A new methodology for non-contact accurate crack width measurement through photogrammetry for automated structural safety evaluation

In mechanical, aerospace and civil structures, cracks are important defects that can cause catastrophes if neglected. Visual inspection is currently the predominant method for crack assessment. This approach is tedious, labor-intensive, subjective and highly qualitative. An inexpensive alternative to current monitoring methods is to use a robotic system that could perform autonomous crack detection and quantification. To reach this goal, several image-based crack detection approaches have been developed; however, the crack thickness quantification, which is an essential element for a reliable structural condition assessment, has not been sufficiently investigated. In this paper, a new contact-less crack quantification methodology, based on computer vision and image processing concepts, is introduced and evaluated against a crack quantification approach which was previously developed by the authors. The proposed approach in this study utilizes depth perception to quantify crack thickness and, as opposed to most previous studies, needs no scale attachment to the region under inspection, which makes this approach ideal for incorporation with autonomous or semi-autonomous mobile inspection systems. Validation tests are performed to evaluate the performance of the proposed approach, and the results show that the new proposed approach outperforms the previously developed one.