Structural Identification Using Computer Vision-Based Bridge Health Monitoring

被引:88
|
作者
Khuc, Tung [1 ,2 ]
Catbas, F. Necati [3 ,4 ]
机构
[1] Natl Univ Civil Engn, Dept Bridge & Highways Engn, 55 Giai Phong St, Hanoi 100000, Vietnam
[2] Univ Cent Florida, 4000 Cent Florida Blvd, Orlando, FL 32816 USA
[3] Univ Cent Florida, Dept Civil Environm & Construct Engn, 4000 Cent Florida Blvd, Orlando, FL 32816 USA
[4] Bogazici Univ, TR-34342 Istanbul, Turkey
基金
美国国家科学基金会;
关键词
VEHICLE DETECTION; SYSTEM-IDENTIFICATION; INFLUENCE LINES; DISPLACEMENT; CLASSIFICATION; TRACKING; SENSOR;
D O I
10.1061/(ASCE)ST.1943-541X.0001925
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper presents a new structural identification (St-Id) framework along with a damage indicator, displacement unit influence surface using computer vision-based measurements for bridge health monitoring. Unit influence surface (UIS) of a certain response (e.g.,displacement, strain) at a measurement location on a beam-type or plate-type structure (e.g.,single-span or multispan bridge with its deck) is defined as a response function of the unit load with respect to the any given location of the unit load on that structure. The novel aspect of this paper is a framework integrating vehicle load (input) modeling using computer vision and the development of a new damage indicator, UIS, using image-based structural identification. This framework is demonstrated on the large-scale bridge model in the University of Central Florida Structures Laboratory for verification and validation. The UIS damage indicators successfully identified the simulated damage on the bridge model, including damage detection and damage localization.
引用
收藏
页数:13
相关论文
共 50 条
  • [21] A quantitative comparison study for structural flexibility identification using Accelerometric and computer vision-based vibration data
    Li, Panjie
    Yan, Shuaihui
    Zhang, Jian
    Feng, Maria Q.
    Feng, Dongming
    Li, Shengli
    JOURNAL OF SOUND AND VIBRATION, 2024, 576
  • [22] Research on the Application of Computer Vision in Bridge Health Monitoring
    Cao, Yimin
    Huang, Mingzheng
    Sun, Yixin
    Li, Cheng
    PROCEEDINGS OF THE 2ND INTERNATIONAL CIVIL ENGINEERING AND ARCHITECTURE CONFERENCE, CEAC 2022, 2023, 279 : 127 - 136
  • [23] A computer vision-based system for monitoring Vojta therapy
    Khan, Muhammad Hassan
    Helsper, Julien
    Farid, Muhammad Shahid
    Grzegorzek, Marcin
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2018, 113 : 85 - 95
  • [24] Applications of Computer Vision-Based Structural Monitoring on Long-Span Bridges in Turkey
    Dong, Chuanzhi
    Bas, Selcuk
    Catbas, Fikret Necati
    SENSORS, 2023, 23 (19)
  • [25] Experimental validation of cost-effective vision-based structural health monitoring
    Feng, Dongming
    Feng, Maria Q.
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 88 : 199 - 211
  • [26] Vision-Based Structural Modal Identification Using Hybrid Motion Magnification
    Zhang, Dashan
    Zhu, Andong
    Hou, Wenhui
    Liu, Lu
    Wang, Yuwei
    SENSORS, 2022, 22 (23)
  • [27] A computer vision-based method for bridge model updating using displacement influence lines
    Martini, Alberto
    Tronci, Eleonora M.
    Feng, Maria Q.
    Leung, Ryan Y.
    ENGINEERING STRUCTURES, 2022, 259
  • [28] A Computer Vision-based Approach for Structural Displacement Measurement
    Ji, Yunfeng
    SENSORS AND SMART STRUCTURES TECHNOLOGIES FOR CIVIL, MECHANICAL, AND AEROSPACE SYSTEMS 2010, 2010, 7647
  • [29] Computer Vision for Structural Dynamics and Health Monitoring
    Thurlow, P. G.
    INFRASTRUCTURE ASSET MANAGEMENT, 2021, 8 (03) : 164 - 164
  • [30] Machine Vision-Based Conveyor and Structural Health Monitoring Robot for Industrial Application Using Deep Learning
    Khalid
    Faizabadi, Ahmed Rimaz
    Mallik, Moksud Alam
    PROCEEDINGS OF SECOND INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER ENGINEERING AND COMMUNICATION SYSTEMS, ICACECS 2021, 2022, : 21 - 34