Computer Vision-Based Health Monitoring of Mecklenburg Bridge Using 3D Digital Image Correlation

Abstract: A collaborative investigation between the University of Virginia (UVA) and the Virginia Transportation Research Council was performed on the Mecklenburg Bridge (I-85 over Route 1 in Mecklenburg County). The research team aided the Virginia Department of Transportation - Richmond District in the characterization of the bridge behavior of one of the bridge beams that had been repaired due to a previous web buckling and crippling failure. The investigation focused on collecting full-field three-dimensional digital image correlation (3D-DIC) deformation measurements during the dropping sequence (removal of jacking to support beam on bearing/pier). Additionally, measurements were taken of the section prior to and after dropping using a handheld laser scanner to assess the potential of lateral deformation or out-of-plane buckling. Results from the study demonstrated that buckling of the tested beam did not occur, but did provided a series of approaches that can be used to evaluate the effectiveness of repaired steel beam ends. Specifically, the results provided an approach that could estimate the dead load distribution through back-calculation.