PSI - Issue 84

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ScienceDirect

Procedia Structural Integrity 84 (2026) 1047–1054

© 2026 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Abstract Structural health monitoring is essential to evaluate the safety and performance of bridges over time, providing insights into their dynamic behavior and enabling the early detection of potential damage. Traditional monitoring approaches often rely on accelerometers, which provide accurate measurements but face both practical and numerical challenges such as costly and time consuming installation and integration errors from the double integration process. Vision-based techniques have recently gained attention as a non-contact, cost-effective alternative, enabling direct displacement measurements over wide areas with minimal installation effort and cost. In this study, the proposed vision-based monitoring approach is applied to a reinforced concrete railway arch bridge spanning a river. Two consumer-grade cameras were installed beneath a single span, and checkerboard-pattern targets were positioned on a transverse beam and selected arch hangers to assess the impact of train passages on the structure. In addition, a finite element model of the bridge was developed to simulate its dynamic behavior during train passages. Then, the results were compared with the displacements obtained from post-processed vision-based measurements. III Fabre Conference: Existing Bridges, Viaducts, and Tunnels: Research, Innovation, and Applications Vision-based dynamic monitoring of a RC railway arch bridge Giorgia Ghirelli a , Federico Ponsi a , Ghita Eslami Varzaneh a , Laura Dieci a , Elisa Bassoli a, *, Bruno Brisighella a,b , Loris Vincenzi a a Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, Modena, 41125, Italy b College of Civil Engineering, Fuzhou University, Fuzhou, 350108, China

Peer-review under responsibility of the scientific committee of the Conference Keywords: Vision-based monitoring; Dynamic monitoring; Railway arch bridge.

* Corresponding author. Tel.: +39-059-205-6213. E-mail address: elisa.bassoli@unimore.it

2452-3216 © 2026 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Conference 10.1016/j.prostr.2026.06.134