CN114264799B - Detection method for filling fullness of cement-based grouting material - Google Patents
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- 238000011049 filling Methods 0.000 title claims abstract description 46
- 239000000463 material Substances 0.000 title claims abstract description 44
- 239000004568 cement Substances 0.000 title claims abstract description 25
- 238000001514 detection method Methods 0.000 title description 10
- 238000000034 method Methods 0.000 claims abstract description 53
- 238000012360 testing method Methods 0.000 claims abstract description 38
- 239000010426 asphalt Substances 0.000 claims abstract description 31
- 239000000203 mixture Substances 0.000 claims abstract description 29
- 238000003709 image segmentation Methods 0.000 claims abstract description 4
- 239000011800 void material Substances 0.000 claims description 20
- 238000012545 processing Methods 0.000 claims description 19
- 238000004364 calculation method Methods 0.000 claims description 17
- 230000010412 perfusion Effects 0.000 claims description 14
- 238000010606 normalization Methods 0.000 claims description 10
- 239000002002 slurry Substances 0.000 claims description 8
- 230000014509 gene expression Effects 0.000 claims description 6
- JBTHDAVBDKKSRW-UHFFFAOYSA-N chembl1552233 Chemical compound CC1=CC(C)=CC=C1N=NC1=C(O)C=CC2=CC=CC=C12 JBTHDAVBDKKSRW-UHFFFAOYSA-N 0.000 claims description 4
- 239000003086 colorant Substances 0.000 claims description 4
- 229940073450 sudan red Drugs 0.000 claims description 4
- 230000007797 corrosion Effects 0.000 claims description 3
- 238000005260 corrosion Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 230000011218 segmentation Effects 0.000 claims description 3
- 238000001035 drying Methods 0.000 claims description 2
- 238000007781 pre-processing Methods 0.000 claims description 2
- 238000002360 preparation method Methods 0.000 claims description 2
- 239000011148 porous material Substances 0.000 abstract description 10
- 238000010998 test method Methods 0.000 abstract description 6
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 8
- 238000010276 construction Methods 0.000 description 6
- 239000003638 chemical reducing agent Substances 0.000 description 4
- 201000010099 disease Diseases 0.000 description 4
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 4
- 230000000694 effects Effects 0.000 description 4
- 238000010219 correlation analysis Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 239000002253 acid Substances 0.000 description 2
- 229910021538 borax Inorganic materials 0.000 description 2
- 238000009792 diffusion process Methods 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 238000002156 mixing Methods 0.000 description 2
- 238000011056 performance test Methods 0.000 description 2
- 230000037452 priming Effects 0.000 description 2
- 239000004328 sodium tetraborate Substances 0.000 description 2
- 235000010339 sodium tetraborate Nutrition 0.000 description 2
- 238000007605 air drying Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 238000009833 condensation Methods 0.000 description 1
- 230000005494 condensation Effects 0.000 description 1
- 229920001577 copolymer Polymers 0.000 description 1
- 239000011440 grout Substances 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 239000000049 pigment Substances 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 239000001062 red colorant Substances 0.000 description 1
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- Analysing Materials By The Use Of Radiation (AREA)
- Consolidation Of Soil By Introduction Of Solidifying Substances Into Soil (AREA)
Abstract
The invention discloses a method for detecting pouring plumpness of a cement-based grouting material, which is characterized in that the effective distinction of grouting material, asphalt mixture and a gap is realized by adopting two-dimensional slicing, image segmentation and other modes, and the areas of the grouting material and the gap are automatically calculated by adopting matlab; and respectively accumulating the areas of all grouting materials and gaps on each slice, and then calculating the grouting plumpness of the grouting test piece. The method solves the problem that the conventional filling fullness test method only considers the pores of which the communicated pores are not filled by the grouting material, and the actual filling fullness measured by the conventional test method is higher.
Description
Technical Field
The invention belongs to a road asphalt detection technology, and particularly relates to a detection method for filling fullness of a cement-based grouting material.
Background
With the rapid increase of traffic load and traffic volume, rutting has become one of the main diseases of asphalt pavement at present, and the durability and the comfort of the pavement are seriously affected. Research shows that the composite pavement paved by the pouring type mixture has excellent rut resistance. The poured asphalt mix (GAC) consists of two parts: a porous asphalt mix skeleton (PAC) and a cement-based Grouting Material (GM). Among these, GM perfusion plumpness has a significant impact on GAC performance. The high void fraction of PAC and sufficient flowability of GM are key factors to ensure that GAC is filled. Therefore, in the construction process of the grouting pavement, the grouting saturation is an important index for evaluating the quality of the grouting pavement, and the rut resistance, the water damage resistance and the durability of the pavement are directly affected.
Currently, the flow properties of GM are mainly evaluated by cone-barrel method (flow time) and truncated cone circular die method (diffusion diameter), wherein japanese specifications set the flow time of GM to 10-14s based on cone-barrel regulations. The practical process finds that the range is too wide, which can cause the filling fullness to be lower than 60 percent and seriously affect the performance of the filling type mixture. Furthermore, there is a lack of research on the correlation of flow performance tests with the effect of GAC perfusion, and the perfusion plumpness is a key performance indicator for GAC, and current research does not explicitly give the minimum value of perfusion plumpness, and the corresponding flow performance requirements. That is, in the existing detection, no method can detect the saturation of the road surface after grouting, so that the accurate detection of the saturation after grouting can effectively evaluate the construction quality of the road surface, and plays an important role in reducing road surface diseases.
On the other hand, the void fraction of asphalt mixtures has a significant impact on their performance. For poured asphalt mixtures, the internal voids include closed voids, semi-connected and connected voids that are not filled with grout. However, the conventional filling fullness test method only considers the pores of the connected pores which are not filled by the filling material, thereby causing problems of higher actual filling fullness measured by the conventional test method, lower measured porosity and the like.
Disclosure of Invention
The invention aims to: aiming at the problems that the prior art cannot detect the minimum value and the accuracy of the fullness of the grouting material is not high, the invention provides a method for detecting the grouting saturation of the road asphalt pavement.
The technical scheme is as follows: the method adopts two-dimensional slicing and image segmentation treatment to realize the distinction of grouting materials, asphalt mixtures and gaps through the color difference of the grouting materials, calculates the areas of the grouting materials and the gaps based on matlab software, and further calculates the grouting plumpness of the grouting test piece after accumulating the areas of all the grouting materials and the gaps on each slice respectively; the method further comprises the steps of pouring grouting materials with different flow rates into the large-gap asphalt mixture with the same void rate, calculating the pouring plumpness according to the slices, and determining the lowest pouring plumpness of the grouting asphalt mixture according to the principle that the pouring plumpness on the slices with different depths are basically the same.
Further, the method for calculating the filling fullness of the grouting test piece comprises the following steps:
(1) Two-dimensional slicing is carried out on the grouting test piece, and image acquisition is carried out after drying;
(2) Processing the image based on MATLAB, including comparing pixels of RGB three channels, extracting dark gray channel parts higher than other two channels, and converting the rest parts into gray images; the contrast enhancement algorithm is adopted to improve the difference of different composition components, median filtering is adopted to inhibit partial noise points existing in aggregate and asphalt cement areas, image noise is reduced, image edges are kept, black gaps are used as references, and a proper segmentation threshold is selected for image binarization, so that a gap part in an image is obtained;
(3) Combining the slice and the gap part of the grouting test piece, and adopting a corrosion expansion algorithm to fill holes, so as to eliminate visible noise points and obtain the two-dimensional space distribution condition of each component;
(4) According to the processing result of the two-dimensional image, obtaining the calculated filling fullness G of the sample c The initial void is represented by the sum of the remaining void and the grouting slurry, and the calculation formula is as follows:
wherein G is c -calculating perfusion fullness,%; a is that c -the area of the grouting slurry; a is that v Area of the void.
Furthermore, the sampling process in the step (1) comprises adding sudan red as a colorant in the preparation process of the grouting test piece to improve the color contrast.
The step (2) comprises the following specific steps of:
(21) Carrying out normalization processing on gray images, and assuming that the original data reference sequence and the comparison sequence are respectively x 0 (k) And x i (k)，i＝1，2，...，m；k＝1，2，...，n；
(22) According to data expectation, gray correlation coefficients between the reference sequence and the comparison sequence are calculated, and the calculation expression is as follows:
in the formula delta 0i (k) -reference sequenceAnd comparison sequence->Difference sequence of> ζ—discrimination coefficient, ζ=0.5;
(23) The gray correlation degree is calculated by the average value of the gray correlation coefficients, and the calculation expression is as follows:
further, in the normalization processing in step (21), according to the difference of the data expectations, the data expectations of "larger and better" and the data expectations of "smaller and better" are calculated by the following calculation formulas, respectively, the calculation expressions are as follows:
"larger and better" data normalization process:
"larger and better" data normalization process:
in the method, in the process of the invention,-a sequence of data pre-processing; x is x i (k) -an original sequence; maxx i (k)—x i (k) A maximum value; minx i (k)—x i (k) Minimum value.
Compared with the prior art, the method provided by the invention comprises the following substantial progress and remarkable effects:
(1) The grouting fullness of the grouting material obtained by calculation according to the method comprises the determination of the lowest grouting fullness of the grouting asphalt mixture, and meets the grouting material fluidity requirements under different matrix asphalt mixture void fractions;
(2) The conventional filling fullness test method only considers the pores of the communicated pores which are not filled by the grouting material, so that the actual filling fullness measured by the conventional test method is higher, the measured porosity is lower, the method comprises the steps of closing the pores, semi-communicated pores and the pores of the communicated pores which are not filled by the grouting material in consideration of internal gaps, and the detection result and the obtained filling fullness are more accurate;
(3) The method comprises the steps of determining the minimum filling fullness of the grouting asphalt mixture, and determining the fluidity requirement of the grouting asphalt mixture under different matrix asphalt mixture void ratios, wherein the obtained application result can effectively evaluate the construction quality of the grouting asphalt mixture and plays an important role in reducing pavement diseases.
Drawings
FIG. 1 is a schematic illustration of the operation of the embodiment for sectioning and sampling of a perfusion test piece;
FIG. 2 (a) is an image of a GM cut into slices after addition of a Sudan red colorant;
FIG. 2 (b) is an image of a section to be stained sections removed and converted into a gray scale;
FIG. 2 (c) is an image after the contrast enhancement algorithm is used to enhance the difference between the different components;
FIG. 2 (d) is a two-dimensional spatial distribution after GM and void fraction are combined and hole filling is performed using a corrosive expansion algorithm, eliminating visible noise points;
FIG. 3 is a graph showing the results of the test of filling fullness of different GAC test pieces by the cone-barrel method and the truncated cone circular mold method in practice;
FIG. 4 shows the distribution of GM in GAC for different flow properties according to the method of the invention (three test pieces M1, M5 and M9 with perfusion fullness gradients).
Detailed Description
For a detailed description of the disclosed embodiments, reference will now be made to the accompanying drawings and examples.
In the construction process of the grouting pavement, the grouting fullness is used as an important index for evaluating the quality of the grouting pavement, and the rut resistance, the water damage resistance and the durability of the pavement are directly affected. In the existing detection, no method can detect the fullness of the road surface after grouting, so that the accurate detection of the saturation after grouting can effectively evaluate the construction quality of the road surface, and plays an important role in reducing road surface diseases. Aiming at the technical problem, the grouting test piece is prepared firstly in the embodiment, and compared with the prior art, the grouting mixture (GAC) is composed of a porous asphalt mixture skeleton (PAC) and a cement-based Grouting Material (GM), cement slurries with different water cement ratios and water reducing agent doping amounts are prepared as the GM in the embodiment, the flow property (cone barrel method and truncated cone circular mould method) and the mechanical strength of the cement slurries are tested, the grouting plumpness corresponding to the GAC test piece are tested, the distribution condition of the grouting plumpness of different layers of the test piece is researched by combining a digital image processing technology, and the minimum requirement of the grouting plumpness of the test piece is determined. Based on the test results and gray correlation techniques, the correlation between the two flow performance test methods and the GAC perfusion effect is determined, and meanwhile, the embodiment also verifies that the method provided by the invention is suitable for the determination requirements of the GAC flow performance requirements with different void ratios.
In the embodiment, cement is adopted as a cementing material, polycarboxylic acid copolymer and borax are respectively adopted as a water reducing agent and a retarder to adjust the flow property of cement-based Grouting Materials (GM), and on the basis of a preliminary test, two modes of adjusting the water cement ratio (0.4,0.45 and 0.5) and the mixing amount (0%, 0.03% and 0.06%) of the polycarboxylic acid water reducing agent are adopted to prepare the GM with different flow properties. Early-stage experiments show that the addition of 0.3% borax can ensure that the condensation time of GM exceeds 30min, and can meet the requirements of construction and experiments, and 5wt% of Sudan red is added into GM as a colorant to improve the color contrast ratio for the convenience of processing digital images.
Specifically, the invention realizes effective distinction of the grouting material, the asphalt mixture and the gap by adopting two-dimensional slicing, image segmentation and other modes through the color difference of the grouting material, the asphalt mixture and the gap, and automatically calculates the areas of the grouting material and the gap by adopting matlab. And respectively accumulating the areas of all grouting materials and gaps on each slice, and then calculating the grouting fullness of the grouting test piece. If the dislike of the grouting material and the asphalt mixture is difficult to distinguish, the color contrast of the grouting material and the asphalt mixture can be increased by adding pigment into the grouting material.
The detection method of the invention comprises the following specific implementation steps:
(1) The GAC was first cut to obtain images at 1cm,3cm and 5cm heights of the test pieces.
And (3) removing 1cm parts at two ends of the cured mixture test piece by using a single-sided saw, cutting the middle part with uniformly distributed gaps into two discs, and standing and air-drying after the test piece is cut. And then placing the dry test piece on a plane, and respectively placing a light source at two sides of the platform to ensure sufficient illumination and uniform brightness. And shooting images from top to bottom by adopting a digital camera, wherein the images are required to be focused clearly, and each test piece can obtain 6 images for analysis. A specific flow of specimen cutting and image acquisition is shown in fig. 1.
(2) Image processing
Six two-dimensional cross-sectional images can be obtained after each test piece is cut. And processing the image by adopting MATLAB software. In the picture, the grouting material presents dark gray, the aggregate color is lighter, the darkest part corresponds to the gap, and the rest part corresponds to the asphalt cement. According to the characteristics, firstly, according to the RGB three-channel principle, the values of three channels of an image are respectively compared, the part of the dark gray channel higher than the other two channels is extracted to be the grouting material, and the rest part is converted into a gray image. The gray scale image is then preprocessed: the contrast enhancement algorithm is adopted to improve the difference of different components, the median filtering is adopted to inhibit some darker noise points in aggregate and asphalt cement areas, image noise is reduced, image edges are kept, black gaps are used as references, and a proper segmentation threshold is selected for image binarization, so that the gap portions in the images are obtained. Finally, the grouting material and the gap part are combined and the hole filling is carried out by adopting a corrosion expansion algorithm, so that visible noise points are eliminated, the two-dimensional space distribution condition of each component is ensured to be accurately acquired, and a process image of the grouting test piece image processing is shown in fig. 2.
In the image processing process, gray correlation analysis and calculation are included, and the specific calculation process is as follows:
the gray correlation analysis is to calculate the degree of correlation between the reference number series (target value) and the comparison number series (influencing factor) and rank them, so that the main factor influencing the target value can be obtained. Firstly, carrying out normalization processing on an original data sequence, wherein the processing method comprises the following steps:
let the original data reference sequence and comparison sequence be x respectively 0 (k) And x i (k) I=1, 2, m; k=1, 2,..n. According to the difference of data expectations, the normalization processing is respectively carried out by adopting the formula (3) and the formula (4) for the data expectations of 'bigger and better' and 'smaller and better'.
In the method, in the process of the invention,-a data pre-processed sequence; x is x i (k) -an original sequence; maxx i (k)-x i (k) A maximum value; minx i (k)-x i (k) Minimum value.
After normalizing the original data sequence, the gray correlation coefficient between the reference sequence and the comparison sequence can be calculated by equation (5).
In the formula delta 0i (k) -reference sequenceAnd comparison sequence->Difference sequence of> ζ -discrimination coefficient, wherein ζ=0.5.
The gray correlation degree is an average value of gray correlation coefficients, and is defined as follows:
the gray correlation represents the degree of correlation between the reference sequence and the comparison sequence. If a particular comparison sequence is more important to the reference sequence than the other comparison sequences, the gray correlation of the comparison sequence to the reference sequence is greater than the other sequences.
(3) Calculation of fullness
According to the processing result of the two-dimensional image, obtaining the calculated filling fullness G of the test piece c The initial void is represented by the sum of the remaining void and GM, and the calculation method is as shown in formula (1), and the calculated filling fullness G of 6 pictures of each test piece c And taking an average value to obtain the calculated perfusion plumpness of the test piece.
Wherein G is c -calculating perfusion fullness,%; a is that c -the area of the cement slurry; a is that v Area of the void.
And (3) calculating the filling fullness of the mixture by using the void ratio of GCA-13 and the grouting density and performing density index test on the test piece before and after grouting. Perfusion plumpness is calculated according to equation (2). A total of 9 (numbers M1 to M9) test groups were tested for comparison and the test data are shown in Table 1.
Wherein G is m -perfusion fullness,%; m is m 1 -specimen mass before priming, g; m is m 2 -specimen mass after priming, g; rho-cement-based material density, g/cm 3 The method comprises the steps of carrying out a first treatment on the surface of the V-volume of test piece, cm 3 The method comprises the steps of carrying out a first treatment on the surface of the Void fraction of VV-GCA.
TABLE 1 actual measurement and calculation of perfusion fullness results
According to table 1, and with reference to fig. 3 and 4, it can be known that the measured filling fullness is substantially identical to the calculated filling fullness, the difference between the measured filling fullness and the calculated filling fullness is less than 5%, and the calculated filling fullness is mostly less than the measured filling fullness, which is caused by the following reasons: on the one hand, when the image processing technology is adopted to extract the gaps, a small amount of asphalt cement is erroneously identified as the gaps due to the fact that the colors of the gaps are similar to those of the asphalt cement, and the filling fullness is smaller due to the increase of the area of the gaps; on the other hand, the Marshall test piece has the gap distribution with two large ends and small middle, the gap distribution at the middle is relatively uniform, the slurry is easier to pour due to the larger gap ratio at the two ends, the actual measurement of the filling plumpness represents the whole filling plumpness of the test piece, and the calculation of the filling plumpness represents the filling plumpness in the middle range, so that the filling plumpness is slightly smaller than the actual measurement of the filling plumpness. In conclusion, the calculated filling fullness has good correlation with the actually measured filling fullness, so that the method can be completely used for detecting the grouting saturation of the road surface after grouting.
According to the method provided by the invention, the flow performance and mechanical strength of different GM are tested, the calculated perfusion plumpness is obtained according to the slice images, and the flow performance index and the correlation analysis thereof are carried out by combining gray correlation. The results show that: the flow property of GM can be improved by increasing the water-cement ratio and the mixing amount of the water reducer, but the mechanical strength of the GM can be influenced; compared with a cone barrel method, the correlation between the truncated cone method and the filling fullness is higher; in order to ensure the filling effect of GAC, the GAC filling fullness of 25% void fraction is more than 85%, and the flow time and diffusion diameter of GM are less than 11.3s and more than 27.2cm, respectively.
Claims (4)
1. A method for detecting filling fullness of cement-based grouting material is characterized by comprising the following steps: according to the method, through the color difference of grouting materials, asphalt mixtures and gaps, the two-dimensional slicing and image segmentation processing are adopted to realize the distinction of the grouting materials and the gaps, and the areas of the grouting materials and the gaps are calculated based on matlab software, so that the grouting plumpness of the grouting materials is calculated after the areas of all grouting materials and the gaps on each slice are respectively accumulated; the method further comprises the steps of pouring grouting materials with different flow rates into the large-gap asphalt mixture with the same void rate, calculating the pouring plumpness according to the slices, and determining the lowest pouring plumpness of the grouting asphalt mixture according to the principle that the pouring plumpness on the slices with different depths are basically the same;
the method for calculating the filling fullness of the grouting test piece comprises the following steps of:
(1) Two-dimensional slicing is carried out on the grouting test piece, and image acquisition is carried out after drying;
(2) Processing the image based on MATLAB, including comparing pixels of RGB three channels, extracting dark channel parts higher than other two channels, and converting the rest parts into gray images; the contrast enhancement algorithm is adopted to improve the difference of different composition components, median filtering is adopted to inhibit partial noise points existing in aggregate and asphalt cement areas, image noise is reduced, image edges are kept, black gaps are used as references, and a proper segmentation threshold is selected for image binarization, so that a gap part in an image is obtained;
(3) Combining the slice and the gap part of the grouting test piece, and adopting a corrosion expansion algorithm to fill holes, so as to eliminate visible noise points and obtain the two-dimensional space distribution condition of each component;
(4) According to the processing result of the two-dimensional image, obtaining the calculated filling fullness G of the sample c The initial void is represented by the sum of the remaining void and the grouting slurry, and the calculation formula is as follows:
wherein G is c -calculating perfusion fullness,%; a is that c -the area of the grouting slurry; a is that v Area of the void.
2. The method for detecting filling fullness of a cement-based grouting material according to claim 1, wherein: the sampling process of the step (1) comprises adding Sudan red as a colorant in the preparation process of the grouting test piece to improve the color contrast.
3. The method for detecting filling fullness of a cement-based grouting material according to claim 1, wherein: the step (2) comprises the following specific steps of:
(21) Carrying out normalization processing on gray images, and assuming that the original data reference sequence and the comparison sequence are respectively x 0 (k) And x i (k)，i＝1，2，...，m；k＝1，2，...，n；
(22) According to data expectation, gray correlation coefficients between the reference sequence and the comparison sequence are calculated, and the calculation expression is as follows:
in the formula delta 0i (k) -reference sequenceAnd comparison sequence->Difference sequence of> ζ—discrimination coefficient, ζ=0.5;
(23) The gray correlation degree is calculated by the average value of the gray correlation coefficients, and the calculation expression is as follows:
4. the method for detecting filling fullness of a cement-based grouting material according to claim 3, wherein: in the normalization processing in step (21), according to the difference in data expectation, the data expectation of "larger and better" and the data expectation of "smaller and better" are calculated by the following calculation formulas, respectively, the calculation expressions being as follows:
"larger and better" data normalization process:
"larger and better" data normalization process:
in the method, in the process of the invention,-a sequence of data pre-processing; x is x i (k) -an original sequence; maxx i (k)—x i (k) A maximum value; minx i (k)—x i (k) Minimum value.
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