Structural Health Monitoring of Bridges based on Vision Method Using Shiny Targets

In this study, a displacement monitoring technique using an economy camera based on the vision-based method is proposed and developed. The structural displacement can be extracted by utilizing an ordinary shiny device that is attached to one of the elements of the structure and monitoring its motion by an economy video camera. In the proposed vision-based methodology, shiny targets such as LED targets are used to obtain more high-quality images with higher contrast that lead to getting better displacement recording from the captured video. First, a LED centroid recognition and scaling method are described to obtain the time history of structural movements due to the ambient vibration. Next, the natural frequencies of the structure can be determined by utilizing different classical system identification methods in the frequency domain and time domain, like the Peak Picking method and the SSI method. Finally, as a case study, the proposed methodology used for the Tabiat bridge in Tehran, which is a three-dimensional steel truss bridge for pedestrians over a heavy traffic highway, the results are compared with those obtained from the high-accurate and expensive wireless seismic sensors. The results show that although the vision-based proposed technique is a fast and low-cost method, it can investigate the dynamic characteristics of the structure with reasonable precision.