Structural health monitoring of bridges using three-dimensional digital image correlation

Due to the aging civil infrastructure (i.e. bridges), there is a critical need for monitoring and assessing structural integrity of large scale structures. Currently, bridge health is assessed primarily using qualitative visual inspection, which is not always reliable because some damage is difficult to detect or quantify visually. This thesis presents results of using three-dimensional digital image correlation (3D DIC) as an alternative approach to provide quantitative bridge structural health monitoring.;3D DIC is a non-contact, full-field, optical measuring technique that uses a stereo pair of digital cameras to measure surface geometry, displacement, and strain. DIC can be used for long term monitoring by imaging a bridge periodically and computing strain and displacement from images recorded at different dates or operating conditions. Specifically, DIC was used to monitor crack widths, quantify spalling, and monitor long term full-field strain and displacement. These techniques are first verified in several laboratory tests before being used to monitor 15 areas on three local bridges. The DIC approach was able to quantify concrete loss due to spalling, measure expansion of preexisting cracks and detect newly formed cracks. This thesis discusses the results, challenges and solutions to implementing DIC on large structures in the field. The long term monitoring results reveal that DIC is a promising approach to monitor the integrity of large scale civil infrastructure.