ABSTRACT
Fully understanding the bridge performance under traffic loadings is critical for improving bridge design, condition assessment, and load rating. Modern structural health monitoring (SHM) has enabled measurements of the traffic loads and dynamic bridge response to help enhance the knowledge on the mechanism of vehicle-bridge interactions; however, challenges still exist for accurately measuring the moving traffic loads and synchronizing the loads with the corresponding traffic-induced response. Recently, with the tremendous advancements in unmanned aerial vehicles (UAVs) technology (including better camera performance and longer flight times), UAVs can offer unique advantages to hover at specified heights and key locations and access difficult to reach areas and critical angles while providing relatively stable and high-quality imagery. By leveraging the recent advantages in UAV technologies, image computation, and camera vision-based SHM, this study proposes a UAV-based SHM system to track vehicular loading and measure the displacement of the bridge at the same time. In the system, multiple UAVs will hover adjacent to a bridge and communicate with each other to take videos of the moving traffic and structure response from different angles simultaneously. Then, an object identification algorithm in image computation will be developed to identify and track moving vehicles. Digital Image Correlation (DIC) will be employed to quantify the three-dimensional dynamic displacement of the bridge. The feasibility of using videos from multiple UAVs in object identification and displacement measurement will be investigated. In the future, the data measured by the proposed UAV-based SHM system can be fused with data from traditional weigh-in-motion systems to allow precise estimation of moving traffic loadings while measuring corresponding structural response, thus providing valuable data for accurate modeling and assessing bridge performance under traffic loads.
