辽宁工程技术大学学报（自然科学版）2026，Vol.45Issue(2)：216-223,8.DOI:10.11956/j.issn.1008-0562.20250450
基于动静载荷数据的桥梁贝叶斯有限元模型多目标更新方法
A multi-objective update method for Bayesian finite element models of bridges based on static and dynamic load data
摘要
Abstract
To address the low prediction accuracy and limited engineering applicability of single-objective optimization method in traditional finite element model updating,a multi-objective updating method of Bayesian finite element model based on static and dynamic load data is proposed to improve the simulation ability of the model to the structural response of continuous beam bridge under composite load.The global dynamic characteristic parameters such as the first three frequencies and modes of the structure are obtained by dynamic load test,and the multi-objective non-dominated sorting genetic algorithm II(NSGA-II)is used to synchronously optimize the frequency residual and modal confidence criterion residual,ensuring the accurate calibration of the dynamic characteristics of the finite element model.Based on the deflection data of the key sections obtained from the static load test,a multi-level verification system was established to verify the local response of the modified model.The results show that the proposed multi-objective optimization method can effectively coordinate the conflicts between different objectives,and the response frequency error of the modified model is controlled between 0.70%-4.02%.The static load test shows that the model deflection prediction error range is 2.97%-9.27%,which is at an acceptable level.The research conclusions can provide theoretical and methodological support for health monitoring and performance evaluation of similar bridge structures.关键词
动静载荷/贝叶斯理论/多目标优化/有限元模型/模型修正/动力特性Key words
live and dead loads/Bayesian theory/multi-objective optimization/finite element model/model updating/dynamic characteristics分类
建筑与水利引用本文复制引用
包龙生,韩旭,赵家康,陈思,于玲..基于动静载荷数据的桥梁贝叶斯有限元模型多目标更新方法[J].辽宁工程技术大学学报（自然科学版）,2026,45(2):216-223,8.基金项目
国家重点研发计划项目(2018YFC0809600) （2018YFC0809600）
沈阳市科技计划项目(23-407-3-19) （23-407-3-19）
内蒙古自治区自然科学基金项目(2025QN05118) （2025QN05118）
