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Elastomeric bridge bearings are widely used in bridges in order to allow deformations caused by temperature variations, traffic loading, shrinkage due to prestress or aging, and construction misalignments. However, manufacturing imperfections in these bearings (such as deviations in rubber layer thickness and non-parallel steel plates) affect their structural performance. Currently, quality control of these bearings involves destructive testing, which is costly and time consuming. This paper presents an alternative, vision-based approach for assessing the internal structure of elastomeric bridge bearings, which eliminates the need to destroy them. Threedimensional digital image correlation (3D-DIC) is used to estimate the thickness of different rubber layers and any shim rotation or distortion based on deformation patterns on the surfaces of the bearings during compression testing. 3D-DIC provides full-field measurements of displacement and strain on the surface by tracking the distribution of grayscale values of pixelbased subsets in the sequence of stereo images. The presented approach enables engineers to efficiently evaluate bearings for quality control purposes.

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