CN112233166A - A method for evaluating pore size distribution based on three-dimensional pore space images of porous media - Google Patents
A method for evaluating pore size distribution based on three-dimensional pore space images of porous media Download PDFInfo
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- CN112233166A CN112233166A CN202010954831.8A CN202010954831A CN112233166A CN 112233166 A CN112233166 A CN 112233166A CN 202010954831 A CN202010954831 A CN 202010954831A CN 112233166 A CN112233166 A CN 112233166A
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- 239000011148 porous material Substances 0.000 title claims abstract description 114
- 238000000034 method Methods 0.000 title claims description 16
- 238000004364 calculation method Methods 0.000 claims abstract description 21
- 239000011159 matrix material Substances 0.000 claims abstract description 14
- 238000011156 evaluation Methods 0.000 claims abstract description 12
- QSHDDOUJBYECFT-UHFFFAOYSA-N mercury Chemical compound [Hg] QSHDDOUJBYECFT-UHFFFAOYSA-N 0.000 claims abstract description 5
- 229910052753 mercury Inorganic materials 0.000 claims abstract description 5
- 238000012360 testing method Methods 0.000 claims abstract description 5
- 238000002459 porosimetry Methods 0.000 claims abstract 2
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- 238000003384 imaging method Methods 0.000 description 1
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Abstract
本发明公开一种基于多孔介质三维孔隙空间图像的孔径分布评估方法，所述孔径分布评估方法类比压汞法的测试原理，利用离散区间内部预定义的不同半径尺寸的孔隙球体，对真实孔隙空间进行填充，直至将孔隙完全填充，然后，对孔隙空间内部已填充的球体体积进行统计计算分析，进而获得孔径分布信息，计算步骤包括：定义离散三维图像中孔隙几何形状；原始三维图像矩阵的填充；最大孔隙半径值的计算；孔隙区域的标记；孔隙占比分数统计计算。本发明孔径分布评估方法计算结果与理论值的相符度高，精准的对多孔介质的孔径分布信息进行提取，通过逻辑算法，能够快速标记出孔隙区域，执行速度快，标记效率高。
The invention discloses a pore size distribution evaluation method based on a three-dimensional pore space image of a porous medium. The pore size distribution evaluation method is analogous to the testing principle of mercury porosimetry. Filling is performed until the pores are completely filled, and then, statistical calculation and analysis are performed on the volume of the sphere filled in the pore space, and then the pore size distribution information is obtained. The calculation steps include: defining the geometric shape of the pores in the discrete 3D image; filling the original 3D image matrix ; Calculation of the maximum pore radius value; Marking of the pore area; Statistical calculation of the proportion of pores. The calculation result of the pore size distribution evaluation method of the present invention has a high degree of agreement with the theoretical value, accurately extracts the pore size distribution information of the porous medium, and can quickly mark the pore area through a logical algorithm, with fast execution speed and high marking efficiency.
Description
Technical Field
The invention relates to a pore size distribution evaluation method, in particular to a pore size distribution evaluation method based on a three-dimensional pore space image of a porous medium.
Background
Thanks to the rapidly developing digital microscopic imaging techniques (CT and FIB/SEM), the microscopic three-dimensional pore structure inside the porous media material is visualized. Based on the three-dimensional pore structure image, corresponding pore size distribution information can be directly extracted. The existing algorithm is mainly similar to the mercury intrusion testing principle, and calculates the pore diameter distribution by executing different types of distance transformation (Euclidean distance or chessboard distance transformation), however, due to the discrete nature of the digital image and the lack of clear and definite definition of pore geometry, the accuracy of the calculation result is poor in some cases, and besides, the execution efficiency of the existing algorithm is low for three-dimensional large-scale images.
Disclosure of Invention
The invention aims to provide a pore size distribution evaluation method based on a three-dimensional pore space image of a porous medium
The purpose of the invention can be realized by the following technical scheme:
a pore size distribution evaluation method based on a porous medium three-dimensional pore space image is similar to a mercury intrusion method test principle, and comprises the following specific calculation steps of filling real pore spaces by utilizing pore spheres with different predefined radius sizes in a discrete interval until the pores are completely filled, and then carrying out statistical calculation and analysis on the filled sphere volumes in the pore spaces to further obtain pore size distribution information:
s1, defining the geometrical shape of the pore in the discrete three-dimensional image;
s2, filling an original three-dimensional image matrix;
s3, calculating a maximum pore radius value;
s4, marking of pore regions;
and S5, statistically calculating the pore ratio fraction.
Further, the step S1 predefines spheres of different radius sizes according to a sphere formula by assuming a sphere of pore geometry in a three-dimensional discrete space.
Further, in order to prevent the three-dimensional image matrix from being read out beyond the boundary in the subsequent calculation in step S2, the size of the original three-dimensional image matrix is first expanded and filled.
Further, the expansion size is equal to the size of the three-dimensional image matrix in the same direction, and all filling values of the filling operation are selected as pore pixels.
Further, the step S3 is to traverse the pore pixel points in the three-dimensional image, and at each pore position, fill the discrete pore spheres with different radii that have been predefined previously, to find the sphere with the largest radius size that can be placed at the position, and record and store the radius value.
Further, in step S4, after obtaining the sphere with the maximum radius size that can be placed at each pore pixel position in the three-dimensional image, traversing the pore pixels in the image again, and marking the pixel points that can be covered by the maximum sphere at each position, where the marking value is the corresponding maximum radius size value.
Furthermore, the marking value follows a principle of priority of a larger marking value in the marking process, namely if the aperture radius value to be marked subsequently is larger, the previously marked aperture radius value is replaced and updated, otherwise, the original marking value is maintained unchanged.
Further, in step S5, the marked three-dimensional image is used as a research object, the number of pixel points having different pore radius mark values inside the three-dimensional image is respectively counted to obtain the corresponding ratio, and finally the pore size distribution information of the real pore structure image is obtained.
The invention has the beneficial effects that:
1. the method for evaluating the pore size distribution has high conformity of the calculation result and the theoretical value, and accurately extracts the pore size distribution information of the porous medium;
2. the aperture distribution evaluation method can rapidly mark the aperture area through a logic algorithm, and has high execution speed and high marking efficiency.
Drawings
The invention will be further described with reference to the accompanying drawings.
FIG. 1 is a schematic diagram of the discrete sphere construction of the present invention;
FIG. 2 is a schematic of an aperture pixel of the present invention;
FIG. 3 is a schematic diagram of the logic algorithm for void region marking of the present invention;
FIG. 4 is a schematic illustration of the pore size distribution of the present invention;
FIG. 5 is a schematic diagram of the aperture frequency of a pixel of the present invention;
FIG. 6 is a schematic diagram of the aperture frequency of a pixel of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
A pore size distribution evaluation method based on a porous medium three-dimensional pore space image is based on a testing principle of a mercury intrusion method, and comprises the following specific calculation steps of filling real pore space by utilizing pore spheres with different predefined radius sizes in a discrete interval until pores are completely filled, and then carrying out statistical calculation analysis on the volume of the filled spheres in the pore space to further obtain pore size distribution information:
s1, defining the pore geometry in the discrete three-dimensional image: assuming that the geometric shape of the pore space in the three-dimensional discrete space is a sphere, predefining the spheres with different radius sizes according to a sphere formula, wherein the calculation formula is as follows:
(x-a)2+(y-b)2+(z-c)2≤R2
wherein the X, Y, Z variables are each integers;
a series of discrete spheres with different radii are established according to the formula, as shown in fig. 1, the square values of the radius R in fig. 1 are 0, 1, 2:
s2, filling of an original three-dimensional image matrix: in order to prevent the three-dimensional image matrix from being read out from the boundary, the size of the original three-dimensional image matrix is expanded and filled, wherein the expanded size is equal to the size of the three-dimensional image matrix in the same direction, and the filling values are all selected as pore pixels, as shown in fig. 2, wherein 0 represents a pore, and 1 represents a matrix:
s3, calculation of maximum pore radius value: traversing pore pixel points in the three-dimensional image, filling discrete pore spheres with different predefined radiuses at each pore position successively to find a sphere with the maximum radius size which can be placed at the position, and recording and storing the radius value;
s4, labeling of pore region: after obtaining a sphere with the maximum radius size which can be placed at each pore pixel position in the three-dimensional image, traversing the pore pixels in the image again, and marking pixel points which can be covered by the maximum sphere at each position, wherein the marking value is the corresponding maximum radius size value;
in the marking process, a principle of priority of a larger marking value is followed, namely if the subsequent pore radius value to be marked is larger, the previously marked pore radius value is replaced and updated, otherwise, the original marking value is maintained unchanged, and the marking process is as shown in fig. 3;
s5, statistical calculation of pore ratio fraction: taking the marked three-dimensional image as a research object, respectively counting the number of pixel points with different pore radius mark values in the three-dimensional image to obtain corresponding proportion, and finally obtaining the aperture distribution information of the real pore structure image.
Example 1
Selecting an artificially synthesized porous medium material with known pore size distribution information, and verifying the accuracy of the algorithm, wherein the method specifically comprises the following steps:
p1, artificially synthesized porous medium material and pore size distribution thereof, as shown in fig. 4 and 5;
p2, comparing the calculation results of the algorithm and the existing algorithm (the Munch algorithm and the Yang algorithm) with theoretical values respectively, as shown in FIG. 6, and verifying the results to show that the calculation result of the aperture distribution of the algorithm is better consistent with the theoretical values, while the existing algorithm and the theoretical values have larger deviation in the two aspects of the aperture interval range and the corresponding volume ratio, and the algorithm can accurately extract the aperture distribution information of the porous medium.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.
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| CN112967378A (en) * | 2021-03-03 | 2021-06-15 | 安徽理工大学 | Rapid random reconstruction method for large-size pore crack structure in porous medium |
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