Research On Rock Mass Structure Characterization Parameters Based On 3D Reconstruction Of Tunnel Point Clou

With the development of deep underground mining in China,there have been problems faced by increasing mining depth,such as complex lithological structure information and low level of underground intelligence,which urgently need to be solved.One of the key issues is how to effectively obtain information on various discontinuities in rock mass,including joints,fractures,bedding,etc.,which have a decisive impact on the stability of the rock mass.In order to better solve this problem,adopting intelligent collection of rock mass structure information is a necessary means in line with practical development,and it is also one of the main challenges for engineering rock mass quality evaluation under complex conditions.When measuring the characteristics of structural planes,traditional geological measurement methods can no longer meet the needs of high-precision,high-efficiency,low-risk,and multi-scale acquisition of structural information.In order to solve the problems encountered in the collection of rock mass structural information,non-contact geological measurement has gradually been developed,with representative measurement methods being 3D laser scanning measurement and unmanned aerial vehicle photogrammetry.With the improvement of measurement methods and the advancement of modern computer technology,the collection of rock mass structure information has expanded from points to surfaces,and from surfaces to three-dimensional space,reflecting the characteristics of rock mass structure more realistically.This article focuses on the needs of on-site intelligent measurement and adopts an improved point cloud recognition method for structural planes.Taking the3D point cloud data of underground tunnel excavation face as an example,the rock mass structure characterization parameters based on tunnel point cloud 3D reconstruction are studied,and automatic extraction and analysis of geometric information of rock mass structure is achieved.The research content and achievements of this article are as follows:（1）Use a 3D laser scanner and a drone high-definition camera to obtain tunnel rock mass structure information data,compare the advantages and disadvantages of obtaining point cloud data between the two,and conduct a detailed analysis.（2）On the basis of summarizing the research methods of structural planes,based on the obtained point cloud data,preprocessing operations are carried out on the point cloud data,and then the Ball Voting Algorithm（BPA）and Delaunay triangulation are used to implement the triangular mesh model.（3）Based on an improved structural surface fitting method,the shape of the fitted structural surface is changed by using the size of the threshold to better characterize the true situation of the triangular surface of the rock mass.Based on the improved normal vector clustering algorithm,structural planes are divided.During the clustering process,similarity thresholds and limiting conditions are added to control the degree of clustering and display the true clustering results of the tunnel rock mass structure.（4）After dividing the structural surface by the improved normal vector clustering algorithm,the structural surface production was extracted by using the relationship between the structural surface and the production state,the spacing was extracted by using the correspondence between each triangular surface sheet and the normal vector axis of the corresponding structural quilt,and the structural surface trace length was extracted according to the window method,and then combined with the two-dimensional roughness coefficient JRC^2D proposed by Barton and the semi-empirical formula proposed by Du Shigui,the three-dimensional roughness coefficient JRC^3Dwas extracted.（5）Based on the on-site information of underground tunnel structural planes,the method proposed in this article has been validated and analyzed.The method proposed in this article has guiding significance for the collection of underground tunnel structural plane information and provides important basis for tunnel stability analysis.