Broken gangue material bearing compression three-dimensional structure reconstruction and transparency characterization method

Abstract

The invention discloses a broken gangue material bearing compression three-dimensional structure reconstruction and transparency characterization method, which comprises the following steps: carrying out CT (Computed Tomography) scanning on broken gangue under different grading and different compression conditions, and carrying out binarization and noise reduction processing on a two-dimensional CT image obtained by scanning by utilizing an Otsu algorithm and a median filtering algorithm to obtain a clear binarized image; on the basis, carrying out three-dimensional reconstruction on crushed gangue samples under different compression conditions by adopting Avizo three-dimensional analysis software based on a rapid watershed algorithm of a topology theory; furthermore, gaps, frameworks and motion states of the crushed gangue samples are analyzed through equivalent isovolumetric ball quantitative analysis, a framework extraction algorithm of graphic distance transformation and a block position tracking method in the compression process, so that the transparent characterization of the crushed gangue material is realized. Compared with a traditional particle flow numerical simulation means, the method has the advantages that factors such as real shapes of the gangue blocks and occlusion, embedding extrusion and crushing among the blocks are considered, so that the result of the gangue compression and crushing state is more visual and accurate.

Description

Technical Field

[0001] The present invention belongs to the technical field, and relates to a method for three-dimensional structural reconstruction and transparency characterization of bulk materials, and specifically to a method for three-dimensional structural reconstruction and transparency characterization of crushed gangue materials under load compression. Background Art

[0002] The research method for visualizing the spatiotemporal evolution of the internal structure of gangue solid waste filling materials during the bearing process is currently based on particle flow numerical simulation. Specifically, in the research process, the irregularly shaped and angular gangue blocks are usually simplified into spheres or random convex polyhedrons. This method has the following defects: it cannot simulate the bite, embedding and crushing between gangue blocks during the bearing compression process, resulting in a certain deviation between the simulation results and the actual situation.

[0003] In order to overcome the above defects, some scholars have preliminarily realized the experimental research on the transparency of coarse-grained soil fabric characteristics through CT scanning. However, the research results are mainly based on two-dimensional CT slices, and the three-dimensional structural model of the internal structure of coarse-grained soil has not been established, and the transparency and quantitative characterization of the three-dimensional structure of coarse-grained soil have not been achieved. Therefore, for the research on the visualization of the spatiotemporal evolution of the internal structure during the bearing process of gangue solid waste filling materials, there is still a lack of research methods on three-dimensional structures.

[0004] Based on this, this patent design develops a method for three-dimensional structural reconstruction and transparency characterization of crushed gangue material under load compression. CT scanning can be performed during the compression process of the crushed gangue and the three-dimensional reconstruction can be obtained to obtain a digital three-dimensional structural model of the internal structural characteristics of the crushed gangue sample, and the crushed gangue sample can be transparently characterized. Summary of the invention

[0005] Purpose of the invention: In order to overcome the deficiencies in the prior art, the present invention provides a method for reconstruction and transparent characterization of the three-dimensional structure of crushed gangue materials under load compression. By performing CT scanning on the crushed gangue samples under different grading and different compression conditions, and using the Otsu algorithm and the median filter algorithm to binarize and reduce noise on the scanned two-dimensional CT images, a clear binary pre-processed image is obtained; based on this, the Avizo three-dimensional analysis software is used to perform three-dimensional reconstruction of the crushed gangue samples under different compression conditions based on the fast watershed algorithm of topological theory; finally, the gaps, skeletons, and motion states of the crushed gangue samples are further analyzed through equivalent equal volume sphere quantitative analysis, skeleton extraction algorithm of graphic distance transformation, and block position tracking method during compression, so as to realize the transparent characterization of the crushed gangue materials. Compared with the traditional particle flow numerical simulation method, this method takes into account the real shape of the gangue block and the factors such as the bite, interlocking and crushing between the blocks, so that the obtained gangue compression crushing state results are more intuitive and accurate.

[0006] To achieve the above object, the technical solution adopted by the present invention is:

[0007] The object of the present invention is to provide a method for characterizing the three-dimensional structure of crushed gangue material under load compression and transparency, comprising the following steps:

[0008] S1. By performing CT scanning on the internal structure of the crushed gangue samples of different gradations under different compression states, CT slice images of the internal structure of the crushed gangue samples are obtained;

[0009] S2. The internal structure CT slice image is subjected to binarization and noise reduction processing to obtain a preprocessed image;

[0010] S3. The preprocessed image is reconstructed by Avizo software to obtain a digital three-dimensional structural model of the crushed gangue sample;

[0011] S4. Based on the digital three-dimensional structural model, the pre-processed images are analyzed for voids, skeletons and motion states of the crushed gangue samples through three different paths and methods, thereby achieving transparent characterization of the crushed gangue materials.

[0012] Optionally, in some embodiments of the present invention, in step S1, the CT visualization compactor loaded with crushed gangue samples is loaded, limited and pressure maintained, CT scanned, and loading-pressure maintained-scanning is continued in a cycle to obtain two-dimensional slices of crushed gangue samples of different gradations under different load-bearing and compression conditions.

[0013] Optionally, in some embodiments of the present invention, the different gradations refer to aggregates of different gangue particle sizes, which are divided into a gradation G1 mainly composed of small-sized gangue particles, a gradation G2 mainly composed of medium-sized gangue particles, a gradation G3 mainly composed of large-sized gangue particles, and a gradation G4 of uniform gangue particles. Specifically, the mass percentage of rocks in each gangue particle size range in different gradations is:

[0014] Grading G1: 0-5mm gangue 44.7%, 5-10mm gangue 18.5%, 10-15mm gangue 14.2%, 15-20mm gangue 12%, 20-25mm gangue 10.6%;

[0015] Grading G2: 0-5mm gangue 10%, 5-10mm gangue 20%, 10-15mm gangue 40%, 15-20mm gangue 20%, 20-25mm gangue 10%;

[0016] Grading G3: 0-5mm gangue 9.52%, 5-10mm gangue 12.33%, 10-15mm gangue 18.63%, 15-20mm gangue 18.31%, 20-25mm gangue 41.21%;

[0017] Grading G4: 0-5mm gangue 20%, 5-10mm gangue 20%, 10-15mm gangue 20%, 15-20mm gangue 20%, 20-25mm gangue 20%.

[0018] Optionally, in some embodiments of the present invention, the different bearing compression conditions refer to conducting large-scale triaxial compression tests on different particle gradings using different confining pressure conditions, and the confining pressures are selected as 1.0MPa, 1.5MPa, 2.0MPa and 2.4MPa, respectively, and the axial pressures of the pressure-maintaining nodes are selected as 1MPa, 2MPa, 3MPa, 5MPa and 10MPa, respectively.

[0019] Optionally, in some embodiments of the present invention, in step S2, the binarization processing includes using the Otsu algorithm in MATLAB software to obtain the optimal threshold of the internal structure CT slice image of the crushed gangue sample, and binarizing the internal structure CT slice image based on this threshold to convert it into a binary image including only matrix and voids.

[0020] Optionally, in some embodiments of the present invention, in step S2, the noise reduction processing includes using a median filtering algorithm to perform noise reduction processing on the internal structure CT slice image to obtain a clear binary image containing two phases, a black phase and a white phase, wherein the black phase represents the voids and the white phase represents the gangue matrix.

[0021] Optionally, in some embodiments of the present invention, in step S3, the three-dimensional structural reconstruction performed by Avizo software includes using the fast watershed algorithm based on topological theory of Avizo three-dimensional analysis software to perform three-dimensional reconstruction of broken gangue samples under different loading stress compression conditions, and independently distinguishing each gangue block in the model through cyclic color illumination model rendering technology to obtain a digital three-dimensional structural model of the internal structural characteristics of the broken gangue sample.

[0022] Optionally, in some embodiments of the present invention, in step S4, the method of analyzing the voids, skeleton and motion state of the crushed gangue sample by three different paths and methods respectively on the pre-processed image to achieve transparent characterization of the crushed gangue material includes at least one of the following a, b, c:

[0023] a. Based on the pre-processed images, the void space, shape, volume, and equivalent diameter are transparently characterized by quantitative analysis of the void equivalent volume sphere;

[0024] b. Based on the preprocessed image, the skeleton extraction algorithm of the graphic distance transformation is adopted to realize the transparent representation of the contact network structure between blocks;

[0025] c. Based on the preprocessed images, the block position tracking method is used to track the position coordinates of the blocks in the crushed gangue sample under different stress states, thereby realizing the transparent representation of the block movement during the crushed gangue bearing compression process.

[0026] Optionally, in some embodiments of the present invention, the void equivalent isovolumetric sphere quantitative analysis described in method a specifically includes performing an inverse operation on the digital three-dimensional structural model of the crushed gangue sample to obtain a void space distribution model of the crushed gangue sample, rendering through a cyclic color lighting model to obtain a void space marking model of the crushed gangue sample, extracting and analyzing the pore structure in the void space marking model, and replacing each pore structure with an imaginary isovolumetric sphere.

[0027] Optionally, in some embodiments of the present invention, the equivalent diameter of each pore structure is determined by the following formula:

[0028]

[0029] Where Deq is the equivalent diameter and Vpore is the void volume.

[0030] Optionally, in some embodiments of the present invention, the skeleton extraction algorithm of the graphic distance transformation described in method b specifically includes defining a sphere in the model to represent a gangue block in the sample, wherein the center of the sphere is located at the centroid of the block, the size of the sphere represents the volume of the block, and a short stick connecting the centers of two spheres represents the contact between adjacent blocks. The thicker the short stick, the higher the contact stability. Ultimately, the three-dimensional contact network distribution evolution of the crushed gangue sample under load compression is obtained, thereby achieving transparent characterization of the contact network structure between blocks.

[0031] Optionally, in some embodiments of the present invention, the block position tracking method described in method c specifically includes tracking the position coordinates of blocks in the crushed gangue sample under different stress states, obtaining a three-dimensional vector diagram of the block movement in the crushed gangue sample, and realizing a transparent representation of the block movement during the load-bearing compression process of the crushed gangue sample.

[0032] Beneficial effects: The present invention provides a method for reconstruction and transparent characterization of the three-dimensional structure of crushed gangue materials under compression, which adopts a combination of two-dimensional and three-dimensional methods, and uses the Avizo three-dimensional analysis software based on the fast watershed algorithm of topological theory to reconstruct the three-dimensional crushed gangue samples under different compression conditions, and further analyzes the gaps, skeletons, and motion states of the crushed gangue samples through equivalent equal volume sphere quantitative analysis, skeleton extraction algorithm of graphic distance transformation, and block position tracking method during compression, thereby achieving transparent characterization of the crushed gangue materials. Compared with traditional particle flow numerical simulation methods, this method takes into account the real shape of the gangue blocks and the factors such as the bite, squeeze and crushing between the blocks, so that the obtained gangue compression crushing state results are more intuitive and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 The present invention is a flow chart of a method for reconstructing the three-dimensional structure of crushed gangue material under load and compression and a method for transparent characterization.

[0034] Figure 2 This is the distribution diagram of axial pressure and confining pressure during loading of large-scale triaxial compression test.

[0035] Figure 3 Binarization processing of CT slice images, (a) CT scan slice, (b) before binarization processing and denoising, (c) after binarization processing and denoising.

[0036] Figure 4 It is a three-dimensional structural model and its longitudinal section.

[0037] Figure 5 This is the evolution diagram of the gap distribution.

[0038] Figure 6 The evolution diagram of contact network distribution of crushed gangue sample, (a) three-dimensional diagram, (b) longitudinal section diagram, (c) cross section diagram.

[0039] Figure 7 Longitudinal sections of crushed gangue samples under different axial stress states when the confining pressure is 1.0 MPa, (a) 3 MPa, (b) 5 MPa, and (c) 10 MPa. DETAILED DESCRIPTION

[0040] The present invention will be further described below in conjunction with the accompanying drawings and Examples. According to the following examples, the present invention can be better understood. However, it is easy for those skilled in the art to understand that the specific material ratios, process conditions and results described in the examples are only used to illustrate the present invention, and should not and will not limit the present invention described in detail in the claims.

[0041] Example

[0042] Aiming at the problem that the internal structure of crushed gangue is difficult to analyze during compression, this patent proposes a simple and clear three-dimensional reconstruction and transparent characterization method for crushed gangue, such as Figure 1 As shown, the specific steps are as follows:

[0043] (S1) By performing CT scanning on the internal structure of the crushed gangue samples of different gradations under different compression states, CT slice images of the internal structure of the crushed gangue samples are obtained.

[0044] The specific method is as follows: first, prepare crushed gangue samples of different gradations. Specifically, different gradations refer to aggregates of different gangue particle sizes, which are divided into gradation G1 dominated by small-size gangue particles, gradation G2 dominated by medium-size gangue particles, gradation G3 dominated by large-size gangue particles, and gradation G4 of uniform gangue particles, as shown in Table 1;

[0045] Table 1 Particle grading scheme design

[0046]

[0047] Crushed gangue samples of different gradations (G1, G2, G3 and G4) were loaded into the limited pressure CT scanner, and the CT visualization compactor loaded with samples was placed in the MTS press for loading test. Figure 2 As shown, in this step, axial pressure is applied under a certain confining pressure condition. The confining pressure is selected as 1.0MPa, 1.5MPa, 2.0MPa and 2.4MPa respectively, and the axial pressure of the pressure-maintaining nodes is selected as 1MPa, 2MPa, 3MPa, 5MPa and 10MPa respectively. Before the test starts, the confining pressure is loaded to the predetermined stress value. At the beginning of the experiment, the confining pressure remains unchanged and the axial pressure continues to increase. When a certain axial pressure is loaded, the pressure is maintained, and then a CT scan is performed. After that, the above loading-pressure-maintaining-CT scanning steps are repeated. During the test, the pressure-maintaining nodes are selected as axial pressures of 1, 2, 3, 5 and 10MPa respectively. After completing the CT scanning imaging of the above nodes, the next confining pressure is changed to perform the above test until the CT scanning imaging of different axial stresses under all confining pressure conditions is completed.

[0048] Specifically, in this embodiment, taking the confining pressure of 1.0MPa as an example, when the axial pressure reaches the set pressure (1MPa) / displacement (10mm), the loading is stopped, and at the same time, the displacement of the press head is limited, the nut is tightened, and the sample in the barrel is limited and pressure-maintained. After the press is depressurized, the CT visualization compactor is taken out and placed in the CT machine for scanning to obtain a two-dimensional slice; after the scanning is completed, the CT visualization compactor is placed in the press again, and the sample is loaded to the next axial pressure (2MPa) / displacement (20mm) level, and then the limit pressure-maintaining-scanning-loading is performed again, and this cycle is repeated. During the test, the pressure-maintaining nodes select axial pressures of 1, 2, 3, 5 and 10MPa in turn.a After completing the CT scanning imaging of the above nodes, 1.0MP a Two-dimensional slices under different load compression conditions under confining pressure, such as Figure 3 (a) shown.

[0049] (S2) The internal structure CT slice image is binarized and denoised to obtain the preprocessed image

[0050] First, image binarization

[0051] Firstly, the optimal threshold T for binary segmentation of CT images of crushed gangue samples was obtained by using the Otsu algorithm in MATLAB software. h(max) ;

[0052] Then, the gray value of each pixel in the image is transformed. Specifically, the pixel gray value is lower than the optimal threshold T h(max) is converted to 0 (black, representing the void phase), which is higher than the optimal threshold T h(max) The grayscale image is converted to 255 (white, representing the gangue matrix phase), and finally the CT grayscale image is converted into a binary image including only the matrix and the voids.

[0053] The basic principle of Otsu's algorithm is: the size of the image F(x,y) is A×B, T h For the segmentation threshold of the foreground and background, we have: M1+M2=A×B

[0054] Wherein, x and y are the length and width of the image, respectively. The image size in the embodiment is 12.70 cm × 8.89 cm. F(x, y) represents an image with a length of x and a width of y. A and B are the number of pixels in the length and width of the image, respectively. The pixel size in the embodiment is 1500 × 1050. M1 is the number of foreground pixels, M2 is the number of background pixels, and the proportions of foreground and background pixels to the total number of pixels in the image are and Then we have:

[0055]

[0056] If the average grayscale of the foreground is calculated to be g1, and the average grayscale of the background is g2, then the average grayscale g of the entire image is:

[0057]

[0058] Take the image segmentation threshold S = g, then the variance between foreground and background classes R:

[0059]

[0060] Combining the above two formulas, we get the equivalent formula:

[0061] The traversal method is used to calculate the inter-class variance of the grayscale image under different segmentation thresholds, and the segmentation threshold T that maximizes the inter-class variance R is obtained by comparison. h(max) That is, the optimal threshold value for image binary segmentation. In this embodiment, the optimal threshold value T for image binary segmentation is h(max) is 155.

[0062] Second, noise reduction processing

[0063] The median filtering algorithm is used to replace the gray value of each pixel in the two-dimensional gray image with the median of the gray values ​​of all pixels in its neighborhood window (usually 3×3 or 5×5, 3×3 is selected in this embodiment), so that the surrounding pixel values ​​are close to the true value, so as to eliminate isolated noise points and obtain a clear binary image containing black (voids) and white (gangue matrix) phases, i.e., the preprocessed image. The images before and after processing are shown in FIG. Figure 3 As shown in (b) and (c).

[0064] (S3) The preprocessed image is reconstructed into a three-dimensional structure using Avizo software to obtain a digital three-dimensional structural model of the crushed gangue sample.

[0065] The specific method is as follows: the original CT image is converted into a series of slices that can clearly characterize the internal structure of the broken gangue sample after binarization and noise reduction processing. Based on this series of slices, the Avizo 3D analysis software is used to perform 3D reconstruction of the broken gangue samples under different compression conditions using the fast watershed algorithm based on topological theory, and the matrix and voids are distinguished. Each gangue block in the model is independently distinguished by the cyclic color illumination model rendering technology, that is, the identified matrix phase is distinguished by color, and a digital 3D structural model of the internal structural characteristics of the broken gangue sample is obtained, such as Figure 4 shown.

[0066] (S4) Based on the digital three-dimensional structure model, the pre-processed image is analyzed by three different paths and methods to respectively analyze the voids, skeleton and movement state of the crushed gangue sample, so as to achieve the transparent characterization of the crushed gangue material.

[0067] (a) Based on the preprocessed image, the void space, shape, volume, and equivalent diameter are transparently characterized by quantitative analysis of the void equivalent volume sphere.

[0068] Based on the Avizo analysis results in the previous step, the digital 3D reconstruction model of the broken gangue sample is inverted, and the original identified gangue matrix phase is converted into the void phase to obtain the void space distribution model of the broken gangue sample. Each void in the model is independently distinguished by the cyclic color illumination model rendering, that is, the voids in different spaces are divided into different distinguishing colors to obtain the void space marking model of the broken gangue, such as Figure 5 shown.

[0069] Based on the void space labeling model of crushed gangue sample, the void volume is extracted and each void (also called pore structure) in the model is replaced by an imaginary sphere of equal volume. The equivalent diameter of each void can be determined by the following formula (where Deq is the equivalent diameter and Vpore is the void volume), thus realizing the transparent characterization of void space, shape, volume and equivalent diameter.

[0070]

[0071] (b) Based on the preprocessed image, the skeleton extraction algorithm of the graph distance transform is used to achieve transparent representation of the contact network structure between blocks.

[0072] The specific method is: based on Avizo software, the skeleton extraction algorithm of graphic distance transformation is used to extract the three-dimensional network model of the contact between blocks in the crushed gangue sample, such as Figure 6 As shown in the figure, the sphere in the model represents the gangue block in the sample, where the center of the sphere is located at the centroid of the block, the size of the sphere represents the size of the block volume, and the short stick connecting the centers of the two spheres represents the contact between adjacent blocks. The thicker the short stick, the higher the contact stability. Finally, the three-dimensional contact network distribution evolution of the crushed gangue sample under load compression was obtained, and the transparent representation of the contact network structure between blocks was achieved.

[0073] (c) Based on the preprocessed images, the block position tracking method is used to track the position coordinates of the blocks in the crushed gangue sample under different stress states, realizing the transparent representation of the block movement during the crushed gangue bearing compression process.

[0074] The specific method is as follows: during the CT scanning compression test with different gradations, the position coordinates (x, y, z) of the blocks in the crushed gangue sample under different stress states are tracked to obtain the three-dimensional vector diagram of the block movement in the crushed gangue sample, so as to realize the transparent representation of the block movement in the crushed gangue bearing compression process. Figure 7 shown.

[0075] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for characterizing the three-dimensional structure of crushed gangue material under load compression and transparency, characterized in that: The following steps are involved: S1. By performing CT scanning on the internal structure of the crushed gangue samples of different gradations under different compression states, CT slice images of the internal structure of the crushed gangue samples are obtained; S2. The internal structure CT slice image is subjected to binarization and noise reduction processing to obtain a preprocessed image; S3. The preprocessed image is reconstructed by Avizo software to obtain a digital three-dimensional structural model of the crushed gangue sample; S4. Based on the digital three-dimensional structural model, the pre-processed images are analyzed for voids, skeletons and motion states of the crushed gangue samples through three different paths and methods, thereby achieving transparent characterization of the crushed gangue materials.

2. The method according to claim 1, characterized in that In step S1, the CT visualization compactor loaded with the crushed gangue sample is loaded, limited and pressure maintained, CT scanned, and loading-pressure maintained-scanning is continued in a cycle to obtain two-dimensional slices of crushed gangue samples of different gradations under different load-bearing and compression conditions.

3. The method according to claim 2, characterized in that The different gradations refer to aggregates of different gangue particle sizes, which are divided into gradation G1 mainly composed of small-sized gangue particles, gradation G2 mainly composed of medium-sized gangue particles, gradation G3 mainly composed of large-sized gangue particles, and gradation G4 of uniform gangue particles. Specifically, the mass percentage of rocks in each gangue particle size range in different gradations is: Grading G1: 0-5mm gangue 44.7%, 5-10mm gangue 18.5%, 10-15mm gangue 14.2%, 15-20mm gangue 12%, 20-25mm gangue 10.6%; Grading G2: 0-5mm gangue 10%, 5-10mm gangue 20%, 10-15mm gangue 40%, 15-20mm gangue 20%, 20-25mm gangue 10%; Grading G3: 0-5mm gangue 9.52%, 5-10mm gangue 12.33%, 10-15mm gangue 18.63%, 15-20mm gangue 18.31%, 20-25mm gangue 41.21%; Grading G4: 0-5mm gangue 20%, 5-10mm gangue 20%, 10-15mm gangue 20%, 15-20mm gangue 20%, 20-25mm gangue 20%; The different bearing compression conditions refer to large-scale triaxial compression tests on different particle gradations using different confining pressure conditions, with the confining pressures selected as 1.0 MPa, 1.5 MPa, 2.0 MPa and 2.4 MPa, respectively, and the axial pressures of the pressure-maintaining nodes selected as 1 MPa, 2 MPa, 3 MPa, 5 MPa and 10 MPa, respectively.

4. The method according to claim 1, characterized in that In step S2, the binarization processing includes using the Otsu algorithm in MATLAB software to obtain the optimal threshold of the internal structure CT slice image of the crushed gangue sample, and binarizing the internal structure CT slice image based on this threshold. In step S2, the noise reduction processing includes using a median filtering algorithm to perform noise reduction on the internal structure CT slice image to obtain a clear binary image containing a black phase and a white phase, wherein the black phase represents the void and the white phase represents the gangue matrix.

5. The method according to claim 1, characterized in that In step S3, the three-dimensional structural reconstruction performed by Avizo software includes using the fast watershed algorithm based on topological theory of Avizo three-dimensional analysis software to perform three-dimensional reconstruction of the broken gangue samples under different loading stress compression conditions, and using the cyclic color illumination model rendering technology to independently distinguish each gangue block in the model to obtain a digital three-dimensional structural model of the internal structural characteristics of the broken gangue sample.

6. The method according to claim 1, characterized in that In step S4, the method of analyzing the voids, skeleton and motion state of the crushed gangue sample by three different paths and methods respectively to achieve transparent characterization of the crushed gangue material includes at least one of the following a, b, and c: a. Based on the pre-processed images, the void space, shape, volume, and equivalent diameter are transparently characterized by quantitative analysis of the void equivalent volume sphere; b. Based on the preprocessed image, the skeleton extraction algorithm of the graphic distance transformation is adopted to realize the transparent representation of the contact network structure between blocks; c. Based on the preprocessed images, the block position tracking method is used to track the position coordinates of the blocks in the crushed gangue sample under different stress states, thereby realizing the transparent representation of the block movement during the crushed gangue bearing compression process.

7. The method according to claim 6, characterized in that The void equivalent equal volume sphere quantitative analysis described in method a specifically includes: performing an inversion operation on the digital three-dimensional structure model of the crushed gangue sample to obtain a void space distribution model of the crushed gangue sample, rendering by a cyclic color illumination model to obtain a void space labeling model of the crushed gangue sample, extracting and analyzing the pore structure in the void space labeling model, replacing each pore structure with an imaginary equal volume sphere, and preferably, the equivalent diameter of each pore structure is determined by the following formula: Where Deq is the equivalent diameter and Vpore is the void volume.

8. The method according to claim 6, characterized in that The skeleton extraction algorithm of the graphic distance transformation described in method b specifically includes defining a sphere in the model to represent the gangue block in the sample, wherein the center of the sphere is located at the centroid of the block, the size of the sphere represents the volume of the block, and the short stick connecting the centers of the two spheres represents the contact between adjacent blocks. The thicker the short stick, the higher the contact stability. Finally, the three-dimensional contact network distribution evolution of the crushed gangue sample under load compression is obtained, thereby realizing the transparent characterization of the contact network structure between blocks.

9. The method according to claim 6, characterized in that The block position tracking method described in method c specifically includes tracking the position coordinates of the blocks in the crushed gangue sample under different stress states, obtaining a three-dimensional vector diagram of the block movement in the crushed gangue sample, and realizing a transparent representation of the block movement during the load-bearing compression process of the crushed gangue sample.

Images