Damage detection in an offshore jacket platform using genetic algorithm based finite element model updating with noisy modal data

Offshore jacket platforms are one of the most motivating structures for damage detection due to their importance and productivity. In this study, the application of finite element model updating in damage detection of an offshore jacket platform is investigated. The objective function of this method is based on the measured and analytical modal data, including natural frequencies and mode shapes. However, the measured data is expected to be noisy. Also, to avoid obtaining false damage results, a penalty term is added to the objective function. To update the model, genetic algorithm is utilized as a robust global searching tool. Afterward, the efficiency of this method is evaluated on several damage cases in presence of 0, 1, 2 and 3 percent noise with measured modal data. The results show that this method can detect the damage of this kind of structure satisfactorily even if modal data is not precisely obtained.