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Photogrammetric Image Sequence Analysis for Deformation Measurement and Crack Detection Applied to a Shear Test on a Carbon Reinforced Concrete Member

2023; Springer Nature; Linguagem: Inglês

10.1007/978-3-031-32511-3_130

2366-2557

Frank Liebold, Sarah Bergmann, Sven Bosbach, Viviane Adam, Steffen Marx, Martin Claßen, Josef Hegger, Hans‐Gerd Maas,

Structural Health Monitoring Techniques

This publication presents a digital image correlation (DIC) based technique applied to a shear test on a carbon-reinforced concrete member. DIC methods are based on image sequences where the first image is recorded under zero-load without deformations while further images are taken from deformed stages. The image processing starts with the computation of subpixel-precise displacement vector fields using photogrammetric image matching algorithms. In our method, instead of computing strains, another approach is used to quantify deformations and to detect cracks. The matching points are triangulated into a triangular mesh. Then, a deformation model is used that includes a split of the triangle into two parts. The relative translation between these parts is computed and is considered as deformation vector. The detection of cracks is performed by a thresholding applied to the norm of the deformation vectors. Furthermore, the deformation vector is decomposed into the components parallel and perpendicular to the crack. The decomposition requires the knowledge of the crack normal, for which a possible estimation scheme is proposed. The presented method is suitable for brittle material, and it was applied to a monocular image sequence of a shear test of a carbon reinforced concrete member. The test specimen was made of high-strength concrete and was reinforced with a multilayer carbon reinforcement. The selected shear test was intended to analyze the shear behavior of a multi-span system with a distributed load.