Evaluating Accuracy and Resolution of a Next-generation Digital Image Correlation (DIC) System for Bridge Monitoring

Date
2019
Authors
Chapagain, Biswash
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Abstract

The Ultra-high-resolution next-generation Ghannoum Vision System (GVIS) DIC system is currently being developed at the University of Texas at San Antonio (UTSA) for monitoring bridge deformation during the bridge load tests and monitor crack and damage progress in the bridge over long periods of time. The experiment was carried out at UTSA Large Scale Laboratory to investigate the accuracy, noise level, lighting sensitivity, and camera placement sensitivity for long term monitoring using GVIS. The system uses two cameras and computer programs to compute the measurement data in three spatial dimensions relative to the cameras by selecting the subset in an image (i.e., targets). The test procedure includes capturing the images with high-resolution cameras and processing images using GVIS software. Test parameters were two DIC algorithms, experiment distance from the camera sensor, target size, and target texture for three target types which includes: High contrast target (HCT), concrete target and steel target. Conclusions were drawn that the accuracy of the system decreases with the increase in the distance of the target location from the camera sensor. Similarly, noise level and shift in target location due to lighting variation increase with the increase in the target distance from the cameras. Algorithm 2 was preferred over Algorithm 1 and was recommended for use in the DIC system. High contrast target was recommended as a target type, and target size of at least 60x60 pixels and preferably equal to 100x100 pixels was recommended for all the DIC applications. Furthermore, it was recommended to further investigate the camera placement sensitivity for long term monitoring using the DIC system.

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This item is available only to currently enrolled UTSA students, faculty or staff.
Keywords
algorithm, bridge monitoring, calibration, digital image correlation, noise level, target texture
Citation
Department
Civil and Environmental Engineering