Estimation of In-Plane Strain Field Using Computer Vision to Capture Local Damages in Bridge Structures

Abstract

AbstractThe monitoring of variation in strain field near the ends of girder and bearings in steel plate girder bridges to capture local damages, is of a paramount importance for condition assessment of its service life. It is well-known that, the thickness reduction due to corrosion and failure at bearings, possibly will decrease the necessary functional requirements of structure. By understanding the computer vision technique, it is implemented for a typical bending test under quasi-static loading to aluminum plate girder bridge model specimen at laboratory level, for estimating in-plane strain field variation near end of girder. In this research work, the experiments are carried out using low-cost camera and two-dimensional digital image correlation (2D-DIC) technique is employed for analysis. The experiment is repeated under two different loading conditions and change in boundary conditions, to capture small responses with noise in it. The in-plane strain field patterns at different time step corresponding to the applied quasi-static load can be clearly understood from 2D-DIC results. The obtained results are in good agreement with the strain gauge measurements. The residual strain can also be captured at the unloading condition. From the strain captured at the Web section, it is between 15 and 35μ which is very low strain value. Hence, the computer vision camera can capture the low strain variations which corresponds to local damages in steel plate girder bridge structures through 2D-DIC technique.KeywordsIn-plane strain fieldComputer visionDICQuasi-static loadingLocal damageCondition monitoring