An MLS-based high-accuracy measurement and automatic analysis method for roadway deformation

The 3D laser scanning has increasingly been applied in the field of monitoring roadway deformation. Different from a terrestrial laser scanner (TLS), a mobile laser scanner (MLS) is more flexible in on-site operations, but its scanning range accuracy is only precise to the centimeter level. still remains in centimeters. In addition, extracting deformation information from point cloud data of roadway is a complex process. In order to improve the accuracy of deformation monitoring and the efficiency of point cloud processing, with the aid of the identification plate for measurement (IPM) and the statistical analysis methods, an MLS-based high-accuracy measurement and automatic analysis method of roadway deformation is proposed. In this approach, the center point of the identification plate for measurement (IPM-CP) is taken as the control point for deformation monitoring (CPDM). The IPMs in the point cloud are positioned based on the locations of the seed points. The K-radius search algorithm and the density-based spatial clustering of applications with noise (DBSCAN) algorithm are introduced to extract and segment the point cloud of the target area (PCTA). The calculation methods for the key parameters of the algorithms are developed. The judgement index for identifying the IPM point cloud and the methods for target point extraction are presented. The convergence features of the surrounding rocks is analyzed by comparing the lengths of measuring lines of monitoring sections at different stages. The method was applied and validated in the Sanshandao Gold Mine for roadway deformation monitoring. The results show that this method is able to automatically obtain a highly precise data on roadway deformation.