基于响应面优化的结构有限元模型修正

针对结构有限元分析中模型精度低的问题，提出了响应面优化的模型修正方法.利用优化拉丁方试验设计样本点，F值检验筛选出修正参数构造不完全4阶多项式响应面并检验响应面有效性.引入遗传算法以响应面计算值与试验值的残差为目标来优化修正参数，将修正值代入初始模型中得到修正模型.三自由度系统数值算例，验证了模型中参数准确、参数不存在和参数有误差3种工况下，响应面优化方法的模型修正能力.以GARTEUR飞机模型为对象，筛选显著性参数进行模型修正，结果表明修正后模型不但在修正频段和预测频段具有良好的复现和预测能力，还能预测结构局部修改后的频率，证实了经过参数筛选后响应面优化的模型修正有效性.

Structural finite element model updating based on response surface optimization

In order to solve the low accuracy problem in structural finite element analysis, a model updating method of surface response optimization was proposed. The sample points acquired by optimal Latin hypercube experimental design and the F-test evaluation utilized for parameter selection were used to construct the polynomial response surface model, and then the validity of response surface was tested. The residual error of the results between response surface and experiment was taken as the objective function. The genetic algorithm was employed to optimize the updating parameters. The updated model was obtained by substituting updated parameters into initial finite element model (FEM). The ability of the model updating methodology was proved under three working conditions, accurate parameters, no parameters and inaccurate parameters by the three degree-of-freedom numerical model. The model of GARTEUR was taken as an example. Significant parameters were selected out to implement the model updating. The results show that it not only proves the reappearance and prediction ability of the updated FEM, but also shows the ability to predict the modal frequency of locally modified structures, and verifies the validity of the model updating methodology.