Algorithm development for automated key block analysis in tunnels from LiDAR point cloud data
L.E. Carter-Greaves, Matthew Eyre, D. Vogt, John Coggan
Abstract
The process of scaling and support installation in recently blasted tunnels is one of the most hazardous aspects of the underground construction process. An algorithm is developed that can process point clouds captured via LiDAR which can identify the rock mass discontinuities and perform a kinematic key-block analysis. Points clouds containing nine million points can be processed in under one second and the algorithm operates autonomously requiring no human input. The resultant inputs can provide insight into the underlying rock mass and its geo-mechanical behaviour to an entering scaling crew to aid in risk mitigation.
Topics & Concepts
Point cloudBlock (permutation group theory)Key (lock)Process (computing)Classification of discontinuitiesRock mass classificationLidarComputer sciencePoint (geometry)AlgorithmData miningEngineeringReal-time computingRemote sensingGeologyArtificial intelligenceMathematicsGeotechnical engineeringGeometryComputer securityOperating systemMathematical analysis3D Surveying and Cultural HeritageImage Processing and 3D ReconstructionTunneling and Rock Mechanics