modal analysis techniques for the continuous monitoring of offshore wind turbines. The experimental data has been obtained during a long-term monitoring campaign on an offshore wind turbine in the Belgian North Sea. State-of-the art operational modal analysis techniques and the use of appropriate vibration measurement equipment can provide accurate estimates of natural frequencies, damping ratios and mode shapes of offshore wind turbines. To allow a proper continuous monitoring the methods have been automated and their reliability improved. The advanced modal analysis tools, which will be used, include the poly-reference Least Squares Complex Frequency-domain estimator (pLSCF), commercially known as PolyMAX, the polyreference maximum likelihood estimator (pMLE), and the frequency-domain subspace identification (FSSI) technique. The robustness of these estimators with respect to a possible change in the implementation options that could be defined by the user (e.g. type of polynomial coefficients used, parameter constraint used….) will be investigated. In order to improve the automation of the techniques, an alternative representation for the stabilization charts as well as robust cluster algorithms will be presented.

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