Please use this identifier to cite or link to this item: https://doi.org/10.1115/OMAE2010-20627
Title: System identification of jack-up platform by spectral analysis
Authors: Wang, X.M.
Koh, C.G. 
Thanh, T.N.
Zhang, J. 
Issue Date: 2010
Source: Wang, X.M.,Koh, C.G.,Thanh, T.N.,Zhang, J. (2010). System identification of jack-up platform by spectral analysis. Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE 1 : 411-420. ScholarBank@NUS Repository. https://doi.org/10.1115/OMAE2010-20627
Abstract: For the purpose of structural health monitoring (SHM), it is beneficial to develop a robust and accurate numerical strategy so as to identify key parameters of offshore structures. In this regard, it is difficult to use time-domain methods as the time history of wave load is not available unless output-only methods can be developed. Alternatively, spectral analysis widely used in offshore engineering to predict structural responses due to random wave conditions can be used. Thus the power spectral density (PSD) of structural response may be more appropriate than time history of structural responses in defining the objective (fitness) function for system identification of offshore structures. By minimizing PSD differences between measurements and simulations, the proposed numerical strategy is completely carried out in frequency domain, which can avoid inherent problems rising from random phase angles and unknown initial conditions in time domain. A jack-up platform is studied in the numerical study. A search space reduction method (SSRM) incorporating the use of genetic algorithms (GA) as well as a substructure approach are adopted to improve the accuracy and efficiency of identification. As a result, the stiffness parameters of jack-up legs can be well identified even under fairly noisy conditions. Copyright © 2010 by ASME.
Source Title: Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE
URI: http://scholarbank.nus.edu.sg/handle/10635/50806
ISBN: 9780791849095
DOI: 10.1115/OMAE2010-20627
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