Identification and evaluation method of rock mass structural surface fluctuation based on 3D laser scanning

Abstract

This invention proposes a method for identifying and evaluating the undulation of rock mass structural surfaces based on 3D laser scanning. The method comprises the following steps: S1. Using a 3D laser scanner to perform 3D laser scanning of a specified rock mass measurement range to obtain a point cloud of the rock mass in the specified area; S2. Preprocessing the point cloud to obtain a point cloud set, screening boundary point clouds from the point cloud set, and fitting structural surfaces using the boundary point clouds; S3. Calculating and marking the undulation of each structural surface; S4. Evaluating the stability of the rock mass based on the undulation of each structural surface. By determining the rock mass structural surface and its undulation, and by evaluating the efficiency of identifying the characteristics of the rock mass structural surface, the present invention can further determine the stability of the rock mass.

Description

Technical Field

[0001] The present invention relates to a rock mass structure identification method, belongs to the technical field of rock mass structure surface feature identification, and particularly relates to a rock mass structure surface fluctuation identification and evaluation method based on three-dimensional laser scanning. Background Art

[0002] The rock mass encountered in geotechnical engineering is composed of structural surfaces and rock blocks. The development characteristics of the structural surfaces are important factors in determining the physical and mechanical properties of the rock mass. In particular, the undulation of the structural surface is a key input parameter for determining the shear strength of the structural surface and has a significant impact on the permeability and deformation characteristics of the rock mass. Because the development scale of structural surfaces varies greatly and the undulation of the structural surface is highly random, the local area measured manually is likely to be unrepresentative, and manual measurement of each structural surface individually is also extremely inefficient.

[0003] As an emerging surveying and mapping technology, 3D laser scanning has been widely used in fields such as topographic mapping and deformation monitoring. It can obtain 3D coordinate information by non-contact scanning of surface point clouds, restoring the measured object. Scanning within a 360° horizontal range and a 270° vertical range overcomes the shortcomings of traditional measurement methods and significantly improves the efficiency of identifying the features of rock mass structural surfaces. Therefore, it is crucial to propose a method for identifying and evaluating the undulation of rock mass structural surfaces based on 3D laser scanning. This method can identify the structural surfaces and their local features, facilitating further assessment of the stability of the rock mass structure. Summary of the Invention

[0004] The purpose of the present invention is to overcome the above-mentioned defects and problems existing in the prior art and to provide a method for identifying and evaluating the undulation of rock structural surfaces based on three-dimensional laser scanning, which uses rock point clouds to construct structural surfaces and grow them, thereby determining abnormal point clouds inside and outside the structural surface and further analyzing the degree of concavity and convexity.

[0005] To achieve the above objectives, the technical solution of the present invention is: a method for identifying and evaluating the undulation of rock mass structural surfaces based on three-dimensional laser scanning, comprising:

[0006] S1. Use a 3D laser scanner to perform 3D laser scanning on the set rock mass measurement range to obtain a point cloud of the rock mass in the specified area;

[0007] S2. Preprocess the point cloud to obtain a point cloud set; filter the boundary point cloud from the point cloud set and fit the structural surface using the boundary point cloud;

[0008] S3. Calculate and mark the undulation of each structural surface;

[0009] S4. Evaluate the stability of the rock mass based on the undulation of the structural surface.

[0010] On the basis of the above technical solution, preferably, in step S1, when performing three-dimensional laser scanning, an odd number of measuring points are arranged along the horizontal extension direction of the set rock mass, the distance between adjacent measuring points does not exceed 1 / 3 of the maximum scanning distance of the three-dimensional laser scanner, and the point clouds obtained by adjacent measuring points for the same rock mass overlap by more than 15%, and targets are set in the scanning area where the point clouds overlap.

[0011] Preferably, in step S2, the point cloud is preprocessed to obtain a point cloud set, specifically including:

[0012] The acquired point cloud is denoised; after eliminating the noise points, the point clouds of each measuring point are fused according to the posture of the target in the overlapping area of ​​the point clouds; the distance between adjacent point clouds in the fused point cloud is set to 5mm and resampled; all the point clouds after resampling are the point cloud set; each point cloud in the point cloud set is transferred to the world coordinate system to obtain the real three-dimensional coordinates.

[0013] Further preferably, in step S2, the step of screening the boundary point cloud from the point cloud set and fitting the structural surface using the boundary point cloud specifically includes:

[0014] S21, selecting a point cloud P from the point cloud set as a center point, and obtaining a first neighborhood point set within a circular neighborhood with a preset radius centered on the center point;

[0015] S22, constructing a covariance matrix C based on the principal components of the first neighborhood point set, obtaining eigenvalues ​​of the covariance matrix C, and determining the curvature of the first neighborhood point set based on the eigenvalues;

[0016] If the curvature of the first neighborhood point set is less than the curvature threshold, it indicates that the point clouds of the first neighborhood point set are located in the same plane, and step S23 is executed;

[0017] If the curvature of the first neighborhood point set is not less than the curvature threshold, the point clouds of the first neighborhood point set are checked one by one and the location of the point cloud causing the regional abnormality is marked as the first abnormal point cloud, and several first abnormal point clouds are constructed into a first abnormal point cloud set, the position of the center point is adjusted or the preset radius is reduced, and step S22 is re-executed;

[0018] S23, performing plane fitting of the first neighborhood point set, and taking the plane fitted by the first neighborhood point set as a structural surface; the expression of the fitted plane is:

[0019] v1x+v2y+v3z+d=0;

[0020] v = (v1, v2, v3);

[0021] Where: v = (v1, v2, v3) is the normal vector of the fitting plane, x, y, z are the three-dimensional coordinate axes, and d is the distance from the fitting plane to the origin of the world coordinate system;

[0022] S24: Take any point cloud outside the boundary of the circular area where the first neighborhood point set is located as a new center point, obtain a second neighborhood point set again within the circular neighborhood of the new center point with a preset radius, and recalculate the curvature of the second neighborhood point set and the normal vector of the fitted plane according to the method of steps S22 and S23, and determine the curvature of the second neighborhood point set;

[0023] If the curvature of the second neighborhood point set is less than the curvature threshold, the point cloud of the second neighborhood point set is deemed to be coplanar, and it is further determined whether the angle deviation between the normal vector of the fitting plane of the second neighborhood point set and the normal vector of the fitting plane of the first neighborhood point set exceeds the first angle threshold;

[0024] If the angle does not exceed the first angle threshold, the point cloud of the second neighborhood point set is added to the first neighborhood point set;

[0025] If the angle exceeds the first threshold, the point cloud in the second neighborhood point set is saved separately as a new structural surface;

[0026] Calculate the normal vector for each point cloud located on the same structural surface and set the second angle threshold;

[0027] If the angle between the normal vector of the point cloud and the normal vector of the structural surface does not exceed the second angle threshold, the point cloud is retained;

[0028] If the angle between the normal vector of the point cloud and the normal vector of the structural surface exceeds the second angle threshold, the abnormal point cloud is removed from the neighborhood point set corresponding to the current structural surface, marked and saved as a second abnormal point cloud, and a second abnormal point cloud set containing several second abnormal point clouds is constructed;

[0029] If the curvature of the second neighborhood point set is not less than the curvature threshold, the location of the point cloud that causes the regional anomaly is marked, and the point cloud is added to the first abnormal point cloud set. The position of the center point is adjusted or the preset radius is reduced, and the second neighborhood point set is obtained again, and step S24 is executed again;

[0030] S25. Repeat steps S21-S24 until all non-marked abnormal point clouds in the point cloud set are fitted into structural surfaces.

[0031] More preferably, the step S22 specifically includes:

[0032] Construct the covariance matrix as:

[0033]

[0034] Where: pi is a point in the first neighborhood point set, i = 1, 2, 3, ..., n;

[0035] Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalue λ and eigenvector V, λV = CV, eigenvalue λ = (λ1, λ2, λ3), λ1 ≥ λ2 ≥ λ3, eigenvector V = (V1, V2, V3);

[0036] Set the curvature s as follows:

[0037]

[0038] The curvature threshold is 0.15.

[0039] Further preferably, in step S22, the step of checking the point clouds of the first neighborhood point set one by one and marking the locations of the point clouds causing regional anomalies to construct the first abnormal point cloud set specifically refers to:

[0040] Specify a reference direction, traverse the point cloud in the circular neighborhood of the center point in a clockwise direction, and sequentially number the point clouds in the neighborhood point set according to the angle with the reference direction; when the curvature of the first neighborhood point set is not less than the curvature threshold, eliminate several point clouds in the first neighborhood point set with point cloud numbers from large to small; if after eliminating several point clouds, the curvature of the recalculated first neighborhood point set is still less than the curvature threshold, then mark the eliminated point clouds as the first abnormal point cloud and add them to the first abnormal point cloud set.

[0041] Preferably, the first angle threshold is 3°; the second angle threshold is 10°.

[0042] Further preferably, the step S3 specifically includes:

[0043] S31, identifying the point cloud in the first abnormal point cloud set, that is, identifying whether the point cloud in the first abnormal point cloud set belongs to any structural surface;

[0044] If it belongs to any structural surface, the point cloud is removed from the first abnormal point cloud set;

[0045] If it does not belong to any structural surface, the first abnormal point cloud is considered to belong to the boundary of the rock mass;

[0046] S32. For the structural surface with the second abnormal point cloud, determine whether there is a depression or a bulge;

[0047] S33. For a structural surface identified as having a depression or a protrusion, obtain a trace of the structural surface and draw several virtual line segments parallel to the trace, such that the virtual line segments pass through the second abnormal point cloud and its vicinity. Draw contour lines deviating from the structural surface based on the distance between the real three-dimensional coordinates of each point cloud on the virtual line segment and the structural surface, with equal spacing between adjacent contour lines; and obtain the distance of the contour line farthest from the structural surface.

[0048] S34. Calculate a first area of ​​a region enclosed by a contour line closest to the structural surface, and use the ratio of the first area to the projected area of ​​the structural surface to measure the undulation of the structural surface.

[0049] More preferably, the step S34 specifically includes:

[0050] Use a straight line to fit the vertices of the contour lines closest to the structural surface, and construct a virtual circumscribed circle so that the outline of the virtual circumscribed circle has the most vertices of the contour lines. Calculate the first area using the following formula:

[0051]

[0052] Where: r is the radius of the virtual circumcircle, k1 and k2 are adjustment coefficients, x1 is the number of contour vertices that intersect the outline of the virtual circumcircle, and x2 is the number of contour vertices located inside the virtual circumcircle;

[0053] Let the projected area of ​​the structural surface be S0, and then the ratio of the first area to the projected area of ​​the structural surface S1 / S0 is used as the undulation of the structural surface.

[0054] More preferably, the step S4 specifically includes:

[0055] After obtaining the undulation S1 / S0 of the structural surface and the distance h from the contour line farthest from the structural surface, the stability of the rock mass is judged according to the following situations:

[0056] The first type: if the ratio of the undulation S1 / S0 does not exceed 10%, the stability of the rock mass is considered to be level 1;

[0057] The second type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest line connecting the vertices of the area enclosed by the contour line closest to the structural surface and the length of the structural surface is greater than 30°, the stability of the rock mass is considered to be level 2;

[0058] The third type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest line connecting the vertices of the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area S enclosed by the contour line farthest from the structural surface are equal. hThe rate of change of the difference with the distance from the contour line farthest from the structural surface (S1-S h ) / h>25, the stability of the rock mass is considered to be level 3;

[0059] The fourth type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest line connecting the vertices of the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area S enclosed by the contour line farthest from the structural surface are equal. h The rate of change of the difference with the distance from the contour line farthest from the structural surface (S1-S h ) / h≤25, the stability of the rock mass is considered to be level 4;

[0060] The stability of the rock mass is arranged from highest to worst, namely level 4, level 3, level 2, and level 1.

[0061] Compared with the prior art, the present invention has the following beneficial effects:

[0062] 1. The present invention provides a method for identifying and evaluating the undulation of rock mass structural surfaces based on three-dimensional laser scanning. The method can quickly obtain the rock mass structural surface and identify possible undulations or depressions on the surface of the structural surface from the fitting and growth process of the structural surface, thereby further identifying the stability state of the rock mass. It can automatically and quickly identify environmental risk factors, and has good auxiliary significance for engineering construction and disaster prevention.

[0063] 2. In the rock mass structural surface fluctuation identification and evaluation method based on three-dimensional laser scanning of the present invention, whether the structural surface is stable and the stability classification can be quickly evaluated according to the set value range. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0065] Figure 1 This is a flow chart of the steps of a method for identifying and evaluating the undulation of a rock structure surface based on three-dimensional laser scanning according to the present invention. DETAILED DESCRIPTION

[0066] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0067] Example 1:

[0068] like Figure 1 As shown, the present invention provides a method for identifying and evaluating the undulation of rock mass structural surfaces based on three-dimensional laser scanning, comprising the following steps:

[0069] S1. Use a 3D laser scanner to perform 3D laser scanning on the set rock mass measurement range to obtain a point cloud of the rock mass in the specified area;

[0070] During 3D laser scanning, an odd number of measuring points are placed along the horizontal extension of the designated rock mass. The spacing between adjacent measuring points does not exceed 1 / 3 of the 3D laser scanner's maximum scanning distance, and the point clouds captured by adjacent measuring points for the same rock mass overlap by more than 15%. Targets are set in the scanning areas where the point clouds overlap. Setting this spacing and ensuring point cloud overlap ensures point cloud accuracy and provides a foundation for subsequent stitching of point clouds from different measuring points. During actual measurement, for rock masses with potential blind spots, the density of local measurements can be increased to capture point clouds from multiple angles.

[0071] S2. Preprocess the point cloud to obtain a point cloud set; filter the boundary point cloud from the point cloud set and fit the structural surface using the boundary point cloud;

[0072] This step includes two aspects. The first is the point cloud preprocessing process, which is to denoise the acquired point cloud. After eliminating the noise points, the point clouds of each measuring point are fused according to the posture of the target in the overlapping area of ​​the point cloud. The distance between adjacent point clouds in the fused point cloud is set to 5mm, and resampling is performed. All point clouds after resampling are the point cloud set. Each point cloud in the point cloud set is transferred to the world coordinate system to obtain the real three-dimensional coordinates.

[0073] Typically, to obtain higher-precision rock mass point clouds, a more refined scanning mode is selected. This results in a massive amount of point cloud data, with scanning a single point taking over ten minutes to generate millions of point clouds. To improve the efficiency of subsequent data processing, resampling is employed to reduce the point cloud density, significantly reducing the total number of points. Point clouds that do not belong to the rock mass can be manually deleted.

[0074] Then, we use the point cloud set to filter the boundary point cloud from the point cloud set and use the boundary point cloud to fit the structural surface, which specifically includes the following:

[0075] S21, selecting a point cloud p from the point cloud set as the center point, and obtaining a first neighborhood point set within a circular neighborhood with a preset radius centered on the center point;

[0076] S22, constructing a covariance matrix C based on the principal components of the first neighborhood point set, obtaining eigenvalues ​​of the covariance matrix C, and determining the curvature of the first neighborhood point set based on the eigenvalues;

[0077] To determine the curvature of the first neighborhood point set based on the eigenvalue, the following steps are performed:

[0078] Construct the covariance matrix as:

[0079]

[0080] Where: p i is a point in the first neighborhood point set, i = 1, 2, 3, ..., n;

[0081] Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalue λ and eigenvector V, λV = CV, eigenvalue λ = (λ1, λ2, λ3), λ1 ≥ λ2 ≥ λ3, eigenvector V = (V1, V2, V3);

[0082] Set the curvature s as follows:

[0083]

[0084] The curvature threshold is 0.15.

[0085] If the curvature of the first neighborhood point set is less than the curvature threshold, it indicates that the point clouds of the first neighborhood point set are located in the same plane, and step S23 is executed;

[0086] If the curvature of the first neighborhood point set is not less than the curvature threshold, the point clouds of the first neighborhood point set are checked one by one and the location of the point cloud causing the regional abnormality is marked as the first abnormal point cloud, and several first abnormal point clouds are constructed into a first abnormal point cloud set, the position of the center point is adjusted or the preset radius is reduced, and step S22 is re-executed;

[0087] The position of the center point can be adjusted here by moving the unit point cloud away from the first abnormal point cloud by an integer multiple of its density, or by reducing the radius of the current circular neighborhood by 5% of the preset radius without changing the current center point position, such as reducing the preset radius by 5% for the first time, reducing the preset radius by 10% for the second time, and so on, until the curvature threshold requirement is met.

[0088] In step S22, the step of checking the point clouds of the first neighborhood point set one by one and marking the locations of the point clouds that cause regional anomalies to construct the first abnormal point cloud set specifically includes:

[0089] Specify a reference direction, traverse the point cloud in the circular neighborhood of the center point in a clockwise direction, and sequentially number the point clouds in the neighborhood point set according to the angle with the reference direction; when the curvature of the first neighborhood point set is not less than the curvature threshold, eliminate several point clouds in the first neighborhood point set with point cloud numbers from large to small; if after eliminating several point clouds, the curvature of the recalculated first neighborhood point set is still less than the curvature threshold, then mark the eliminated point clouds as the first abnormal point cloud and add them to the first abnormal point cloud set.

[0090] For example, for a point cloud with n sequential numbers, first check one by one in the order of the nth, n-1th, and n-2th. If the curvature calculation result after one round of checking is not ideal, start the second round of checking. At this time, the second round of checking is performed according to the nth point cloud + n-1th point cloud, n-1th point cloud + n-2th point cloud, and so on. That is, 2 point clouds are eliminated each time, and one point cloud is repeatedly eliminated, and this process is repeated until the neighborhood point cloud that meets the requirements is screened, and the first abnormal point cloud that is eliminated is added to the first abnormal point cloud set.

[0091] S23, performing plane fitting of the first neighborhood point set, and taking the plane fitted by the first neighborhood point set as a structural surface; the expression of the fitted plane is:

[0092] v1x+v2y+v3z+d=0;

[0093] v = (v1, v2, v3);

[0094] Where: v = (v1, v2, v3) is the normal vector of the fitting plane, x, y, z are the three-dimensional coordinate axes, and d is the distance from the fitting plane to the origin of the world coordinate system;

[0095] S24: Take any point cloud outside the boundary of the circular area where the first neighborhood point set is located as a new center point, obtain a second neighborhood point set again within the circular neighborhood of the new center point with a preset radius, and recalculate the curvature of the second neighborhood point set and the normal vector of the fitted plane according to the method of steps S22 and S23, and determine the curvature of the second neighborhood point set;

[0096] If the curvature of the second neighborhood point set is less than the curvature threshold, the point cloud of the second neighborhood point set is deemed to be coplanar, and it is further determined whether the angle deviation between the normal vector of the fitting plane of the second neighborhood point set and the normal vector of the fitting plane of the first neighborhood point set exceeds the first angle threshold;

[0097] If the angle does not exceed the first angle threshold, the point cloud of the second neighborhood point set is added to the first neighborhood point set to achieve the expansion of the structural surface corresponding to the first neighborhood point set;

[0098] If the angle exceeds the first angle threshold, the point cloud in the second neighborhood point set is saved separately as a new structural surface. This step realizes the process of growing the existing structural surface or generating a new structural surface.

[0099] Calculate the normal vector for each point cloud located on the same structural surface and set the second angle threshold;

[0100] If the angle between the normal vector of the point cloud and the normal vector of the structural surface does not exceed the second angle threshold, the point cloud is retained;

[0101] If the angle between the normal vector of the point cloud and the normal vector of the structural surface exceeds the second angle threshold, the abnormal point cloud is removed from the neighborhood point set corresponding to the current structural surface, marked and saved as a second abnormal point cloud, and a second abnormal point cloud set containing several second abnormal point clouds is constructed;

[0102] If the curvature of the second neighborhood point set is not less than the curvature threshold, the location of the point cloud that causes the regional anomaly is marked, and the point cloud is added to the first abnormal point cloud set. The position of the center point is adjusted or the preset radius is reduced, and the second neighborhood point set is obtained again, and step S24 is executed again;

[0103] In this embodiment, the first angle threshold is set to 3°, and the second angle threshold is set to 10°. The second abnormal point cloud is a point cloud whose normal vector is obviously different from other point clouds on the structural surface.

[0104] The point cloud that causes curvature anomaly has a specific curvature that is obviously inconsistent with the curvature of other point clouds and requires further judgment, so it is marked and saved.

[0105] S25. Repeat steps S21-S24 until all non-marked abnormal point clouds in the point cloud set are fitted into structural surfaces.

[0106] S3. Calculate and mark the undulation of each structural surface;

[0107] The specific contents of this step are:

[0108] S31, identifying the point cloud in the first abnormal point cloud set, that is, identifying whether the point cloud in the first abnormal point cloud set belongs to any structural surface;

[0109] If it belongs to any structural surface, the point cloud is removed from the first abnormal point cloud set;

[0110] If it does not belong to any structural surface, the first abnormal point cloud is considered to belong to the boundary of the rock mass;

[0111] The first abnormal point cloud belonging to the structural surface will be removed from the first abnormal point cloud set until the remaining point clouds are all boundaries of the rock mass. The boundary of the rock mass defines the extreme position of the growth direction of the structural surface.

[0112] S32. For the structural surface with the second abnormal point cloud, determine whether there is a depression or a bulge;

[0113] S33. For a structural surface identified as having a depression or a protrusion, obtain a trace of the structural surface and draw several virtual line segments parallel to the trace, such that the virtual line segments pass through the second abnormal point cloud and its vicinity. Draw contour lines deviating from the structural surface based on the distance between the real three-dimensional coordinates of each point cloud on the virtual line segment and the structural surface, with equal spacing between adjacent contour lines; and obtain the distance of the contour line farthest from the structural surface.

[0114] The trace is a key element of the structural surface. The endpoints of the trace determine the edge feature position of the structural surface and correspond to the maximum extension range of the structural surface. The trace is contained in the structural surface. The trace is a three-dimensional line. However, since the three-dimensional coordinates of each point cloud including the second abnormal point cloud in the world coordinate system are known, the relative position relationship between the second abnormal point cloud and the trace is easy to obtain, and the contour line can reflect the shape characteristics of the convex or concave parts.

[0115] S34. Calculate a first area of ​​a region enclosed by a contour line closest to the structural surface, and use the ratio of the first area to the projected area of ​​the structural surface to measure the undulation of the structural surface.

[0116] The step S34 specifically includes:

[0117] Use a straight line to fit the vertices of the contour lines closest to the structural surface, and construct a virtual circumscribed circle so that the outline of the virtual circumscribed circle has the most vertices of the contour lines. Calculate the first area using the following formula:

[0118]

[0119] Where: r is the radius of the virtual circumcircle, k1 and k2 are adjustment coefficients, x1 is the number of contour vertices that intersect the outline of the virtual circumcircle, and x2 is the number of contour vertices located inside the virtual circumcircle;

[0120] Let the projected area of ​​the structural surface be S0, and then the ratio of the first area to the projected area of ​​the structural surface S1 / S0 is used as the undulation of the structural surface.

[0121] S4. Evaluate the stability of the rock mass based on the undulation of the structural surface.

[0122] The step S4 specifically includes:

[0123] After obtaining the undulation S1 / S0 of the structural surface and the distance h from the contour line farthest from the structural surface, the stability of the rock mass is judged according to the following situations:

[0124] The first type: if the ratio of the undulation S1 / S0 does not exceed 10%, the stability of the rock mass is considered to be level 1;

[0125] The second type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest line connecting the vertices of the area enclosed by the contour line closest to the structural surface and the length of the structural surface is greater than 30°, the stability of the rock mass is considered to be level 2;

[0126] The third type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest line connecting the vertices of the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area S enclosed by the contour line farthest from the structural surface are equal. h The rate of change of the difference with the distance from the contour line farthest from the structural surface (S1-S h ) / h>25, the stability of the rock mass is considered to be level 3;

[0127] The fourth type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest line connecting the vertices of the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area S enclosed by the contour line farthest from the structural surface are equal. h The rate of change of the difference with the distance from the contour line farthest from the structural surface (S1-S h ) / h≤25, the stability of the rock mass is considered to be level 4;

[0128] The stability of the rock mass is arranged from highest to worst, namely level 4, level 3, level 2, and level 1.

[0129] Although the embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A method for identifying and evaluating the undulation of rock mass structural surfaces based on three-dimensional laser scanning, characterized in that: include: S1. Use a 3D laser scanner to perform 3D laser scanning on the set rock mass measurement range to obtain a point cloud of the rock mass in the specified area; S2. Preprocess the point cloud to obtain a point cloud set; filter the boundary point cloud from the point cloud set and fit the structural surface using the boundary point cloud; In step S2, the step of screening the boundary point cloud from the point cloud set and fitting the structural surface using the boundary point cloud specifically includes: S21. Select 1 point cloud from the point cloud collection As the center point, obtain a first neighborhood point set within a circular neighborhood with a preset radius centered on the center point; S22, constructing the covariance matrix based on the principal components of the first neighborhood point set , find the covariance matrix The eigenvalue of , and the curvature of the first neighborhood point set is determined according to the eigenvalue; If the curvature of the first neighborhood point set is less than the curvature threshold, it indicates that the point clouds of the first neighborhood point set are located in the same plane, and step S23 is executed; If the curvature of the first neighborhood point set is not less than the curvature threshold, the point clouds of the first neighborhood point set are checked one by one and the location of the point cloud causing the regional abnormality is marked as the first abnormal point cloud, and several first abnormal point clouds are constructed into a first abnormal point cloud set, the position of the center point is adjusted or the preset radius is reduced, and step S22 is re-executed; S23, performing plane fitting of the first neighborhood point set, and taking the plane fitted by the first neighborhood point set as a structural surface; the expression of the fitted plane is: ； ； in: is the normal vector of the fitted plane, 、 、 are three-dimensional coordinate axes, is the distance from the fitting plane to the origin of the world coordinate system; S24: Take any point cloud outside the boundary of the circular area where the first neighborhood point set is located as a new center point, obtain a second neighborhood point set again within the circular neighborhood of the new center point with a preset radius, and recalculate the curvature of the second neighborhood point set and the normal vector of the fitted plane according to the method of steps S22 and S23, and determine the curvature of the second neighborhood point set; If the curvature of the second neighborhood point set is less than the curvature threshold, the point cloud of the second neighborhood point set is deemed to be coplanar, and it is further determined whether the angle deviation between the normal vector of the fitting plane of the second neighborhood point set and the normal vector of the fitting plane of the first neighborhood point set exceeds the first angle threshold; If the angle does not exceed the first angle threshold, the point cloud of the second neighborhood point set is added to the first neighborhood point set; If the first angle threshold is exceeded, the point cloud in the second neighborhood point set is saved separately as a new structural surface; Calculate the normal vector for each point cloud located on the same structural surface and set the second angle threshold; If the angle between the normal vector of the point cloud and the normal vector of the structural surface does not exceed the second angle threshold, the point cloud is retained; If the angle between the normal vector of the point cloud and the normal vector of the structural surface exceeds the second angle threshold, the abnormal point cloud is removed from the neighborhood point set corresponding to the current structural surface, marked and saved as a second abnormal point cloud, and a second abnormal point cloud set containing several second abnormal point clouds is constructed; If the curvature of the second neighborhood point set is not less than the curvature threshold, the location of the point cloud that causes the regional anomaly is marked, and the point cloud is added to the first abnormal point cloud set. The position of the center point is adjusted or the preset radius is reduced, and the second neighborhood point set is obtained again, and step S24 is executed again; S25, repeating steps S21-S24 until all non-marked abnormal point clouds in the point cloud set are fitted into structural surfaces; S3. Calculate and mark the undulation of each structural surface; The step S3 specifically includes: S31, identifying the point cloud in the first abnormal point cloud set, that is, identifying whether the point cloud in the first abnormal point cloud set belongs to any structural surface; If it belongs to any structural surface, the point cloud is removed from the first abnormal point cloud set; If it does not belong to any structural surface, the first abnormal point cloud is considered to belong to the boundary of the rock mass; S32. For the structural surface with the second abnormal point cloud, determine whether there is a depression or a bulge; S33. For a structural surface identified as having a depression or a protrusion, obtain a trace of the structural surface and draw several virtual line segments parallel to the trace, such that the virtual line segments pass through the second abnormal point cloud and its vicinity. Draw contour lines deviating from the structural surface based on the distance between the real three-dimensional coordinates of each point cloud on the virtual line segment and the structural surface, with equal spacing between adjacent contour lines; and obtain the distance of the contour line farthest from the structural surface. S34, calculating a first area of ​​a region enclosed by a contour line closest to the structural surface, and measuring the undulation of the structural surface using a ratio of the first area to the projected area of ​​the structural surface; The step S34 specifically includes: Use a straight line to fit the vertices of the contour lines closest to the structural surface, and construct a virtual circumscribed circle so that the outline of the virtual circumscribed circle has the most vertices of the contour lines. Calculate the first area using the following formula: ； in: is the radius of the virtual circumcircle, 、 are adjustment coefficients, is the number of contour vertices that intersect the outline of the virtual circumcircle, is the number of contour vertices located inside the virtual circumcircle; Let the projected area of ​​the structural surface be , then according to the ratio of the first area to the projected area of ​​the structural surface As the undulation of the structural surface; S4. Evaluate the stability of the rock mass based on the undulation of the structural surface.

2. The method for identifying and evaluating the undulation of rock mass structural surfaces based on three-dimensional laser scanning according to claim 1, characterized in that: In step S1, when performing three-dimensional laser scanning, an odd number of measuring points are arranged along the horizontal extension direction of the set rock mass, the distance between adjacent measuring points does not exceed 1 / 3 of the maximum scanning distance of the three-dimensional laser scanner, and the point clouds obtained by adjacent measuring points for the same rock mass overlap by more than 15%, and targets are set in the scanning area where the point clouds overlap.

3. The method for identifying and evaluating rock mass structural surface undulation based on three-dimensional laser scanning according to claim 2, characterized in that: In step S2, the point cloud is preprocessed to obtain a point cloud set, which specifically includes: The acquired point cloud is denoised; after eliminating the noise points, the point clouds of each measuring point are fused according to the posture of the target in the overlapping area of ​​the point clouds; the distance between adjacent point clouds in the fused point cloud is set to 5mm and resampled; all the point clouds after resampling are the point cloud set; each point cloud in the point cloud set is transferred to the world coordinate system to obtain the real three-dimensional coordinates.

4. The method for identifying and evaluating rock mass structural surface undulation based on three-dimensional laser scanning according to claim 1, characterized in that: The step S22 specifically includes: Construct the covariance matrix as: ； in: is a point in the first neighborhood point set, ; Perform eigenvalue decomposition on the covariance matrix to obtain the eigenvalue and eigenvectors , , eigenvalue , , the eigenvector ; Set the curvature as follows: ； The curvature threshold is 0.

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5. The method for identifying and evaluating the undulation of rock mass structural surfaces based on three-dimensional laser scanning according to claim 4, characterized in that: In step S22, the step of checking the point clouds of the first neighborhood point set one by one and marking the locations of the point clouds that cause regional anomalies to construct the first abnormal point cloud set specifically includes: Specify a reference direction, traverse the point cloud in the circular neighborhood of the center point in a clockwise direction, and number the point clouds in the neighborhood point set according to the angle with the reference direction; when the curvature of the first neighborhood point set is not less than the curvature threshold, eliminate the point clouds in the first neighborhood point set with the point cloud numbers from large to small; If after removing several point clouds, the curvature of the recalculated first neighborhood point set is still smaller than the curvature threshold, the removed point clouds are marked as first abnormal point clouds and added to the first abnormal point cloud set.

6. The method for identifying and evaluating the undulation of rock mass structural surfaces based on three-dimensional laser scanning according to claim 5, characterized in that: The first angle threshold is 3°; the second angle threshold is 10°.

7. The method for identifying and evaluating rock mass structural surface undulation based on three-dimensional laser scanning according to claim 1, characterized in that: The step S4 specifically includes: In obtaining the undulation of the structural surface Distance from the contour line that deviates farthest from the structural surface Finally, the stability of the rock mass is judged according to the following situations: The first type: If the fluctuation If the ratio does not exceed 10%, the stability of the rock mass is considered to be level 1; The second type: If the fluctuation If the ratio of exceeds 10%, and the angle between the longest line connecting the vertices in the area enclosed by the contour line closest to the structural surface and the trace length of the structural surface is greater than 30°, the stability of the rock mass is considered to be level 2; The third type: If the fluctuation The ratio of the two is greater than 10%, and the angle between the longest line connecting the vertices of the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area of ​​the area enclosed by the contour line farthest from the structural surface are equal. The rate of change of the difference with the distance from the contour line farthest from the structural surface , then the stability of the rock mass is considered to be level 3; Fourth: If the fluctuation The ratio of the two is greater than 10%, and the angle between the longest line connecting the vertices of the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area of ​​the area enclosed by the contour line farthest from the structural surface are equal. The rate of change of the difference with the distance from the contour line farthest from the structural surface , then the stability of the rock mass is considered to be level 4; The stability of the rock mass is arranged from highest to worst, namely level 4, level 3, level 2, and level 1.

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