In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for ...In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for acquiring discontinuity measurements from 3D models,such as point clouds generated using laser scanning or photogrammetry.However,even with numerous automated and semiautomated methods presented in the literature,there is not one single method that can automatically characterize discontinuities accurately in a minimum of time.In this paper,we critically review all the existing methods proposed in the literature for the extraction of discontinuity characteristics such as joint sets and orientations,persistence,joint spacing,roughness and block size using point clouds,digital elevation maps,or meshes.As a result of this review,we identify the strengths and drawbacks of each method used for extracting those characteristics.We found that the approaches based on voxels and region growing are superior in extracting joint planes from 3D point clouds.Normal tensor voting with trace growth algorithm is a robust method for measuring joint trace length from 3D meshes.Spacing is estimated by calculating the perpendicular distance between joint planes.Several independent roughness indices are presented to quantify roughness from 3D surface models,but there is a need to incorporate these indices into automated methodologies.There is a lack of efficient algorithms for direct computation of block size from 3D rock mass surface models.展开更多
Although boundary displacement and traction are independent field variables in boundary conditions of an elasticity problem at a non-singular boundary point, there exist definite relations of singularity intensities b...Although boundary displacement and traction are independent field variables in boundary conditions of an elasticity problem at a non-singular boundary point, there exist definite relations of singularity intensities between boundary displacement derivatives and tractions at a singular boundary point. The analytical forms of the relations at a singular smooth point for 2D isotropic elastic problems have been established in this work. By using the relations, positions of the singular boundary points and the corresponding singularity intensities of the unknown boundary field variables can be determined a priori. Therefore, more appropriate shape functions of the unknown boundary field variables in singular elements can be constructed. A numerical example shows that the accuracy of the BEM analysis using the developed theory is greatly increased.展开更多
This paper presents an automated method for discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces.Specifically,the method consists of five steps:(1)detection of trace feature points by...This paper presents an automated method for discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces.Specifically,the method consists of five steps:(1)detection of trace feature points by normal tensor voting theory,(2)co ntraction of trace feature points,(3)connection of trace feature points,(4)linearization of trace segments,and(5)connection of trace segments.A sensitivity analysis was then conducted to identify the optimal parameters of the proposed method.Three field cases,a natural rock mass outcrop and two excavated rock tunnel surfaces,were analyzed using the proposed method to evaluate its validity and efficiency.The results show that the proposed method is more efficient and accurate than the traditional trace mapping method,and the efficiency enhancement is more robust as the number of feature points increases.展开更多
Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results ca...Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.展开更多
This paper introduces the use of point cloud processing for extracting 3D rock structure and the 3DEC-related reconstruction of slope failure,based on a case study of the 2019 Pinglu rockfall.The basic processing proc...This paper introduces the use of point cloud processing for extracting 3D rock structure and the 3DEC-related reconstruction of slope failure,based on a case study of the 2019 Pinglu rockfall.The basic processing procedure involves:(1)computing the point normal for HSV-rendering of point cloud;(2)automatically clustering the discontinuity sets;(3)extracting the set-based point clouds;(4)estimating of set-based mean orientation,spacing,and persistence;(5)identifying the block-forming arrays of discontinuity sets for the assessment of stability.The effectiveness of our rock structure processing has been proved by 3D distinct element back analysis.The results show that Sf M modelling and rock structure computing provides enormous cost,time and safety incentives in standard engineering practice.展开更多
Smartphones are usually packed with a large number of features.An increasing number of researchers are paying attention to the technological capabilities of smartphones,which is a new topic and research interest.This ...Smartphones are usually packed with a large number of features.An increasing number of researchers are paying attention to the technological capabilities of smartphones,which is a new topic and research interest.This paper proposes a method using smartphones and digital photogrammetry to measure the discontinuity orientation of a rock mass.Smartphone photos satisfying a certain overlap rate provide an efficient method for generating point cloud models of rock outcrops based on image matching.Using the target and the generated point cloud model allows for determining actual geographic coordinates and the measurement of discontinuity orientations.The method proposed has been applied to two different study areas.The discontinuity orientations measured by the proposed method are compared with those measured by the manual method in two cases.The results show a good agreement,verifying the reliability and accuracy of the proposed method.The main contribution of this paper is to use knowledge of coordinate rotation to determine the actual geographic location of the model through a square target.The equipment used in this study is simple,and photogrammetric field surveys are easy to carry out.展开更多
Discontinuity is critical for strength,deformability,and permeability of rock mass.Set information is one of the essential discontinuity characteristics and is usually accessed by orientation grouping.Traditional meth...Discontinuity is critical for strength,deformability,and permeability of rock mass.Set information is one of the essential discontinuity characteristics and is usually accessed by orientation grouping.Traditional methods of identifying optimal discontinuity set numbers are usually achieved by clustering validity indexes,which mainly relies on the aggregation and dispersion of clusters and leads to the inaccuracy and instability of evaluation.This paper proposes a new method of Fisher mixed evaluation(FME)to identify optimal group numbers of rock mass discontinuity orientation.In FME,orientation distribution is regarded as the superposition of Fisher mixed distributions.Optimal grouping results are identified by considering the fitting accuracy of Fisher mixed distributions,the probability monopoly and central location significance of independent Fisher centers.A Halley-Expectation-Maximization(EM)algorithm is derived to achieve an automatic fitting of Fisher mixed distribution.Three real rock discontinuity models combined with three orientation clustering algorithms are adopted for discontinuity grouping.Four clustering validity indexes are used to automatically identify optimal group numbers for comparison.The results show that FME is more accurate and robust than the other clustering validity indexes in optimal discontinuity group number identification for different rock models and orientation clustering algorithms.展开更多
本文使用SqueezeNet网络作为基础,构建深度学习点云结构面智能识别模型,案例采用RockBench公开数据库中的数据来验证深度学习模型的识别效果。扫描岩体位于西班牙拜克斯营地地区的TP-7101公路沿线,使用Optech LLRIS 3D激光扫描仪获取点...本文使用SqueezeNet网络作为基础,构建深度学习点云结构面智能识别模型,案例采用RockBench公开数据库中的数据来验证深度学习模型的识别效果。扫描岩体位于西班牙拜克斯营地地区的TP-7101公路沿线,使用Optech LLRIS 3D激光扫描仪获取点云数据。以点云XYZ坐标和法向量作为输入数据,之后挑选550个点构建训练数据集,设置模型的最优参数并以此训练深度学习模型。将训练好的深度学习模型应用到整个点云数据中,对点云数据进行结构面分组。同时,引入Ordering Points to Identify the Clustering Structure(OPTICS)和Density-Based Spatial Clustering of Applications with Noise(DBSCAN)对得到的结构面组进行划分,得到单个结构面。最后,计算出各个结构面的产状。为了验证深度学习模型的识别准确率,采用传统的BP神经网络方法进行验证,计算5组结构面的平均值产状,并与前人计算结果进行对比。经过对比,深度学习模型的计算准确率明显高于浅层BP神经网络模型,其倾向平均误差为9.6456°、倾角平均误差为7.6890°。整体来看,深度学习模型结构更加复杂、提取信息的能力更强,产状计算误差更小。展开更多
Grasslands in the Qinghai–Tibet Plateau play an important role in preserving ecological security and high biodiversity in this region.However,the distribution of the composition and structure of plant community and t...Grasslands in the Qinghai–Tibet Plateau play an important role in preserving ecological security and high biodiversity in this region.However,the distribution of the composition and structure of plant community and the mechanism by which it maintains itself in this region are still poorly understood.Here,we designed 195 grassland plots in 39 grassland sites along an approximately 1700 m elevation gradient on the Northeastern Qinghai–Tibet Plateau.We found that the grassland community height decreased significantly with increasing elevation,whereas community coverage did not significantly change.With increasing elevation,plant species richness(αdiversity)increased significantly,but the community variability(βdiversity)decreased significantly.The constrained clustering analysis suggested that theα-andβ-diversity in the grasslands transformed gradually with elevation,and that three discontinuous points(based on community structure)were observed at elevation of 3640,4252 and 4333 m.Structural equation modeling(SEM)indicated that the increase in precipitation and the decrease in temperature significantly positively influencedαdiversity,which was negatively correlated withβdiversity.These results demonstrate a quantitative-to-qualitative change in the community composition and structure along this elevational gradient on the Qinghai–Tibet Plateau.展开更多
基金funded by the U.S.National Institute for Occupational Safety and Health(NIOSH)under the Contract No.75D30119C06044。
文摘In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for acquiring discontinuity measurements from 3D models,such as point clouds generated using laser scanning or photogrammetry.However,even with numerous automated and semiautomated methods presented in the literature,there is not one single method that can automatically characterize discontinuities accurately in a minimum of time.In this paper,we critically review all the existing methods proposed in the literature for the extraction of discontinuity characteristics such as joint sets and orientations,persistence,joint spacing,roughness and block size using point clouds,digital elevation maps,or meshes.As a result of this review,we identify the strengths and drawbacks of each method used for extracting those characteristics.We found that the approaches based on voxels and region growing are superior in extracting joint planes from 3D point clouds.Normal tensor voting with trace growth algorithm is a robust method for measuring joint trace length from 3D meshes.Spacing is estimated by calculating the perpendicular distance between joint planes.Several independent roughness indices are presented to quantify roughness from 3D surface models,but there is a need to incorporate these indices into automated methodologies.There is a lack of efficient algorithms for direct computation of block size from 3D rock mass surface models.
文摘Although boundary displacement and traction are independent field variables in boundary conditions of an elasticity problem at a non-singular boundary point, there exist definite relations of singularity intensities between boundary displacement derivatives and tractions at a singular boundary point. The analytical forms of the relations at a singular smooth point for 2D isotropic elastic problems have been established in this work. By using the relations, positions of the singular boundary points and the corresponding singularity intensities of the unknown boundary field variables can be determined a priori. Therefore, more appropriate shape functions of the unknown boundary field variables in singular elements can be constructed. A numerical example shows that the accuracy of the BEM analysis using the developed theory is greatly increased.
基金supported by the Special Fund for Basic Research on Scientific Instruments of the National Natural Science Foundation of China(Grant No.4182780021)Emeishan-Hanyuan Highway ProgramTaihang Mountain Highway Program。
文摘This paper presents an automated method for discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces.Specifically,the method consists of five steps:(1)detection of trace feature points by normal tensor voting theory,(2)co ntraction of trace feature points,(3)connection of trace feature points,(4)linearization of trace segments,and(5)connection of trace segments.A sensitivity analysis was then conducted to identify the optimal parameters of the proposed method.Three field cases,a natural rock mass outcrop and two excavated rock tunnel surfaces,were analyzed using the proposed method to evaluate its validity and efficiency.The results show that the proposed method is more efficient and accurate than the traditional trace mapping method,and the efficiency enhancement is more robust as the number of feature points increases.
基金supported by the National Key R&D Program of China(No.2023YFC3081200)the National Natural Science Foundation of China(No.42077264)the Scientific Research Project of PowerChina Huadong Engineering Corporation Limited(HDEC-2022-0301).
文摘Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.
基金supported by the National Innovation Research Group Science Fund(No.41521002)the National Key Research and Development Program of China(No.2018YFC1505202)。
文摘This paper introduces the use of point cloud processing for extracting 3D rock structure and the 3DEC-related reconstruction of slope failure,based on a case study of the 2019 Pinglu rockfall.The basic processing procedure involves:(1)computing the point normal for HSV-rendering of point cloud;(2)automatically clustering the discontinuity sets;(3)extracting the set-based point clouds;(4)estimating of set-based mean orientation,spacing,and persistence;(5)identifying the block-forming arrays of discontinuity sets for the assessment of stability.The effectiveness of our rock structure processing has been proved by 3D distinct element back analysis.The results show that Sf M modelling and rock structure computing provides enormous cost,time and safety incentives in standard engineering practice.
基金supported by the National Natural Science Foundation of China(Grant No.51769014),which is gratefully acknowledged.
文摘Smartphones are usually packed with a large number of features.An increasing number of researchers are paying attention to the technological capabilities of smartphones,which is a new topic and research interest.This paper proposes a method using smartphones and digital photogrammetry to measure the discontinuity orientation of a rock mass.Smartphone photos satisfying a certain overlap rate provide an efficient method for generating point cloud models of rock outcrops based on image matching.Using the target and the generated point cloud model allows for determining actual geographic coordinates and the measurement of discontinuity orientations.The method proposed has been applied to two different study areas.The discontinuity orientations measured by the proposed method are compared with those measured by the manual method in two cases.The results show a good agreement,verifying the reliability and accuracy of the proposed method.The main contribution of this paper is to use knowledge of coordinate rotation to determine the actual geographic location of the model through a square target.The equipment used in this study is simple,and photogrammetric field surveys are easy to carry out.
基金supported by the National Natural Science Foundation of China(Grant Nos.42272338,41827807 and 41902275)Shanghai Sailing Program(Grant No.18YF1424400)+7 种基金Joint Fund for Basic Research of High-speed Railway of National Natural Science Foundation of China,China Railway Corporation(U1934212)China State Railway Group Co.,Ltd.(P2019G038)Department of Transportation of Zhejiang Province(202213)China Railway First Survey and Design Institute Group Co.,Ltd.(19-21-1,2022KY53ZD(CYH)-10)China Railway Tunnel Group Co.,Ltd.(CZ02-02-08)PowChina Hebei Transportation Highway Investment Development Co.,Ltd.(TH-201908)Sichuan Railway Investment Group Co.,Ltd.(SRIG2019GG0004)The Science and Technology major program of Guizhou Province[2018]3011.
文摘Discontinuity is critical for strength,deformability,and permeability of rock mass.Set information is one of the essential discontinuity characteristics and is usually accessed by orientation grouping.Traditional methods of identifying optimal discontinuity set numbers are usually achieved by clustering validity indexes,which mainly relies on the aggregation and dispersion of clusters and leads to the inaccuracy and instability of evaluation.This paper proposes a new method of Fisher mixed evaluation(FME)to identify optimal group numbers of rock mass discontinuity orientation.In FME,orientation distribution is regarded as the superposition of Fisher mixed distributions.Optimal grouping results are identified by considering the fitting accuracy of Fisher mixed distributions,the probability monopoly and central location significance of independent Fisher centers.A Halley-Expectation-Maximization(EM)algorithm is derived to achieve an automatic fitting of Fisher mixed distribution.Three real rock discontinuity models combined with three orientation clustering algorithms are adopted for discontinuity grouping.Four clustering validity indexes are used to automatically identify optimal group numbers for comparison.The results show that FME is more accurate and robust than the other clustering validity indexes in optimal discontinuity group number identification for different rock models and orientation clustering algorithms.
文摘本文使用SqueezeNet网络作为基础,构建深度学习点云结构面智能识别模型,案例采用RockBench公开数据库中的数据来验证深度学习模型的识别效果。扫描岩体位于西班牙拜克斯营地地区的TP-7101公路沿线,使用Optech LLRIS 3D激光扫描仪获取点云数据。以点云XYZ坐标和法向量作为输入数据,之后挑选550个点构建训练数据集,设置模型的最优参数并以此训练深度学习模型。将训练好的深度学习模型应用到整个点云数据中,对点云数据进行结构面分组。同时,引入Ordering Points to Identify the Clustering Structure(OPTICS)和Density-Based Spatial Clustering of Applications with Noise(DBSCAN)对得到的结构面组进行划分,得到单个结构面。最后,计算出各个结构面的产状。为了验证深度学习模型的识别准确率,采用传统的BP神经网络方法进行验证,计算5组结构面的平均值产状,并与前人计算结果进行对比。经过对比,深度学习模型的计算准确率明显高于浅层BP神经网络模型,其倾向平均误差为9.6456°、倾角平均误差为7.6890°。整体来看,深度学习模型结构更加复杂、提取信息的能力更强,产状计算误差更小。
基金National Natural Science Foundation of China(31901172)Science and Technology Project of Qinghai Provincial Department of Transportation(2019-07).
文摘Grasslands in the Qinghai–Tibet Plateau play an important role in preserving ecological security and high biodiversity in this region.However,the distribution of the composition and structure of plant community and the mechanism by which it maintains itself in this region are still poorly understood.Here,we designed 195 grassland plots in 39 grassland sites along an approximately 1700 m elevation gradient on the Northeastern Qinghai–Tibet Plateau.We found that the grassland community height decreased significantly with increasing elevation,whereas community coverage did not significantly change.With increasing elevation,plant species richness(αdiversity)increased significantly,but the community variability(βdiversity)decreased significantly.The constrained clustering analysis suggested that theα-andβ-diversity in the grasslands transformed gradually with elevation,and that three discontinuous points(based on community structure)were observed at elevation of 3640,4252 and 4333 m.Structural equation modeling(SEM)indicated that the increase in precipitation and the decrease in temperature significantly positively influencedαdiversity,which was negatively correlated withβdiversity.These results demonstrate a quantitative-to-qualitative change in the community composition and structure along this elevational gradient on the Qinghai–Tibet Plateau.
