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.
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Foundation item: Supported by the National Natural Science Fundation of China (51079136)(51179179).
Juan Liu was born in 1977. She is a PhD candidate at Ocean University of China. Her current research interests include structure damage diagnosis and VIV of risers.
Weiping Huang was born in 1954. He is a professor at Ocean University of China. His current research interests include damage diagnosis, VIV, and fluid-structure coupled analysis.
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Liu, J., Huang, W. & Shi, X. An improved method of structure damage diagnosis for jacket platforms. J. Marine. Sci. Appl. 10, 485–489 (2011). https://doi.org/10.1007/s11804-011-1095-9
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DOI: https://doi.org/10.1007/s11804-011-1095-9