Automatic Crack Detection and Quantification for Tunnel Lining Surface from 3D Terrestrial LiDAR Data
Hong Zhou, Binwei Gao, Wenjin Wu
Abstract
In the process of tunnel construction and operation, the traditional method of crack inspection in tunnel operation is through manual photographing and field recording which is not only labor-intensive with lower data quality but also hard to obtain the important geometric information of the cracks. With the development of terrestrial laser scanning technology, Three-dimensional point cloud collection from a tunnel becomes feasible and affordable. In this paper, we propose an automatic crack detection method to automatically identify the cracks from the 3D point cloud of a tunnel and also extract the corresponding dimension information of the cracks. Through a field experiment with a tunnel project, the feasibility of the proposed method was validated, and the experiment results showed that the proposed method could detect the severe crack diseases with a width of more than 0.6 mm with the relative errors of the width and the length within 10%.