CN113640326A - Multistage mapping reconstruction method for nano-pore resin-based composite material micro-nano structure - Google Patents
Multistage mapping reconstruction method for nano-pore resin-based composite material micro-nano structure Download PDFInfo
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- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 4
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Abstract
The invention relates to a multistage mapping reconstruction method for a nano-pore resin matrix composite material micro-nano structure, which comprises the following steps: s1: acquiring a two-dimensional CT slice of the composite material, obtaining a two-dimensional slice of a fiber reinforcement structure through numerical processing, and superposing the two-dimensional slice into a fiber three-dimensional structure; s2: identifying the fiber center line and constructing the fiber to accurately obtain the three-dimensional fiber structure of the composite material with a microscopic scale; s3: acquiring a two-dimensional scanning electron microscope picture of a resin matrix, carrying out numerical processing, and mapping the processed micro-morphology feature information into a three-dimensional structure information numerical value set; s4: and constructing a resin matrix at the gap by taking the established three-dimensional fiber structure with the microscopic scale as a frame, thereby realizing the multi-level mapping reconstruction of the nano-pore resin matrix composite material micro-nano structure. By adopting the technical scheme of the invention, the accurate reconstruction of the micro-nano structure of the nano-pore resin matrix composite material can be realized.
Description
Technical Field
The invention relates to the field of composite material microstructure analysis, in particular to a multistage mapping reconstruction method for a nano-pore resin-based composite material micro-nano structure.
Background
The nano-pore resin-based composite material is a complex multi-level structure composite material formed by mutually interpenetrating nano-scale resin aerogel and meso-scale reticular fibers, as shown in figure 1, has the advantages of light weight, reliability, low cost, easiness in molding and processing and the like, and is one of the most common ablation type thermal protection materials for breaking through a thermal barrier environment of a space vehicle. The heat-proof and heat-insulating performance of the nano-pore resin-based composite material is closely related to the multilevel structure of the nano-pore resin-based composite material. Therefore, the micro-nano structure of the nano-pore resin matrix composite material is accurately analyzed, and the method has great significance for further revealing the heat insulation prevention mechanism and the microstructure optimization design of the material.
At present, researchers have mainly reconstructed the three-dimensional structure of composite materials by three methods. The first is a bat model construction method based on computer programming technology, which can satisfy the random characteristics of nanoparticles and fibers, but cannot reflect the real structure of the material. The second method is a material cutting reconstruction method based on a focused ion beam-scanning electron microscope (FIB-SEM) dual-beam technology, but the ion beam energy is too high to damage the structure of the resin-based material, so the method is not suitable for three-dimensional reconstruction of the nanoporous resin-based composite material. The third method is a three-dimensional scanning imaging method based on the Micro/Nano-CT technology, which can effectively reconstruct a fiber structure with a microscopic scale, but due to the limitation of resolution, the reconstructed fiber structures have the phenomena of mutual crossing, adhesion and the like, and the Micro/Nano-CT technology cannot identify a material structure with a nanoscale. Therefore, the existing method can not realize the accurate three-dimensional reconstruction of the complicated multilevel structure of the nano-pore resin-based composite material temporarily.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a multistage mapping reconstruction method of a nano-pore resin-based composite material micro-nano structure, which can be used for carrying out accurate three-dimensional reconstruction on a complex multistage structure composite material.
The purpose of the invention can be realized by the following technical scheme:
a multi-stage mapping reconstruction method for a nano-pore resin-based composite material micro-nano structure is provided, the composite material comprises a nano resin matrix and a fiber reinforcement, and the method comprises the following steps:
s1: acquiring a two-dimensional CT slice of the composite material, obtaining a two-dimensional slice of a fiber reinforcement structure through numerical processing, and superposing the two-dimensional slice into a fiber three-dimensional structure;
s2: accurately obtaining a three-dimensional fiber structure of the composite material in a microscopic scale based on the identification of the fiber central line and the fiber structure;
s3: acquiring a two-dimensional scanning electron microscope picture of a resin matrix, carrying out numerical processing, and mapping the processed micro-morphology feature information into a three-dimensional structure information numerical value set;
s4: and according to the numerical value set obtained in the step S3, constructing a resin matrix at the gap of the three-dimensional fiber structure by taking the established three-dimensional fiber structure with the mesoscale as a frame, thereby realizing the multilevel mapping reconstruction of the micro-nano structure of the nano-pore resin matrix composite material.
Further, the specific step of step S1 includes:
(1) processing the Nano-pore resin-based composite material into a block for testing Micro/Nano-CT;
(2) scanning and slicing the composite material by utilizing a Micro/Nano-CT technology to obtain a slice image;
(3) removing the resin matrix through threshold segmentation by using Mimics software to obtain a two-dimensional CT slice of the fiber structure;
(4) and carrying out filtering noise reduction and threshold segmentation processing on the surface of the fiber based on the numerical result of the two-dimensional CT slice of the fiber structure, and superposing the fiber surface into a three-dimensional fiber structure.
Furthermore, the number of the two-dimensional CT slices is 400-3000, the image resolution is 0.5-10 μm, and the slice image thickness is 0.5-2 μm.
Further, when threshold segmentation is carried out by using Mimics software, a part with the gray scale of 10000-40000 is selected.
Further, the specific step of step S2 includes:
(1) carrying out numerical processing on the three-dimensional structure of the fiber based on MATLAB software, identifying the central axis of each fiber by a machine learning method, and mapping out a fiber central axis distribution model;
(2) and constructing the central axis value of each fiber into smooth fibers with flawless surfaces based on MATLAB software, and establishing a three-dimensional fiber structure without cross and adhesion, thereby accurately obtaining the three-dimensional fiber structure with the microscopic scale of the nano-porous resin matrix composite material.
Further, the specific step of step S3 includes:
(1) acquiring a two-dimensional SEM picture of a nano resin matrix in the nano-pore resin matrix composite material by using a field emission scanning electron microscope;
(2) filtering and denoising and threshold segmentation processing are carried out on the obtained two-dimensional image based on MATLAB software;
(3) and then mapping the processed micro-morphology feature information to a reconstruction algorithm, and accurately establishing a three-dimensional structure information numerical value set of the nano resin matrix.
Furthermore, the number of the scanning electron microscope photos is 100-800, and the magnification is 5000 times to 30000 times.
Furthermore, the molecular weight of the nano resin matrix is 800-1200.
Further, the nanoporous resin-based composite material comprises 20 wt.% to 80 wt.% of a nanocesin matrix and the balance of fiber reinforcement.
Compared with the prior art, the method can accurately obtain the three-dimensional fiber structure without cross and adhesion through the numerical processing of the two-dimensional CT slices, the mapping construction of the fiber central axis model and the numerical construction of the three-dimensional fiber structure. The nano resin aerogel two-dimensional image is subjected to filtering, noise reduction, threshold segmentation and other processing, and then mapped into a three-dimensional structure information numerical value set, so that the nano resin aerogel structure can be accurately analyzed. The established three-dimensional fiber structure with the microscopic scale is used as a frame, and the nano resin aerogel matrix is constructed at fiber gaps according to the set of the mapped three-dimensional structure information numerical values, so that the multistage mapping reconstruction of the nano-pore resin matrix composite material micro-nano structure can be accurately realized.
Drawings
FIG. 1 is a microstructure of a nanoporous resin-based composite material in an example;
FIG. 2 is a flow chart of an embodiment of the present invention;
FIG. 3 is a two-dimensional CT slice of a composite material obtained in the example;
FIG. 4 is a two-dimensional CT slice of a fiber structure obtained in the example;
FIG. 5 is a three-dimensional structure of a fiber structure reconstructed in examples;
fig. 6 is a three-dimensional reconstructed image of the nanoporous resin-based composite obtained in the example.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.
Examples
A multilevel mapping reconstruction method of a nano-pore resin matrix composite micro-nano structure is used for carrying out three-dimensional reconstruction on a needled quartz fiber/phenolic resin composite, wherein the molecular weight of resin in a phenolic resin solution is about 1000, and the mass percentage of solute in the solution is 30%; the volume content of the quartz fiber at the time of impregnation was 60%. The steps are as follows:
step 1: processing the needled quartz fiber/phenolic resin composite material into a block with the size of 2mm multiplied by 2mm for testing Micro/Nano-CT;
step 2: scanning and slicing the composite material by using a Micro/Nano-CT technology to obtain 600 slice images with the image resolution of 1 mu m, and needling a two-dimensional CT slice (shown in figure 3) of the quartz fiber/phenolic resin composite material;
and step 3: using the Mimics software, the resin matrix was removed by threshold segmentation (selecting the section with 18200-37100 gray levels) to obtain two-dimensional CT slices of the fiber structure (as shown in FIG. 4). Carrying out filtering noise reduction and threshold segmentation processing on the surface of the fiber based on the numerical result of the two-dimensional CT slice of the fiber structure, and superposing the fiber surface into a three-dimensional fiber structure;
and 4, step 4: carrying out numerical processing on the three-dimensional structure of the fiber based on MATLAB software, identifying the central axis of each fiber by a machine learning method, and mapping out a fiber central axis distribution model;
and 5: constructing the central axis value of each fiber into smooth fiber with a defect-free surface based on MATLAB software, and establishing a three-dimensional fiber structure without cross and adhesion, thereby accurately obtaining the three-dimensional fiber structure of the microscopic scale of the nanopore resin-based composite material (as shown in figure 5);
step 6: obtaining 200 two-dimensional SEM pictures of the nano resin aerogel in the nano-pore resin matrix composite material with the magnification of 5000-20000 times through a field emission scanning electron microscope;
and 7: and carrying out filtering noise reduction, threshold segmentation and other processing on the obtained two-dimensional image based on MATLAB software. Then mapping the processed micro-morphology feature information to a reconstruction algorithm, and accurately establishing a three-dimensional structure information numerical value set of the nano resin aerogel;
and 8: and (4) according to the structural information numerical value set of the nano resin aerogel obtained in the step (7), constructing a nano resin aerogel matrix at fiber gaps by taking the established three-dimensional fiber structure with the microscopic scale as a frame. Thereby realizing the multi-level mapping reconstruction of the nano-pore resin-based composite material micro-nano structure (as shown in figure 6).
The foregoing is directed to preferred embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow. However, any simple modification, equivalent change and modification of the above embodiments according to the technical essence of the present invention are within the protection scope of the technical solution of the present invention.
Claims (10)
1. A multi-stage mapping reconstruction method for a nano-pore resin-based composite material micro-nano structure is disclosed, wherein the composite material comprises a nano-resin matrix and a fiber reinforcement body, and the method is characterized by comprising the following steps:
s1: acquiring a two-dimensional CT slice of the composite material, obtaining a two-dimensional slice of a fiber reinforcement structure through numerical processing, and superposing the two-dimensional slice into a fiber three-dimensional structure;
s2: accurately obtaining a three-dimensional fiber structure of the composite material in a microscopic scale based on the identification of the fiber central line and the fiber structure;
s3: acquiring a two-dimensional scanning electron microscope picture of a resin matrix, carrying out numerical processing, and mapping the processed micro-morphology feature information into a three-dimensional structure information numerical value set;
s4: and according to the numerical value set obtained in the step S3, constructing a resin matrix at the gap of the three-dimensional fiber structure by taking the established three-dimensional fiber structure with the mesoscale as a frame, thereby realizing the multilevel mapping reconstruction of the micro-nano structure of the nano-pore resin matrix composite material.
2. The method for multilevel mapping reconstruction of a nano-pore resin-based composite material micro-nano structure according to claim 1, wherein the specific step of the step S1 comprises:
(1) processing the Nano-pore resin-based composite material into a block for testing Micro/Nano-CT;
(2) scanning the composite material by utilizing a Micro/Nano-CT technology to obtain a composite material slice image;
(3) removing the resin matrix through threshold segmentation by using Mimics software to obtain a two-dimensional CT slice of the fiber structure;
(4) and carrying out filtering noise reduction and threshold segmentation processing on the surface of the fiber based on the numerical result of the two-dimensional CT slice of the fiber structure, and superposing the fiber surface into a three-dimensional fiber structure.
3. The method for multilevel mapping reconstruction of the micro-nano structure of the nanoporous resin-based composite material according to claim 2, wherein the number of the slice images is 400-3000.
4. The method for multilevel mapping reconstruction of the micro-nano structure of the nanoporous resin-based composite material according to claim 2, wherein the resolution of the slice image is 0.5-10 μm.
5. The method for multilevel mapping reconstruction of the micro-nano structure of the nanoporous resin-based composite material according to claim 2, wherein the thickness of the slice image is 0.5-2 μm.
6. The method for multilevel mapping reconstruction of a nano-pore resin-based composite material micro-nano structure according to claim 1, wherein the specific step of the step S2 comprises:
(1) carrying out numerical processing on the three-dimensional structure of the fiber based on MATLAB software, identifying the central axis of each fiber by a machine learning method, and mapping out a fiber central axis distribution model;
(2) and constructing the central axis value of each fiber into smooth fibers with flawless surfaces based on MATLAB software, and establishing a three-dimensional fiber structure without cross and adhesion, thereby accurately obtaining the three-dimensional fiber structure with the microscopic scale of the nano-porous resin matrix composite material.
7. The method for multilevel mapping reconstruction of a nano-pore resin-based composite material micro-nano structure according to claim 1, wherein the specific step of the step S3 comprises:
(1) acquiring a two-dimensional SEM picture of a nano resin matrix in the nano-pore resin matrix composite material by using a scanning electron microscope;
(2) filtering and denoising and threshold segmentation processing are carried out on the obtained two-dimensional image based on MATLAB software;
(3) and then mapping the processed micro-morphology feature information to a reconstruction algorithm, and accurately establishing a three-dimensional structure information numerical value set of the nano resin matrix.
8. The method for multilevel mapping reconstruction of a micro-nano structure of a nanoporous resin-based composite material according to claim 7, wherein the number of the scanning electron microscope photos is 100-800, and the magnification is 5000-30000 times.
9. The method for multilevel mapping reconstruction of a nano-pore resin-based composite material micro-nano structure according to claim 1, wherein the molecular weight of the nano-resin matrix is 800-1200.
10. The method for multilevel mapping reconstruction of the micro-nano structure of the nanopore resin-based composite material according to claim 1, wherein the nanopore resin-based composite material comprises 20 wt.% to 80 wt.% of a nanometer resin matrix and the balance of a fiber reinforcement.
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Citations (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006202115A (en) * | 2005-01-21 | 2006-08-03 | National Institute Of Advanced Industrial & Technology | Image processing method and image processing program |
| US7317964B1 (en) * | 2003-04-04 | 2008-01-08 | The United States Of America As Represented By The Secretary Of The Air Force | High speed and repeatability serial sectioning method for 3-D reconstruction of microstructures |
| CN102096827A (en) * | 2011-01-18 | 2011-06-15 | 东华大学 | Profiled fiber automatic recognition method based on scale invariability and support vector machine classification |
| CN103971395A (en) * | 2014-05-21 | 2014-08-06 | 安徽工业大学 | Mimicry reconstruction and performance computing method of fiber filter medium structure |
| WO2015024580A1 (en) * | 2013-08-19 | 2015-02-26 | Universidad De Burgos | Computer implemented method to obtain the orientations of fibres inside composite materials using computed tomography scan |
| CN104504193A (en) * | 2014-12-20 | 2015-04-08 | 西安工业大学 | Construction method for taper-changeable composite fiber winding models |
| US20150262417A1 (en) * | 2012-06-26 | 2015-09-17 | Schkuberger Technology Corporation | Method for building a 3d model of a rock sample |
| CN105590338A (en) * | 2015-12-07 | 2016-05-18 | 中国科学院微电子研究所 | Three-dimensional reconstruction method for image of scanning electron microscope |
| CN106202728A (en) * | 2016-07-12 | 2016-12-07 | 哈尔滨工业大学 | Based on Micro CT D braided composites non-homogeneous Voxel grid discrete method |
| RU2015142116A (en) * | 2015-10-05 | 2017-04-07 | Акционерное общество "Научно-исследовательский центр по изучению свойств поверхности и вакуума" (АО "НИЦПВ") | Method for quantitative three-dimensional surface reconstruction of silicon micro- and nanostructures |
| US20170132781A1 (en) * | 2015-09-11 | 2017-05-11 | Irock Technologies Co., Ltd. | Porous media anaylysis system and method |
| US20180018816A1 (en) * | 2016-07-14 | 2018-01-18 | The First Affiliated Hospital Of Sun Yat-Sen University | Integrated method for three-dimensional visualization reconstruction of the fascicular structure inside human peripheral nerves |
| CN107909107A (en) * | 2017-11-14 | 2018-04-13 | 深圳码隆科技有限公司 | Fiber check and measure method, apparatus and electronic equipment |
| CN109406364A (en) * | 2018-11-07 | 2019-03-01 | 盐城市纤维检验所 | A kind of measuring method of fiber filter media structure porosity |
| WO2020002705A1 (en) * | 2018-06-29 | 2020-01-02 | Universiteit Antwerpen | Item inspection by radiation imaging using an iterative projection-matching approach |
| CN111704743A (en) * | 2020-05-22 | 2020-09-25 | 华东理工大学 | Ablation-resistant nanoporous resin-based composite material and preparation method thereof |
| WO2020236729A1 (en) * | 2019-05-17 | 2020-11-26 | Voxeleron, LLC | Deep learning-based segmentation of corneal nerve fiber images |
| CN112164085A (en) * | 2020-09-28 | 2021-01-01 | 华南理工大学 | Fiber image segmentation and diameter statistical method based on image processing |
| CN112329300A (en) * | 2020-11-02 | 2021-02-05 | 中山大学 | Fiber reinforced composite material micro finite element modeling method based on CT scanning image |
| CN112489019A (en) * | 2020-12-01 | 2021-03-12 | 合肥工业大学 | Method for rapidly identifying chopped fibers in GFRC image based on deep learning |
| CN112734933A (en) * | 2021-01-18 | 2021-04-30 | 东华大学 | Method for reducing three-dimensional structure of non-woven material through central axis of fiber |
| CN112991518A (en) * | 2021-03-10 | 2021-06-18 | 上海工程技术大学 | Three-dimensional reconstruction method for microstructure of non-woven fabric |
-
2021
- 2021-08-18 CN CN202110946727.9A patent/CN113640326B/en active Active
Patent Citations (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7317964B1 (en) * | 2003-04-04 | 2008-01-08 | The United States Of America As Represented By The Secretary Of The Air Force | High speed and repeatability serial sectioning method for 3-D reconstruction of microstructures |
| JP2006202115A (en) * | 2005-01-21 | 2006-08-03 | National Institute Of Advanced Industrial & Technology | Image processing method and image processing program |
| CN102096827A (en) * | 2011-01-18 | 2011-06-15 | 东华大学 | Profiled fiber automatic recognition method based on scale invariability and support vector machine classification |
| US20150262417A1 (en) * | 2012-06-26 | 2015-09-17 | Schkuberger Technology Corporation | Method for building a 3d model of a rock sample |
| WO2015024580A1 (en) * | 2013-08-19 | 2015-02-26 | Universidad De Burgos | Computer implemented method to obtain the orientations of fibres inside composite materials using computed tomography scan |
| CN103971395A (en) * | 2014-05-21 | 2014-08-06 | 安徽工业大学 | Mimicry reconstruction and performance computing method of fiber filter medium structure |
| CN104504193A (en) * | 2014-12-20 | 2015-04-08 | 西安工业大学 | Construction method for taper-changeable composite fiber winding models |
| US20170132781A1 (en) * | 2015-09-11 | 2017-05-11 | Irock Technologies Co., Ltd. | Porous media anaylysis system and method |
| RU2015142116A (en) * | 2015-10-05 | 2017-04-07 | Акционерное общество "Научно-исследовательский центр по изучению свойств поверхности и вакуума" (АО "НИЦПВ") | Method for quantitative three-dimensional surface reconstruction of silicon micro- and nanostructures |
| CN105590338A (en) * | 2015-12-07 | 2016-05-18 | 中国科学院微电子研究所 | Three-dimensional reconstruction method for image of scanning electron microscope |
| CN106202728A (en) * | 2016-07-12 | 2016-12-07 | 哈尔滨工业大学 | Based on Micro CT D braided composites non-homogeneous Voxel grid discrete method |
| US20180018816A1 (en) * | 2016-07-14 | 2018-01-18 | The First Affiliated Hospital Of Sun Yat-Sen University | Integrated method for three-dimensional visualization reconstruction of the fascicular structure inside human peripheral nerves |
| CN107909107A (en) * | 2017-11-14 | 2018-04-13 | 深圳码隆科技有限公司 | Fiber check and measure method, apparatus and electronic equipment |
| WO2020002705A1 (en) * | 2018-06-29 | 2020-01-02 | Universiteit Antwerpen | Item inspection by radiation imaging using an iterative projection-matching approach |
| CN109406364A (en) * | 2018-11-07 | 2019-03-01 | 盐城市纤维检验所 | A kind of measuring method of fiber filter media structure porosity |
| WO2020236729A1 (en) * | 2019-05-17 | 2020-11-26 | Voxeleron, LLC | Deep learning-based segmentation of corneal nerve fiber images |
| CN111704743A (en) * | 2020-05-22 | 2020-09-25 | 华东理工大学 | Ablation-resistant nanoporous resin-based composite material and preparation method thereof |
| CN112164085A (en) * | 2020-09-28 | 2021-01-01 | 华南理工大学 | Fiber image segmentation and diameter statistical method based on image processing |
| CN112329300A (en) * | 2020-11-02 | 2021-02-05 | 中山大学 | Fiber reinforced composite material micro finite element modeling method based on CT scanning image |
| CN112489019A (en) * | 2020-12-01 | 2021-03-12 | 合肥工业大学 | Method for rapidly identifying chopped fibers in GFRC image based on deep learning |
| CN112734933A (en) * | 2021-01-18 | 2021-04-30 | 东华大学 | Method for reducing three-dimensional structure of non-woven material through central axis of fiber |
| CN112991518A (en) * | 2021-03-10 | 2021-06-18 | 上海工程技术大学 | Three-dimensional reconstruction method for microstructure of non-woven fabric |
Non-Patent Citations (4)
| Title |
|---|
| 姜娟 等: "三维针刺CFRP复合材料的制备及显微结构研究", 《应用化工》, vol. 41, no. 07 * |
| 殷忠义 等: "碳纤维针刺预制体增强TDE-85树脂材料细观研究", 《电子工艺技术》, vol. 40, no. 02 * |
| 赵秀阳 等: "基于三维重构的材料微观结构研究现状", 《材料导报》, vol. 19, no. 10 * |
| 郭海庆 等: "基于SEM图像处理的岩体细观微裂隙三维重建模拟分析", 《水电能源科学》, vol. 31, no. 11 * |
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