Recognition and characterization of blasting half-holes in hydraulic tunnels based on TLS point cloud

Hydraulic tunnels in Southwest China usually face complex geological conditions that make blast quality control during excavation essential to ensure construction safety. Among various quality indicators, blasting half-holes are widely used to evaluate excavation performance. This study utilizes terrestrial laser scanning (TLS) technology to construct a three-dimensional digital model of blast-excavated tunnel surfaces by optimizing the scanning station arrangement and point cloud preprocessing workflow. A novel half-blast-hole recognition approach, integrating the RANSAC algorithm with TLS data, is developed to achieve accurate extraction of half-hole geometric features. The proposed method has been successfully implemented and validated in a hydraulic tunnel project. The research results indicate that: (1) The proposed method significantly improves the accuracy of RANSAC (Random Sample Consensus)-based shape detection in small-scale point cloud models by optimizing the preprocessing workflow. It demonstrates high reliability and precision in identifying blasting half-holes in hydraulic tunnels. (2) The half-hole rate and the axial blasting load influence range exhibit differentiated spatial distribution patterns. The half-hole rate is the highest in the vault area, followed by the left and right spandrels, and the lowest in the left and right sidewalls. In contrast, the axial influence range of the blasting load is the greatest in the sidewalls, followed by the spandrels, and the smallest in the vault area. (3) The sidewall regions exhibit significantly higher sensitivity to borehole deviation compared to the vault area. Moreover, geological defects exacerbate half-hole fragmentation and reduce surrounding rock stability. These findings provide valuable references for blasting quality evaluation and drilling–blasting parameter optimization in similar engineering projects.