An improved method of structure damage diagnosis for jacket platforms

Abstract

In the exploitation of ocean oil and gas, many offshore structures may be damaged due to the severe environment, so an effective method of diagnosing structural damage is urgently needed to locate the damage and evaluate its severity. Genetic algorithms have become some of the most important global optimization tools and been widely used in many fields in recent years because of their simple operation and strong robustness. Based on the natural frequencies and mode shapes of the structure, the damage diagnosis of a jacket offshore platform is attributed to an optimization problem and studied by using a genetic algorithm. According to the principle that the structural stiffness of a certain direction can be greatly affected only when the brace bar in the corresponding direction is damaged, an improved objective function was proposed in this paper targeting measurement noise and the characteristics of modal identification for offshore platforms. This function can be used as fitness function of a genetic algorithm, and both numerical simulation and physical model test results show that the improved method may locate the structural damage and evaluate the severity of a jacket offshore platform satisfactorily while improving the robustness of evolutionary searching and the reliability of damage diagnosis.

Keywords

damage diagnosis / genetic algorithm / objective function / mode shape error function

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