Abstract:Rock joints are the main factor influencing the stability of surrounding rock. With the increasing complexity of engineering geological conditions, accurate identification of rock joints has become a key step in ensuring engineering safety. In response to the problems of long working time and high intensity of current contact measurement methods,this article introduces an automatic recognition method for rock jointsbased on Z+F high-precision 3D laser scanner. By using Z+F 3D laser scanner to obtain high-precision 3D point cloud data, combinedwith professional point cloud processing software for point cloud noise reduction, cropping, and other processing, and using the automatic recognition function of the Point Studio software joints recognition module, the joints of the rock mass can be effectively identified. The grouped rock joints information is generated into pole maps and equal density Schmidt maps for rock joints grouping, and the attitude information of the rock joints such as direction, angle, trace length, and spacing is exported. Compared with the on-site contact measurement results, the average error of the intelligent identification of structural surfaces is 1.6 °, and the average error of the jointsis 1.4 °, which can meet the needs of on-site detection and provide a reference for intelligent identification of structural surfaces and rapid parameter extraction in geotechnical engineering.Provide a basis for monitoring and support work.