湖南大学学报（自然科学版）2024，Vol.51Issue(5)：95-105,11.DOI:10.16339/j.cnki.hdxbzkb.2024051
基于遗传算法的斜拉桥基准模型参数修正方法
Parameter Updating Method of Benchmark Model for Cable-stayed Bridges Based on Genetic Algorithm
摘要
Abstract
Health monitoring plays an important role in guaranteeing the structural safety of a cable-stayed bridge throughout its life.However,the use of sensor data for health monitoring of cable-stayed bridges has some limitations.Combining the Benchmark model to monitor bridge structures can compare and evaluate different health monitoring methods criteria in a given state,which is valuable for bridge design,operation and management.This paper proposes a modified Benchmark model for health monitoring technology of cable-stayed bridges.Firstly,a simplified finite element model of the spine-beam model is established using Matlab software to conduct the dynamic analysis and model modification of the structure.In addition,a detailed finite element model is established as a simplified supplementary model and modal correction model.Then,an orthogonal test design is used to perform a significance analysis on the dynamic characteristic parameters of the cable-stayed bridge for the parameters to be modified in the modeling process,and the sensitive parameters are clarified.Finally,the model parameters are modified based on the genetic algorithm,and the dynamic adaptive technique and the method of parallel selection are proposed to optimize the structure of the genetic algorithm,which interferes with the genetic selection process and gives higher dispersion to the initial population.Compared with the GA function,the method with the improved genetic algorithm has higher computational efficiency and smaller error for model parameters.关键词
斜拉桥/基准模型/鱼骨梁模型/板壳单元模型/健康监测/改进遗传算法Key words
cable-stayed bridges/Benchmark model/spine-beam model/plate-shell model/health monitoring/improved genetic algorithm分类
建筑与水利引用本文复制引用
马海英,邱媛,夏烨,赖明辉,李清岭..基于遗传算法的斜拉桥基准模型参数修正方法[J].湖南大学学报（自然科学版）,2024,51(5):95-105,11.基金项目
中央高校基本科研业务经费资助项目(2023-2-YB-17),Fundamental Research Funds for the Central Universities(2023-2-YB-17) （2023-2-YB-17）
