Rock mass structure coplanar analysis and digital geological logging method based on non-contact measurement

Abstract

The invention discloses a rock mass structure coplanar analysis and digital geological logging method based on non-contact measurement, and belongs to the technical field of rock mass structural plane analysis, and the method comprises the steps: collecting three-dimensional point cloud coordinate information of a rock mass surface through non-contact measurement equipment, and then obtaining three-dimensional space point cloud data contained in each rock mass structural plane; based on the three-dimensional space point cloud data of each rock mass structural plane, extracting a corresponding topological structural plane contour; based on the topological structural plane contour, a progressive local coplanar discontinuous search method is adopted to carry out coplanar analysis, and multiple groups of coplanar structural plane sets are obtained; and on the basis of a plurality of groups of coplanar structural plane sets, connecting the structural plane traces of each group of coplanar structural planes to obtain a digital geological record graph of the rock mass structural plane. According to the method, the efficient and safe geological logging requirements of the rock mass structural surface in the geotechnical engineering design site construction process of water conservancy and hydropower, traffic tunnels, mine roadways and the like are met.

Description

Technical Field

[0001] This invention belongs to the field of rock mass structure plane analysis technology, specifically involving a method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement. Background Technology

[0002] Geotechnical engineering construction requires extensive rock excavation, and rock mass structural planes are key features revealing the stability of heterogeneous rock masses. They appear in any exposed rock mass near sites such as open slopes, underground tunnels, and mining goafs. Internal structural planes not only reduce the cohesion of the rock mass material but also control the instability and failure modes. Due to the complexity of the construction environment, such as rock weathering and fissure water, rock mass failures in geotechnical engineering are often frequent and dangerous. Therefore, it is crucial to quickly obtain the spatial distribution, anisotropy, and geometric properties of rock mass structural planes during rock excavation.

[0003] To visually represent the spatial relationships of rock mass structural surfaces, exposed rock mass structural surfaces or traces are typically plotted on a two-dimensional plane and their characteristic parameters recorded, forming a planar geological map. Scan-line or scan-area mapping (also known as window mapping) is an early and traditional method for representing the planar characteristics of rock masses. Compared to three-dimensional visualization using point clouds or vector data, it more intuitively displays the cutting and combination characteristics of the rock mass and nearby tectonic activity. It is still widely used in the design and construction of geotechnical engineering projects such as water conservancy and hydropower, transportation tunnels, and mine roadways. Currently, the methods and means for investigating numerous hard structural surfaces that "depict" rock mass structural types are still quite outdated. The most commonly used method for measuring rock mass structures is still manual precision surveying, which requires manual on-site recording of the rock mass structure after each excavation distance. This has led to the development of methods such as full-trace long-distance surveying and surveying network methods. However, due to subjective human factors or harsh and complex mapping environments, it is difficult to guarantee personal safety and seriously affects construction progress.

[0004] Currently, with the development of emerging remote sensing technologies such as close-range photography and laser scanning, the automatic extraction and analysis of non-contact rock mass structural surfaces has become a research hotspot in the field of rock engineering. This provides a new means for objectively and rapidly realizing digital mapping and geometric feature description of rock mass geological logging based on the window method. There is already a large body of mature research on the automatic identification of non-contact rock mass structural surfaces, and many scholars have provided publicly available datasets and related code or software. This research foundation has enabled the automatic identification of dominant rock mass structural groups and the segmentation of individual structural surfaces, providing necessary digital information for the distribution characteristics and location of structural surfaces in geotechnical engineering.

[0005] Furthermore, structural planes exhibit local "coplanarity" in their spatial distribution. Specifically, multiple approximately coplanar structural planes can usually be observed on the bedding planes of a rock mass. However, due to "rock bridges" or incomplete rock mass exposure, these structural planes show a local discontinuous distribution in that direction. Once bedding-parallel failure occurs in the rock mass, the structural planes may continue along the bedding planes. Therefore, analyzing the coplanar characteristics of discontinuities is of great significance for studying the mechanical properties and failure mechanisms of rock masses. Especially during the geological compilation and mapping of rock masses, professionals often manually find these coplanar lines and draw them to facilitate the generalization of the impact of important structures. Sampling methods for geological compilation and mapping of rock mass structural planes can be divided into line sampling, semi-trace sampling, and window mapping. Among them, window mapping provides better quality data than scan line sampling because this method reduces the inherent bias of the sampling direction while increasing the number of structural planes recorded. In automated window mapping methods, images were initially used as the data source, and edge detection methods were used to identify structural plane traces and map them onto a planar image. Subsequently, a few scholars also completed spatial planar projection of traces from discontinuities automatically extracted from point clouds. However, none of the above studies considered the coplanar characteristics of the structure, making it difficult to generalize the overall distribution trend of rock mass discontinuities.

[0006] In summary, existing related technologies have the following drawbacks: (1) Most existing non-contact rock mass measurement technologies rely mainly on point cloud or triangular mesh basic data and realize automatic identification and single-face segmentation of the dominant group of three-dimensional structural surfaces. However, the massive point cloud or triangular mesh data is huge, making it difficult to save the identification results and the loading and parsing process is slow.

[0007] (2) Due to the incomplete exposure of rock masses or the connection of "rock bridges", structural planes exhibit local discontinuous distribution in the direction of bedding planes or joint planes. Especially during the geological compilation and mapping process, professionals usually manually find these coplanar lines and draw them to facilitate the generalization of the impact of important structures. However, existing research has not yet achieved coplanar feature analysis of structural planes, resulting in the problem of over-segmentation of the resulting planes identified by most algorithms.

[0008] (3) At present, the methods and means of investigating a large number of hard structural surfaces that “depict” rock mass structure types are still very backward. The main method is manual on-site measurement. Due to human subjective factors or harsh and complex mapping environment, the efficiency of engineering survey and construction is seriously restricted. Summary of the Invention

[0009] To address the aforementioned shortcomings in existing technologies, the present invention provides a method for coplanar analysis and digital geological logging of rock mass structures based on non-contact measurement, which solves the above-mentioned technical problems. It utilizes non-contact measurement methods to collect point clouds and automatically identifies coplanar structural surfaces through coplanar analysis, thereby meeting the needs for efficient and safe geological logging of rock mass structural surfaces during the on-site construction of geotechnical engineering projects such as water conservancy and hydropower, transportation tunnels, and mine roadways.

[0010] To achieve the aforementioned objectives, the technical solution adopted by this invention is: a method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement, comprising the following steps: S100. Collect the three-dimensional point cloud coordinate information of the rock mass surface through non-contact measuring equipment, and then obtain the three-dimensional spatial point cloud data contained in each rock mass structural surface. S200. Based on the three-dimensional spatial point cloud data of each rock mass structural surface, extract the corresponding topological structural surface contour; S300. Based on the topological structure surface contour, a progressive local coplanar discontinuous search method is adopted to perform coplanar analysis by setting the coplanar judgment criteria by setting the angle between the structure surface normal vectors and the average distance, and obtaining multiple sets of coplanar structure surfaces. S400: Based on a set of multiple coplanar structural surfaces, the structural surface traces of each set of coplanar structural surfaces are connected to obtain a digital geological logging map of the rock mass structural surfaces.

[0011] Further, in step S200, for any rock mass structural surface, the corresponding topological structural surface contour is extracted, including: S201. Reduce the dimensionality of the three-dimensional point cloud data of the rock mass structure surface to two-dimensional space; S202, In two-dimensional space, based on The convex hull algorithm extracts the two-dimensional polygonal contours corresponding to the rock mass structural surfaces. S203. Restore the node data of the two-dimensional polygon contour to the three-dimensional polygon boundary point set in three-dimensional space to form the corresponding topological surface contour; in the three-dimensional polygon boundary point set, all boundary points are located on the same plane.

[0012] Further, in step S300, for any seed structure surface, a progressive local coplanar discontinuity search method is used to obtain the corresponding set of coplanar structure surfaces, including: S301. Set the search range for structure surfaces that are coplanar with the seed structure surface, and determine the structure surfaces to be selected; The search range is a cylinder whose axial direction is consistent with the normal vector of the seed structure surface, given a certain height and radius. S302. Project the center point of the structural surface to be selected onto the intersection line of the plane containing the seed structural surface and the horizontal plane. Calculate the distance from different projection points to the seed point, and sort the distances from smallest to largest as the search order for coplanar analysis of the structural surface to be selected and the seed structural surface; the seed point is the geometric center point of the seed structural surface. S303. Starting from the seed point, determine the coplanarity of each structural surface to be selected according to the search order; S304. In the process of determining coplanarity, based on the normal vector and center point of the set of coplanar structural surfaces that have been determined to be coplanar, the current coplanarity judgment criterion is determined, and then it is determined whether the currently searched structural surface is coplanar with the set of determined coplanar structural surfaces. If so, proceed to step S305; If not, proceed to step S306; S305. Add the currently searched structural surface to the set of coplanar structural surfaces, and update the normal vector and center point of the seed structural surface to the average normal vector and geometric center point of the current set of coplanar structural surfaces. S306. Determine that the currently searched structural surface is not coplanar with the set of coplanar structural surfaces, end the coplanarity determination of the current structural surface, move to the next structural surface according to the search order, and return to step S304. S307. Search for the next structural surface. Repeat steps S304 to S306 until all structural surfaces within the search range have completed the coplanarity determination, and obtain the set of coplanar structural surfaces corresponding to the current seed structural surface.

[0013] Furthermore, in step S302: The plane containing the seed structure is represented as: The intersection of the plane containing the seed structure surface and the horizontal plane is represented as: The projection point of the i-th projection onto the intersection line of the plane containing the seed structure surface and the horizontal plane is represented as: The distance from the i-th projection point to the seed point is represented as: In the formula, Represents the seed point normal vector. These represent the seed point normal vectors respectively. Components on the x-axis, y-axis, and z-axis Representing seed points x-axis, y-axis, and z-axis coordinates These represent the lines of intersection between the plane containing the seed structure surface and the horizontal plane. x-axis, y-axis, and z-axis coordinates Represents the real parameter; Represent the i-th projection point respectively x-axis, y-axis, and z-axis coordinates This represents the projection coefficient of the i-th projection point. , This represents the center point of the structural surface corresponding to the i-th projection point. The vector to the intersection line, , They represent the center points respectively. x-axis, y-axis, and z-axis coordinates This represents the unit vector indicating the direction of the intersection line. This represents the square norm.

[0014] Furthermore, in step S304, the coplanarity determination criterion is: In the formula, This represents the angle between the normal vectors of the structure surface to be selected and the seed structure surface. This represents the threshold angle between the normal vectors of the selected structural surface and the seed structural surface. This represents the average distance between the structure plane to be selected and the seed structure plane. This represents the set average distance threshold between the selected structural surface and the seed structural surface. Represents the inverse cosine function. and The normal vectors of the structural surface to be selected and the seed structural surface, respectively. and These represent the maximum and minimum distances from the selected structural surface to the seed structural surface, respectively.

[0015] Further, in step S300, based on obtaining the set of coplanar structural surfaces corresponding to any seed structural surface, multiple sets of coplanar structural surface sets are obtained, including: Traverse the structural planes corresponding to each topological structural plane contour, use them as seed structural planes, perform coplanar analysis on them, and obtain the corresponding set of coplanar structural planes. Calculate the flatness, total area, and number of structural surfaces contained in each set of coplanar structural surfaces; The set of coplanar structural surfaces is filtered based on flatness and total area; For the set of coplanar structural surfaces that have been selected and retained, the various sub-structural surfaces are selected as candidates for coplanar structural surface analysis in descending order of the number of structural surfaces they contain. The corresponding coplanar structural surfaces are selected and the set of coplanar structural surfaces corresponding to various sub-structural surfaces is updated until the traversal is completed. Among them, the coplanar structural surfaces selected in order do not participate in the subsequent coplanar structural surface analysis. The structural surfaces that were not selected during the coplanar analysis were designated as non-coplanar structural surfaces, and the other structural surfaces were assigned to the corresponding coplanar structural surface sets, resulting in multiple sets of coplanar structural surfaces.

[0016] Further, step S400 includes the following sub-steps: S401. Perform spatial correction and three-dimensional projection on the coplanar structural surfaces in each set of coplanar structural surfaces to determine the line segments of each set of coplanar structural surfaces. S402. Convert the determined set of coplanar structural surface segments into two-dimensional coordinates and draw them in a plane coordinate system; S403. In the plane coordinate system, the structural traces of each group of coplanar structural surfaces are connected based on the shortest path algorithm to obtain a digital geological logging map of the rock mass structural surfaces.

[0017] Further, step S401 includes the following sub-steps: S401-1. Obtain the fitting plane normal vector of each set of coplanar structural surfaces and the normal vector containing all center points; S401-2. Based on the fitting plane normal vector and including all center points and normal vectors, convert the original structural surface contour points into corrected structural surface contour points. S401-3. Construct a canvas consisting of a specified center point and a plane normal vector, and translate it by a set distance along both sides of the plane normal vector to determine the buffer range; S401-4. Within the buffer zone, project the corrected structural surface contour points onto the corresponding intersection lines, and determine the endpoints on both sides of the projection traces to obtain the set of line segments of each coplanar structural surface.

[0018] Furthermore, step S403 includes the following sub-steps: S403-1. In a planar coordinate system, take each set of coplanar structural surface line segments that have been converted to two-dimensional coordinates as the search object, and obtain the nodes of each line segment. S403-2, Traverse and calculate the distance between any two nodes, and construct a node weighted distance matrix; S403-3, Based on the node weighted distance matrix, The node with the smallest value is defined as the starting point. The node with the largest value is defined as the endpoint; where, The value is the line segment of the coplanar structural surface set in the planar coordinate system. Axis coordinate values; S403-4. Calculate the shortest distance between the starting point and the ending point, and make the connection path pass through every real trace to obtain a digital geological logging map of the rock mass structure surface.

[0019] The beneficial effects of this invention are as follows: (1) Currently used intelligent recognition algorithms for structural surfaces (such as region growing algorithms and unsupervised clustering) all utilize 3D point cloud data for representation. The massive amount of data makes it difficult to meet the needs of subsequent point cloud loading, display, and further analysis. This invention employs a "topological structural surface contour extraction" method, using a 3D point cloud fitting plane dimensionality reduction and dimensionality increase approach, and utilizing... The convex hull algorithm can fit the overall contour of a structural surface in three-dimensional space, enabling the simulation of the spatial structure and shape of a structural surface using a small number of polygon node vectors, effectively reducing the need for fast saving, loading, and parsing of automatic structural surface results.

[0020] (2) Currently, no algorithm can effectively solve the problem of over-segmentation in rock mass structural surface identification, making it difficult to effectively summarize and integrate discontinuous structural surfaces distributed at the same level. This invention proposes the "Progressive Local Coplanar Search for Discontinuities (PLCSD)" algorithm, which can find one or more sets of rock mass structural surfaces that are approximately at the same level in three-dimensional space and provide data support for the subsequent digital geological logging and mapping of trace lines, thus solving the problem of over-segmentation in existing automatic structural surface identification algorithms.

[0021] (3) Based on the point cloud of rock mass structure surface obtained by non-contact measurement, this invention realizes the rapid drawing of digital window geological logging map through vectorized contour extraction, coplanar analysis and geometric space transformation projection. Compared with traditional on-site manual measurement or manual image annotation, it can maximize the objectivity and efficiency of rock mass engineering survey. In particular, it provides a new means for drawing digital geological logging map of structure surface in complex and demanding underground spaces such as roadways, tunnels and exploration adits. Attached Figure Description

[0022] Figure 1 The flowchart illustrates the method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement provided by this invention.

[0023] Figure 2 The present invention provides when The polygonal contour results of fitting a set of two-dimensional point clouds of structural surfaces for different values; where (a) is (b) is the fitted polygon at time m; The fitted polygon at time m; (c) is the polygonal shape at time m; The fitted polygon at time m; (d) is the fitted polygon at time m; Fitted polygon at time m.

[0024] Figure 3 This is a schematic diagram illustrating the search range of a seed structure surface provided by the present invention.

[0025] Figure 4 This is a schematic diagram illustrating the search order for a seed structure surface provided by the present invention.

[0026] Figure 5 This is a schematic diagram illustrating the principle of coplanar structural surface spatial correction provided by the present invention.

[0027] Figure 6 A schematic diagram illustrating the principle of coplanar structural surface trace penetration provided by the present invention.

[0028] Figure 7 The digital window geological logging map provided by the present invention includes (a) the original geological logging map and (b) the geological logging map after coplanar connection. Detailed Implementation

[0029] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0030] This invention provides a method for coplanar analysis of rock mass structures and digital geological logging based on non-contact measurement. It can be applied to the further vectorization mapping of rock mass structure surfaces extracted by various methods, so as to meet the needs of efficient and safe geological logging of rock mass structure surfaces in the on-site construction process of geotechnical engineering such as water conservancy and hydropower, transportation tunnels, and mine roadways.

[0031] refer to Figure 1 This includes the following steps: S100. Collect the three-dimensional point cloud coordinate information of the rock mass surface through non-contact measuring equipment, and then obtain the three-dimensional spatial point cloud data contained in each rock mass structural surface. S200. Based on the three-dimensional spatial point cloud data of each rock mass structural surface, extract the corresponding topological structural surface contour; S300. Based on the topological structure surface contour, a progressive local coplanar discontinuous search method is adopted to perform coplanar analysis by setting the coplanar judgment criteria by setting the angle between the structure surface normal vectors and the average distance, and obtaining multiple sets of coplanar structure surfaces. S400: Based on a set of multiple coplanar structural surfaces, the structural surface traces of each set of coplanar structural surfaces are connected to obtain a digital geological logging map of the rock mass structural surfaces.

[0032] In step S100 of this embodiment, existing mature non-contact three-dimensional measurement equipment and technology are used to acquire the three-dimensional spatial coordinates of the rock surface in the target scene. In a specific example, according to different acquisition principles, it can be divided into close-range photogrammetry (the main equipment is a digital camera to take pictures from multiple angles and obtain the target object surface point cloud data through aerial triangulation), three-dimensional laser scanning (the main equipment is a ground three-dimensional laser scanner, which obtains the target object surface point cloud by actively emitting laser and recording the round-trip reception time), and SLAM laser scanning (the main equipment is a handheld SLAM laser scanner, which obtains the target object point cloud data by continuously moving and recording the round-trip laser path).

[0033] Furthermore, based on the collected 3D point cloud coordinate information, the 3D spatial point cloud data contained in each rock mass structure surface is obtained through an automatic rock mass structure surface identification algorithm. In a specific example, the automatic rock mass structure surface identification algorithm includes unsupervised clustering algorithms (such as Kmeans++, density peak clustering, DBSCAN clustering, etc.), region growing algorithms, deep learning algorithms, etc. Simultaneously, relevant open-source code or software, such as FSS, DSE, Coltop3D, CloudComparefacet plugin, etc., can also be used.

[0034] In this embodiment, after a single rock mass structural surface is extracted, its geometry needs to be further described using a polygonal outline, and all boundary points of this polygon must be defined on a certain plane. The purpose of this is threefold: 1. To simplify the massive point cloud data into defined geometric plane boundaries, thereby reducing the computational load of subsequent analysis; 2. To generalize the original undulating point cloud of the rock surface into a fitted plane to calculate the orientation of each structural surface; 3. The vectorized plane range represents the range of the actual structural surface point cloud and cannot exceed the maximum boundary of the actual point cloud.

[0035] Based on this, in step S200 of this embodiment, for any rock mass structural surface, the corresponding topological structural surface contour is extracted, including: S201. Reduce the dimensionality of the three-dimensional point cloud data of the rock mass structure surface to two-dimensional space; S202, In two-dimensional space, based on The convex hull algorithm extracts the two-dimensional polygonal contours corresponding to the rock mass structural surfaces. S203. Restore the node data of the two-dimensional polygon contour to the three-dimensional polygon boundary point set in three-dimensional space to form the corresponding topological surface contour; in the three-dimensional polygon boundary point set, all boundary points are located on the same plane.

[0036] In step S201 above, the three-dimensional point cloud data of a structural surface is... The process of reducing the dimension to two-dimensional space is as follows: Using formula (1) Convert to normalized matrix The standardized matrix is ​​calculated using formula (2). covariance matrix Then, singular value decomposition (SVD) is performed to obtain an orthogonal matrix. Then, extract Construct a dimension reduction matrix from the first two columns. Finally, the point cloud coordinate matrix after dimensionality reduction is obtained using formula (3). .

[0037] In the above process, formulas (1) to (3) are as follows: (1) (2) (3) In the formula, , , For other The coordinates of the geometric center , They are respectively The maximum and minimum values ​​of the data in the first column are analyzed, and the same applies to the rest. and , , They are respectively The eigenvectors and corresponding eigenvalues ​​obtained from singular decomposition ,in represent The normal vector of the fitted plane. This represents the total number of 3D point cloud data.

[0038] In step S202 above, topology The Alpha Convex Hull (ACH) algorithm is used to obtain the two-dimensional contour of a structural surface. Its main principle is to use a convex hull with a fixed radius... The circle is compared with the circumcircle of the Delaunay triangulation formed by the point cloud, and then the circumcircle with a radius greater than 1 is removed. The sides of the triangle form the outline of the polygon. This parameter determines the "proximity" of a point to other points. The smaller the value, the more compact the generated convex hull will be, allowing it to connect more points. The larger the convex hull, the looser it becomes, allowing it to accommodate larger gaps. Generally speaking, The smaller the value, the closer the generated convex hull is to the classic convex hull; and As the size increases, the generated convex hull will contain more interior points, and can even form connected boundaries in sparse regions of the dataset.

[0039] pass Convex hull algorithm from Extracting contents Set of boundary points of a two-dimensional polygon Among them, is an important parameter implemented in this process, when If the radius is too small, it will cause overfitting of the boundary and generate a complex polygon (Mult-Polygon). Figure 2 (as shown), therefore The radius must be set to be greater than the point cloud spacing, generally about 3 times the point cloud spacing. The above process can be implemented using the Python-alphashape open source library.

[0040] In step S203 above, restoring the node data of the two-dimensional polygon contour to the set of three-dimensional polygon boundary points in three-dimensional space includes: The extracted set of two-dimensional polygon boundary points is obtained through formulas (4) to (5). Restored to a set of boundary points of a 3D polygon .

[0041] (4) (5) In the formula, This represents the reconstructed, standardized set of three-dimensional points. This indicates that the elements are multiplied column by column (i.e., restored proportionally for each dimension). ; .

[0042] By performing the above steps S201~S203, the contour of each rock mass structural surface can be extracted, and all boundary points of the dimensionality-reduced polygon can be obtained. They are all located on the same plane.

[0043] This invention proposes a Progressive Local Coplanar Search for Discontinuities (PLCSD) to find one or more sets of rock mass structural surfaces that are approximately at the same level in three-dimensional space.

[0044] Due to tectonic compression or tension, the orientation of a set of coplanar structural planes may undergo slight twisting over a large area as the extension distance increases. Therefore, the orientation of a set of coplanar structural planes is not fixed, but changes continuously with the determination result. The farther the structural planes are, the greater this change becomes.

[0045] In step S300 of this embodiment, the entire search process for generating a set of coplanar structural surfaces is similar to "region growing". For any seed structural surface, a progressive local coplanar discontinuous search method is used to obtain the corresponding set of coplanar structural surfaces, including: S301. Set the search range for structure surfaces that are coplanar with the seed structure surface, and determine the structure surfaces to be selected; The search range is a cylinder whose axial direction is consistent with the normal vector of the seed structure surface, given a certain height and radius. S302. Project the center point of the structural surface to be selected onto the intersection line of the plane containing the seed structural surface and the horizontal plane. Calculate the distance from different projection points to the seed point, and sort the distances from smallest to largest as the search order for coplanar analysis of the structural surface to be selected and the seed structural surface; the seed point is the geometric center point of the seed structural surface. S303. Starting from the seed point, determine the coplanarity of each structural surface to be selected according to the search order; S304. In the process of determining coplanarity, based on the normal vector and center point of the set of coplanar structural surfaces that have been determined to be coplanar, the current coplanarity judgment criterion is determined, and then it is determined whether the currently searched structural surface is coplanar with the set of determined coplanar structural surfaces. If so, proceed to step S305; If not, proceed to step S306; S305. Add the currently searched structural surface to the set of coplanar structural surfaces, and update the normal vector and center point of the seed structural surface to the average normal vector and geometric center point of the current set of coplanar structural surfaces. S306. Determine that the currently searched structural surface is not coplanar with the set of coplanar structural surfaces, end the coplanarity determination of the current structural surface, move to the next structural surface according to the search order, and return to step S304. S307. Search for the next structural surface. Repeat steps S304 to S306 until all structural surfaces within the search range have completed the coplanarity determination, and obtain the set of coplanar structural surfaces corresponding to the current seed structural surface.

[0046] In this embodiment, before performing coplanar analysis, a coplanarity judgment criterion is first established, defining two coplanar structural surfaces, Joint 1-1# and Joint 1-2#. Due to irregular excavation or blasting, the same structural surface is divided into two, which are approximately parallel in three-dimensional space, and the distance between the two polygons along their normal vector directions is small. Based on this, the coplanarity judgment criterion is set as follows: (6) (7) (8) In the formula, This represents the angle between the normal vectors of the structure surface to be selected and the seed structure surface. This represents the threshold angle between the normal vectors of the selected structural surface and the seed structural surface. This represents the average distance between the structure plane to be selected and the seed structure plane. This represents the set average distance threshold between the structure surface to be selected and the seed structure surface. Represents the inverse cosine function. and The normal vectors of the structural surface to be selected and the seed structural surface, respectively. and These represent the maximum and minimum distances from the selected structural surface to the seed structural surface, respectively. The normal vector is obtained by performing plane fitting on the node coordinates of the topological polygonal contour of the structural surface. and By iterating through the coordinates of all nodes on the candidate structural surface, and calculating their perpendicular distances to the plane containing the seed structural surface, the maximum distance can be obtained. and minimum distance .

[0047] In coplanar analysis, since a set of coplanar structural surfaces have the same orientation and their distance along the normal vector direction is small, a global search range is unnecessary as it would reduce search efficiency. Therefore, this invention takes a seed structural surface as an example, limiting the search range of coplanar structural surfaces to a region with height d, radius r, and axial direction... Within a cylinder whose normal vector aligns with the seed structure surface; simultaneously, all structure surfaces within this cylinder originate from the same dominant structure surface group as the seed structure surface, such as... Figure 3 As shown; further, the geometric median points of all the structural surfaces to be selected are projected onto the intersection line of the plane containing the seed structural surface and the horizontal plane. The distance S from each projection point to the seed point is calculated, and the order of judging the structural surfaces is determined by ascending the value of S, as follows. Figure 4As shown, Sn is the absolute value of the distance from the projection point of the geometric center point of the nth structural surface within the search range to the center point of the seed joint; the lower axis represents the search order within the search range, specifically, from the perspective of the perpendicular intersection line, the spatial features of structural surfaces at different positions from the seed point, where the red numbers mark the search order, which is determined by the order of size of S1, S2, ..., Sn.

[0048] In step S302 above: The plane containing the seed structure is represented as: (9) The intersection of the plane containing the seed structure surface and the horizontal plane is represented as: (10) The projection point of the i-th projection onto the intersection line of the plane containing the seed structure surface and the horizontal plane is represented as: (11) (12) (13) The distance from the i-th projection point to the seed point is represented as: (14) In the formula, Represents the seed point normal vector. These represent the seed point normal vectors respectively. Components on the x-axis, y-axis, and z-axis Representing seed points The x-axis, y-axis, and z-axis coordinates; These represent the lines of intersection between the plane containing the seed structure surface and the horizontal plane. x-axis, y-axis, and z-axis coordinates Represents the real parameter; Represent the i-th projection point respectively x-axis, y-axis, and z-axis coordinates This represents the projection coefficient of the i-th projection point. This represents the center point of the structural surface corresponding to the i-th projection point. The vector to the intersection line, They represent the center points respectively. x-axis, y-axis, and z-axis coordinates Indicates the center point The dot product of the vector to the line of intersection and the unit vector in the direction of the line of intersection. Let the square norm of the unit vectors at the intersection line be denoted; where the real parameter is denoted. The value of can be any real number, used to represent different points on the intersection line.

[0049] In this embodiment, due to structural compression or tension, the orientation of a set of coplanar structural surfaces may undergo slight twisting over a large range as the extension distance increases. Therefore, the orientation of a set of coplanar structural surfaces is not fixed, but changes continuously with the determination result. The farther the structural surfaces are, the greater this change becomes.

[0050] The above process can dynamically estimate the extension direction of the coplanar structural plane, which can be used to solve the situation where the plane direction changes.

[0051] When multiple sets of coplanar structural surfaces are needed, more seed structural surfaces must be selected. As mentioned earlier, any structural surface in a set of coplanar structural surfaces can be used as a seed point. However, if the direction of the selected seed structural surface differs too much from the overall direction, it will cause an overall deviation in the search direction. Therefore, a seed node filter needs to be created, which evaluates the effectiveness of the coplanar search of seed structural surfaces using multiple metrics.

[0052] Based on this, in step S300, in addition to obtaining the set of coplanar structural surfaces corresponding to any seed structural surface, multiple sets of coplanar structural surface sets are obtained, including: Traverse the structural planes corresponding to each topological structural plane contour, use them as seed structural planes, perform coplanar analysis on them, and obtain the corresponding set of coplanar structural planes. Calculate the flatness, total area, and number of structural surfaces contained in each set of coplanar structural surfaces; The set of coplanar structural surfaces is filtered based on flatness and total area; For the set of coplanar structural surfaces that have been selected and retained, the various sub-structural surfaces are selected as candidates for coplanar structural surface analysis in descending order of the number of structural surfaces they contain. The corresponding coplanar structural surfaces are selected and the set of coplanar structural surfaces corresponding to various sub-structural surfaces is updated until the traversal is completed. Among them, the coplanar structural surfaces selected in order do not participate in the subsequent coplanar structural surface analysis. The structural surfaces that were not selected during the coplanar analysis were designated as non-coplanar structural surfaces, and the other structural surfaces were assigned to the corresponding coplanar structural surface sets, resulting in multiple sets of coplanar structural surfaces.

[0053] In the above process, flatness and total area can be regarded as the basic attributes of the set of coplanar structural surfaces obtained by using each structural surface as a seed surface; among them, flatness reflects the degree of undulation of the set of coplanar structural surfaces, and total area reflects the size of the spatial distribution range of the set of coplanar structural surfaces. By setting thresholds for the two attributes, undesirable seed structural surfaces can be filtered out, and the filtered seed structural surfaces are then searched for coplanar surfaces again to determine the set of coplanar structural surfaces.

[0054] Among them, the flatness of the set of coplanar structural surfaces and total area The calculation formulas are as follows: (15) (16) In the formula, , , These are the eigenvalues ​​of a set of coplanar structural surfaces. The number of structural surfaces contained in each set of coplanar structural surfaces; This represents the area of ​​the i-th structure surface in the set of coplanar structure surfaces.

[0055] Step S400 in this embodiment includes the following sub-steps: S401. Perform spatial correction and three-dimensional projection on the coplanar structural surfaces in each set of coplanar structural surfaces to determine the line segments of each set of coplanar structural surfaces. S402. Convert the determined set of coplanar structural surface segments into two-dimensional coordinates and draw them in a plane coordinate system; S403. In the plane coordinate system, the structural traces of each group of coplanar structural surfaces are connected based on the shortest path algorithm to obtain a digital geological logging map of the rock mass structural surfaces.

[0056] In step S401, under natural conditions, the directions from a set of coplanar structural surfaces exhibit slight differences. Therefore, before planar projection, the coplanar structural surfaces undergo spatial correction to ensure the consistency of their directions and improve the visualization effect of the drawing. Figure 5 As shown in the figure , and (This refers to the fitting plane normal vectors for coplanar structural surface set 1#, coplanar structural surface set 2#, and coplanar structural surface set 2#). After spatial correction, the three-dimensional projection of the structural surfaces needs to be completed. Its function is to extend and project the structural surfaces onto a mapping plane within a specified range and obtain their trajectory positions.

[0057] Therefore, step S401 above includes the following sub-steps: S401-1. Obtain the fitting plane normal vector of each set of coplanar structural surfaces and the normal vector containing all center points; S401-2. Based on the fitting plane normal vector and including all center points and normal vectors, convert the original structural surface contour points into corrected structural surface contour points. S401-3. Construct a canvas consisting of a specified center point and a plane normal vector, and translate it by a set distance along both sides of the plane normal vector to determine the buffer range; S401-4. Within the buffer zone, project the corrected structural surface contour points onto the corresponding intersection lines, and determine the endpoints on both sides of the projection traces to obtain the set of line segments of each coplanar structural surface.

[0058] Specifically, the fitting plane normal vector of each set of coplanar structural surfaces is obtained through formulas (1) to (3). and what it contains Geometric midpoint of each structural surface and normal vector Then, the original structural surface contour points are obtained using formula (17). Converted to corrected structural surface contour points ; (17) In the formula, ; Indicates based on and The rotation matrix is ​​calculated using Rodrigues' rotation formula.

[0059] In step S402, a rectangular area of ​​the canvas is selected, and any point on the X-axis is obtained. and the origin of the coordinate system The three-dimensional points are obtained by formulas (18) to (19). Convert to two-dimensional coordinates and plot them in a planar coordinate system.

[0060] (18) (19) In the formula, , , Indicates the angle between two vectors; and Representing the set of line segments of coplanar structural surfaces The transformed two-dimensional coordinates.

[0061] In step S403, to generalize the overall spatial cutting relationship of the structural surfaces, the structural surface traces of the coplanar structural surface group can be connected. This is achieved by weighting the trace segments by distance. Here, it is necessary to find the shortest path from the lowest point to the highest point among a set of projected traces of coplanar structural surfaces. The shortest path algorithm used in this invention is a method for calculating the single-source shortest path in a weighted graph. Its basic principle is to use a greedy strategy and a priority queue to gradually expand the shortest path tree, ensuring that the path from the starting point to all other points is the shortest.

[0062] Based on this, step S403 includes the following sub-steps: S403-1. In a planar coordinate system, take each set of coplanar structural surface line segments that have been converted to two-dimensional coordinates as the search object, and obtain the nodes of each line segment. S403-2, Traverse and calculate the distance between any two nodes, and construct a node weighted distance matrix; S403-3, Based on the node weighted distance matrix, The node with the smallest value is defined as the starting point. The node with the largest value is defined as the endpoint; where, The value is the line segment of the coplanar structural surface set in the planar coordinate system. Axis coordinate values; S403-4. Calculate the shortest distance between the starting point and the ending point, and make the connection path pass through every real trace to obtain a digital geological logging map of the rock mass structure surface.

[0063] Specifically, each set of coplanar structural surface segments converted to two-dimensional coordinates is used as the search object, and the nodes of each segment are obtained. When two nodes are at opposite ends of the true path, the distance between them is recorded as the true distance. When two nodes are not on the same true path, the distance between them is weighted by a factor of 10. The shortest path algorithm is then used to calculate the pairwise distances between all nodes, constructing a weighted distance matrix. The node with the smallest value is the starting point. , The node with the largest value is the endpoint. The starting point can be obtained through formula (20). arrive The shortest distance, and can guarantee that the connecting path will traverse every actual trace length, the geological logging results after the connection are as follows: Figure 6 and Figure 7 As shown.

[0064] The main steps of the shortest path algorithm described above include: 1. Set a starting point and set its distance to itself to 0, and its distance to all other points to infinity; 2. Use a priority queue (usually a min-heap) to store all nodes, and sort them according to the currently known shortest path distance; 3. Each time, retrieve the current shortest path node from the priority queue, iterate through all nodes adjacent to the shortest path node, and calculate the path length between the two nodes: (20) In the formula, Represents the shortest path node. This represents the nodes adjacent to the node on the shortest path. Represents a node To the node Edge weights.

[0065] If this path is longer than the current record If shorter, then update. And The node is re-added to the priority queue, and the algorithm terminates when all nodes have been visited or the shortest path to the target node is determined.

[0066] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

[0067] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement, characterized in that, Includes the following steps: S100. Collect the three-dimensional point cloud coordinate information of the rock mass surface through non-contact measuring equipment, and then obtain the three-dimensional spatial point cloud data contained in each rock mass structural surface. S200. Based on the three-dimensional spatial point cloud data of each rock mass structural surface, extract the corresponding topological structural surface contour; S300. Based on the topological structure surface contour, a progressive local coplanar discontinuous search method is adopted to perform coplanar analysis by setting the coplanar judgment criteria by setting the angle between the structure surface normal vectors and the average distance, and obtaining multiple sets of coplanar structure surfaces. S400: Based on a set of multiple coplanar structural surfaces, the structural surface traces of each set of coplanar structural surfaces are connected to obtain a digital geological logging map of the rock mass structural surfaces.

2. The method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement according to claim 1, characterized in that, In step S200, for any rock mass structural surface, the corresponding topological structural surface contour is extracted, including: S201. Reduce the dimensionality of the three-dimensional point cloud data of the rock mass structure surface to two-dimensional space; S202, In two-dimensional space, based on The convex hull algorithm extracts the two-dimensional polygonal contours corresponding to the rock mass structural surfaces. S203. Restore the node data of the two-dimensional polygon contour to the three-dimensional polygon boundary point set in three-dimensional space to form the corresponding topological surface contour; in the three-dimensional polygon boundary point set, all boundary points are located on the same plane.

3. The method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement according to claim 1, characterized in that, In step S300, for any seed structure surface, a progressive local coplanar discontinuity search method is used to obtain the corresponding set of coplanar structure surfaces, including: S301. Set the search range for structure surfaces that are coplanar with the seed structure surface, and determine the structure surfaces to be selected; The search range is a cylinder whose axial direction is consistent with the normal vector of the seed structure surface, given a certain height and radius. S302. Project the center point of the structural surface to be selected onto the intersection line of the plane containing the seed structural surface and the horizontal plane. Calculate the distance from different projection points to the seed point, and sort the distances from smallest to largest as the search order for coplanar analysis of the structural surface to be selected and the seed structural surface; the seed point is the geometric center point of the seed structural surface. S303. Starting from the seed point, determine the coplanarity of each structural surface to be selected according to the search order; S304. In the process of determining coplanarity, based on the normal vector and center point of the set of coplanar structural surfaces that have been determined to be coplanar, the current coplanarity judgment criterion is determined, and then it is determined whether the currently searched structural surface is coplanar with the set of determined coplanar structural surfaces. If so, proceed to step S305; If not, proceed to step S306; S305. Add the currently searched structural surface to the set of coplanar structural surfaces, and update the normal vector and center point of the seed structural surface to the average normal vector and geometric center point of the current set of coplanar structural surfaces. S306. Determine that the currently searched structural surface is not coplanar with the set of coplanar structural surfaces, end the coplanarity determination of the current structural surface, move to the next structural surface according to the search order, and return to step S304. S307. Search for the next structural surface. Repeat steps S304 to S306 until all structural surfaces within the search range have completed the coplanarity determination, and obtain the set of coplanar structural surfaces corresponding to the current seed structural surface.

4. The method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement according to claim 3, characterized in that, In step S302: The plane containing the seed structure is represented as: The intersection of the plane containing the seed structure surface and the horizontal plane is represented as: The projection point of the i-th projection onto the intersection line of the plane containing the seed structure surface and the horizontal plane is represented as: The distance from the i-th projection point to the seed point is represented as: In the formula, Represents the seed point normal vector. These represent the seed point normal vectors respectively. Components on the x-axis, y-axis, and z-axis Representing seed points x-axis, y-axis, and z-axis coordinates These represent the lines of intersection between the plane containing the seed structure surface and the horizontal plane. x-axis, y-axis, and z-axis coordinates Represents the real parameter; Represent the i-th projection point respectively x-axis, y-axis, and z-axis coordinates This represents the projection coefficient of the i-th projection point. , This represents the center point of the structural surface corresponding to the i-th projection point. The vector to the intersection line, , They represent the center points respectively. x-axis, y-axis, and z-axis coordinates This represents the unit vector indicating the direction of the intersection line. This represents the square norm.

5. The method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement according to claim 3, characterized in that, In step S304, the coplanarity determination criterion is: In the formula, This represents the angle between the normal vectors of the structure surface to be selected and the seed structure surface. This represents the threshold angle between the normal vectors of the selected structural surface and the seed structural surface. This represents the average distance between the structure plane to be selected and the seed structure plane. This represents the set average distance threshold between the selected structural surface and the seed structural surface. Represents the inverse cosine function. and The normal vectors of the structural surface to be selected and the seed structural surface, respectively. and These represent the maximum and minimum distances from the selected structural surface to the seed structural surface, respectively.

6. The method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement according to claim 3, characterized in that, In step S300, based on obtaining the set of coplanar structural surfaces corresponding to any seed structural surface, multiple sets of coplanar structural surface sets are obtained, including: Traverse the structural planes corresponding to each topological structural plane contour, use them as seed structural planes, perform coplanar analysis on them, and obtain the corresponding set of coplanar structural planes. Calculate the flatness, total area, and number of structural surfaces contained in each set of coplanar structural surfaces; The set of coplanar structural surfaces is filtered based on flatness and total area; For the set of coplanar structural surfaces that have been selected and retained, the various sub-structural surfaces are selected as candidates for coplanar structural surface analysis in descending order of the number of structural surfaces they contain. The corresponding coplanar structural surfaces are selected and the set of coplanar structural surfaces corresponding to various sub-structural surfaces is updated until the traversal is completed. Among them, the coplanar structural surfaces selected in order do not participate in the subsequent coplanar structural surface analysis. The structural surfaces that were not selected during the coplanar analysis were designated as non-coplanar structural surfaces, and the other structural surfaces were assigned to the corresponding coplanar structural surface sets, resulting in multiple sets of coplanar structural surfaces.

7. The method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement according to claim 1, characterized in that, Step S400 includes the following sub-steps: S401. Perform spatial correction and three-dimensional projection on the coplanar structural surfaces in each set of coplanar structural surfaces to determine the line segments of each set of coplanar structural surfaces. S402. Convert the determined set of coplanar structural surface segments into two-dimensional coordinates and draw them in a plane coordinate system; S403. In the plane coordinate system, the structural traces of each group of coplanar structural surfaces are connected based on the shortest path algorithm to obtain a digital geological logging map of the rock mass structural surfaces.

8. The method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement according to claim 7, characterized in that, Step S401 includes the following sub-steps: S401-1. Obtain the fitting plane normal vector of each set of coplanar structural surfaces and the normal vector containing all center points; S401-2. Based on the fitting plane normal vector and including all center points and normal vectors, convert the original structural surface contour points into corrected structural surface contour points. S401-3. Construct a canvas consisting of a specified center point and a plane normal vector, and translate it by a set distance along both sides of the plane normal vector to determine the buffer range; S401-4. Within the buffer zone, project the corrected structural surface contour points onto the corresponding intersection lines, and determine the endpoints on both sides of the projection traces to obtain the set of line segments of each coplanar structural surface.

9. The method for coplanar analysis of rock mass structure and digital geological logging based on non-contact measurement according to claim 7, characterized in that, Step S403 includes the following sub-steps: S403-1. In a planar coordinate system, take each set of coplanar structural surface line segments that have been converted to two-dimensional coordinates as the search object, and obtain the nodes of each line segment. S403-2, Traverse and calculate the distance between any two nodes, and construct a node weighted distance matrix; S403-3, Based on the node weighted distance matrix, The node with the smallest value is defined as the starting point. The node with the largest value is defined as the endpoint; where, The value is the line segment of the coplanar structural surface set in the planar coordinate system. Axis coordinate values; S403-4. Calculate the shortest distance between the starting point and the ending point, and make the connection path pass through every real trace to obtain a digital geological logging map of the rock mass structure surface.

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