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Model Updating Method Based on Kriging Model for Structural Dynamics

机译:基于Kriging模型的结构动态模型更新方法

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Model updating in structural dynamics has attracted much attention in recent decades. And high computational cost is frequently encountered during model updating. Surrogate model has attracted considerable attention for saving computational cost in finite element model updating (FEMU). In this study, a model updating method using frequency response function (FRF) based on Kriging model is proposed. The optimal excitation point is selected by using modal participation criterion. Initial sample points are chosen via design of experiment (DOE), and Kriging model is built using the corresponding acceleration frequency response functions. Then, Kriging model is improved via new sample points using mean square error (MSE) criterion and is used to replace the finite element model to participate in optimization. Cuckoo algorithm is used to obtain the updating parameters, where the objective function with the minimum frequency response deviation is constructed. And the proposed method is applied to a plane truss model FEMU, and the results are compared with those by the second-order response surface model (RSM) and the radial basis function model (RBF). The analysis results showed that the proposed method has good accuracy and high computational efficiency; errors of updating parameters are less than 0.2%; damage identification is with high precision. After updating, the curves of real and imaginary parts of acceleration FRF are in good agreement with the real ones.
机译:近几十年来,结构动态的模型更新引起了很多关注。在模型更新期间经常遇到高计算成本。代理模型引起了可观的关注,以节省有限元模型更新(FEMU)的计算成本。在本研究中,提出了一种基于Kriging模型的频率响应函数(FRF)的模型更新方法。通过使用模态参与标准选择最佳激励点。通过实验(DOE)设计选择初始采样点,并且使用相应的加速度响应函数构建Kriging模型。然后,使用均线误差(MSE)标准,通过新的采样点改进Kriging模型,用于替换有限元模型以参与优化。 Cuckoo算法用于获得更新参数,其中构造了具有最小频率响应偏差的目标函数。并且该方法应用于平面桁架模型Femu,并将结果与​​二阶响应表面模型(RSM)和径向基函数模型(RBF)进行比较。分析结果表明,该方法具有良好的准确性和高计算效率;更新参数的误差小于0.2%;损坏识别高精度。更新后,加速FRF的真实和虚部的曲线与真实的达成良好。

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