温度和车辆荷载耦合产生的桥梁极值应力预测

doi:10.13229/j.cnki.jdxbgxb.20231358

吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (5): 1588-1594.doi: 10.13229/j.cnki.jdxbgxb.20231358

• 交通运输工程·土木工程 • 上一篇下一篇

温度和车辆荷载耦合产生的桥梁极值应力预测

樊学平^1,²(),杨渡²,李九谕²,赵启凡²,刘月飞^1,²

^1.兰州大学西部灾害与环境力学教育部重点实验室，兰州 730030
^2.兰州大学土木工程与力学学院，兰州 730030

收稿日期:2023-12-06 出版日期:2025-05-01 发布日期:2025-07-18
通讯作者: 樊学平 E-mail:fxp_2004@163.com
基金资助:
国家自然科学基金项目(51608243);兰州大学中央高校基本科研业务费专项项目(lzujbky-2025-05)

Dynamic prediction of bridge coupled extreme stresses produced by temperature and vehicle loads

Xue-ping FAN^1,²(),Du YANG²,Jiu-yu LI²,Qi-fan ZHAO²,Yue-fei LIU^1,²

^1.Key Laboratory of Mechanics on Disaster and Environment in Western China of the Ministry of Education，Lanzhou University，Lanzhou 730030，China
^2.School of Civil Engineering and Mechanics，Lanzhou University，Lanzhou 730030，China

Received:2023-12-06 Online:2025-05-01 Published:2025-07-18
Contact: Xue-ping FAN E-mail:fxp_2004@163.com

摘要/Abstract

摘要：

本文首先采用移动平均法对温度和车辆荷载耦合产生的监测极值应力进行平滑处理，取处理后的低频数据为趋势项信息，初始数据减去趋势项数据为车辆荷载效应信息，趋势项减去其均值为温度荷载效应信息，通过以上步骤来实现桥梁极值应力的解耦。其次，建立双变量贝叶斯动态线性趋势性模型（BDLTM）对低频极值应力进行预测分析，采用GRU神经网络模型对高频极值应力进行预测分析。最后，进行耦合极值应力的叠加预测，利用天津富民桥的监测耦合数据验证所建模型的可行性。本文研究成果将为桥梁的预防性养护维护决策提供理论基础。

关键词: 结构工程, 桥梁耦合极值应力, 移动平均法, BDLTM-GRU模型, BDLTM, GRU神经网络

Abstract:

Firstly， moving average method is adopted to decouple the coupled extreme stresses produced by temperature and vehicle loads， the low-frequency data after processed by moving average method is the trend item information， the initial data minus the trend item is the vehicle load effect information， and the trend item minus its mean is the temperature load effect information. Secondly， a bivariate Bayesian dynamic linear trend model （BDLTM） is built to predict and analyze low-frequency extreme stress， GRU neural network model is provided to predict and analyze high-frequency extreme stresses. Finally， the dynamic coupled extreme stresses are predicted. The monitoring coupled data from Tianjin Fumin Bridge is provided to illustrate the feasibility and application of the proposed model. The research results of this paper will provide the theoretical foundation for preventive maintenance and decision-making of the service bridges.

Key words: structural engineering, bridge coupled extreme stresses, moving average method, BDLTM-GRU, BDLTM, GRU neural network

中图分类号:

TU39

樊学平,杨渡,李九谕,赵启凡,刘月飞. 温度和车辆荷载耦合产生的桥梁极值应力预测[J]. 吉林大学学报(工学版), 2025, 55(5): 1588-1594.

Xue-ping FAN,Du YANG,Jiu-yu LI,Qi-fan ZHAO,Yue-fei LIU. Dynamic prediction of bridge coupled extreme stresses produced by temperature and vehicle loads[J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(5): 1588-1594.

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监测点	BDLTM-GRU	BDLTM	GRU
FBG01074	0.586 6	0.665 4	0.684 8
FBG01076	0.502 3	0.540 0	0.545 5
FBG01077	0.656 6	0.743 5	0.771 3
FBG01078	0.332 0	0.386 7	0.435 1

温度和车辆荷载耦合产生的桥梁极值应力预测

Dynamic prediction of bridge coupled extreme stresses produced by temperature and vehicle loads

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