CN113129275B - Three-dimensional structure characterization method based on rock-soil mass material digital image - Google Patents
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- 238000012512 characterization method Methods 0.000 title claims abstract description 25
- 239000000463 material Substances 0.000 title claims abstract description 17
- 239000002689 soil Substances 0.000 title claims abstract description 11
- 239000011148 porous material Substances 0.000 claims abstract description 51
- 238000000034 method Methods 0.000 claims abstract description 20
- 238000009826 distribution Methods 0.000 claims abstract description 10
- 238000001914 filtration Methods 0.000 claims abstract description 5
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- 238000004364 calculation method Methods 0.000 claims description 8
- 238000005429 filling process Methods 0.000 claims description 8
- 239000011800 void material Substances 0.000 claims description 6
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- 230000001788 irregular Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- QSHDDOUJBYECFT-UHFFFAOYSA-N mercury Chemical compound [Hg] QSHDDOUJBYECFT-UHFFFAOYSA-N 0.000 description 1
- 229910052753 mercury Inorganic materials 0.000 description 1
- 238000001956 neutron scattering Methods 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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Abstract
The invention discloses a three-dimensional structure characterization method based on a rock-soil mass material digital image, and relates to the technical field of three-dimensional image processing. Reconstructing a three-dimensional model by adopting a rock-soil mass material computer microscopic digital image, and calculating pore distribution conditions of different sizes to represent the three-dimensional pore structure of the target material. Acquiring a computer digital image of a material to be detected, and acquiring a binary image by adopting a threshold segmentation and image filtering method; superposing the binary image along the normal direction of the binary image in the original sample to obtain a binary three-dimensional model; calculating a space distance based on the binary three-dimensional model; taking a pore voxel corresponding to the maximum value in the distance values as a sphere center, and selecting a sphere with a proper radius to fill the pore; recording the radius of the ball, and updating the three-dimensional model until all pores are filled; and summarizing the radius value and the number of the statistical balls to generate a visual result. The method has stable and reliable measuring and calculating result and wide application range, and can provide powerful support for microscopic research of target materials.
Description
Technical Field
The invention relates to the technical field of three-dimensional image processing, in particular to a three-dimensional structure characterization method based on a rock-soil mass material digital image.
Background
In the related field of capital construction, the method is widely applied to the production of various rock-soil mass materials and is also the key point of scientific research. The pore network which is randomly and widely distributed in the material determines the pore size distribution and the connectivity of the material, so that important technical indexes such as permeability, water retention and the like are affected, and therefore, the method for scientifically and efficiently measuring and calculating and representing the three-dimensional structure of the pore network has important significance. The three-dimensional structure of the rock-soil body is roughly divided into two types by current measurement and characterization: the method is based on a physical actual measurement method, such as a mercury indentation method, neutron scattering and the like, but has the defects of narrow applicable scale range, damaged samples, non-uniform and standard test operation flow and the like; another type of method is based on computer digital image for measurement and calculation, such as computer tomography (Computed Tomography, CT), scanning electron microscope (scanning electron microscope, SEM) focused ion beam and scanning electron microscope dual-beam system (FIB-SEM), but in the existing research, two-dimensional calculation method is mostly adopted for measurement and calculation, and only two-dimensional plane characterization is applicable, and the defects of irregular pore characterization misalignment and the like exist; the three-dimensional calculation method is adopted in a small amount, the measurement and characterization results of different two-dimensional planes are simply accumulated, the difference between the characterization results and the actual situation is large, and the three-dimensional pore structure of the target material cannot be truly characterized. In addition, when the description of the three-dimensional pores with different radiuses is characterized based on the digital image, errors exist in the measurement volume and the actual volume based on the characteristics of digital image rasterization, and the characterization errors are increased to a certain extent.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a novel characterization method, which realizes measurement and characterization of pore structure distribution conditions in a three-dimensional space based on a three-dimensional model reconstructed by a rock-soil mass material computer digital image and solves the problem that the prior method can not accurately and reliably measure three-dimensional pores; meanwhile, in order to overcome the rasterization characteristic of the digital image, the characterization schemes of spheres with different radiuses are optimized, so that the volume error when spheres with different radiuses are described is greatly reduced. The measuring and calculating result is stable and reliable, the application range is wide, and powerful technical support can be provided for other subsequent works.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows: a three-dimensional structure characterization method based on a rock-soil mass material digital image comprises the following steps:
S1: acquiring a computer digital image of a material to be detected, and acquiring a binary image only containing clear noise-free points of pores and a framework by adopting a threshold segmentation and image filtering method, wherein 1 represents a framework region, and 0 represents a pore region;
S2: superposing the binary image obtained in the step S1 along the normal direction of the binary image in the sample to obtain a binary three-dimensional model with the same length and width as the acquired image and the same height as the number of the images;
S3: calculating the distance between each pore voxel and the nearest skeleton voxel based on the binary three-dimensional model, and marking the distance value at the corresponding position of the pore voxel, namely obtaining a three-dimensional array which is consistent with the original model in size and in which each element represents the distance between the corresponding position of the original three-dimensional model and the nearest skeleton voxel;
S4: filling the pores by taking the pore voxel corresponding to the maximum value in the marked distance value as a sphere center and taking the sphere with the maximum value as a radius; if the balls used for filling do not interfere with the existing skeleton area, filling is completed; if the filled ball interferes with the existing skeleton region, the position of the ball center is kept motionless, the radius is continuously reduced until the ball does not interfere with the existing skeleton region, and then the filling is completed.
S5: recording the radius of the ball used when the filling is completed S4, updating the three-dimensional model, and combining the area covered by the filling ball with the existing skeleton area to be used as a new skeleton area; the unfilled void region remains as void region;
S6: repeating S4-S5 on the updated three-dimensional model until all pores of the three-dimensional model are filled; and summarizing the radius and the corresponding number of the spheres used in the filling process, counting the percentage of the respective volumes of the spheres with different radii to the total pore area volume, and then converting the actual distances in the corresponding display of different radii in the three-dimensional model according to the scaling of the original digital image.
Further, based on the sizes of balls used in the filling process, summarizing the sizes and the corresponding numbers of all the balls used in the filling process, and converting the voxel distance into the actual distance to obtain a three-dimensional structure characterization result; the unit conversion method is as follows:
r＝ri×L
Wherein r i is a certain size of the filling sphere, L is a length of 1 voxel corresponding to reality in the mesoscopic digital image acquired by S1, r is a radius value of the sphere with the radius in reality in the three-dimensional reconstruction model, and the unit is consistent with L;
the calculation method of the pore distribution frequency of different sizes in the three-dimensional structure is as follows:
Wherein P i refers to the distribution frequency of the size pores in the three-dimensional structure, r i refers to a certain size of the filling balls, n i refers to the number of the size balls in the filling process, V i refers to the total volume of the filling of the size balls, and V global refers to the total volume of the pore area.
Further, in the step S4, to reduce the volume error of spheres with different radii based on the digital image and reality, the sphere characterization schemes with different radii are modified: firstly, calculating the number n of voxels occupied by a sphere with the radius r in a digital image, and then merging the voxel of the sphere center with the nearest n-1 voxels, namely, a representation scheme of the sphere with the radius r in the digital image;
where n is the number of voxels that a sphere of radius r occupies in the digital image, [ x ] represents a downward rounding.
The beneficial effects are that: the method provided by the invention can calculate and represent the real three-dimensional pore structure of the target material, but the existing method is mostly limited to a two-dimensional plane, and the representation result is difficult to be close to the real situation. Meanwhile, the measuring and calculating range is comprehensive, and the method is applicable to special-shaped holes such as ink bottle type holes. And the sphere characterization schemes with different radiuses are improved, so that the errors of pore volumes with different radiuses and reality caused by adopting digital image rasterization are greatly reduced, and the accuracy is improved. Compared with the existing experimental means, the method can rapidly and accurately construct and characterize the real three-dimensional structure for measuring and calculating various scaling scales under the condition of not damaging the sample.
Drawings
FIG. 1 is a flow chart of a characterization method;
FIG. 2 is a schematic representation of three-dimensional reconstruction;
FIG. 3 is a representation of three-dimensional structure measurements;
Fig. 4 is a visual population result.
Detailed Description
The technical scheme of the invention is further described below with reference to the accompanying drawings and examples.
The invention discloses a three-dimensional structure characterization method based on a rock-soil mass material digital image, which specifically comprises the following steps as shown in a figure 1:
S1: and obtaining a binary image. Acquiring a computer digital image of a material to be detected, and acquiring a binary image only containing clear noise-free points of pores and a framework by adopting a threshold segmentation and image filtering method, wherein 1 represents a framework region, and 0 represents a pore region; the computer digital image refers to images with different cross sections in the same normal direction of a sample to be detected by adopting microscopic digital image acquisition technologies such as CT, FIB-SEM and the like. In the embodiment, 500 times 500 voxels are selected, a fine image of a certain coal sample is collected by the FIB-SEM, and a binary image is obtained by adopting methods such as threshold segmentation, median filtering and the like.
S2: and (5) three-dimensional reconstruction. Superposing the binary image obtained in the step S1 along the normal direction of the binary image in the sample to obtain a binary three-dimensional model with the same length and width as the acquired image and the same height as the number of the images; in the stack of the three-dimensional model, 1 represents the skeleton region and 0 represents the pore region. In this embodiment 500 binary images are superimposed in sequence along the normal direction of the images, a 500 x 500 array stack is obtained, i.e. a three-dimensional reconstruction model of the material to be measured, as shown in fig. 2.
S3: and (5) calculating the space distance. Calculating the distance between each pore voxel and the nearest skeleton voxel based on the binary three-dimensional model, and marking the distance value at the corresponding position of the pore voxel, namely obtaining a three-dimensional array which is consistent with the original model in size and in which each element represents the distance between the corresponding position of the original three-dimensional model and the nearest skeleton voxel;
The distance calculation method is shown in formula (1):
Where x i,yi,zi represents the measured aperture voxel, x 1,y1,z1 represents the nearest skeleton voxel, and D i represents the distance from the nearest skeleton voxel.
S4: filling. Filling the pores by taking the pore voxel corresponding to the maximum value in the marked distance value as a sphere center and taking the sphere with the maximum value as a radius; if the ball used for filling does not interfere with the existing skeleton area, namely, the ball is not covered with any skeleton voxel, filling is completed; if the filled ball interferes with the existing skeleton area, namely the ball covers a certain skeleton voxel, the position of the ball center is kept unchanged, the radius is continuously reduced until the ball does not interfere with the existing skeleton area, and then the filling is completed.
Wherein, the characterization scheme of the r spheres with different radiuses is as follows: firstly, calculating the number n of voxels occupied by a sphere with the radius r in a digital image, which is shown in a formula (2), and then merging the voxel where the sphere center is positioned with the nearest n-1 voxels, namely, a representation scheme of the sphere with the radius r in the digital image;
where n is the number of voxels that a sphere of radius r occupies in the digital image, [ x ] represents a downward rounding.
S5: recording the radius of the ball used when the filling is completed S4, updating the three-dimensional model, and combining the area covered by the filling ball with the existing skeleton area to be used as a new skeleton area; the unfilled void region remains a void region.
S6: repeating S4-S5 on the updated three-dimensional model until all pores of the three-dimensional model are filled (the three-dimensional model is all skeleton voxels, and element values in a stack are all 1); and summarizing the radius and the corresponding number of the spheres used in the filling process, counting the percentage of the respective volumes of the spheres with different radii to the total pore area volume, and then converting the actual distances in the corresponding display of different radii in the three-dimensional model according to the scaling of the original digital image.
Summarizing statistics and visualization results and generating: the three-dimensional structure characterization result is that pores with different sizes and corresponding distribution frequencies in the three-dimensional structure. The visual filling result is that the original pore areas filled by spheres with different sizes are displayed in different colors after filling is finished. Based on the sizes of balls used in the filling process, the sizes and the corresponding numbers of all the balls used for filling are summarized, so that three-dimensional structure characterization results (shown in figure 3) and visualized filling results (shown in figure 4) after voxel distance is converted into actual distance are sorted out. In this embodiment, the unit conversion method is as follows:
r＝ri×L
Wherein r i is a certain size of the filling sphere, L is a length of 1 voxel corresponding to reality in the mesoscopic digital image acquired by S1, r is a radius value of the sphere with the radius in reality in the three-dimensional reconstruction model, and the unit is consistent with L.
The calculation method of the pore distribution frequency of different sizes in the three-dimensional structure is as follows:
Where r i denotes a certain size of the filling balls, n i denotes the number of the size balls during filling, V i denotes the total volume of the filling of the size balls, V global denotes the total volume of the pore area, and P i denotes the distribution frequency of the size pores in the three-dimensional structure.
While the foregoing is directed to the preferred embodiments of the present invention, it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (1)
1. A three-dimensional structure characterization method based on a rock-soil mass material digital image is characterized by comprising the following steps: the method comprises the following steps:
S1: acquiring a computer digital image of a material to be detected, and acquiring a binary image only containing clear noise-free points of pores and a framework by adopting a threshold segmentation and image filtering method, wherein 1 represents a framework region, and 0 represents a pore region;
S2: superposing the binary image obtained in the step S1 along the normal direction of the binary image in the sample to obtain a binary three-dimensional model with the same length and width as the acquired image and the same height as the number of the images;
S3: calculating the distance between each pore voxel and the nearest skeleton voxel based on the binary three-dimensional model, and marking the distance value at the corresponding position of the pore voxel, namely obtaining a three-dimensional array which is consistent with the original model in size and in which each element represents the distance between the corresponding position of the original three-dimensional model and the nearest skeleton voxel;
s4: filling the pores by taking the pore voxel corresponding to the maximum value in the marked distance value as a sphere center and taking the sphere with the maximum value as a radius; if the balls used for filling do not interfere with the existing skeleton area, filling is completed; if the filled ball interferes with the existing skeleton region, the position of the ball center is kept motionless, the radius is continuously reduced until the ball does not interfere with the existing skeleton region, and then the filling is completed; wherein, sphere characterization scheme with radius r is:
Firstly, calculating the number n of voxels occupied by a sphere with the radius r in a digital image, and then merging the voxel of the sphere center with the nearest n-1 voxels, namely, a representation scheme of the sphere with the radius r in the digital image;
Wherein n is the number of voxels occupied by a sphere of radius r in the digital image, [ x ] represents a downward rounding;
S5: recording the radius of the ball used when the filling is completed S4, updating the three-dimensional model, and combining the area covered by the filling ball with the existing skeleton area to be used as a new skeleton area; the unfilled void region remains as void region;
S6: repeating S4-S5 on the updated three-dimensional model until all pores of the three-dimensional model are filled; summarizing the radius and the corresponding number of spheres used in the filling process, counting the percentage of the respective volumes of spheres with different radii to the total pore area volume, and then converting the actual distances in corresponding displays with different radii in the three-dimensional model according to the scaling of the original digital image;
The voxel distance is converted into the actual distance to obtain a three-dimensional structure characterization result, and the unit conversion method is as follows:
r＝ri×L
Wherein r i is a certain size of the filling sphere, L is a length of 1 voxel corresponding to reality in the mesoscopic digital image acquired by S1, r is a radius value of the sphere with the radius in reality in the three-dimensional reconstruction model, and the unit is consistent with L;
the calculation method of the pore distribution frequency of different sizes in the three-dimensional structure is as follows:
Wherein P i refers to the distribution frequency of the size pores in the three-dimensional structure, r i refers to a certain size of the filling balls, n i refers to the number of the size balls in the filling process, V i refers to the total volume of the filling of the size balls, and V global refers to the total volume of the pore area.
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| CN107817199A (en) * | 2016-09-14 | 2018-03-20 | 中国石油化工股份有限公司 | A kind of construction method of tight sand multi-scale porosity model and application |
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