Optimization and Accuracy Validation of Civil Infrastructure Vision (CIV) System for Large Scale Calibrations

The Civil Infrastructure Vision (CIV) system is a non-contact technology based on principles of Digital Image Correlation (DIC) that was developed at the University of Texas at San Antonio (UTSA). This system is capable of monitoring surface deformations on structural specimens ranging from small-scale to large-scale structural systems. It was developed for monitoring deformations of bridges during bridge load tests and long-term crack and damage progressions in the bridges. The calibration of the system was carried at the Large-Scale Testing Laboratory at UTSA. Detailed research work for identifying several factors that affect calibration was carried out and an iterative process to develop an optimal calibration was developed. The accuracy of the system was then checked by performing validation tests for each of the calibration results and conclusions were drawn. When properly calibrated, the system was found to deliver measurements with an accuracy on the order of few thousands of an inch when the specimen is located at a distance ranging from 40 feet (12.2 meters) to 110 feet (33.5 meters) away from the cameras. The accuracy of the system decreases with an increase in measurement distance.