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CN113129275A - Rock-soil mass material-based digital image three-dimensional structure characterization method - Google Patents

Rock-soil mass material-based digital image three-dimensional structure characterization method Download PDF

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CN113129275A
CN113129275A CN202110346356.0A CN202110346356A CN113129275A CN 113129275 A CN113129275 A CN 113129275A CN 202110346356 A CN202110346356 A CN 202110346356A CN 113129275 A CN113129275 A CN 113129275A
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刘江峰
马士佳
倪宏阳
林远健
李震
孙晨皓
尹乾
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China University of Mining and Technology Beijing CUMTB
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Abstract

本发明公开了一种基于岩土体材料数字图像三维结构表征方法，涉及三维图像处理技术领域。采用岩土体材料计算机细微观数字图像重构三维模型并测算不同尺寸孔隙分布情况来表征目标材料三维孔隙结构。获取待测材料的计算机数字图像，采用阈值分割和图像滤波方法获取二值图像；将二值图像沿其在原样品中的法向方向叠加得到二值三维模型；基于二值三维模型进行空间距离计算；以距离值中最大值对应的孔隙体素为球心，选择合适半径的球体对孔隙进行填充；记录所用球半径，并更新三维模型直至所有孔隙均被填充；汇总统计球半径值和数目，生成可视化结果。本方法测算结果稳定可靠，适用范围广，可为目标材料的细微观研究提供有力支撑。

Figure 202110346356

The invention discloses a three-dimensional structure characterization method based on a digital image of rock and soil materials, and relates to the technical field of three-dimensional image processing. The three-dimensional pore structure of the target material is characterized by reconstructing the three-dimensional model using the computer microscopic digital images of the geotechnical material and measuring the distribution of pores of different sizes. The computer digital image of the material to be tested is obtained, and the binary image is obtained by threshold segmentation and image filtering; the binary image is superimposed along its normal direction in the original sample to obtain a binary 3D model; based on the binary 3D model, the spatial distance is calculated ; Take the pore voxel corresponding to the maximum distance value as the center of the sphere, select a sphere with a suitable radius to fill the pores; record the radius of the sphere used, and update the 3D model until all pores are filled; summarize the sphere radius value and number, Generate visualization results. The calculation results of this method are stable and reliable, and have a wide range of application, which can provide strong support for the microscopic research of target materials.

Figure 202110346356

Description

Rock-soil mass material-based digital image three-dimensional structure characterization method
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:
Figure BDA0003000838670000021
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;
Figure BDA0003000838670000022
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.
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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):
Figure BDA0003000838670000031
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;
Figure BDA0003000838670000032
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:
Figure BDA0003000838670000041
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)

1.一种基于岩土体材料数字图像三维结构表征方法，其特征在于：包括如下步骤：1. a three-dimensional structure characterization method based on rock and soil material digital image, is characterized in that: comprise the steps: S1：获取待测材料的计算机数字图像，采用阈值分割和图像滤波方法获取到仅含孔隙与骨架的清晰无噪点的二值图像，其中1表示骨架区域，0表示孔隙区域；S1: Obtain a computer digital image of the material to be tested, and use threshold segmentation and image filtering to obtain a clear and noise-free binary image containing only pores and skeletons, where 1 represents the skeleton area and 0 represents the pore area; S2：将S1得到的二值图像沿其在原样品中的法向方向叠加，得到一个长宽与采集图像相同、高度与图像数目相等的二值三维模型；S2: superimpose the binary image obtained by S1 along its normal direction in the original sample to obtain a binary three-dimensional model with the same length and width as the collected image and the same height as the number of images; S3：基于二值三维模型进行空间距离计算，计算每个孔隙体素与其最近的骨架体素的距离，并将这一距离值标注在该孔隙体素对应位置，即获取到与原模型尺寸一致且每一元素表示原三维模型对应位置与其最近骨架体素的距离的三维数组；S3: Calculate the spatial distance based on the binary three-dimensional model, calculate the distance between each pore voxel and its nearest skeleton voxel, and mark the distance value at the corresponding position of the pore voxel, that is, the size is consistent with the original model. And each element represents a three-dimensional array of the distance between the corresponding position of the original three-dimensional model and its nearest skeleton voxel; S4：以在标记的距离值中最大值对应的孔隙体素为球心，以该最大值为半径的球体对孔隙进行填充；若填充所用球与现有骨架区域不发生干涉，则填充完成；若填充后球与现有骨架区域发生干涉，则保持球心位置不动，不断缩小半径直至球与现有骨架区域不发生干涉，则填充完成；S4: The pore voxel corresponding to the maximum value in the marked distance value is used as the center of the sphere, and the sphere with the maximum value as the radius is used to fill the pores; if the sphere used for filling does not interfere with the existing skeleton area, the filling is completed; If the ball interferes with the existing skeleton area after filling, keep the position of the center of the sphere unchanged, and continuously reduce the radius until the ball does not interfere with the existing skeleton area, then the filling is completed; S5：记录S4填充完成时所用球半径，并更新三维模型，将填充用球覆盖的区域与现有骨架区域合并作为新的骨架区域；未填充的孔隙区域仍为孔隙区域；S5: Record the radius of the ball used when the filling of S4 is completed, and update the 3D model, and merge the area covered by the filling ball with the existing skeleton area as a new skeleton area; the unfilled pore area is still the pore area; S6：对更新后三维模型重复S4-S5，直至三维模型所有孔隙均被填充；汇总填充过程中所用球体的半径和对应的数目，统计不同半径球各自体积占总孔隙区域体积的百分比，再依据原数字图像缩放比例换算出三维模型中不同半径对应显示中的实际距离。S6: Repeat S4-S5 for the updated 3D model until all pores of the 3D model are filled; summarize the radii and corresponding numbers of spheres used in the filling process, and count the percentages of the respective volumes of spheres with different radii in the total pore area volume, and then based on The scaling ratio of the original digital image is converted into the actual distance in the display corresponding to different radii in the 3D model. 2.根据权利要求1所述的基于岩土体材料数字图像三维结构表征方法，其特征在于：基于填充过程中记录所用球的尺寸，汇总所有填充用球的尺寸及对应数目，将体素距离换算为实际距离后得到三维结构表征结果；单位折算方法如下：2. The three-dimensional structure characterization method based on digital images of rock and soil materials according to claim 1, characterized in that: based on the size of the balls used for recording in the filling process, the size and the corresponding number of all balls used for filling are summarized, and the voxel distance is calculated. The three-dimensional structure characterization result is obtained after conversion to the actual distance; the unit conversion method is as follows: r＝ri×Lr=r i ×L 其中，ri指填充球的某一尺寸，L指S1获取的细观数字图像中1体素对应现实中的长度，r指三维重构模型中该半径的球体在现实中的半径值，单位与L一致；Among them, ri refers to a certain size of the filled sphere, L refers to the length of 1 voxel in the mesoscopic digital image obtained by S1 corresponding to reality, r refers to the radius value of the sphere of this radius in the 3D reconstruction model in reality, unit consistent with L; 三维结构中不同尺寸孔隙分布频率计算方法如下：The calculation method of the distribution frequency of pores of different sizes in the three-dimensional structure is as follows:
Figure FDA0003000838660000011
Figure FDA0003000838660000011
 其中，Pi指该尺寸孔隙在三维结构中的分布频率，ri指填充用球的某一尺寸，ni指填充过程中该尺寸球的数量，Vi指该尺寸球填充的总体积，Vglobal指孔隙区域总体积。Among them, Pi refers to the distribution frequency of pores of this size in the three-dimensional structure, ri refers to a certain size of the spheres used for filling , ni refers to the number of spheres of this size during the filling process, and Vi refers to the total volume filled by spheres of this size, V global refers to the total volume of the pore area. 3.根据权利要求1或2所述的基于岩土体材料数字图像三维结构表征方法，其特征在于：所述步骤S4中，半径为r的球体表征方案为：先计算半径为r的球体在数字图像中其占据的体素数目n，再将球心所在体素及与其最近的n-1个体素合并，即为半径r的球体在数字图像中的表征方案；3. The three-dimensional structure characterization method based on digital images of rock and soil materials according to claim 1 or 2, characterized in that: in the step S4, the characterization scheme of the sphere with radius r is: first calculate the sphere with radius r in The number of voxels it occupies in the digital image is n, and then the voxel where the center of the sphere is located and its nearest n-1 voxel are combined, which is the representation scheme of the sphere of radius r in the digital image;
Figure FDA0003000838660000021
Figure FDA0003000838660000021
 式中，n为半径r的球体在数字图像中其占据的体素数目，[*]表示向下取整。In the formula, n is the number of voxels occupied by a sphere of radius r in the digital image, and [*] means rounded 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
CN116046629A (en) * 2023-01-04 2023-05-02 哈尔滨工业大学 A method for real-time quantitative analysis of field microstructure and three-dimensional reconstruction of multiphase microstructure
CN118447075A (en) * 2024-05-06 2024-08-06 华中科技大学 Method, device, medium and equipment for analyzing pore characteristics in sand particles

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