Detection of discontinuity pattern and orientation for tunnel faces by using 2D and 3D image analysis techniques

This study proposes a new measurement system based on Structure from Motion (SfM) photogrammetry to evaluate tunnel faces. The main goal is to determine the tunnel face discontinuity patterns and orientations for the tunnel face stability evaluation. A 3D point cloud model is generated from overlapping images of the tunnel face 3D polystyrene model through SfM photogrammetry. The discontinuity patterns and orientations are determined through facet extraction of the K-D tree plugin in CloudCompare. The same sets of overlapping images were analyzed in four different quality settings (low, medium, high, and ultra-high) with various sets of point cloud number that control the accuracy of the discontinuity's measurement. In this study, the high-quality setting shows the consistent measurement of the discontinuity patterns and orientations compared with the real 3D polystyrene tunnel face model. Validation of the pattern results from CloudCompare was carried out using JudGeo. Cluster analysis shows two sets of discontinuity with means of dip and dip direction of 82°/164° and 84°/307°, respectively. Both orientations were manually verified with a geological compass. The high-quality point cloud and manual compass measurement of the orientation highlight the similarity of the concentration for both discontinuity sets for the replica tunnel face. This tunnel face proposed method has the advantages of evaluating inaccessible areas and avoiding professional bias. •To analyze discontinuity using 2D and 3D image analysis techniques by replicating a 3D tunnel face model made of polystyrene.•Identify discontinuity pattern and orientation for tunnel face stability evaluation.•Development of a new quantitative discontinuity estimation towards tunnel face evaluation using image analysis technique.