CN113129275A - Rock-soil mass material-based digital image three-dimensional structure characterization method - Google Patents
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- 239000000463 material Substances 0.000 title claims abstract description 19
- 239000002689 soil Substances 0.000 title claims abstract description 13
- 238000012512 characterization method Methods 0.000 title claims description 20
- 239000011148 porous material Substances 0.000 claims abstract description 50
- 238000000034 method Methods 0.000 claims abstract description 23
- 238000009826 distribution Methods 0.000 claims abstract description 10
- 238000001914 filtration Methods 0.000 claims abstract description 5
- 230000011218 segmentation Effects 0.000 claims abstract description 5
- 238000005429 filling process Methods 0.000 claims description 9
- 239000011800 void material Substances 0.000 claims description 8
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 abstract description 5
- 239000013077 target material Substances 0.000 abstract description 4
- 238000011160 research Methods 0.000 abstract description 3
- 238000012545 processing Methods 0.000 abstract description 2
- 238000004364 calculation method Methods 0.000 description 4
- 238000002591 computed tomography Methods 0.000 description 3
- 230000007547 defect Effects 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 230000001788 irregular Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000003245 coal Substances 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000010884 ion-beam technique Methods 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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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
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- G—PHYSICS
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10081—Computed x-ray tomography [CT]
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
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Abstract
The invention discloses a rock-soil body material-based digital image three-dimensional structure representation method, and relates to the technical field of three-dimensional image processing. And reconstructing a three-dimensional model by adopting the computer microscopic digital image of the rock-soil mass material and measuring and calculating the distribution conditions of pores with 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 images along the normal direction of the binary images in the original sample to obtain a binary three-dimensional model; calculating the space distance based on the binary three-dimensional model; selecting a sphere with a proper radius to fill the pore by taking a pore voxel corresponding to the maximum value in the distance values as a sphere center; recording the radius of the used sphere, and updating the three-dimensional model until all pores are filled; and summarizing and counting the radius value and the number of the spheres to generate a visual result. The method has stable and reliable measuring and calculating results 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 rock-soil body material-based digital image three-dimensional structure characterization method.
Background
In the related field of capital construction, the rock-soil mass material is widely applied in the production and is also the key point of scientific research. The pore network randomly and widely distributed in the material determines the pore size distribution and the connectivity of the material, and further influences important technical indexes such as permeability, water retention and the like, so that the method has important significance in scientifically and efficiently measuring, calculating and representing the three-dimensional structure of the pore network. The three-dimensional structures of the current measurement and characterization rock-soil body are roughly divided into two types: one is based on physical actual measurement methods, such as mercury intrusion method, neutron scattering and the like, but the methods have the defects of narrow applicable scale range, sample damage, non-uniform and non-standard test operation flow and the like; the other method is to measure and calculate based on a computer digital image, such as Computed Tomography (CT), Scanning Electron Microscope (SEM) focused ion beam, scanning electron microscope (FIB-SEM) dual beam system, etc., but in the existing research, a two-dimensional calculation method is mostly used for measuring and calculating, and only a two-dimensional plane is represented, and defects such as irregular pore representation misalignment exist; and a small amount of three-dimensional calculation methods are adopted, the characterization results of different two-dimensional plane measurement and calculation 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 three-dimensional pore space with different radiuses is described and characterized based on the digital image, the characterization error is increased to a certain extent due to the characteristic of digital image rasterization and the error between the calculated volume and the actual volume based on the digital image.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a new characterization method, which is used for measuring and calculating the distribution condition of a characterized pore structure in a three-dimensional space based on a rock-soil body material computer digital image reconstruction three-dimensional model and solving the problem that the three-dimensional pore can not be accurately and reliably measured by the existing method; meanwhile, in order to overcome the rasterization characteristics of the digital image, the representation schemes of spheres with different radiuses are optimized so as to greatly reduce the volume error when describing the spheres with different radiuses. 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 purpose, the technical scheme adopted by the invention is as follows: a rock-soil mass material digital image-based three-dimensional structure characterization method comprises the following steps:
s1: acquiring a computer digital image of a material to be detected, and acquiring a clear noiseless binary image only containing pores and a skeleton by adopting a threshold segmentation and image filtering method, wherein 1 represents a skeleton region, and 0 represents a pore region;
s2: superposing the binary images obtained in the step S1 along the normal direction of the binary images in the original sample to obtain a binary three-dimensional model with the same length and width as the collected images and the same height as the number of the images;
s3: calculating the spatial distance based on the binary three-dimensional model, calculating the distance between each pore voxel and the nearest skeleton voxel, and marking the distance value at the corresponding position of the pore voxel, namely acquiring a three-dimensional array which has the same size with the original model and each element representing the distance between the corresponding position of the original three-dimensional model and the nearest skeleton voxel;
s4: filling the pore by taking the pore voxel corresponding to the maximum value in the marked distance values as the center of a sphere and taking the maximum value as the radius of the sphere; if the ball used for filling does not interfere with the existing framework region, filling is finished; if the filled ball interferes with the existing framework region, the position of the center of the ball is kept still, the radius is continuously reduced until the ball does not interfere with the existing framework region, and then filling is finished.
S5: recording the radius of the ball used when the filling is finished in S4, updating the three-dimensional model, and combining the area covered by the ball for filling and the existing skeleton area 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; summarizing the radiuses and the corresponding numbers of the spheres used in the filling process, counting the percentage of the respective volumes of the spheres with different radiuses in the total pore area volume, and converting the actual distances in the three-dimensional model in the corresponding display of the different radiuses according to the scaling of the original digital image.
Further, based on the size of the ball used in the filling process, summarizing the size and the corresponding number of all the balls used for filling, and converting the voxel distance into an actual distance to obtain a three-dimensional structure representation result; the unit conversion method is as follows:
r＝ri×L
wherein r isiThe radius is a certain size of a filling sphere, L is the length of a 1 voxel in a mesoscopic digital image acquired by S1 corresponding to the reality, r is the radius value of a sphere with the radius in the three-dimensional reconstruction model in the reality, and the unit is consistent with L;
the method for calculating the distribution frequency of pores with different sizes in the three-dimensional structure comprises the following steps:
wherein, PiRefers to the distribution frequency, r, of pores of that size in a three-dimensional structureiRefers to a certain size, n, of the ball for fillingiRefers to the number of balls of that size, V, during the filling processiRefers to the total volume, V, of the ball filling of that sizeglobalRefers to the total volume of the void region.
Further, in step S4, in order to reduce the volume error based on the spheres with different radii of the digital image and the reality, the sphere characterization schemes with different radii are modified: calculating the number n of voxels occupied by a sphere with the radius r in the digital image, and combining the voxel with the center of the sphere and the nearest n-1 voxels to obtain 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, [. sup. ] denoting rounding down.
Has the advantages that: the method provided by the invention can measure and calculate the real three-dimensional pore structure of the characterization target material, but the existing method is mostly limited to a two-dimensional plane, and the characterization result is difficult to be close to the real situation. Meanwhile, the measuring range is comprehensive, and the method can be suitable for the irregular pores such as 'ink bottle type' and the like. And the representation scheme of spheres with different radiuses is improved, so that the error between the pore volumes with different radiuses and the reality caused by the adoption of digital image rasterization is greatly reduced, and the accuracy is improved. Compared with the existing experimental means, the method can quickly 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 of a three-dimensional reconstruction;
FIG. 3 is a three-dimensional structure characterization measurement;
fig. 4 is a visual filling result.
Detailed Description
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
The invention relates to a rock-soil mass material-based digital image three-dimensional structure characterization method, which has a specific flow shown in figure 1 and comprises the following steps:
s1: and (6) obtaining a binary image. Acquiring a computer digital image of a material to be detected, and acquiring a clear noiseless binary image only containing pores and a skeleton by adopting a threshold segmentation and image filtering method, wherein 1 represents a skeleton region, and 0 represents a pore region; the computer digital image is obtained by acquiring images of 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 this embodiment, 500 × 500 voxels are selected to collect a microscopic image of a certain coal sample by FIB-SEM, and binary images are obtained by using methods such as threshold segmentation and median filtering.
S2: and (4) three-dimensional reconstruction. Superposing the binary images obtained in the step S1 along the normal direction of the binary images in the original sample to obtain a binary three-dimensional model with the same length and width as the collected images and the same height as the number of the images; in the stack of the three-dimensional model, 1 represents a skeleton region and 0 represents a pore region. In this embodiment, 500 binary images are sequentially superimposed along the normal direction of the image, so as to obtain 500 × 500 array stacks, i.e., a three-dimensional reconstruction model of the material to be measured, as shown in fig. 2.
S3: and calculating the space distance. Calculating the spatial distance based on the binary three-dimensional model, calculating the distance between each pore voxel and the nearest skeleton voxel, and marking the distance value at the corresponding position of the pore voxel, namely acquiring a three-dimensional array which has the same size with the original model and each element representing 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):
wherein x isi,yi,ziRepresenting measured pore voxels, x1,y1,z1Representing the skeleton voxel closest thereto, DiRepresenting the distance to its nearest skeletal voxel.
S4: and (6) filling. Filling the pore by taking the pore voxel corresponding to the maximum value in the marked distance values as the center of a sphere and taking the maximum value as the radius of the sphere; if the ball used for filling does not interfere with the existing skeleton region, namely the ball does not cover any skeleton voxel, the filling is finished; if the filled ball interferes with the existing skeleton area, namely the ball covers a certain skeleton voxel, the position of the center of the ball is kept still, the radius is continuously reduced until the ball does not interfere with the existing skeleton area, and then filling is finished.
The characterization scheme of spheres with different radii is as follows: calculating the number n of voxels occupied by a sphere with the radius r in a digital image, and combining the voxel with the center of the sphere and the nearest n-1 voxels to obtain 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, [. sup. ] denoting rounding down.
S5: recording the radius of the ball used when the filling is finished in S4, updating the three-dimensional model, and combining the area covered by the ball for filling and the existing skeleton area 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 the element values in the stack are all 1); summarizing the radiuses and the corresponding numbers of the spheres used in the filling process, counting the percentage of the respective volumes of the spheres with different radiuses in the total pore area volume, and converting the actual distances in the three-dimensional model in the corresponding display of the different radiuses according to the scaling of the original digital image.
And (3) summarizing statistics and generating a visual result: the three-dimensional structure representation result is the pores with different sizes and the corresponding distribution frequency in the three-dimensional structure. The visual filling result is that the original pore areas filled by the spheres with different sizes are displayed in different colors after the filling is finished. And summarizing the sizes and the corresponding numbers of all the balls for filling based on the sizes of the balls for recording in the filling process, thereby finishing a three-dimensional structure characterization result (such as figure 3) and a visual filling result (such as figure 4) after converting the voxel distance into an actual distance. In the present embodiment, the unit conversion method is as follows:
r＝ri×L
wherein r isiThe radius is a certain size of a filled sphere, L is a length of a 1 voxel in the mesoscopic digital image acquired at S1 corresponding to the real world, r is a radius value of a sphere with the radius in the three-dimensional reconstruction model in the real world, and the unit is consistent with L.
The method for calculating the distribution frequency of pores with different sizes in the three-dimensional structure comprises the following steps:
wherein r isiRefers to a certain size, n, of the ball for fillingiRefers to the number of balls of that size, V, during the filling processiRefers to the total volume, V, of the ball filling of that sizeglobalTotal volume of finger hole area, PiRefers to the frequency of distribution of pores of that size in a three-dimensional structure.
The foregoing is a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (3)
1. A rock-soil mass material digital image-based three-dimensional structure characterization method is characterized by comprising the following steps of: the method comprises the following steps:
s1: acquiring a computer digital image of a material to be detected, and acquiring a clear noiseless binary image only containing pores and a skeleton by adopting a threshold segmentation and image filtering method, wherein 1 represents a skeleton region, and 0 represents a pore region;
s2: superposing the binary images obtained in the step S1 along the normal direction of the binary images in the original sample to obtain a binary three-dimensional model with the same length and width as the collected images and the same height as the number of the images;
s3: calculating the spatial distance based on the binary three-dimensional model, calculating the distance between each pore voxel and the nearest skeleton voxel, and marking the distance value at the corresponding position of the pore voxel, namely acquiring a three-dimensional array which has the same size with the original model and each element representing the distance between the corresponding position of the original three-dimensional model and the nearest skeleton voxel;
s4: filling the pore by taking the pore voxel corresponding to the maximum value in the marked distance values as the center of a sphere and taking the maximum value as the radius of the sphere; if the ball used for filling does not interfere with the existing framework region, filling is finished; if the filled ball interferes with the existing framework region, keeping the position of the center of the ball still, and continuously reducing the radius until the ball does not interfere with the existing framework region, and finishing filling;
s5: recording the radius of the ball used when the filling is finished in S4, updating the three-dimensional model, and combining the area covered by the ball for filling and the existing skeleton area 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; summarizing the radiuses and the corresponding numbers of the spheres used in the filling process, counting the percentage of the respective volumes of the spheres with different radiuses in the total pore area volume, and converting the actual distances in the three-dimensional model in the corresponding display of the different radiuses according to the scaling of the original digital image.
2. The rock-soil mass material digital image-based three-dimensional structure characterization method according to claim 1, wherein: based on the size of the ball used in the filling process, summarizing the size and the corresponding number of all the balls used for filling, and converting the voxel distance into an actual distance to obtain a three-dimensional structure representation result; the unit conversion method is as follows:
r＝ri×L
wherein r isiThe radius is a certain size of a filling sphere, L is the length of a 1 voxel in a mesoscopic digital image acquired by S1 corresponding to the reality, r is the radius value of a sphere with the radius in the three-dimensional reconstruction model in the reality, and the unit is consistent with L;
the method for calculating the distribution frequency of pores with different sizes in the three-dimensional structure comprises the following steps:
wherein, PiRefers to the distribution frequency, r, of pores of that size in a three-dimensional structureiRefers to a certain size, n, of the ball for fillingiRefers to the number of balls of that size, V, during the filling processiRefers to the total volume, V, of the ball filling of that sizeglobalRefers to the total volume of the void region.
3. The rock-soil mass material digital image-based three-dimensional structure characterization method according to claim 1 or 2, wherein: in step S4, the sphere with radius r is characterized by: calculating the number n of voxels occupied by a sphere with the radius r in the digital image, and combining the voxel with the center of the sphere and the nearest n-1 voxels to obtain 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, [. sup. ] denoting rounding down.
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| CN115872760A (en) * | 2022-10-24 | 2023-03-31 | 西安鑫垚陶瓷复合材料股份有限公司 | Filling method of strip holes in ceramic matrix composite prefabricated body |
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