Rock profile characteristic analysis system and use method thereof

Abstract

The invention discloses a rock section feature analysis system and a use method thereof, and relates to the technical field of rock section observation, three-dimensional point cloud data is used for analyzing a structural plane, and a Delaunay subdivision mode is a subdivision method of the structural plane based on spatial points. A triangle obtained when the rock section is subdivided in the Delaunay subdivision mode is closest to a regular triangle, and Delaunay triangulation is a subdivision mode formed by combining one or more groups of triangulation rule subdivision A and triangulation rule subdivision B. The method has the advantages that point cloud data are obtained by adopting three-dimensional laser scanning and three-dimensional white light scanning technologies; compared with a traditional comparison method and a traditional parameter evaluation method, the method has the advantages that the influence of subjective factors is reduced, and evaluation deviation caused by different personal engineering experiences is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of rock profile observation, and specifically to a rock profile feature analysis system and a using method thereof. Background Art

[0002] A large number of discontinuous structural planes are contained in the rock mass structure, and the structural plane is the fundamental cause of the discontinuity, anisotropy and inhomogeneity of the rock mass. Therefore, studying the problem of measuring the morphological characteristics of the structural plane is of great significance for understanding the instability problems of rock masses such as mine excavation. As one of the important factors affecting the joint shear behavior, due to its complex surface morphology and great randomness, how to reasonably quantitatively describe it has always been a difficult and hot issue in the study of jointed rock mass mechanics;

[0003] Since the Norwegian scholar Barton proposed the joint roughness coefficient JRC in 1973, the evaluation method of joint roughness has developed from qualitative to quantitative and from two-dimensional to three-dimensional, and has become one of the important research topics in the fields of rock mechanics and engineering geology. Scholars at home and abroad have carried out a large number of studies on this. At present, the methods for evaluating joint roughness are mainly divided into three types: the comparison method, the parameter evaluation method and the back calculation method. The specific process of evaluating the joint morphological characteristics by the comparison method is to first extract several 2D contour lines on the joint surface by using a surface profiler or a 3D scanner, and then evaluate its JRC value by comparing with 10 standard contour curves. This method is simple to operate. However, through investigation, scholars found that the reliability of the JRC value evaluated by it is too dependent on personal engineering experience and has great subjectivity;

[0004] In order to overcome the drawbacks of the above comparison method, scholars have carried out a large number of research works on the quantitative characterization of joint morphological characteristics, and proposed to use some quantitative parameters to evaluate joint roughness, that is, the parameter evaluation method. The parameter evaluation method is generally divided into two types: the 2D parameter evaluation method and the 3D parameter evaluation method. When evaluating the joint morphological characteristics by the 2D parameter method, multiple profile lines are usually selected on the joint surface, and then quantitatively evaluated by using 2D parameters, and the JRC value is determined by means of a function fitting relationship, and the average value of the JRC values of these profile lines is used as the roughness of the joint. This method is simple in data processing, but it only considers the morphological characteristics of the selected 2D profile lines, and the geometric surface information revealed is limited, which will lead to the problem of incomplete description of the joint surface characteristics. To solve this problem, some scholars proposed roughness parameters considering the 3D morphological characteristics of joints, that is, the 3D parameter evaluation method. For this reason, we propose a rock profile feature analysis system and a using method thereof. Summary of the Invention

[0005] The purpose of the present invention is to provide a rock profile feature analysis system and a using method thereof.

[0006] To solve the problems raised in the above background art, the present invention provides the following technical solutions: A method for analyzing rock profile characteristics uses three-dimensional point cloud data to analyze structural planes. The Delaunay triangulation method is a triangulation method for structural planes based on spatial points. When the Delaunay triangulation method is used to triangulate a rock profile, the resulting triangles are closest to equilateral triangles. The Delaunay triangulation is a triangulation method composed of a combination of one or more triangular regular triangulations A and triangular regular triangulations B. An unmanned aerial vehicle is used to carry a high-resolution camera or lidar to conduct an aerial survey of the rock mass to obtain a three-dimensional image or point cloud data of the rock mass. The acquired data is preprocessed, including denoising, registration, and stitching. The specific operation steps of the method for analyzing rock profile characteristics are as follows:

[0007] Step 1: Quadrilateralize the point cloud data with the fitting plane of adjacent four points, determine the point spacing of the structural plane according to requirements, and subdivide the point cloud data into a spatial quadrilateral according to four points A, B, C, and D.

[0008] Step 2: Triangulate the spatial quadrilateral into two spatial triangles ABD and BCD according to triangulation B. Make the circumcircle of triangle BCD, use the same center point and radius value as the circumsphere, and calculate the distance D from the center to the fourth point by means of the distance formula between two points. Then calculate the radius R of the circumsphere by means of the formula for the circumcircle of a triangle.

[0009] Step 3: When the radius R ≥ distance D, the fourth point is inside the circumsphere. At this time, the triangle is not a Delaunay triangle, and a "side change" operation is required. Replace the BD side with the AC side, and at the same time replace triangulation B with triangulation A.

[0010] Step 4: Process all spatial quadrilaterals one by one, including radius R and distance D, and realize the Delaunay triangulation of the point cloud data.

[0011] As a further solution of the present invention: The three-dimensional point cloud data needs to be obtained by three-dimensional laser scanning and three-dimensional white light scanning methods. Then, the point cloud data of the structural plane is processed into equal-spacing in the x-y plane, and the rock mass structural plane is discretized into micro-unit bodies to quantitatively characterize the morphological characteristics of the rock mass structural plane by using statistical parameters. The commonly used discretization triangulation methods are quadrilateral triangulation and triangular triangulation.

[0012] As a further solution of the present invention: in the steps 1 to 4, the projection plane is the X-Y plane. When analyzing the subdivision method, 45 natural joints are taken as samples to study the influence of Delaunay triangulation, two regular triangulations and quadrilateral subdivision on the evaluation of joint morphology characteristics, anisotropy, spacing effect, and size effect regularity. With the help of 3D scanning technology and 3D printing technology, joint model specimens with different morphology characteristics are made, and then their test results are analyzed, and the influence of the subdivision method on the shear strength evaluation is studied. A total of 32 sets of structural planes are collected and statistically analyzed to analyze the influence of the subdivision method on the joint shear strength, and the best subdivision method of different statistical parameters under the shear strength is recorded. In the space quadrilateral, it is subdivided according to the regular triangulation. The regular triangulation can ensure that the generated triangles have regular shapes and sizes. The fitting plane of adjacent four points is used to perform quadrilateral subdivision on the point cloud data, and the rock mass structural plane is discretized into micro-element bodies, and the morphology characteristics of the rock mass structural plane are quantitatively characterized by statistical parameters. Then, the same rock mass structural plane is analyzed by different subdivision methods, and the characteristic differences of the rock mass structural plane under different subdivision methods are compared.

[0013] As a further solution of the present invention: in the step 3, when the radius R < distance D, the fourth point is outside the circumscribed sphere, and the triangle at this time is a Delaunay triangle.

[0014] As a further solution of the present invention: in the step 4, the calculation formulas of the radius R and the distance D are as follows:

[0015]

[0016] In the above formulas, (X 1 , Y 1 , Z 1 ) and (X 2 , Y 2 , Z 2 ) are the coordinates of the center of the circle and the fourth point respectively, where a, b, and c are the three side lengths of the triangle, and S is the area of the triangle.

[0017] As a further solution of the present invention: the four points in the three-dimensional space have a height difference on the z-axis, and its projection plane A'B'C'D' is a square. The Delaunay function command is run on the MATLAB software, and the relative position of the circumscribed circle of the triangle and the fourth point is judged according to the distance between points on the XOY plane, and at the same time, the triangulation method of a single discrete quadrilateral is judged, so as to realize Delaunay triangulation. After the point cloud data is processed, an equally spaced XOY plane is obtained, and at the same time, the equal distance D from the center of the circumscribed circle of the triangle to the fourth point and the circumscribed circle radius R are obtained.

[0018] In addition, the present invention also provides a rock profile feature analysis system, including the following steps: The rock profile feature analysis system includes a profile feature acquisition module, a profile feature analysis module, a profile feature recording module, a feature 3D printing module, a replicated model shear experiment module, and an experimental data analysis and recording module.

[0019] As a further aspect of the present invention: The functions of each module are as follows:

[0020] Profile feature acquisition module: Used to collect and record the surface feature conditions of the rock, and actively repair the recorded fuzzy features to ensure the acquisition of a complete rock structural plane;

[0021] Profile feature analysis module: Used to perform a force analysis on the collected rock structural plane, quantitatively analyze and describe the morphological features, area, length, angle, and curvature of the rock structural plane, and at the same time analyze and describe the anisotropy, spacing effect, and size effect of the profile features;

[0022] Profile feature recording module: Used to record and store the data analyzed and described by the profile feature analysis module;

[0023] Feature 3D printing module: Used to print the constructed 3D rock structural plane, and the printing needs to be completely replicated according to the morphological features of the originally collected rock structural plane;

[0024] Replicated model shear experiment module: Used to perform a shear experiment on the replicated model, record the shear force and shear strength data during the experiment, and monitor the influence of the dissection method on the shear strength;

[0025] Experimental data analysis and recording module: Used to analyze and record the shear experiment data of the replicated rock structural plane, and analyze the influence of the dissection method on the shear strength.

[0026] As a further aspect of the present invention: After the feature 3D printing module finishes printing the rock structural plane, mark the printed rock structural plane as the structural plane, mark the structural planes in sequence, then use the replicated model shear experiment module to perform a shear experiment on the structural planes, monitor and record the shear stress caused by the structural plane shear experiment, and then use the experimental data analysis and recording module to analyze and process all the obtained data to obtain the final result.

[0027] Adopting the above technical solution, compared with the prior art, the beneficial effects of the present invention are as follows:

[0028] 1. The present invention obtains point cloud data by using three-dimensional laser scanning and three-dimensional white light scanning technologies, and processes it by means of Delaunay triangulation, which can more accurately describe the complex morphology of rock structural planes. Compared with traditional comparison methods and parameter evaluation methods, this method reduces the influence of subjective factors and avoids evaluation deviations caused by different personal engineering experiences. At the same time, through research and experimental analysis using a large number of samples, it provides a more reliable method for evaluating the characteristics of structural planes in the fields of rock mechanics and engineering geology, helps to more accurately predict the stability and mechanical behavior of rock masses under various engineering conditions, and provides strong technical support for the safe design and construction of projects such as mine excavation and tunnel construction;

[0029] 2. The triangles obtained by the present invention through Delaunay triangulation are closest to equilateral triangles, and then a uniform and smooth patch grid is obtained, which can avoid situations such as accuracy loss and algorithm errors caused by extreme values. By dividing the point cloud data into quadrilaterals using the fitting plane of adjacent four points and then performing two triangulations, not only can the uncertainty problem of the triangulation plane be solved, but also the program calculation amount is reduced by half, and the calculation speed is also improved to a certain extent;

[0030] 3. The present invention accurately evaluates the characteristics of rock structural planes, thereby realizing the optimization of engineering design, reducing unnecessary material use and energy consumption. At the same time, through in-depth research on rock structural planes, problems of possible rock mass instability can be predicted and prevented in advance, the incidence of engineering accidents can be reduced, and economic losses and environmental damage caused by accidents can be reduced. By using the triangulation method, it can more flexibly adapt to the complex morphology of rock structural planes because the shape of triangles is simpler and easier to fit irregular surfaces, and in computational geometry and numerical analysis, the calculation and processing of triangles are usually simpler and more efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of the digital structural plane triangulation method in the embodiment of the present invention;

[0032] Figure 2 It is a schematic diagram of the least squares fitting plane in the embodiment of the present invention;

[0033] Figure 3 It is a flow chart of Delaunay triangulation in the embodiment of the present invention;

[0034] Figure 4 It is a schematic diagram of the circumscribed sphere of the three-dimensional space triangulation B in the embodiment of the present invention;

[0035] Figure 5 It is a schematic diagram of the circumscribed sphere of the three-dimensional space triangulation A in the embodiment of the present invention;

[0036] Figure 6 Schematic diagram of the circumcircle of triangulation B in the X-Y plane in the embodiment of the present invention;

[0037] Figure 7 Schematic diagram of the spatial position of triangulation B in the embodiment of the present invention. Specific embodiments

[0038] The following further describes the specific embodiments of the present invention with reference to the accompanying drawings. It should be noted here that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation to the present invention.

[0039] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0040] A method for analyzing the characteristics of a rock profile of the present invention uses three-dimensional point cloud data to analyze structural planes. The Delaunay triangulation method is a triangulation method for structural planes based on spatial points. The triangles obtained by triangulating the rock profile using the Delaunay triangulation method are the closest to equilateral triangles. The Delaunay triangulation is a triangulation method composed of one or more triangulation rules A and triangulation rules B. An unmanned aerial vehicle is used to carry a high-resolution camera or lidar to conduct an aerial survey of the rock mass to obtain a three-dimensional image or point cloud data of the rock mass. The obtained data is preprocessed, including denoising, registration, and stitching. The specific operation steps of the method for analyzing the characteristics of the rock profile are as follows:

[0041] Step 1: Quadrilateral triangulation of the point cloud data with the fitting plane of adjacent four points, determine the point spacing of the structural plane according to requirements, and subdivide the point cloud data into spatial quadrilaterals according to four points A, B, C, and D.

[0042] Step 2: Triangulate the spatial quadrilateral into two spatial triangles ABD and BCD according to triangulation B. Make the circumcircle of triangle BCD, use the same center point and radius value as the circumscribed sphere, and calculate the distance D from the center to the fourth point using the distance formula between two points. Then calculate the radius R of the circumscribed sphere using the circumcircle formula of the triangle.

[0043] Step 3: When the radius R ≥ distance D, the fourth point is inside the circumscribed sphere. At this time, the triangle is not a Delaunay triangle, and a "side replacement" operation needs to be performed. Replace the BD side with the AC side, and at the same time replace triangulation B with triangulation A.

[0044] Step 4: Process all spatial quadrilaterals one by one, including the radius R and the distance D, and implement the Delaunay triangulation of the point cloud data.

[0045] In one embodiment of the present invention: The three-dimensional point cloud data needs to be obtained by three-dimensional laser scanning and three-dimensional white light scanning methods. Then, the point cloud data of the structural plane is processed into equidistant ones in the X-Y plane, and the rock mass structural plane is discretized into micro-unit bodies to quantitatively characterize the morphological characteristics of the rock mass structural plane by using statistical parameters. The commonly used discrete subdivision methods are quadrilateral subdivision and triangular subdivision.

[0046] In one embodiment of the present invention: In steps 1 to 4, the projection plane is the X-Y plane. When analyzing the subdivision method, 45 natural joints are used as samples to study the effects of Delaunay triangulation, two regular triangulations, and quadrilateral subdivision on the evaluation of joint morphological characteristics, anisotropy, spacing effect, and size effect regularity. With the help of 3D scanning technology and 3D printing technology, joint model specimens with different morphological characteristics are made, and then their test results are analyzed, and the influence of the subdivision method on the shear strength evaluation is studied. A total of 32 groups of structural planes are collected and then statistically analyzed to analyze the influence of the subdivision method on the joint shear strength, and the best subdivision method of different statistical parameters under the shear strength is recorded. In the spatial quadrilateral, it is subdivided according to the regular triangulation. The regular triangulation can ensure that the generated triangles have regular shapes and sizes. The fitting plane of adjacent four points is used to perform quadrilateral subdivision on the point cloud data. The rock mass structural plane is discretized into micro-unit bodies, and the morphological characteristics of the rock mass structural plane are quantitatively characterized by using statistical parameters. Then, the same rock mass structural plane is analyzed by using different subdivision methods to compare the characteristic differences of the rock mass structural plane under different subdivision methods.

[0047] In one embodiment of the present invention: In step 3, when the radius R < distance D, the fourth point is outside the circumscribed sphere, and the triangle at this time is a Delaunay triangle.

[0048] In one embodiment of the present invention: In step 4, the calculation formulas of the radius R and the distance D are as follows:

[0049]

[0050] In the above formulas, (X 1 , Y 1 , X 1 ) and (X 2 , Y 2 , Z 2 ) are the coordinates of the center of the circle and the fourth point respectively, where a, b, and c are the three side lengths of the triangle, and S is the area of the triangle.

[0051] In an embodiment of the present invention: Four points in three-dimensional space have height differences on the z-axis, and their projection plane A'B'C'D' is a square. The Delaunay function command is run on MATLAB software. According to the distances between points on the XOY plane, the relative positions of the circumcircles of triangles and the fourth point are judged, and at the same time, the triangulation methods of individual discrete quadrilaterals are judged, so as to achieve Delaunay triangulation. After the point cloud data is processed, an equidistant XOY plane is obtained, and at the same time, the equal distances D from the centers of the circumcircles of the triangles to the fourth point and the circumradius R are obtained.

[0052] Example 1. Please refer to the attached Figure 1 - attached Figure 5 , the triangulation method has an impact on the regularity of the anisotropy of the structural plane. The anisotropic characteristics of the same structural plane are different under different triangulation methods. When the structural plane A is quadrilaterally triangulated, the shear direction of the maximum value of z2S is 270°, while when it is triangularly regularly triangulated as B, the shear direction is 180°. The Delaunay triangulation is in a curved shape, while other triangulation methods are approximately circular.

[0053] The present invention also provides a rock profile feature analysis system, including the following steps: The rock profile feature analysis system includes a profile feature acquisition module, a profile feature analysis module, a profile feature recording module, a feature 3D printing module, a replicated model shear experiment module, and an experimental data analysis and recording module.

[0054] In an embodiment of the present invention: The functions of each module are as follows:

[0055] Profile feature acquisition module: Used to collect and record the surface feature conditions of the rock, and actively repair the recorded fuzzy features to ensure a complete rock structural plane is collected;

[0056] Profile feature analysis module: Used to perform a force analysis on the collected rock structural plane, quantitatively analyze and describe the morphological features, area, length, angle, and curvature of the rock structural plane, and at the same time analyze and describe the anisotropy, spacing effect, and size effect of the profile features;

[0057] Profile feature recording module: Used to record and store the data analyzed and described by the profile feature analysis module;

[0058] Feature 3D printing module: Used to print the constructed 3D rock structural plane, and the printing needs to be completely replicated according to the morphological features of the original collected rock structural plane;

[0059] Replicated model shear experiment module: Used to perform a shear experiment on the replicated model, record the shear force and shear strength data during the experiment, and monitor the influence of the triangulation method on the shear strength;

[0060] Experimental data analysis and recording module: used to analyze and record the shear test data of the replicated rock structural plane, and analyze the influence of the dissection method on the shear strength.

[0061] In one embodiment of the present invention: after the feature 3D printing module finishes printing the rock structural plane, the printed rock structural plane is marked as the structural plane, and the structural plane is marked in sequence. Then, the replicated model shear test module is used to conduct a shear test on the structural plane, and the shear stress caused by the shear test of the structural plane is monitored and recorded. Then, the experimental data analysis and recording module is used to analyze and process all the obtained data to obtain the final result.

[0062] Example 2. Please refer to the appendix Figure 3 - Appendix Figure 7 To quantitatively characterize the influence of four dissection methods on the anisotropic characteristics of the same structural plane, as well as the differences in the anisotropic characteristics of 37 structural planes, the anisotropic parameter K proposed by Belem et al. a and the structural plane anisotropy coefficient DAC proposed by Song et al. were calculated, and the mean value and standard deviation of 37 structural planes were calculated. The specific formulas are as follows:

[0063]

[0064] In the formula, P X and P Y represent the three-dimensional topography characterization parameters along the X and Y directions respectively, and the value range is [0,1]. When K a =1, the surface structural plane shows isotropy. When 0 < K a ≤1, it indicates that the surface of the structural plane shows anisotropy, and the smaller K a , the greater the degree of its anisotropic characteristics. The specific formula is as follows:

[0065]

[0066] Among them:

[0067]

[0068] In the above formulas, DAC is the structural plane anisotropy parameter, which is the statistical parameter characterizing the topography characteristics of the structural plane in the i-th and analysis directions. SP is the average value of the statistical parameters, is the coefficient of variation of the statistical parameters, n is the total number of analysis directions. The value range of the structural plane anisotropy coefficient DAC is [0,1]. When DAC = 0, the topography characteristics of the structural plane are isotropic. When 0 < DAC < 1, it indicates that the structural plane is anisotropic, and the greater the DAC, the greater the degree of anisotropy of the structural plane, and its topography characteristics are more affected by the direction.

[0069] Specifically, by using 3D laser scanning and 3D white light scanning technologies to obtain point cloud data and processing it using the Delaunay triangulation method, the complex morphology of rock structural planes can be described more precisely. Compared with traditional comparison methods and parameter evaluation methods, this method reduces the influence of subjective factors and avoids evaluation deviations caused by different personal engineering experiences. At the same time, through research and experimental analysis using a large number of samples, it provides a more reliable method for evaluating the characteristics of structural planes in the fields of rock mechanics and engineering geology, helps to more accurately predict the stability and mechanical behavior of rock masses under various engineering conditions, and provides strong technical support for the safety design and construction of projects such as mine excavation and tunnel construction.

[0070] Specifically, the triangles obtained by using the Delaunay triangulation method are the closest to equilateral triangles, and then a uniform and smooth patch grid is obtained, which can avoid situations such as accuracy loss and algorithm errors caused by extreme values. By dividing the point cloud data into quadrilaterals with the fitting plane of adjacent four points and then performing two triangulations, not only can the uncertainty problem of the triangulation plane be solved, but also the program calculation amount is reduced by half and the calculation speed is also improved to a certain extent.

[0071] Specifically, by accurately evaluating the characteristics of rock structural planes, the optimization of engineering design can be achieved, reducing unnecessary material use and energy consumption. At the same time, through in-depth research on rock structural planes, problems of possible rock mass instability can be predicted and prevented in advance, reducing the incidence of engineering accidents and the economic losses and environmental damage caused by accidents. By using the triangulation method, it can more flexibly adapt to the complex morphology of rock structural planes because the shape of triangles is simpler and easier to fit irregular surfaces, and in computational geometry and numerical analysis, the calculation and processing of triangles are usually simpler and more efficient.

[0072] Working principle:

[0073] Firstly, the method uses 3D point cloud data to analyze the structural surface, and adopts the Delaunay partitioning method, which is composed of triangulation rule partitioning A and B. When operating, the fitting plane of the four adjacent points is firstly used to quadrilateralize the point cloud data, and then subdivided into spatial quadrilaterals, and then divided according to the triangulation B, and the radius of the circumscribed circle and the distance from the center of the circle to the fourth point are calculated. According to the relationship between the radius and the distance, it is judged whether it is a Delaunay triangle. If not, a "side change" operation is performed, and all spatial quadrilaterals are processed to realize the Delaunay partitioning of the point cloud data. The 3D point cloud data is obtained by 3D laser scanning and white light scanning, and processed into equal spacing. 45 natural joints are used as samples to study the influence of different partitioning methods. After that, the system includes It includes profile feature collection, analysis, recording, 3D printing, copy model shearing experiment and experimental data analysis and recording modules. Through these modules, the influence of the partitioning method on the anisotropic characteristics of the structural surface can be quantitatively characterized, and the relevant parameters can be calculated. The Delaunay partitioning method of the present invention can obtain a nearly equilateral triangle and a uniform and smooth surface mesh to avoid problems caused by extreme values. Quadrilateral division and two triangulations can solve uncertainties and improve calculation speed. Finally, accurate evaluation of rock structural surface characteristics can optimize engineering design, reduce material and energy consumption, predict and prevent rock instability, and reduce accident rates. The use of triangulation can flexibly adapt to complex shapes, and the calculation process is simpler and more efficient. At this point, the entire workflow ends.

[0074] The above-mentioned front, back, left, right, top and bottom are all based on the figures in the specification. Figure 1 As a benchmark, according to the person's observation perspective, the side of the device facing the observer is defined as the front, the left side of the observer is defined as the left, and so on.

[0075] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the scope of protection of the present invention.

[0076] It should be noted that the device structure and the drawings of the present invention mainly describe the principle of the present invention. In terms of the technology of the design principle, the settings of the power mechanism, power supply system and control system of the device are not fully described. On the premise that the technical personnel in this field understand the principle of the above invention, the details of the power mechanism, power supply system and control system can be clearly known. The control method of the application document is automatic control through a controller, and the control circuit of the controller can be realized by simple programming by the technical personnel in this field.

[0077] The standard parts used therein can all be purchased from the market, and can all be customized according to the descriptions in the specification and the drawings. The specific connection methods of each part all adopt conventional means such as bolts, rivets, welding, etc. that are mature in the prior art. The machines, parts and equipment all adopt conventional models in the prior art, and the components known to those skilled in the art, their structures and principles can all be known by those skilled in the art through technical manuals or through conventional experimental methods.

[0078] The embodiments of the present invention have been described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the described embodiments. For those skilled in the art, without departing from the principle and spirit of the present invention, various changes, modifications, substitutions and variations made to these embodiments still fall within the protection scope of the present invention.

Claims

1. A method for analyzing rock profile characteristics, using three-dimensional point cloud data to analyze structural surfaces, characterized in that: The Delaunay triangulation method is a method of triangulating structural surfaces based on spatial points. The triangles obtained by using the Delaunay triangulation method to triangulate rock profiles are closest to regular triangles. The Delaunay triangulation method is a triangulation method composed of one or more triangulation regular triangulations A and B. The rock mass is photographed by using a drone equipped with a high-resolution camera or a laser radar to obtain a three-dimensional image or point cloud data of the rock mass. The obtained data is preprocessed, including denoising, registration and splicing. The specific steps of the rock profile feature analysis method are as follows: Step 1: Quadrilateralize the point cloud data using the fitting plane of the four adjacent points, determine the point spacing of the structural surface according to the requirements, and subdivide the point cloud data into spatial quadrilaterals according to the four points A, B, C and D; Step 2: Divide the spatial quadrilateral into two spatial triangles ABD and BCD according to the triangulation B, draw the circumscribed circle of triangle BCD, use the same center point and radius value as the circumscribed sphere, and use the distance formula between two points to calculate the distance D from the center of the circle to the fourth point, and then use the triangle circumscribed circle class formula to calculate the radius R of the circumscribed sphere; Step 3: When the radius R ≥ the distance D, the fourth point is inside the circumscribed sphere. The triangle is not a Delaunay triangle at this time, and a "side change" operation is required to change the BD side to the AC side, and at the same time change the triangulation B to the triangulation A. Step 4: Process all spatial quadrilaterals one by one, including radius R and distance D, and implement Delaunay decomposition of point cloud data.

2. A method for analyzing rock profile characteristics according to claim 1, characterized in that: The three-dimensional point cloud data needs to be acquired through three-dimensional laser scanning and three-dimensional white light scanning methods, and then the point cloud data of the structural surface is processed into equal spacing in the xy plane, and the rock structural surface is discretized into micro-units to quantitatively characterize the morphological characteristics of the rock structural surface using statistical parameters. Commonly used discrete segmentation methods are quadrilateral segmentation and triangular segmentation.

3. A method for analyzing rock profile characteristics according to claim 1, characterized in that: In the steps 1 to 4, the projection plane is the XY plane. When analyzing the partitioning method, 45 natural joints are used as samples to study the effects of Delaunay triangulation, two regular triangulations, and quadrilateral partitioning on the evaluation of joint morphology characteristics, anisotropy, spacing effect, and size effect regularity. With the help of 3D scanning technology and 3D printing technology, joint model specimens with different morphological characteristics are made, and then the test results are analyzed. The effect of the partitioning method on the shear strength evaluation is studied, and a total of 32 groups of structural surfaces are collected and statistically analyzed. The influence of the partitioning method on the shear strength of the joints is analyzed, and the best partitioning method of different statistical parameters under shear strength is recorded. In the spatial quadrilateral, the regular triangulation is used to partition. The regular triangulation can ensure that the generated triangles have regular shapes and sizes. The fitting planes of the four adjacent points are used to quadrilateralize the point cloud data. The rock structure surface is discretized into micro-units, and statistical parameters are used to quantitatively characterize the morphological characteristics of the rock structure surface. Then, different partitioning methods are used to analyze the same rock structure surface, and the characteristic differences of the rock structure surface under different partitioning methods are compared.

4. A method for analyzing rock profile characteristics according to claim 1, characterized in that: In the step 3, when the radius R is less than the distance D, the fourth point is outside the circumscribed sphere, and the triangle at this time is a Delaunay triangle.

5. A method for analyzing rock profile characteristics according to claim 1, characterized in that: In step 4, the calculation formulas of radius R and distance D are as follows: In the above formula, (X1, Y1, Z1) and (X2, Y2, Z2) are the coordinates of the center and the fourth point respectively, where a, b and c are the lengths of the three sides of the triangle, and S is the area of ​​the triangle.

6. A method for analyzing rock profile characteristics according to claim 1, characterized in that: The four points in the three-dimensional space have a height difference on the z-axis, and their projection plane A'B'C'D' is a square. The Delaunay function command is run on the MATLAB software. The relative position of the triangle circumscribed circle and the fourth point is determined according to the distance between the points on the XOY plane, and the triangulation method of a single discrete quadrilateral is determined at the same time, thereby realizing Delaunay triangulation. After processing the point cloud data, an XOY plane with equal spacing is obtained, and at the same time, the distance D from the center of the triangle circumscribed circle to the fourth point and the radius R of the circumscribed circle are obtained.

7. A rock profile characteristic analysis system applicable to the rock profile characteristic analysis method according to any one of claims 1 to 6, characterized in that: The rock profile feature analysis system comprises a profile feature acquisition module, a profile feature analysis module and a profile feature recording module.

8. A rock profile characteristic analysis system according to claim 7, characterized in that: The functions of each module are as follows: Profile feature acquisition module: used to collect and record rock surface features, and actively repair the recorded fuzzy features to ensure that the complete rock structure surface is collected; Profile feature analysis module: used to analyze the stress of the collected rock structure surface, quantitatively analyze and describe the morphological characteristics, area, length, angle and curvature of the rock structure surface, and analyze and describe the anisotropy, spacing effect and size effect of the profile characteristics; Profile feature recording module: used to record and store the data analyzed and described by the profile feature analysis module.

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