为了得到南中环桥的基准有限元模型，结合Kriging模型和改进的万有引力搜索算法(GSA)，利用荷载试验数据对初始有限元模型进行修正。叙述Kriging模型和万有引力搜索算法的基本原理，引入随机交叉变异的方法到基本万有引力算法中，提出了一种改进优化算法，并通过测试函数对其进行验证；介绍南中环桥的工程概况、荷载试验内容和初始有限元模型；接着选定6个待修正参数，通过试验设计得到修正参数所对应的频率和位移的样本，并建立Kriging模型来预测结构响应；以频率和位移的试验值和计算值残差为目标函数，分别利用改进的GSA、粒子群优化算法（PSO）和GSA算法在修正参数的设计空间内寻找目标函数的最小值，对比分析修正结果。结果表明：改进算法对于测试函数具有较好的稳定性和更高的精度；经过模型修正，除个别测点外，频率、位移的相对误差显著降低；相比PSO和GSA，改进的GSA得到了更小的目标函数值，修正后的频率、位移相对误差更小。
Abstract
Here, to obtain the benchmark finite element model of Nanzhonghuan bridge, Kriging model and the improved gravitational search algorithm (GSA) were combined to modify the initial finite element model using load test data. Firstly, the basic principles of Kriging model and GSA were described. The random crossover mutation method was introduced into the basic GSA to propose the improved GSA, it was verified with the testing function. Then, Nanzhonghuan bridge’s project brief situation, load test content and its initial finite element model were introduced. Furthermore, 6 parameters to be modified were selected, frequency and displacement samples corresponding to parameters to be modified were obtained through test design, and Kriging model was established to predict the structure’s responses. Finally, taking the residual of test value and calculated value of frequency and displacement as the objective function, the improved GSA, particle swarm optimization (PSO) and GSA algorithms were used, respectively to search the minimum value of the objective function in the design space of parameters to be modified and the modified results were contrastively analyzed. The results showed that the improved GSA has better stability and higher accuracy for the testing function; through model updating, relative errors of frequency and displacement are significantly reduced except for few measured points; compared with PSO and GSA, the improved GSA can get smaller objective function value, relative errors of frequency and displacement after model updating are smaller.
关键词
桥梁工程 /
模型修正 /
Kriging模型 /
钢混叠合梁拱桥 /
改进万有引力搜索算法 (GSA)
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Key words
bridge engineering /
model updating /
Kriging model /
steel-concrete composite beam arch bridge /
improved gravitational search algorithm (GSA)
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