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Crack Identification of Plates Using Genetic Algorithm

机译:基于遗传算法的钢板裂纹识别

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摘要

In this paper, a method for identifying of a crack in a plate that uses a genetic algorithm (GA) based on changes in natural frequencies is presented. To calculate the natural frequencies of the cracked plates, a FEM (Finite Element Method) program, which is based on the BFM (Bogner, Fox and Schmidt) model, is developed since the accuracy of the forward solver is important. In the analysis, two types of cracks, i.e., internal and edge cracks are considered. To identify the crack location and the depth from frequency measurements, the width and position of the crack in a plate are coded into a fixed-length binary digit string. Using GA, the square sum of residuals between the measured data and the calculated data is minimized in the identification process and thus the crack is identified. To avoid a high calculation cost, the response surface method (RSM) is also adopted in the minimizing process. The combination of GA and RSM makes the identification more effective and robust. The applicability of the proposed method is confirmed by the results of numerical simulation.
机译:在本文中,提出了一种基于自然频率变化的使用遗传算法(GA)的钢板裂纹识别方法。为了计算裂纹板的固有频率,由于前向求解器的精度很重要,因此开发了基于BFM(Bogner,Fox和Schmidt)模型的FEM(有限元方法)程序。在分析中,考虑了两种类型的裂纹,即内部裂纹和边缘裂纹。为了从频率测量中确定裂纹的位置和深度,将板中裂纹的宽度和位置编码为固定长度的二进制数字串。使用GA,可以在识别过程中将测量数据和计算数据之间的残差平方和最小化,从而识别出裂纹。为了避免高昂的计算成本,在最小化过程中还采用了响应面法(RSM)。 GA和RSM的结合使识别更加有效和可靠。数值仿真结果证实了该方法的适用性。

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