Feasibility investigation for a bridge damage identification method through moving vehicle laboratory experiment

被引:53
|
作者
Chang, Kai-Chun [1 ]
Kim, Chul-Woo [1 ]
Kawatani, Mitsuo [2 ]
机构
[1] Kyoto Univ, Dept Civil & Earth Resources Engn, Kyoto 6158540, Japan
[2] Kobe Univ, Dept Civil Engn, Kobe, Hyogo 6578501, Japan
基金
日本学术振兴会;
关键词
bridge health monitoring (BHM); bridge-vehicle interaction; pseudo-static damage identification; element stiffness index; moving vehicle; laboratory experiments; DYNAMIC-RESPONSE; VIBRATION; SYSTEM; FREQUENCIES; BEAM;
D O I
10.1080/15732479.2012.754773
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper investigated the feasibility of the pseudo-static damage identification method derived from a bridge-vehicle interaction system through a moving vehicle laboratory experiment. The element stiffness index, defined as the ratio of flexural rigidity of a damaged member to that of an intact member, serves as the damage indicator. Three vehicle models and two travelling speeds were considered in the experiment to examine the effect of vehicle's dynamic characteristic and travelling speed on identified results. It is demonstrated that locations and severities of damages are detectable using the proposed method in spite of the probable changes of roadway roughness and environmental conditions. In addition, adopting higher vehicle speed as well as the vehicle with frequency close to that of the bridge increased the probability of detecting damages.
引用
收藏
页码:328 / 345
页数:18
相关论文
共 50 条
  • [21] Bridge Structural Identification Using Moving Vehicle Acceleration Measurements
    Eshkevari, Soheil Sadeghi
    Pakzad, Shamim
    DYNAMICS OF CIVIL STRUCTURES, VOL 2, 2019, : 251 - 261
  • [22] Damage Detection in Bridge Structures under Moving Vehicle Loads Using Delay Vector Variance Method
    Zhu, Jinsong
    Zhang, Yifeng
    JOURNAL OF PERFORMANCE OF CONSTRUCTED FACILITIES, 2019, 33 (05)
  • [23] Bridge damping identification by vehicle scanning method
    Yang, Y. B.
    Zhang, Bin
    Chen, Yanan
    Qian, Yao
    Wu, Yuntian
    ENGINEERING STRUCTURES, 2019, 183 : 637 - 645
  • [24] Reality of virtual damage identification based on neural networks and vibration analysis of a damaged bridge under a moving vehicle
    Xiong, Chun-bao
    Lu, Hua-li
    Zhu, Jin-song
    NEURAL COMPUTING & APPLICATIONS, 2018, 29 (05): : 1331 - 1341
  • [25] Bridge damage identification through frequency changes
    Abedin, Mohammad
    Mehrabi, Armin B.
    SENSORS AND SMART STRUCTURES TECHNOLOGIES FOR CIVIL, MECHANICAL, AND AEROSPACE SYSTEMS 2021, 2021, 11591
  • [26] Simultaneous identification of bridge damage and vehicle parameters based on bridge strain responses
    Zhang, Lu
    Feng, Dongming
    Wu, Gang
    STRUCTURAL CONTROL & HEALTH MONITORING, 2022, 29 (06):
  • [27] Identification of moving vehicle parameters using bridge responses and estimated bridge pavement roughness
    Wang, Haoqi
    Nagayama, Tomonori
    Zhao, Boyu
    Su, Di
    ENGINEERING STRUCTURES, 2017, 153 : 57 - 70
  • [28] Identification of moving vehicle forces on bridge structures via moving average Tikhonov regularization
    Pan, Chu-Dong
    Yu, Ling
    Liu, Huan-Lin
    SMART MATERIALS AND STRUCTURES, 2017, 26 (08)
  • [29] IDENTIFICATION OF MOVING LOADS THROUGH BRIDGE DYNAMIC RESPONSES
    Han, Man-Jun
    Lee, Hyeong-Jin
    Jung, Bum-Seok
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON STRUCTURE HEALTH MONITORING & INTELLIGENT INFRASTRUCTURE: STRUCTURAL HEALTH MONITORING & INTELLIGENT INFRASTRUCTURE, 2007,
  • [30] Improved Vehicle Scanning Method for Bridge Damage Detection
    Yang, D. S.
    Wang, C. M.
    Duan, W. H.
    PROCEEDINGS OF THE 17TH EAST ASIAN-PACIFIC CONFERENCE ON STRUCTURAL ENGINEERING AND CONSTRUCTION, EASEC-17 2022, 2023, 302 : 426 - 436