PSI - Issue 78

Arash Rahimi et al. / Procedia Structural Integrity 78 (2026) 1767–1774

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Fig. 11. Acceleration data (ACC.13) of bridge subjected to double moving vehicle (C25, C27 and C29)

Conclusions This study developed and experimentally tested a scaled-down benchmark railway bridge model to investigate vibration-based damage identification under controlled laboratory conditions. The experimental setup incorporated low-cost accelerometers, a laser–LDR detection system, and environmental monitoring, enabling synchronized acquisition of structural response and vehicle dynamics data. A wide range of operational conditions was tested, varying vehicle mass, speed, and configuration (single and dual cars), producing a comprehensive monitoring database. outcomes can be summarized as the LDR-based detection system proved effective for accurate vehicle classification, axle counting, and speed estimation, ensuring precise alignment between load position and measured structural response. The acceleration responses exhibited clear correlations with vehicle mass and speed, with heavier and faster vehicles inducing larger vibration amplitudes and broader frequency content. the generated dataset represents a valuable benchmark case study for testing and validating algorithms in operational modal analysis, drive by monitoring, and damage identification. the proposed scaled model and associated measurement framework demonstrate strong potential as a cost-effective and flexible laboratory platform for advancing vibration-based SHM research, supporting the development and refinement of algorithms prior to full-scale field deployment. Acknowledgements This study was supported by FABRE – “Research consortium for the evaluation and monitoring of bridges, viaducts and other structures” (www.consorziofabre.it/en). Any opinion expressed in the paper does not neces-sarily reflect the view of the funder. References Corbally, R., Malekjafarian, A., 2022. Laboratory verification of vehicle contact point response for bridge condition monitoring. Kim, C.-W., Chang, K.-C., McGetrick, P.J., Inoue, S., Hasegawa, S., 2017. Utilizing moving vehicles as sensors for bridge condition screening—A laboratory verification. Sensors and Materials 29(2), 153–163. Chang, K.-C., Kim, C.-W., Kawatani, M., 2013. Feasibility investigation for a bridge damage identification method through moving vehicle laboratory experiment. Structure and Infrastructure Engineering 10(3), 328–345. https://doi.org/10.1080/15732479.2012.754773 Shokrollahi, S., Adel, F., Ahmadian, H., 2017. An investigation into the accelerometer mounting effects on signal transmissibility in modal measurements. Scientia Iranica 24(5), 2436–2444. https://doi.org/10.24200/sci.2017.4244