A method for identifying the evolution characteristics of the particle shape contour of soft rock filler during the weathering process

Abstract

The present invention discloses a method for identifying the evolution characteristics of the shape profile of soft rock filler particles during the weathering process. By extracting and quantitatively analyzing the shape profile of soft rock filler particles during the weathering process, the evolution characteristics of the shape of soft rock filler particles during the weathering process are revealed. In this invention, the Image-Pro Plus software is used to measure the particle sizes of each sample before and after weathering and analyze its characteristic parameters. It can effectively quantify and analyze the disintegration and fragmentation behavior of soft rock filler particles, deepen the understanding of the fragmentation mechanism of soft rock filler particles, and promote the understanding of the road performance of soft rock fillers.

Description

Technical Field

[0001] The present invention relates to the field of rock formation identification, and particularly to a method for identifying the evolution characteristics of the shape and contour of soft rock filler particles during the weathering process. Background Art

[0002] Soft rock has the characteristics of being easily weathered, easily softened when encountering water, and significant strength attenuation, and belongs to a special type of subgrade filler. Although it is often encountered in engineering, its application in actual subgrade filling projects is not common. However, in recent years, the development strategy of "green, intensive, and economical" in China's infrastructure construction has been continuously deepened. If soft rock can be used for subgrade filling, it can not only reduce the extraction volume of conventional fillers but also reduce the occupation of land resources by waste disposal, with significant economic and environmental benefits.

[0003] However, the problem with using soft rock for subgrade filling is that with the progress of weathering, soft rock particles are prone to disintegration and fragmentation. Therefore, it is extremely necessary to study the disintegration and fragmentation characteristics of particles in soft rock fillers. Zhang Zongtang obtained the mass distribution of each particle group of the disintegration products through indoor disintegration tests of red sandstone in the article "Experimental Study on the Disintegration Characteristics of Expansive Rock under Dry-Wet Cycles", and used a fractal dimension solution method based on the correlation between mass and particle size to explore the disintegration and fragmentation process of rocks under dry-wet cycles. Fu Hongyuan et al. carried out disintegration tests of carbonaceous mudstone under the action of load and dry-wet cycles in the article "Experimental Study on the Disintegration Characteristics of Carbonaceous Mudstone Considering Load and Dry-Wet Cycles", and used methods such as scanning electron microscopy and X-ray diffraction to analyze the morphological changes and grading characteristic laws during the disintegration of carbonaceous mudstone, and then introduced the theory of disintegration and fractal to study the mass, particle size, and morphological distribution characteristics of particles during the disintegration of carbonaceous mudstone. Generally speaking, existing research methods mostly focus on the change of grading, and there are few quantitative research methods for the shape evolution characteristics of filler particles. Moreover, during the weathering process, the contour of filler particles is bound to change. Therefore, finding a method to extract the contour of particles and analyze the correlation between related indicators and particle morphology is extremely important for understanding the weathering and disintegration behavior and mechanical evolution of soft rock fillers. Summary of the Invention

[0004] In view of the above deficiencies in the prior art, the present invention provides a method for identifying the evolution characteristics of the shape and contour of soft rock filler particles during the weathering process.

[0005] In order to achieve the above invention object, the technical solution adopted by the present invention is as follows:

[0006] A method for identifying the evolution characteristics of the shape and contour of soft rock filler particles during the weathering process, comprising the following steps:

[0007] S1. Simulate the weathering process and obtain the contour characteristics of soft rock particles;

[0008] S2. Randomly group the soft rock particles after simulated weathering;

[0009] S3. Use digital image processing algorithms to process each group of soft rock particles and calculate the evaluation parameters of the soft rock particles;

[0010] S4. Obtain the evolution characteristics of the shape profiles of soft rock filler particles before and after weathering for different particle size groups based on the evaluation parameters calculated in S3.

[0011] Furthermore, the specific steps of S1 are as follows:

[0012] S11. Place the soft rock filler in the natural environment;

[0013] S12. Use the N method in the maximum density curve theory to design the gradation of the soft rock filler. The specific method is as follows:

[0014]

[0015] where p m is the passing percentage (%) of aggregate particles on the sieve aperture D m ; D m is the specific sieve aperture (mm); m is the specific sieve; D max is the maximum particle size (mm) of the aggregate, which is 40 mm here; n is the shape factor, which is taken as 0.7 here;

[0016] S13. Put the graded aggregate into the oven for drying treatment. After drying, load the filler into a metal tray with holes of 2.5 cm in diameter at the bottom and cover it with a plastic sieve mesh of 1 mm in diameter to facilitate drainage. The filler is evenly distributed and the thickness does not exceed 1 cm;

[0017] S14. Place the metal tray in the natural environment and regularly take out the filler in it for drying. Taking 5 mm as the dividing line, contour analysis is carried out for particles larger than 5 mm;

[0018] S15. Divide the fillers in the 5 - 10 mm, 10 - 20 mm, and 20 - 40 mm particle size groups into four equal parts, and randomly take one sample from each equal part, that is, take four parallel samples for each particle size group, and denote them as GS 5～10 -i-j, GS 10～20 -i-j, GS 20～40 -i-j. Ensure that there are 100 particles in each sample during the sampling process;

[0019] S16. Set up a reference scale whiteboard, fix a high-definition camera directly above it, adjust the camera angle, take pictures of the particles in different samples. During the shooting process of the filler with the same particle size range, the camera position and camera shooting parameters remain unchanged, and the arrangement should be random and the materials should not overlap or contact each other;

[0020] S17. Take a photo of each arranged sample to obtain the pellet arrangement image. After remixing the photographed pellets, place them in the natural environment for the next cycle of weathering.

[0021] Further, in step S3, the digital image processing module of Image-Pro Plus (IPP) software is used to process the images of the particles obtained from the disintegration of soft rock during the weathering process, and then the relevant evaluation parameters of the soft rock particles are calculated. The specific method is as follows:

[0022] S31. Import the taken photo into Image-Pro Plus software, and use the brightness, contrast, and gamma correction controls on the software's contrast enhancement panel to enhance the image and preprocess the picture.

[0023] S32. Use the AOI tool to depict the contours of each pellet, and generate a measurement object through convert AOI to object to measure the area, perimeter, major axis size, minor axis size, and shape parameters of each particle.

[0024] S33. For GS 5～10 -0-2, 3, 4, perform the operations of steps S31 - S32 to obtain the parameters such as the area, perimeter, major axis size, minor axis size, equivalent diameter, abundance, roundness, and shape factor of all particles in the 5 - 10 mm particle size range of the four samples without weathering.

[0025] S34. For the eight samples of GS 10～20 -0-1, 2, 3, 4 and GS 20～40 -0-1, 2, 3, 4, perform the operations of steps S31 - S33, and the shape parameters and their distribution characteristics of the particles in different particle size ranges of the filler under the weathering of each cycle can be obtained.

[0026] Further, in step S32, the calculation methods for the parameters of equivalent diameter D, abundance C, roundness R, and shape factor F are as follows:

[0027] The area of the circle equal to the projected area of the particle, where A is the actual area of the particle;

[0028] B is the minor axis size of the particle, and L is the major axis size of the particle;

[0029] A' is the area of the circumscribed circle of the particle;

[0030] P = πD, where P is the circumference of the circle equal in area to the particle, and S is the actual circumference of the particle.

[0031] Further, step S4 specifically includes:

[0032] S41. Starting from the second cycle, compare the evaluation parameters of the soft rock particles in the previous cycle with those of the soft rock particles in each cycle to obtain the stability degree of the soft rock.

[0033] S42. Use the grey relational analysis method to calculate the relationship between the shape parameters of the weathered soft rock filler and its corresponding stability degree to obtain the correlation coefficient.

[0034] Further, in the above S41, the calculation method of the stability degree of the soft rock is as follows:

[0035]

[0036] where SD (i,i+1) is the degree of correlation; I is the slake durability index of the soft rock filler; i is the month;

[0037] Further, the specific steps of the grey relational analysis method in the above S42 are as follows:

[0038] S421. Take the stability degree as the reference sequence, and calculate the correlation coefficient with the abundance, roundness, and shape factor as the comparison sequences;

[0039] S422. Calculate the average value of the correlation coefficients, and use the obtained average value to represent the degree of correlation between the comparison sequence and the reference sequence.

[0040] Further, the calculation method of the correlation coefficient in the above S421 is as follows:

[0041]

[0042] where y(k) is the reference sequence, x l (k) is the comparison sequence, k is the cycle, ρ is the resolution coefficient, and Δ l (k) is the absolute value of the difference between the reference sequence and the comparison sequence;

[0043] Further, the calculation method of the average value of the correlation coefficients in the above S422 is as follows:

[0044]

[0045] where n is the total number of samples.

[0046] The present invention has the following beneficial effects:

[0047] Currently, most studies adopt the method of screening the soft rock filler before and after the dry-wet cycle, and compare the gradation changes of the filler before and after, which cannot explore the evolution of the particle shape profile.

[0048] The present invention uses Image-Pro Plus software to measure the particle sizes of samples before and after weathering and analyze their characteristic parameters. It can effectively quantify and analyze the disintegration and fragmentation behavior of soft rock filler particles, deepen the understanding of the fragmentation mechanism of soft rock filler particles, and promote the understanding of the road performance of soft rock fillers. Description of the Drawings

[0049] Figure 1 It is a flow chart of a research method for the disintegration and fragmentation characteristics of soft rock filler particles during the weathering process provided by an embodiment of the present invention.

[0050] Figure 2 For an embodiment of the present invention, a weathered filler sample with a particle size of 20 - 40 mm is divided into four equal parts and randomly arranged, and an image is taken. Detailed Embodiments

[0051] The following describes the detailed embodiments of the present invention to facilitate those skilled in the art to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the detailed embodiments. For those ordinary skilled in the art in the technical field, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are within the scope of protection.

[0052] A method for identifying the evolution characteristics of the shape contour of soft rock filler particles during the weathering process, as Figure 1 shown, includes the following steps:

[0053] S1. Simulate the weathering process and obtain the contour characteristics of soft rock particles;

[0054] S2. Randomly group the soft rock particles after simulating the weathering;

[0055] S3. Use digital image processing algorithms to process each group of soft rock particles and calculate the evaluation parameters of the soft rock particles;

[0056] S4. Obtain the evolution characteristics of the shape contour of soft rock filler particles of different particle size groups before and after weathering according to the evaluation parameters calculated in S3.

[0057] Specifically,

[0058] (1) Gradation design. The sieve hole sizes for each grade of soft rock filler particle sizes are set to 0.075, 2, 5, 10, 20, 40 (unit: mm). The N method in the maximum density curve theory is applied to the gradation design of soft rock fillers, as shown in Formula 1.

[0059]

[0060] Among them, p m is the aggregate particle passing through the sieve hole aperture Dm by percentage content (%) on; D m is the specific sieve pore diameter (mm); m is the specific sieve pore; D max is the maximum particle size of the aggregate (mm), here it is 40 mm; n is the shape factor, here it is taken as 0.7.

[0061] (2) Put the graded aggregate into the oven for drying treatment. Load the dried filler into a metal tray. There are holes with a diameter of 2.5 cm at the bottom of the tray, and a plastic sieve mesh with a diameter of 1 mm is covered to facilitate drainage. The filler is evenly distributed and the thickness does not exceed 1 cm.

[0062] (3) Place the metal tray on an unobstructed rooftop to fully expose it to natural climatic conditions for one year.

[0063] (4) Take out the filler from the rooftop on the 1st of each month, dry it and then conduct sieving. The results of previous studies show that when the particles are too fine, the contour recognition error is relatively large. And considering that fine particles are generally more stable, it is recommended to use 5 mm as the dividing line, and the contour analysis is carried out for particles larger than 5 mm.

[0064] (5) Use a spraying device to wash the filler particles to remove surface impurities, enhance the color development of the granular material, and achieve more accurate recognition of the contour features.

[0065] (6) Random sampling. Divide the fillers in the 5 - 10 mm, 10 - 20 mm, and 20 - 40 mm particle groups into four equal parts, and randomly select one sample from each equal part, that is, take four parallel samples for each particle group, and record them as GS 5～10 -i-j, GS 10～20 -i-j, GS 20～40 -i-j. Ensure that there are about 100 particles in each sample during the sampling process.

[0066] Note: In GS 5～10- i-j, 5 - 10 mm represents the particle size range; i = 0 - 12 represents the month, j = 1 - 4 represents the number of the sample; GS is the abbreviation of Grain Size. Take GS 5～10 -0-1 as an example, it represents the 1st sample of the 5 - 10 mm particle size range when not weathered.

[0067] (7) Place a whiteboard with a reference scale on the desktop or the ground, fix a high-definition camera directly above it, and adjust the camera angle. Debug the shooting parameters of the camera before shooting to ensure the best shooting effect. During the shooting of the fillers in the same particle size range, the camera position and the camera shooting parameters remain unchanged.

[0068] (8) Take GS 5～10Taking -0-1 as an example, randomly place the filler particles in the sample on the whiteboard in step 4, and the arrangement should ensure that the material distribution is random and the particles do not overlap or contact each other.

[0069] (9) Take photos of each arranged sample to obtain the image of the particle arrangement. After re - mixing the photographed particles, place them in the natural environment for weathering in the next month.

[0070] (10) Use the digital image processing module of Image - Pro Plus (IPP) software to process the images of the particles obtained from the disintegration of soft rock during weathering, and then calculate the relevant evaluation parameters of the soft rock particles. The specific steps are as follows:

[0071] ① Import the photographed photos into Image - Pro Plus (IPP) software. Use the brightness, contrast, and gamma correction controls on the contrast enhancement panel in the software to enhance the image and pre - process the picture. Calibrate the measurement system in the software with the scale on the cardboard to ensure that the actual size and contour features of the filler particles can be measured.

[0072] ② Use the AOI tool to depict the contours of each particle, and generate measurement objects through convert AOI to object. Automatically measure the shape parameters of each particle in the system, such as area (A), perimeter (S), major axis size (L), minor axis size (B), etc., and edit formulas in excel based on the above test results to calculate parameters such as the equivalent diameter (D), abundance (C), roundness (R), shape factor (F), etc. of each particle.

[0073] Note: The area of the circle equal to the projected area of the particle, A is the actual area of the particle;

[0074] B is the minor axis size of the particle, L is the major axis size of the particle;

[0075] A' is the circumscribed circle area of the particle;

[0076] P = πD, P is the circumference of the circle with the same area as the particle, S is the actual circumference of the particle.

[0077] (11) Perform the operations in steps 8 - 10 on GS 5～10 -0-2, 3, 4. Then, the area, perimeter, major axis size, minor axis size, equivalent diameter, abundance, roundness, shape factor, etc. of all particles in four samples of the 5 - 10 mm particle size range under unweathered conditions can be obtained. On this basis, statistical analysis can be carried out on the distribution characteristics and average values of the above - mentioned shape parameters of the filler particles in this particle size range.

[0078] (12) For GS 10～20 -0-1, 2, 3, 4 and GS 20～40 -0-1, 2, 3, 4 eight samples, perform the operations in steps 8 - 11, and the shape parameters and their distribution characteristics of the particles in different particle size ranges of the filler under monthly weathering can be obtained.

[0079] (13) Abundance characterizes the oblateness of particles, roundness characterizes the roundness of particles, and shape factor characterizes the complexity of the particle contour. The closer the three are to 0, the sharper the particles are, and the more stable the filler is; the closer to 1, the rounder the particles are, and the more severely the filler is broken. Study the parameters such as the abundance, roundness, and shape factor of the particles during the weathering and disintegration process of soft rock filler and their stability degree, further determine the characteristic parameters that can best reflect the disintegration state of soft rock filler during the weathering process, and then obtain the evolution characteristics of the shape contours of soft rock filler particles in different grain groups before and after one year of weathering.

[0080] Result verification

[0081] As shown in Table 1 are the output measurement results

[0082] Table 1 Output measurement results

[0083]

[0084] Table 2 shows the correlation coefficients required for the disintegration and fragmentation analysis of soft rock particles calculated based on the output measurement results

[0085] Table 2 Calculate the average value of the evaluation index

[0086]

[0087] Table 3 shows the stability degree values from February to December

[0088] Table 3 Stability degree values

[0089]

[0090] Abundance characterizes the oblateness of particles, roundness characterizes the roundness of particles, and shape factor characterizes the complexity of the particle contour. The closer the three are to 0, the sharper the particles are; the closer to 1, the rounder the particles are. Use the above formula to calculate the correlation degree between the abundance, roundness, shape factor of the particles and their stability degree during the weathering and disintegration process of soft rock filler, and γ i∈(0,1). The closer it is to 0, the lower the correlation degree; the closer it is to 1, the higher the correlation degree. By calculation, the characteristic parameter with the highest correlation degree with the stability degree of soft rock filler is obtained. At this time, the closer this characteristic parameter is to 0, it indicates that the soft rock particles are sharper and the filler is less stable; the closer this characteristic parameter is to 1, it indicates that the soft rock particles are rounder and the filler is more stable, thereby reflecting the weathering and disintegration state of the soft rock filler, and further obtaining the evolution characteristics of the shape profiles of soft rock filler particles in different grain groups before and after one-year weathering.

[0091] As shown in Table 4

[0092] Table 4 Correlation degrees of abundance, roundness, shape factor of particles with their stability degrees

[0093]

[0094] It can be seen from the results in the table that the roundness has the highest correlation degree with the stability degree of soft rock filler, with an average value of 0.9030 and the best evaluation effect; followed by the shape factor, with an average value of 0.7394; the weakest is the abundance, with an average value of 0.6697, and the average correlation degree with roundness differs by 25.8%. Therefore, the roundness has a relatively high correlation degree with the stability degree of soft rock filler. During the weathering process, the roundness of the soft rock increases from small to large, the particle contour gradually approaches a circular shape, and the filler gradually becomes more stable.

[0095] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0096] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0097] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions for implementing the process Figure 1 one process or multiple processes and / or blocks Figure 1 steps for implementing the functions specified in one block or multiple blocks.

[0098] In the present invention, specific embodiments are used to illustrate the principles and implementation manners of the present invention. The description of the above embodiments is only for helping to understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present invention.

[0099] Those of ordinary skill in the art will realize that the embodiments described herein are for helping the reader understand the principles of the present invention, and it should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations that do not depart from the essence of the present invention based on the technical revelations disclosed in the present invention, and these deformations and combinations are still within the protection scope of the present invention.

Claims

1. A method for identifying the evolution characteristics of the shape contour of soft rock filler particles during the weathering process, characterized in that, It includes the following steps: S1. Simulate the weathering process and obtain the contour characteristics of soft rock particles. The specific steps are as follows: S11. Place the soft rock filler in the natural environment. S12. Use the N method in the maximum density curve theory to design the gradation of the soft rock filler. The specific method is as follows: ； Among them, is the passing percentage of aggregate particles through the sieve pore size ; is the sieve pore size; m is the sieve pore; is the maximum particle size of the aggregate; is the shape factor; S13. Put the graded aggregate into the oven for drying. After drying, load the filler into a metal tray. There are holes with a diameter of 2.5 cm at the bottom of the tray, and a plastic sieve with a diameter of 1 mm is covered to facilitate drainage. The filler is evenly distributed and the thickness does not exceed 1 cm. S14. Place the metal tray in the natural environment, and regularly take out the filler in it for drying. Taking 5 mm as the demarcation line, contour analysis is carried out for particles larger than 5 mm. S15. Divide the fillers in the particle size groups of 5 - 10 mm, 10 - 20 mm, and 20 - 40 mm into four equal parts, and randomly take one sample from each equal part, that is, take four parallel samples for each particle size group, and label them as GS 5~10 - i-j ,GS 10~20 - i-j ,GS 20~40 - i-j 。 For each sample, 100 particles are taken for sampling; S16. Set up a reference scale whiteboard, fix a high-definition camera directly above it, adjust the camera angle, and take pictures of the particles in different samples. During the shooting process of the same particle size range of the filler, the camera position and camera shooting parameters remain unchanged, and the arrangement should be random and the materials should not overlap or contact each other. S17. Take pictures of each arranged sample to obtain the particle arrangement image. After taking pictures, remix the particles and put them back into the natural environment for the next cycle of weathering. S2. Randomly group the soft rock particles after simulated weathering. S3. Use digital image processing algorithms to process each group of soft rock particles and calculate the evaluation parameters of the soft rock particles. S4. Obtain the evolution characteristics of the shape contours of soft rock filler particles before and after weathering for different particle groups according to the evaluation parameters calculated in S3.

2. The method for identifying the evolution characteristics of the shape profile of soft rock filler particles during the weathering process according to claim 1, wherein In S3, the digital image processing module of Image-Pro Plus software is used to process the images of the particles obtained from the disintegration of soft rock during the weathering process, and then the relevant evaluation parameters of the soft rock particles are calculated. The specific method is as follows: S31. Import the taken pictures into Image-Pro Plus software, and use the brightness, contrast, and gamma correction controls on the software's contrast enhancement panel to enhance the images and preprocess the pictures. S32. Use the AOI tool to depict the contours of each particle, and generate measurement objects through convert AOI to object to measure the area, perimeter, major axis size, minor axis size, and shape parameters of each particle. S33. For GS 5~10 -0-2, 3, 4, perform the operations in steps S31 to S32 to obtain parameters such as the area, perimeter, major axis size, minor axis size, equivalent diameter, abundance, roundness, and shape factor of all particles in four samples with a particle size range of 5 to 10 mm under the condition of no weathering effect; S34. For GS 10~20 -0-1, 2, 3, 4 and GS 20~40 -0-1, 2, 3, 4 eight samples, perform the operations in steps S31 - S33, and the shape parameters and their distribution characteristics of the particles in different particle size ranges of the filler under weathering action in each cycle can be obtained.

3. The method for identifying the evolution characteristics of the particle shape profile of soft rock filler during weathering according to claim 2, characterized in that, The calculation methods of the equivalent diameter D, abundance C, roundness R, and shape factor F parameters in S32 are as follows: , the circular area equal to the projected area of the particle, is the actual area of the particle; , is the short-axis dimension of the particle, is the long-axis dimension of the particle; , , is the area of the circumscribed circle of the particle; , , is the circumference of the equal - area circle of the particle, is the actual circumference of the particle.

4. A method for identifying the evolution characteristics of the shape profile of soft rock filler particles during the weathering process according to claim 1, characterized in that S4 specifically includes: S41. Starting from the second cycle, use the evaluation parameters of the soft rock particles in each cycle to compare with the evaluation parameters of the soft rock particles in the previous cycle to obtain the stability degree of the soft rock. S42. Use the grey relational analysis method to calculate the relationship between the shape parameters of the soft rock filler after weathering and its corresponding stability degree to obtain the correlation coefficient.

5. A method for identifying the evolution characteristics of the shape profile of soft rock filler particles during the weathering process according to claim 4, characterized in that In S41, the calculation method of the stability degree of the soft rock is as follows: ； wherein, is the degree of association; is the disintegration resistance index of the soft rock filler; is the month.

6. A method for identifying the evolution characteristics of the shape profile of soft rock filler particles during the weathering process according to claim 4, wherein The specific steps of the grey relational analysis method in S42 are as follows: S421. Take the stability degree as the reference sequence, and the abundance, roundness, and shape factor as the comparison sequences to calculate the correlation coefficient. S422. Calculate the average value of the correlation coefficients, and use the obtained average value to represent the degree of correlation between the comparison sequence and the reference sequence.

7. A method for identifying the evolution characteristics of the shape profile of soft rock filler particles during the weathering process according to claim 6, characterized in that The calculation method of the correlation coefficient in S421 is as follows: ； Among them, is the reference sequence, is the comparison sequence, is the period, is the discrimination coefficient, is the absolute value of the difference between the reference sequence and the comparison sequence.

8. A method for identifying the evolution characteristics of the shape profile of soft rock filler particles during the weathering process according to claim 6, characterized in that, The calculation method of the average value of the correlation coefficient in S422 is as follows: ； Among them, is the total number of samples.

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