This study introduces an innovative Roughness-CANUPO-Dip-Facet (R-C-D-F) methodology for the measurement of dip angle and direction in geological rock facets. The R-C-D-F method is distinguished by its comprehensive four-step approach, encompassing filtration through roughness analysis, CANUPO analysis, and dip angle filtration, followed by facet segmentation as the measurement step. To achieve precise and efficient results, the method specifically focuses on isolating joint embedment, achieved by systematically filtering out joint bands. This selective filtration process ensures that measurements are conducted exclusively on relevant joint embedment points. The novelty of this methodology lies in its capability to automatically eliminate joint bands while retaining the joint embedment points, facilitating precise measurements without manual intervention. Three site models were evaluated using the R-C-D-F method, alongside four different techniques for measuring dip angle and direction: plane fitting, normal vector conversion, facet segmentation, and compass measurements. The results demonstrated that all methods accurately calculated the dip angle, with an accuracy ranging from 97 % to 99.4 %. The facet segmentation method was selected as the optimal measurement tool due to its automatic nature and capacity to provide accurate results without manual intervention. Furthermore, the optimal local neighbour radius (LNR) for calculating normal vectors was determined, with findings indicating that a larger LNR value enhances accuracy but also increases computational time. A verification was conducted to estimate the dip angle used for filtering and discarding additional points representing joint rock bands, with the optimal value being 45, 30, and 45 degrees for the respective sites.

中文翻译：

---

RCDF机器学习方法测量岩石隧道掌子面3D点云地质结构


本研究介绍了一种创新的粗糙度-CANUPO-Dip-Facet (RCDF) 方法，用于测量地质岩石面的倾角和方向。 RCDF 方法的特点是其全面的四步方法，包括通过粗糙度分析进行过滤、CANUPO 分析和倾角过滤，然后进行面分割作为测量步骤。为了获得精确有效的结果，该方法特别关注隔离联合嵌入，通过系统地滤除联合频带来实现。这种选择性过滤过程可确保仅在相关的关节嵌入点上进行测量。该方法的新颖之处在于它能够自动消除接头带，同时保留接头嵌入点，从而无需人工干预即可进行精确测量。使用 RCDF 方法评估了三个场地模型，以及测量倾角和方向的四种不同技术：平面拟合、法向矢量转换、面分割和罗盘测量。结果表明，所有方法都能准确计算倾角，准确度在97%~99.4%之间。小平面分割方法被选为最佳测量工具，因为它具有自动性质并且能够在无需人工干预的情况下提供准确的结果。此外，还确定了计算法向向量的最佳局部邻居半径 (LNR)，研究结果表明较大的 LNR 值可以提高准确性，但也会增加计算时间。 进行了验证，以估计用于过滤和丢弃代表节理岩石带的附加点的倾角，各个地点的最佳值为 45、30 和 45 度。