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An Improved Method of Structure Damage Diagnosis for Jacket Platforms

机译:夹克平台结构损伤诊断的一种改进方法

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摘要

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.
机译:在海洋石油和天然气的开采中,许多恶劣的环境可能会损坏近海结构,因此迫切需要一种有效的结构损伤诊断方法来定位损伤并评估其严重性。遗传算法已成为最重要的一些算法全局优化工具由于操作简单,鲁棒性强,近年来在许多领域得到了广泛的应用。基于结构的固有频率和振型,基于优化问题对海上平台的损伤诊断进行了研究。根据一定的原理,只有当相应方向的支撑杆损坏时,才能较大地影响某一方向的结构刚度,提出了一种针对测量噪声和噪声特性的改进目标函数。海上平台的模态识别,该功能可用作遗传算法以及数值模拟和物理模型试验结果均表明,改进的方法可以较好地定位结构损伤,评估套管海上平台的严重性,同时提高了演化搜索的鲁棒性和损伤诊断的可靠性。

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  • 来源
    《船舶与海洋工程学报(英文版)》 |2011年第4期|485-489|共5页
  • 作者单位

    Engineering Institute, Ocean University of China, Qingdao 266071, China;

    Construction Engineering Institute, Agricultural University of Qingdao, Qingdao 266009,China;

    Engineering Institute, Ocean University of China, Qingdao 266071, China;

    Engineering Institute, Ocean University of China, Qingdao 266071, China;

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  • 入库时间 2022-08-18 01:12:17
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