Coupled Vibration of a Vehicle Group-Bridge System and Its Application in the Optimal Strategy for Bridge Health Monitoring

被引:1
作者
Yan, Xiaoyu [1 ]
Zhao, Zhuo [2 ]
He, Haoxiang [2 ]
机构
[1] Open Univ China, Sch Engn, Beijing 100039, Peoples R China
[2] Beijing Univ Technol, Key Lab Urban Secur & Disaster Engn China, Minist Educ, Beijing 100124, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 12期
关键词
bridge health monitoring; vehicle group-bridge system; coupling vibration; monitoring strategy; road roughness; DYNAMIC-RESPONSE; MODE SHAPES;
D O I
10.3390/app14125236
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The accuracy of bridge performance monitoring and evaluation is easily affected by unfavorable factors such as vehicle coupling and test noise. In order to accurately evaluate the dynamic response and health monitoring threshold of the bridge under different operating conditions, a time-varying dynamic vehicle group model including the main uniform mass and the coupling mass was established, and the influence of road roughness was considered in the coupling equation. A bridge monitoring strategy considering signal noise ratio and vehicle-bridge interaction was proposed, and the effectiveness of the monitoring strategy was verified by taking a simple supported beam as an example. The results showed that the proposed time-varying dynamic vehicle group model could accurately consider the influence of road roughness and estimate the threshold of health monitoring, and the proposed bridge monitoring strategy could filter out a large amount of low signal-to-noise ratio or meaningless data, thus saving computing resources and realizing the lightweight safety monitoring of bridges.
引用
收藏
页数:20
相关论文
共 27 条
[1]   A novel damage identification method based on short time Fourier transform and a new efficient index [J].
Ahmadi, Hamid Reza ;
Mahdavi, Navideh ;
Bayat, Mahmoud .
STRUCTURES, 2021, 33 :3605-3614
[2]   Probabilistic Comparative Analysis of Vehicle-Bridge Interaction Models for Predicting Bridge Response under Moving Vehicles [J].
Aloisio, Angelo ;
Alaggio, Rocco .
JOURNAL OF ENGINEERING MECHANICS, 2024, 150 (03)
[3]  
[Anonymous], 1986, GB7031-86
[4]  
[Anonymous], 1982, ISO/TC108/SC2/WG4 N57
[5]   Block-wise recursive sliding variational mode decomposition method and its application on online separating of bridge vehicle-induced strain monitoring signals [J].
Dan, Danhui ;
Zeng, Gang ;
Pan, Ruiyang ;
Yin, Pengcheng .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 198
[6]   Bridge vehicle-induced effect influence line characteristic function based on monitoring big data: definition and identification [J].
Dan, Danhui ;
Kong, Zhaowen .
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2023, 22 (05) :2987-3005
[7]   Signal Reconstruction from Mobile Sensors Network Using Matrix Completion Approach [J].
Eshkevari, Soheil Sadeghi ;
Pakzad, Shamim N. .
TOPICS IN MODAL ANALYSIS & TESTING, VOL 8, 2020, :61-75
[8]   Damage identification method for tied arch bridge suspender based on quasi-static displacement influence line [J].
Fan, Congcong ;
Zheng, Yuanxun ;
Wang, Boli ;
Zhou, Yu ;
Sun, Meng .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 200
[9]   Critical evaluation of factors on extracting multiple bridge frequencies from drive-by measurements [J].
Jayakumar, Prawin ;
Vasamsetti, Sri Harika .
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING, 2022, 44 (11)
[10]   Vehicle-Bridge Interaction Modelling Using Precise 3D Road Surface Analysis [J].
Kreslin, Maja ;
Cesarek, Peter ;
Znidaric, Ales ;
Kokot, Darko ;
Kalin, Jan ;
Vezocnik, Rok .
SENSORS, 2024, 24 (02)