Automatic Detection of Delamination on Tunnel Lining Surfaces from Laser
3D Point Cloud Data by 3D Features and Support Vector Machine
Abstract
A completely automatic and accurate detection algorithm for the
delamination on tunnel concrete lining surfaces from laser 3D point
cloud data is proposed. A Mobile Mapping System (MMS), which mounts
laser sensors and a positioning system, is utilized to measure the
geometry of tunnel lining surfaces highspeed. The proposed algorithm
consists of 4 steps: removal of tunnel profile components, detection of
peaks of anomalies, localization of anomaly areas, classification of
delamination and appendages. On tunnel linings, there are many
appendages such as cables, lights, signs, and water guides to mask the
features of delamination. In the article, a novel 3D feature was
introduced to realize the accurate classification. An automatic SVM
algorithm was developed using real tunnel lining data and manual
inspection results, showing an accurate delamination map.