Study on Different Residual and Weight Coefficient in Model Updating of Bridge Structure

L. Jie, Huang Min-shui, Zhu Hong-ping
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引用次数: 8

Abstract

Relative merits of different residuals used in the construction of objective function and weight coefficients in single-objective function for structural model updating are investigated in this paper based on the improved genetic algorithm (IGA). Presently there are three residuals which are used mostly in finite element (FE) model updating: frequency residual, mode shape residual, and modal flexibility residual. Relative merits of the three residuals are analyzed through the simulation of a simply supported beam. Then, model updating is studied comparatively based on IGA. Frequency is the main characteristic parameter of bridge structure, which has high identification precision and should be used with priority. When there are several updating parameters, information should be complemented. If identification error of the mode shape is relatively less, the complement of the mode shape is feasible. In the end, through the analysis of weight coefficients for different residuals in single-objective function, it can be seen that the model updating performance is better when the frequency residual has a larger weight coefficient.
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桥梁结构模型更新中不同残差系数和权重系数的研究
基于改进遗传算法(IGA),研究了结构模型更新中不同残差在目标函数构造和单目标函数权重系数中的相对优劣。目前有限元模型更新中最常用的残差有三种:频率残差、模态振型残差和模态柔度残差。通过对简支梁的仿真,分析了三种残差的相对优劣。然后对基于IGA的模型更新进行了比较研究。频率是桥梁结构的主要特征参数,识别精度高,应优先使用。当有几个更新参数时,应补充信息。如果模态振型的识别误差相对较小,则模态振型的补型是可行的。最后,通过分析单目标函数中不同残差的权系数,可以看出,当频率残差的权系数较大时,模型的更新性能较好。
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