结构模型修正中不同残差及权重系数研究

研究了基于改进遗传算法对结构模型修正中用于构建目标函数的不同残差的优缺点和单目标函数中的权重系数。目前工程实践中进行有限元模型修正较多地采用三种残差,包括频率、振型和柔度,本文分析了这三种残差用于模型修正的优缺点,采用改进的遗传算法、利用一个模拟刚度减少的简支梁的仿真模型,对基于不同残差的模型修正进行了比较研究。频率是系统的主要特征参数且识别精度高,修正应优先采用。当修正参数较多,需要补充信息且振型识别误差较小时,可考虑补充振型信息。最后通过对用于构建单目标函数的不同残差采用不同权重系数的比较分析,可以看出当频率残差采用较大权重时的模型修正效果较好。

Study on different residual and weight coefficient in model updating of structure

Relative merits of different residual used in the construction of objective function and weight coefficient in single objective function for structural model updating are investigated in the paper based on improved genetic algorithm(IGA).Presently there are three residuals which are used mostly in finite element model updating of engineering practice,such as frequency residual,mode shape residual and modal flexibility residual,in the paper relative merits of the three residuals are analyzed through the simulation of a simply supported beam,model updating are studied comparatively based on IGA.Frequency is the main characteristic parameter in engineering structure,which has high identification precision and should be used in priority.When there are several updating parameters,information should be complemented and identification error of mode shape is relatively less,the complement of mode shape is feasible.In the end by the analysis of weight coefficient for different residuals in single objective function,it can be seen that model updating performance is better when frequency residual has a larger weight coefficient.