Automated crack detection and measurement based on digital image correlation

The acquisition and evaluation of the crack behaviour in experiments on quasi-brittle materials, such as concrete, mortar, or masonry is essential for understanding their structural behaviour. This publication presents a fully automated procedure to detect cracks and measure crack kinematics in laboratory experiments instrumented with digital image correlation (DIC). Crack lines are extracted using well-established image processing methods showing excellent agreement with the physical crack pattern. In contrast to most existing crack detectors that rely on pixel intensities of true images, the presented crack detection is based on the DIC principal tensile strain field what allows the extraction of much finer cracks and more reliable crack locations. The crack widths and slips are measured using the DIC displacement field accounting for local rotations of the specimen. Additionally, automated visualisations of the crack kinematic measurements including data smoothing are presented. Several sensitivity analyses evaluating the performance and the uncertainty of the crack detector and the crack kinematic measurements have been conducted. These analyses show that the obtained results depend on the DIC configuration and that the procedure is limited in the case of very closely spaced cracks. With appropriate DIC parameters, the procedure allows detecting crack locations with high precision and measuring crack kinematics very accurately even in large-scale experiments with complex crack patterns. (C) 2020 The Author(s). Published by Elsevier Ltd.