Application of Finite-Element Model Updating in Damage Detection of Offshore Jacket Platforms using Particle Swarm Optimization with Noisy Modal Data
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Offshore jacket platforms are one of the most motivating structures for damage detection due to their importance and productivity. Model updating, which is applied as a powerful tool for discovering damage intense and location in several kinds of structures, is a process for minimizing the difference between similar features of the model and real structure. In this study, the modal data including natural frequencies and mode shapes are intended as target features which can be extracted from sensors located in the structure. However, the measured data is expected to be noisy. To minimize the error, particle swarm optimization is used for its abilities in coping with complex search areas. The efficiency of this method is evaluated on several damage cases. The results show that this method can detect the damage of this structure satisfactorily even if modal data is not precisely obtained in the way that the accuracy of achieved results will diminish by higher noise levels.
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