CN109001248B - Asphalt mixture freezing-thawing damage evaluation method based on image information entropy - Google Patents
Asphalt mixture freezing-thawing damage evaluation method based on image information entropy Download PDFInfo
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Abstract
An asphalt mixture freeze-thaw damage evaluation method based on image information entropy belongs to the field of road engineering material damage. The method comprises the following specific steps: the method comprises the following steps: preparing a sample; step two: performing a freeze-thaw cycle test on the asphalt mixture test piece under the conditions of certain temperature and humidity; step three: acquiring a tomography image of the asphalt mixture test piece; step four: calculating the entropy of the image information; step five: and (5) analyzing the freeze-thaw damage state of the asphalt mixture. Compared with the prior art, the method has the advantages that the method can quickly, simply and accurately calculate the communication porosity of the asphalt mixture test piece, and visually output the distribution condition of the communication porosity along the height of the asphalt mixture.
Description
Technical Field
The invention belongs to the field of road engineering material damage, and particularly relates to an asphalt mixture freeze-thaw damage evaluation method based on image information entropy.
Background
The asphalt mixture is a common porous pavement material, the moisture is an important factor influencing the use performance of the asphalt mixture, and particularly, under the condition of freeze thawing alternation, the moisture in the asphalt mixture is frozen and transferred to cause the change of an internal structure. Under the action of multiple freeze-thaw cycles, the damage of the asphalt mixture is aggravated, severe freeze-thaw damage and water damage occur, and the pavement performance of the asphalt mixture is affected, so that the freeze-thaw damage of the asphalt mixture needs to be researched.
At present, research on the freeze-thaw damage of the asphalt mixture mainly focuses on the macroscopic mechanics and volume level, the freeze-thaw damage degree of the asphalt mixture is evaluated according to mechanical parameters such as strength and modulus and parameters such as total porosity, the influence of moisture on the asphalt mixture is mainly on the microscopic level, the parameters on the macroscopic level only can indirectly evaluate the freeze-thaw damage degree, and the freeze-thaw damage mechanism cannot be reflected. At present, related researches on the freeze-thaw damage of the asphalt mixture are also carried out on a microscopic level, but the freeze-thaw damage degree of the asphalt mixture is evaluated by microscopic volume indexes such as void ratio, communication void ratio, void quantity and the like, but the change stages of the volume indexes are not obvious and the freeze-thaw damage degree of the asphalt mixture cannot be accurately reflected, so that a new evaluation method for the freeze-thaw damage of the asphalt mixture is needed to be provided.
Disclosure of Invention
The invention aims to solve the problem that the existing evaluation parameters of the freeze-thaw damage of the asphalt mixture cannot accurately reflect the degree of the freeze-thaw damage of the asphalt mixture, and provides an evaluation method of the freeze-thaw damage of the asphalt mixture based on image information entropy.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
an asphalt mixture freeze-thaw damage evaluation method based on image information entropy comprises the following specific steps:
the method comprises the following steps: sample preparation: preparing an asphalt mixture test piece with the diameter of 100mm and the height of 63.5mm according to road engineering asphalt and asphalt mixture test procedures (JTG E20-2011);
step two: performing a freeze-thaw cycle test on the asphalt mixture test piece;
step three: acquiring a tomography image of the asphalt mixture test piece: scanning asphalt mixture test pieces under different freezing and thawing times by using an industrial CT machine, and ensuring that the position of the test piece from a focus, the scanning time, the scanning voltage, the scanning current and the number of scanning layers are the same during each scanning; reconstructing asphalt mixture test pieces by using reconstruction software, outputting section images at intervals of less than or equal to 1mm on each asphalt mixture test piece, ensuring that the images with the same section are output under different freeze-thaw times, and setting the same image resolution and size;
step four: calculating the entropy of the image information: an MATLAB program is compiled by utilizing the obtained CT scanning tomographic image, the image is subjected to edge detection, the image after the edge detection is output, and the information entropy of the edge detection image is calculated, wherein the specific calculation is as follows:
1. laplacian of gaussian operator
The laplacian gaussian operator is an operator formed by convolution synthesis of a Laplace operator and gaussian, and can improve the stability of the operator on noise and discrete points: the Laplace operator realizes the edge detection by solving the zero crossing point of the second derivative of the image, and the formula is as follows:
the expression of the gaussian function is as follows:
the kernel function defining the LoG operator is:
in the formula, ▽2f is a Laplace operator; f is an image gray scale function; x and y are gray function variables; gσ(x, y) is a Gaussian function; sigma is a standard deviation of the gray function; LoG is Laplace Gaussian operator;
2. calculation of information entropy
And calculating the information entropy of the newly generated edge detection image, wherein the image information entropy calculation formula is as follows:
where H is the information entropy, PiThe proportion of the pixels with the gray value i is represented;
using MATLAB software, compiling image processing and information entropy calculation programs according to the edge detection formulas (1) - (3) and the image information entropy calculation formula (4), and calculating the information entropies of different sections of the asphalt mixture under different freezing and thawing times;
step five: and (3) analyzing the freeze-thaw damage state of the asphalt mixture: selecting a test piece height range with uniformly distributed information entropy, drawing a variation curve of the information entropy of the asphalt mixture test piece under different freezing-thawing cycle times by taking an image information entropy mean value in the range as a parameter, and judging the freezing-thawing damage state of the asphalt mixture according to the increase and decrease of the information entropy so as to finish the evaluation of the freezing-thawing damage degree of the asphalt mixture.
Compared with the prior art, the invention has the beneficial effects that: the method can quickly, simply and accurately calculate the communication porosity of the asphalt mixture test piece, and intuitively output the distribution condition of the communication porosity along the height of the asphalt mixture.
Drawings
FIG. 1 is a schematic view of a cross section of an asphalt mixture scanned under a freeze-thaw condition of 0 times;
FIG. 2 is a schematic cross-sectional view of a scan of an asphalt mixture under a freeze-thaw condition of 9 times;
FIG. 3 is a schematic cross-sectional view of a scan of an asphalt mixture under 18 freeze-thaw conditions;
FIG. 4 is a schematic cross-sectional view of a scan of an asphalt mixture under 30 freeze-thaw conditions;
FIG. 5 is a graph showing the change of information entropy at different heights of an asphalt mixture test piece along with the number of freeze-thaw cycles;
fig. 6 is a schematic diagram of a change curve of the information entropy representative value of the asphalt mixture along with the number of freeze-thaw times under different numbers of freeze-thaw times.
Detailed Description
The technical solution of the present invention is further described below with reference to the drawings and the embodiments, but the present invention is not limited thereto, and modifications or equivalent substitutions may be made to the technical solution of the present invention without departing from the spirit of the technical solution of the present invention, and the technical solution of the present invention is covered by the protection scope of the present invention.
Energy exchange between the asphalt mixture and the outside exists in the freeze-thaw damage process, and the damage degree and the energy exchange have a direct relation, so that the evaluation of the freeze-thaw damage of the asphalt mixture by using energy parameters is the most direct method. The information entropy is a measure of information uncertainty, is an expression of the degree of system disorder, is comprehensively specified by the state of a microscopic subsystem inside the system, and is consistent with the thermodynamic entropy in nature. Parameters related to the thermodynamic entropy in engineering are difficult to obtain, and an information entropy theory method is simple, the calculation process is simple and convenient, and the index sensitivity is high, so the information entropy can be used as an energy parameter to be applied to the identification and detection of material and structural damage, and is already applied to the identification and detection of concrete damage, but is hardly applied to asphalt mixtures, and therefore an asphalt mixture damage identification method based on the information entropy is necessary to be provided.
The change in voids can reflect the damage state of the asphalt mixture. Under the condition of carrying out edge detection on the image, the information entropy can reflect the change condition of the internal gap of the asphalt mixture. When the volume and the number of the gaps are enlarged, the information entropy is in a growing trend, which shows that the internal damage is mainly caused by the enlargement of the volume and the increase of the number of the gaps under the condition that the asphalt mixture absorbs energy; when the gaps are communicated, the information entropy tends to be reduced, which shows that the energy in the asphalt mixture is released and is represented as the communication of the gaps. Therefore, the method is based on the information entropy theory, takes the CT scanning section of the asphalt mixture as an information system, and judges the freeze-thaw damage state of the asphalt mixture according to the increase and decrease change condition of the information entropy.
The first embodiment is as follows: the embodiment describes an asphalt mixture freeze-thaw damage evaluation method based on image information entropy, which comprises the following specific steps:
the method comprises the following steps: sample preparation: preparing an asphalt mixture test piece with the diameter of 100mm and the height of 63.5mm according to road engineering asphalt and asphalt mixture test procedures (JTG E20-2011);
step two: performing a freeze-thaw cycle test on the asphalt mixture test piece;
step three: acquiring a tomography image of the asphalt mixture test piece: scanning an asphalt mixture test piece under different freezing and thawing times (including an initial state without freezing and thawing) by using an industrial CT (computed tomography) machine, and ensuring that the position of the test piece from a focus, scanning time, scanning voltage, scanning current and the number of scanning layers are the same in each scanning process; reconstructing asphalt mixture test pieces by using reconstruction software, outputting section images at intervals of less than or equal to 1mm on each asphalt mixture test piece, ensuring that the images with the same section are output under different freeze-thaw times, and setting the same image resolution and size;
step four: calculating the entropy of the image information: an MATLAB program is compiled by utilizing the obtained CT scanning tomographic image, the image is subjected to edge detection, the image after the edge detection is output, and the information entropy of the edge detection image is calculated, wherein the specific calculation is as follows:
1. laplacian of gaussian operator
The laplacian gaussian operator (LoG, Laplace of gaussian) is an operator synthesized by the Laplace operator and gaussian convolution, and can improve the stability of the operator to noise and discrete points: the Laplace operator realizes the edge detection by solving the zero crossing point of the second derivative of the image, and the formula is as follows:
the expression of the gaussian function is as follows:
the kernel function defining the LoG operator is:
in the formula, ▽2f is a Laplace operator; f is an image gray scale function; x and y are gray function variables; gσ(x, y) is a Gaussian function; sigma is a standard deviation of the gray function; LoG is Laplace Gaussian operator;
2. calculation of information entropy
And calculating the information entropy of the newly generated edge detection image, wherein the image information entropy calculation formula is as follows:
where H is the information entropy, PiThe proportion of the pixels with the gray value i is represented;
using MATLAB software, compiling image processing and information entropy calculation programs according to the edge detection formulas (1) - (3) and the image information entropy calculation formula (4), and calculating the information entropies of different sections of the asphalt mixture under different freezing and thawing times;
step five: and (3) analyzing the freeze-thaw damage state of the asphalt mixture: selecting a test piece height range with uniformly distributed information entropy, drawing a change curve of the information entropy of the asphalt mixture test piece under different freezing-thawing cycle times by taking an image information entropy mean value in the range as a parameter, and judging the freezing-thawing damage state of the asphalt mixture according to the increase and decrease of the information entropy, wherein the information entropy increase indicates that the asphalt mixture is in an energy absorption state, and the damage is mainly caused by the increase of the number of gaps and the expansion of the volume; the reduction of the information entropy shows that the energy is released by the asphalt mixture, and the damage is mainly caused by the communication of gaps; so far, the evaluation of the freeze-thaw damage degree of the asphalt mixture is completed.
The evaluation of the freeze-thaw damage form of the asphalt mixture is completed by a method combining tests with image processing and analysis.
Example 1: the OGFC-13 asphalt mixture is taken as an example, and the freeze-thaw damage is evaluated according to the following steps by using the information entropy.
The method comprises the following steps: sample preparation
OGFC-13 test pieces with the diameter of 100mm and the height of 63.5mm are prepared. The aggregate is produced by andesite from Heilongjiang, and the asphalt is medium petroleum No. 90 petroleum asphalt. The indexes of the raw materials are tested by referring to road engineering asphalt and asphalt mixture test specification (JTG E20-2011) and road engineering aggregate test specification (JTG E42-2005), and all the indexes meet the requirements of road asphalt pavement construction technical specification (JTG F40-2004), and the indexes are shown in tables 1 to 3.
TABLE 1 coarse aggregate technical Properties
TABLE 2 Fine aggregate technical Properties
TABLE 3 bitumen technical Properties
| Detecting the index | Test value | Technical requirements |
| Penetration 25 deg.C, 5s, 100g (0.1mm) | 82.6 | 80-100 |
| Softening Point T (. degree. C.) | 46.2 | >45 |
| Ductility (cm) at 15 DEG C | >100 | >100 |
The method is characterized in that an American Superpave design method is adopted, the OGFC-13 grading median value recommended by technical Specification for construction of road asphalt pavements (JTGF40-2004) is adopted in design grading, and a rotary compaction forming method is adopted to prepare a test piece with the diameter of 100mm and the height of 63.5 mm. The OGFC-13 design void ratio is 21%, and the optimal asphalt dosage is 4.0%. Test pieces are formed according to the designed void ratio and the optimal asphalt using amount, and the volume parameters of the test pieces meet the requirements of the technical specification for the construction of the asphalt pavement of the highway, which is shown in Table 4.
TABLE 4 OGFC-13 volume parameters
Step two: performing a freeze-thaw cycle test
Setting a saturated water freeze-thaw cycle test, and improving the freeze-thaw condition of the asphalt mixture freeze-thaw splitting test in road engineering asphalt and asphalt mixture test specification (JTG E20-2011), wherein the specific freeze-thaw method comprises the steps of placing a test piece under the negative pressure condition of 97.3-98.7 kPa for vacuum water saturation for 15min, then soaking for 0.5h under normal pressure, and freezing for 16h under the condition of keeping 10% of the void water saturation rate at-18 ℃; and taking out the test piece, placing the test piece in a constant-temperature water tank at 20 ℃ for 12h in water bath, wherein the void saturation rate is 100%, and thus, one freeze-thaw cycle is completed, and the test conditions are shown in Table 5.
TABLE 5 saturated Water Freeze-thaw test conditions
Step three: acquisition of cross-sectional images of fusion specimen
The test piece is scanned by adopting a Phoenix v/tome | x S240 type industrial CT machine produced by Phoenix x X-ray of Germany, the scanning voltage is 190kV, the current is 300mA, the scanning time is 17min, the test piece is scanned at the same position, and each test piece scans 1000 layers. And carrying out image reconstruction on the scanned CT image by using VG Studio software, extracting the tomographic images of the test piece at different heights, and adopting the same image size and resolution. Under the water-saturated freeze-thaw condition, the test piece is scanned after freeze-thaw cycles of 0 time, 3 times, 6 times, 9 times, 12 times, 15 times, 18 times, 24 times and 30 times, CT scanning images under different freeze-thaw times are extracted, and the schematic section diagram of the test piece is shown in figures 1-4.
Step four: entropy calculation of image information
And calculating the information entropy of the OGFC-13 section images under different freezing and thawing times by using the compiled Matlab program, and drawing curves of the section information entropy at different heights along with the change of the freezing and thawing times.
Step five: evaluation of degree of Freeze-thaw Damage
The change of section information entropies at different heights along with the freeze-thaw times is shown in a table 6 and a graph 5, and the results in the graph show that the image information entropies are in a regular distribution with small ends and large middle along the height of the test piece, and the middle of the test piece is distributed uniformly, so that the image information entropies are described by the information entropy mean value within the height range of 10-50 mm, and the schematic diagram is shown in fig. 6. Under the water-saturated freeze-thaw condition, along with the increase of the number of freeze-thaw cycles, the entropy of the image information is changed in three stages. The entropy value of the first stage (0-9 freeze-thaw cycles) increased from 0.1854 to 0.2423. The freeze-thaw cycle at this stage increases the energy of the asphalt mixture, increases the number of voids or increases the void volume, and the image shows that the disorder degree of the image information is increased, so the entropy value is increased. In the second stage (9-18 times), the entropy value is sharply reduced, and is reduced from 0.2423 to 0.2088. At this stage, the action of the freeze-thaw cycle continues to work on the asphalt mixture, but the work exceeds the bearing range of the asphalt mixture, the gaps are gradually communicated to generate microcracks, and energy is released, so that the entropy value is reduced. In the third stage (18-30 times), the entropy value is slowly increased from 0.2088 to 0.2151. The freeze-thaw cycle at this stage enables the energy of the asphalt mixture with the damaged structure to be slowly increased, the generation of new gaps is more dominant than the communication of the gaps, the image disorder degree is slowly increased, and the information entropy is increased. Thus, the evaluation of the freezing-thawing damage state of the OGFC-13 asphalt mixture is completed.
TABLE 6 variation of information entropy with freeze-thaw cycle times under saturated water freeze-thaw conditions
| Freezing and |
0 |
3 times of | 6 times of | 9 times of | 12 times (twice) | 15 times of | 18 times of | 24 times of | 30 times (twice) |
| Saturated water | 0.1854 | 0.1943 | 0.2133 | 0.2423 | 0.2115 | 0.2157 | 0.2088 | 0.2117 | 0.2151 |
Claims (1)
1. An asphalt mixture freeze-thaw damage evaluation method based on image information entropy is characterized by comprising the following steps: the method comprises the following specific steps:
the method comprises the following steps: sample preparation: preparing an asphalt mixture test piece with the diameter of 100mm and the height of 63.5mm according to road engineering asphalt and asphalt mixture test procedures JTG E20-2011;
step two: performing a freeze-thaw cycle test on the asphalt mixture test piece;
step three: acquiring a tomography image of the asphalt mixture test piece: scanning asphalt mixture test pieces under different freezing and thawing times by using an industrial CT machine, and ensuring that the position of the test piece from a focus, the scanning time, the scanning voltage, the scanning current and the number of scanning layers are the same during each scanning; reconstructing asphalt mixture test pieces by using reconstruction software, outputting section images at intervals of less than or equal to 1mm on each asphalt mixture test piece, ensuring that the images with the same section are output under different freeze-thaw times, and setting the same image resolution and size;
step four: calculating the entropy of the image information: an MATLAB program is compiled by utilizing the obtained CT scanning tomographic image, the image is subjected to edge detection, the image after the edge detection is output, and the information entropy of the edge detection image is calculated, wherein the specific calculation is as follows:
(1) laplacian of gaussian operator
The Laplace Gaussian operator is an operator formed by convolution synthesis of a Laplace operator and Gaussian, and the stability of the operator to noise and discrete points can be improved; the Laplace operator realizes the edge detection by solving the zero crossing point of the second derivative of the image, and the formula is as follows:
the expression of the gaussian function is as follows:
the kernel function defining the LoG operator is:
in the formula (I), the compound is shown in the specification,
is Laplace operator; f is an image gray scale function; x and y are gray function variables; gσ(x, y) is a Gaussian function; sigma is a standard deviation of the gray function; LoG is Laplace Gaussian operator;
(2) calculation of information entropy
And calculating the information entropy of the newly generated edge detection image, wherein the image information entropy calculation formula is as follows:
where H is the information entropy, PiThe proportion of the pixels with the gray value i is represented;
using MATLAB software, compiling image processing and information entropy calculation programs according to the edge detection formulas (1) - (3) and the image information entropy calculation formula (4), and calculating the information entropies of different sections of the asphalt mixture under different freezing and thawing times;
step five: and (3) analyzing the freeze-thaw damage state of the asphalt mixture: selecting a test piece height range with uniformly distributed information entropy, drawing a variation curve of the information entropy of the asphalt mixture test piece under different freezing-thawing cycle times by taking an image information entropy mean value in the range as a parameter, and judging the freezing-thawing damage state of the asphalt mixture according to the increase and decrease of the information entropy so as to finish the evaluation of the freezing-thawing damage degree of the asphalt mixture.
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