## 1 Introduction  
Rock mass structural planes refer to natural or artificial discontinuities in rock masses, including fractures, faults, joints, bedding, and shear zones. The structural planes developed within the rock mass are the weakest geological interfaces in terms of mechanical properties and are critical factors that determine the mechanical behavior and stability of the rock mass [1]. Accurate and efficient identification of rock mass structural planes and the extraction of dominant orientations have always been key concerns in the fields of geotechnical and geological engineering [2, 3]. Traditional methods for surveying structural planes primarily rely on manual operations using simple tools such as measuring tapes and geological compasses for contact measurements. However, when dealing with high and steep rock masses or slopes, these methods are inefficient and carry significant safety risks [4]. Additionally, the data obtained from manual measurements are limited, and these discrete local data points are difficult to integrate for analysis, making comprehensive assessment of the entire rock mass or slope challenging. With the development of non-contact measurement technologies, photogrammetry (UAV) and terrestrial laser scanning (TLS) have been widely applied in geological engineering. Photogrammetry can capture two-dimensional images of rock mass surfaces, and many researchers have used multi-view vision techniques to quickly reconstruct 3D models of the study area and obtain structural plane information from rock masses based on these 2D images [5; 6; 7]. However, photogrammetry is influenced by factors such as image resolution, camera parameters, 3D model construction algorithms, and external environmental conditions. As a result, the final 3D model often has low coordinate accuracy, low automation in structural plane identification, and significant errors in the extracted structural plane information. Terrestrial laser scanning technology overcomes the limitations of single-point measurements and can acquire high-precision, high-density 3D point cloud data that represent the structural features of the rock mass surface, providing fundamental data for structural plane identification and clustering analysis. As early as the late 20 th century, [PERSON] [8] began research on identifying specific planes within 3D point clouds by searching the neighborhood of each core point, applying the PCA method to fit local planes, and calculating the normal vectors of these planes to replace the core point's normal vector. This approach offered a new idea for accurately computing the normal vectors of point cloud data. [PERSON] [9] constructed a triangulated mesh from point cloud data and calculated the orientation of each triangular facet, implementing a fuzzy K-means clustering algorithm to identify structural planes and calculate their spacing. [PERSON] [10] set a coplanarity threshold and used a variable-sized search cube to select points that met the coplanarity threshold for plane fitting and developed the structural plane analysis software DiAna. [PERSON] [11] processed point cloud data by meshing, set appropriate region-growing thresholds, and achieved intelligent identification of rock mass structural planes, summarizing the impact of threshold changes on identification results. [PERSON] [12] applied an improved RANSAC algorithm and an enhanced Graham scan algorithm to identify rock mass structural planes and provide a refined description of structural plane boundaries. She developed the RDD (RANSAC discontinuity detection) program, which can extract orientation and size information of structural planes. [PERSON] et al. [13] utilized the KNN algorithm to search for the optimal neighborhood, calculated the point cloud normal vectors based on coplanarity criteria and the least squares method, and then converted them into orientation information. Finally, the KDE and DBSCAN algorithms were combined to cluster the point cloud data, achieving the extraction of rock mass structural plane information.