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Computer Vision-based Finite Element Model Updating Method Using Measured Static Data: An Experimental Study

 Computer Vision-based Finite Element Model Updating Method Using Measured Static Data: An Experimental Study
Auteur(s): , , , ORCID
Présenté pendant IABSE Congress: Bridges and Structures: Connection, Integration and Harmonisation, Nanjing, People's Republic of China, 21-23 September 2022, publié dans , pp. 1473-1479
DOI: 10.2749/nanjing.2022.1473
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Accurate FE models play an important role in structure health monitoring (SHM). In the traditional static finite element model updating (FEMU) process, loading tests interrupting the traffic are re...
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Détails bibliographiques

Auteur(s): (Department of Bridge Engineering, College of Civil Engineering, Tongji University, Shanghai 200092, China)
(Department of Bridge Engineering, College of Civil Engineering, Tongji University, Shanghai 200092, China)
(Department of Bridge Engineering, College of Civil Engineering, Tongji University, Shanghai 200092, China)
ORCID (State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai, 200092, China)
Médium: papier de conférence
Langue(s): anglais
Conférence: IABSE Congress: Bridges and Structures: Connection, Integration and Harmonisation, Nanjing, People's Republic of China, 21-23 September 2022
Publié dans:
Page(s): 1473-1479 Nombre total de pages (du PDF): 7
Page(s): 1473-1479
Nombre total de pages (du PDF): 7
DOI: 10.2749/nanjing.2022.1473
Abstrait:

Accurate FE models play an important role in structure health monitoring (SHM). In the traditional static finite element model updating (FEMU) process, loading tests interrupting the traffic are required for obtaining static data, which is inconvenient. This paper proposes a novel static FEMU method based on computer vision technology and WIM system, avoiding the mentioned defects. Firstly, the static response simulation under traffic load is carried out with the computer vision determining the load location and the BIW system deciding the load value. Secondly, signal processing technology extracts the measured static data from the monitoring data. Thirdly, the PSO method is utilized to perform the FEMU. An experiment is designed on a bridge model with an SHM system, and results verify the convenience and accuracy of the proposed method

Copyright: © 2022 International Association for Bridge and Structural Engineering (IABSE)
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