Vision-Based Modal Survey of Civil Infrastructure Using Unmanned Aerial Vehicles

Computer vision techniques for extracting dynamic structural displacements from videos are gaining increasing acceptance for the purposes of system identification and structural health monitoring. However, the application of video-based techniques for modal analysis of full-scale civil infrastructure has been limited, because obtaining measurements of all points on a large structure with a single video frame with sufficient resolution is seldom feasible. In this study, a new approach is presented to facilitate the extraction of frequencies and mode shapes of full-scale civil infrastructure from video obtained by an unmanned aerial vehicle (UAV). This approach addresses directly a number of difficulties associated with modal analysis of full-scale infrastructure using vision-based methods. The proposed approach is evaluated using a story-story shear-building model excited on a shaking table in a laboratory environment, and on a full-scale pedestrian suspension bridge. The results demonstrate the efficacy of the proposed approach.