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

Abstract

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

CLC Number:

TU39

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.

Figures/Tables 4

Fig.1

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Fig.3

Table 1

References 13

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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

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

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