Selection method of laser fracturing rock fracture surface roughness REV

Abstract

The invention discloses a selection method of laser cracking rock fracture surface roughness REV. The selection method comprises the following steps: 1) obtaining laser cracking rock fracture surface and point cloud data; 2) point cloud data processing; 3) calculating the roughness index of the whole rock fracture surface; 4) selecting and calculating a representative unit of the roughness of the rock fracture surface; and (5) judging the fracture surface roughness REV. According to the method, the roughness of the large-size rock fracture surface can be represented without being influenced by the local large fluctuation degree characteristic of the rock fracture surface, automatic processing software can be generated, and equipment is applied to the fields of rock mechanics, fracture mechanics, rock fracture seepage, convective heat transfer and the like and has a wide application prospect. The mutual influence of the fracture surface roughness characteristics on the mechanical characteristics and the water-rock action is analyzed, and the method has wide practicability in the technical field.

Description

Technical Field

[0001] The invention belongs to the technical field of laser-assisted rock breaking, and in particular relates to a method for selecting the roughness REV of a crack surface of a laser-fractured rock. Background Art

[0002] The characterization of rock fracture surfaces after laser processing is crucial for understanding and revealing the rock fracture mechanism. The rock joint surface roughness coefficient (JRC) is one of the key parameters to measure the roughness of rock fracture surfaces, which is crucial for understanding and studying the generation of rock fracture surfaces and rock flow.

[0003] In recent years, laser rock breaking technology has been considered as one of the most promising auxiliary rock breaking methods due to its high efficiency and environmentally friendly characteristics. Researchers have conducted a lot of research from the perspectives of temperature field distribution, mechanical characteristics, and crack distribution of rocks under laser action, and have made a lot of contributions to the research on the failure mode and failure mechanism of rocks under laser action. In addition, researchers have carried out a lot of quantitative research on the roughness characteristics of rock crack surfaces under experimental conditions such as Brazilian splitting and uniaxial compression. However, there are relatively few studies on the roughness of rock crack surfaces after laser action. This is because the rock crack surfaces after laser irradiation are significantly different from the crack surfaces obtained by Brazilian splitting and uniaxial compression. On the one hand, after laser irradiation, a non-uniform transient temperature field is generated inside the rock. Due to the differences in physical and chemical properties between mineral particles, partitions characterized by different temperature stages appear in the rock. These partitions have large temperature differences, which in turn affect the morphology of the rock crack surface, resulting in large fluctuation characteristics on the local rock crack surface, which is not conducive to the characterization of the roughness of large-scale rock crack surfaces. Summary of the invention

[0004] The purpose of the present invention is to provide a method for selecting the roughness REV of a laser fractured rock fracture surface, which can characterize the roughness of a large-scale rock fracture surface without being affected by the local large undulation characteristics of the rock fracture surface.

[0005] To achieve the above object, the present invention provides a method for selecting the roughness REV of the crack surface of laser-fractured rock, comprising the following steps:

[0006] 1) Acquisition of rock fracture surface and point cloud data after laser fracturing;

[0007] Obtaining the rock fracture surface after laser fracturing; then, using 3D laser scanning to obtain the rock fracture surface data after laser fracturing, and storing it as a three-dimensional point cloud data file in stl format;

[0008] 2) Point cloud data processing;

[0009] According to the accuracy requirements, the sampling interval of the point cloud data is determined to be δx, and the point cloud data is discretized based on the Kriging interpolation method. The data of the required positions are retained in the original point cloud data and the data information of the redundant positions is deleted. Then, the absolute elevation in the data is converted into relative elevation, and the converted data is saved as a csv format file containing three columns of information, namely x, y, and z coordinate values, for output, recorded as Mnn(x, y, z);

[0010] 3) Calculate the roughness index of the entire rock fracture surface;

[0011] According to the Mnn (x, y, z) data, the profile roughness coefficient of the crack surface is calculated, recorded as JRC_M, and the average value of the obtained profile roughness coefficient is used as the roughness index of the crack surface;

[0012] 4) Selection and calculation of representative units of rock fracture surface roughness;

[0013] The center point of the projection plane of the crack surface in the XOY direction is recorded as the center point of the rectangle. A rectangle with a length and a width of b is taken. The crack surface area corresponding to the rectangular area is recorded as a representative unit as Rnn(x, y, z). Then, according to the calculation method of step 3), the structural roughness coefficient of the crack surface Rnn(x, y, z) can be obtained, which is recorded as JRC_R.

[0014] 5) Determination of crack surface roughness REV;

[0015] By continuously changing the values ​​of a and b with the sampling interval as the step size, the updated JRC_R value can be obtained, and the relative error between the JRC_M and JRC_R values ​​can be calculated to obtain data with an error of ≤5%, and the Rnn (x, y, z) fracture surface area with the smallest a and b values ​​is determined as the REV of the rock fracture surface roughness.

[0016] As a further solution of the present invention: in step 3), the profile roughness coefficient is calculated using the following formula:

[0017] JRC=32.2+32.47Log 10 Z2

[0018]

[0019] Where Z2 is the root mean square of the first-order difference of the two-dimensional fracture profile coordinates, dimensionless; i,j is the coordinate of the z value of the two-dimensional fracture profile of the jth point in the y direction when the x value is the same, mm; M is the number of sampling points; δx is the sampling interval; through calculation, the roughness coefficients of several contour lines along the x direction on the entire rock structure surface are obtained, and the average value of all contour line roughness coefficients is used as the roughness index of the entire fracture surface.

[0020] As a further solution of the present invention: in step 4), when selecting the projection plane, the side length of the selected area has the following characteristics: a / b=Xmax / Ymax, and a∈[Xmin,Xmax], b∈[Ymin,Ymax].

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] It can characterize the roughness of large-scale rock fracture surfaces without being affected by the large local undulation characteristics of the rock fracture surface;

[0023] Based on the profile roughness coefficient, the roughness of the representative unit is used to characterize the roughness of the complete rock fracture surface after laser irradiation, which can reduce the workload of roughness calculation of large-scale rock fracture surfaces.

[0024] This method can generate automated processing software and equipment for use in fields such as rock mechanics, fracture mechanics, rock fissure seepage and convective heat transfer, and analyze the mutual influence of the roughness characteristics of the fracture surface on its mechanical characteristics and water-rock interaction, and has wide practicality in this technical field. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic flow chart of a method for selecting the roughness REV of the crack surface of a laser-induced rock fracture according to the present invention;

[0026] Figure 2 (a) shows the granite crack surface prepared by laser;

[0027] Figure 2 (b) is the result of granite fracture surface reconstructed by software;

[0028] Figure 2 (c) is the elevation data distribution obtained by discretizing the point cloud data of the granite fracture surface obtained by 3D laser scanning;

[0029] Figure 2 Middle (d) is the statistical result of granite fracture surface elevation distribution;

[0030] Figure 3 The roughness coefficient calculation results of each unit after division. DETAILED DESCRIPTION

[0031] The present invention will be further described below by way of examples.

[0032] like Figure 1 As shown, a method for selecting the roughness REV of the crack surface of laser-fractured rock comprises the following steps:

[0033] 1) Acquisition of rock fracture surface and point cloud data after laser fracturing;

[0034] Obtain the rock fracture surface after laser fracturing; then, use 3D laser scanning to obtain the rock fracture surface data after laser fracturing, and store it in a three-dimensional point cloud data file in stl format; wherein the rock fracture surface after laser fracturing can be obtained by conducting a laser fracturing rock experiment;

[0035] 2) Point cloud data processing;

[0036] According to the accuracy requirements, the sampling interval of the point cloud data is determined to be δx, and the point cloud data is discretized based on the Kriging interpolation method. The data of the required positions are retained in the original point cloud data and the data information of the redundant positions is deleted. Then, the absolute elevation in the data is converted into relative elevation, and the converted data is saved as a csv format file containing three columns of information, namely x, y, and z coordinate values, for output, recorded as Mnn(x, y, z);

[0037] 3) Calculate the roughness index of the entire rock fracture surface;

[0038] According to the Mnn (x, y, z) data, the profile roughness coefficient of the crack surface is calculated, recorded as JRC_M, and the average value of the obtained profile roughness coefficient is used as the roughness index of the crack surface;

[0039] 4) Selection and calculation of representative units of rock fracture surface roughness;

[0040] The center point of the projection plane of the crack surface in the XOY direction is recorded as the center point of the rectangle. A rectangle with a length and a width of b is taken. The crack surface area corresponding to the rectangular area is recorded as a representative unit as Rnn(x, y, z). Then, according to the calculation method of step 3), the structural roughness coefficient of the crack surface Rnn(x, y, z) can be obtained, which is recorded as JRC_R.

[0041] 5) Determination of crack surface roughness REV;

[0042] By continuously changing the values ​​of a and b with the sampling interval as the step size, the updated JRC_R value can be obtained, and the relative error between the JRC_M and JRC_R values ​​can be calculated to obtain data with an error of ≤5%, and the Rnn (x, y, z) fracture surface area with the smallest a and b values ​​is determined as the REV of the rock fracture surface roughness.

[0043] Further, in step 3), the profile roughness coefficient is calculated using the following formula:

[0044] JRC=32.2+32.47Log 10 Z2 (1)

[0045]

[0046] Where Z2 is the root mean square of the first-order difference of the two-dimensional fracture profile coordinates, dimensionless; i,j is the coordinate of the z value of the two-dimensional fracture profile of the jth point in the y direction when the x value is the same, mm; M is the number of sampling points; δx is the sampling interval; through calculation, the roughness coefficients of several contour lines along the x direction on the entire rock structure surface are obtained, and the average value of all contour line roughness coefficients is used as the roughness index of the entire fracture surface.

[0047] Furthermore, in step 4), when the projection plane is selected, the side length of the selected area has the following characteristics: a / b=Xmax / Ymax, and a∈[Xmin,Xmax], b∈[Ymin,Ymax].

[0048] Example:

[0049] The specific steps are as follows:

[0050] 1) Select a disc-shaped granite sample of a certain mineral and conduct a laser splitting test to obtain the rock splitting effect. Figure 2 As shown in (a), the size of the cleavage surface is about 50 mm × 25 mm (length × width);

[0051] 2) Use 3D laser scanning to obtain point cloud data of rock fracture surfaces and save it as an STL format file;

[0052] 3) Use processing software (such as Surfer, Geomagic, etc.) to open the acquired stl format data file of rock structural surface morphology, set the sampling interval δx to 0.2 mm, use Kriging interpolation method to discretize the data, delete redundant data points, and use grid sparse processing on the data to obtain about 31496 rows and 3 columns of data, the 3 columns of data are x, y, z coordinate value information, and then save the processed data as a dat format file;

[0053] 4) Considering the differences between crack surfaces and the influence of boundary effects on surface morphology, Matlab and other software are used to process the exported dat format files, convert the absolute elevation into relative elevation, and save the processed data as csv format files. Figure 2 (b) is the fracture surface morphology obtained by relative elevation reconstruction;

[0054] 5) Use processing software (such as Surfer, Geomagic, etc.) to open the csv format file obtained in the above steps, with a sampling interval of 0.2mm, and you can get the fracture surface elevation distribution results after grid sparse processing, such as Figure 2 As shown in (c), there are 100×51 data points representing elevation information. The fracture surface elevation distribution results obtained by mathematical statistics are as follows: Figure 2As shown in (d), it was found that the average elevation of the crack surface was about 3.211 mm;

[0055] 6) Use Matlab programming to calculate the characteristic parameter Z2 of the structural surface contour line in the data, and calculate the contour line roughness coefficient based on the Z2 value using formula (1) and formula (2).

[0056] This example only analyzes the roughness coefficient of the structural surface along the y direction. The roughness coefficient of the line segment can be calculated by taking the 51 points in the y-axis direction as a line segment. Similarly, Matlab programming is used to calculate the roughness coefficients of all 100 line segments in the y direction. The average value of the 100 roughness coefficients is taken as the roughness coefficient of the crack surface. The calculation result is 15.4311, recorded as JRC_M;

[0057] 7) Take a rectangle with a length and a width of a and b respectively. When a=50mm and b=25mm, the rectangle is the projection plane of the entire crack surface in the XOY direction. In order to reduce the amount of calculation, this embodiment takes rectangles of different sizes with a step length of 5mm, and 10 representative units of the crack surface of different sizes can be obtained. The roughness coefficient of the representative unit is calculated by Matlab programming using the above method. The result is as follows: Figure 3 As shown;

[0058] 8) Based on the above calculation results, calculate the relative error between the roughness coefficient of the representative unit and the roughness coefficient of the entire crack surface, and determine that when the error is less than or equal to 5%, the representative unit with the smallest size is the REV of the crack surface roughness.

[0059] Through calculation, it is found that when a×b=30mm×15mm, it meets the selection criteria of REV, and its roughness coefficient is about 15.7966, and the relative error between it and the roughness coefficient of the entire crack surface is only 2.37%. Therefore, in this embodiment, the crack surface with a length of 30mm and a width of 15mm is considered to be the REV of the crack surface roughness.

Claims

1. A method for selecting the roughness REV of the crack surface of laser-induced rock fracture, characterized in that: The following steps are involved: 1) Acquisition of rock fracture surface and point cloud data after laser fracturing; Obtaining the rock fracture surface after laser fracturing; then, using 3D laser scanning to obtain the rock fracture surface data after laser fracturing, and storing it as a three-dimensional point cloud data file in stl format; 2) Point cloud data processing; According to the accuracy requirements, the sampling interval of the point cloud data is determined to be δx, and the point cloud data is discretized based on the Kriging interpolation method. The data of the required positions are retained in the original point cloud data and the data information of the redundant positions is deleted. Then, the absolute elevation in the data is converted into relative elevation, and the converted data is saved as a csv format file containing three columns of information, namely x, y, and z coordinate values, for output, recorded as Mnn(x, y, z); 3) Calculate the roughness index of the entire rock fracture surface; According to the Mnn (x, y, z) data, the profile roughness coefficient of the crack surface is calculated, recorded as JRC_M, and the average value of the obtained profile roughness coefficient is used as the roughness index of the crack surface; 4) Selection and calculation of representative units of rock fracture surface roughness; The center point of the projection plane of the crack surface in the XOY direction is recorded as the center point of the rectangle. A rectangle with a length and a width of b is taken. The crack surface area corresponding to the rectangular area is recorded as a representative unit as Rnn(x, y, z). Then, according to the calculation method of step 3), the structural roughness coefficient of the crack surface Rnn(x, y, z) can be obtained, which is recorded as JRC_R. 5) Determination of crack surface roughness REV; By continuously changing the values ​​of a and b with the sampling interval as the step size, the updated JRC_R value can be obtained, and the relative error between the JRC_M and JRC_R values ​​can be calculated to obtain data with an error of ≤5%, and the Rnn (x, y, z) fracture surface area with the smallest a and b values ​​is determined as the REV of the rock fracture surface roughness.

2. The method for selecting the roughness REV of the crack surface of a laser-induced rock fracture according to claim 1, characterized in that: In step 3), the profile roughness coefficient is calculated using the following formula: JRC=32.2+32.47Log 10 Z2 Where Z2 is the root mean square of the first-order difference of the two-dimensional fracture profile coordinates, dimensionless; i,j is the coordinate of the z value of the two-dimensional fracture profile of the jth point in the y direction when the x value is the same, mm; M is the number of sampling points; δx is the sampling interval; through calculation, the roughness coefficients of several contour lines along the x direction on the entire rock structure surface are obtained, and the average value of all contour line roughness coefficients is used as the roughness index of the entire fracture surface.

3. A method for selecting the roughness REV of a laser-fractured rock fracture surface according to claim 1 or 2, characterized in that: In step 4), when the projection plane is selected, the side length of the selected area has the following characteristics: a / b=Xmax / Ymax, and a∈[Xmin,Xmax], b∈[Ymin,Ymax].

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