Dynamic Identification of Bridges Using Multiple Synchronized Cameras and Computer Vision

This study investigates the application of computer vision techniques in Structural Health Monitoring (SHM). The advantages of multiple synchronized camera setups in capturing and analyzing the dynamic behavior of bridges are researched. The proposed methodology encompasses approach, setup, and data analysis techniques, with the final scope of extracting modal parameters from videos of a vibrating bridge. An operational pedestrian footbridge forced by human-induced vibrations serves as a case study. The findings demonstrate that computer vision techniques employing a multiple synchronized camera approach offer a precise, cost-effective, efficient, and safe alternative to conventional SHM approaches for the dynamic identification of bridges.