Application of genetic algorithm based finite element model updating in damage detection of offshore jacket platforms

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. To minimize the error, genetic algorithm is used for its abilities in coping with complex search areas in addition to its capabilities to use less simplification than conventional methods. Besides, to avoid obtaining false damage results, a penalty term is added to the objective function. This method is tested on several damage cases successfully. Furthermore, the effect of the application of different number of mode shapes is examined by using first two and five modal data in updating procedure. This examination shows that increasing the number of used modes can improve the efficiency of the method in some cases. Afterward, some useful considerations are suggested to apply this method practically.