A method for calculating the penetration level of surface treatment agents for porous asphalt pavement

Abstract

The present invention discloses a method for calculating the penetration level of a porous asphalt pavement surface treatment agent. The method uses industrial-grade X-ray CT scanning technology to obtain images of samples before and after treatment, uses digital image processing technology to obtain the global void distribution of samples before and after treatment, and proposes void difference centroid depth and its eccentricity index and corresponding algorithm based on full consideration of the penetration behavior of the surface treatment agent through microscopic structural morphology analysis. Compared with the prior art, the method of the present invention can effectively distinguish the penetration levels of different preventive curing agents, avoiding the problem of unclear depth judgment due to void connectivity. The present invention has a clear calculation principle, a simple and easy calculation process, and high calculation accuracy, and can provide an accurate and intuitive digital basis for material optimization and construction quality control of such preventive surface curing agents.

Description

Technical Field

[0001] The invention belongs to the technical field of road maintenance, and in particular relates to a method for calculating the penetration level of a porous asphalt pavement surface treatment agent. Background Art

[0002] Permeable asphalt pavement is susceptible to external factors such as moisture and oxygen due to its large porosity, resulting in early peeling. In order to alleviate this problem of insufficient durability, researchers have proposed spraying preventive curing agents to repair micro-damages of in-service drainage asphalt pavements and replenish the thickness of the asphalt film, so as to restore its anti-stripping performance and improve durability. Preventive curing agents are emulsions including emulsified asphalt base, regeneration agent and other ingredients. Their mechanism of action is to penetrate into the mixture through the internal pores of the drainage asphalt mixture. Therefore, how to quantify its penetration level is the basis for fully understanding the effect of this type of material.

[0003] The use of digital image processing technology to study the mass transfer of road engineering materials has been a research hotspot in recent years. With the development and popularization of various high-precision light source imaging methods, the method of obtaining real-time in-situ images of the internal structure of materials has matured. However, how to extract effective information from the image and connect it with the macroscopic physical behavior is still a difficult point in research. At present, the conventional method is to use the change in the area of ​​​​voids before and after the surface treatment agent to characterize the depth of treatment. The treatment depth is defined as the depth position where the change in the void area is zero. However, for porous asphalt pavements, unlike dense-graded asphalt mixtures, the internal voids are highly connected, and preventive maintenance agents can generally fully penetrate the entire pavement depth. However, the penetration level at different depths varies greatly. Therefore, the penetration level of porous asphalt pavement surface treatment agents is currently difficult to quantify. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and provide a method for calculating the penetration level of porous asphalt pavement surface treatment agents. This method analyzes the microstructure morphology, fully considers the penetration behavior of the surface treatment agent, and proposes indicators that can effectively distinguish the penetration levels of different preventive maintenance agents.

[0005] To achieve the above object, the present invention adopts the following technical solution:

[0006] A method for calculating the penetration level of a porous asphalt pavement surface treatment agent comprises the following steps:

[0007] S1. Use industrial-grade X-ray CT scanning to obtain continuous tomographic grayscale images of porous asphalt mixture samples before and after spraying the surface treatment agent. Preprocess the images, then use the threshold method to distinguish the voids from the asphalt mortar and coarse aggregate of the porous asphalt mixture, and use the image binarization algorithm to define the void area in each grayscale image as white, and the rest as black;

[0008] S2. Based on the image information, the depth position and void ratio of each image are calculated according to formula (1) and formula (2), and the synthetic void ratio is calculated according to formula (3):

[0009] h i =p×i (1)

[0010]

[0011] Where:

[0012] h i : The depth position of the i-th image, mm;

[0013] p: vertical resolution of CT scan, mm / layer;

[0014] V i : The void ratio of the i-th picture, %;

[0015] A i : White area of ​​the ith image, mm 2 ;

[0016] A sum : Area of ​​the sample cross section, mm 2 ;

[0017] n: number of tomographic grayscale images;

[0018] V ave : Sample composite porosity, %;

[0019] S3. Use formula (4) to calculate the image porosity difference ratio K of the sample before and after spraying the surface treatment agent, and obtain the relationship curve between the porosity difference and the image depth position; use formula (5) to calculate the centroid depth h of the porosity difference in the depth direction ave , and use formula (6) to calculate the centroid depth eccentricity P, where the gap difference centroid depth h ave It is used to characterize the penetration depth, and the void difference centroid depth eccentricity P is used to characterize the penetration uniformity;

[0020]

[0021] Where:

[0022] Ki: Depth hi Image void ratio difference ratio at position, %;

[0023] Depth h i Void ratio of the sample image before spraying the surface treatment agent at the position, %;

[0024] Depth h i Void ratio of sample image after spraying surface treatment agent at position, %;

[0025] h ave : Gap difference centroid depth, mm;

[0026] H: thickness of the sample, mm;

[0027] P: eccentricity of the center of mass of the gap difference, %.

[0028] Furthermore, in step S1, the accuracy of the planar and vertical images obtained by the X-ray CT scan is less than 0.1 mm / pixel.

[0029] Furthermore, in step S1, the diameter of the porous asphalt mixture sample is 100±1 mm, and the height is 40 mm to 60 mm.

[0030] Furthermore, in step S1, the preprocessing refers to applying image enhancement and median filtering algorithms to eliminate image brightness unevenness and image noise.

[0031] Further, in step S2, before the surface treatment agent is sprayed, the sample synthesis porosity V ave The relative error of the sample void ratio measured by the volume method is no more than 10%. If the relative error exceeds 10%, the threshold needs to be reselected in step (1) for image segmentation and void identification.

[0032] Beneficial effects of the present invention:

[0033] The present invention provides a method for calculating the penetration level of porous asphalt pavement surface treatment agents, which integrates X-ray CT scanning technology and digital image processing methods. Through microscopic structural morphology analysis, on the basis of fully considering the penetration behavior of the surface treatment agent, the gap difference centroid depth and its eccentricity index and corresponding algorithm are proposed. Compared with the prior art method of judging penetration through macroscopic volume parameters or through the difference in gap area (volume) at different depths before and after sample treatment, the method of the present invention can effectively distinguish the penetration levels of different preventive curing agents, avoiding the problem of unclear depth judgment due to gap connectivity. The present invention has a clear calculation principle, a simple and easy calculation process, and high calculation accuracy, and can provide an accurate and intuitive digital basis for material optimization and construction quality control of such preventive surface curing agents. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 Schematic diagram of the image processing and gap recognition process in Example 2;

[0035] Figure 2 This is a schematic diagram of the calculation results of the image void ratio in Example 2;

[0036] Figure 3 Schematic diagram of the calculation of the void ratio difference in Example 2. DETAILED DESCRIPTION

[0037] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0038] Example 1

[0039] A method for calculating the penetration level of a porous asphalt pavement surface treatment agent comprises the following steps:

[0040] S1. Use industrial-grade X-ray CT scanning to obtain continuous tomographic grayscale images of porous asphalt mixture samples before and after spraying the surface treatment agent. Apply image enhancement and median filtering algorithms to eliminate image brightness unevenness and image noise. Then use the threshold method to distinguish the voids from the asphalt mortar and coarse aggregate of the porous asphalt mixture. Use the image binarization algorithm to define the void area in each grayscale image as white, and the rest as black.

[0041] The accuracy of the planar and vertical images obtained by the X-ray CT scan is preferably less than 0.1 mm / pixel: the sample size is 100±1 mm in diameter and between 40 mm and 60 mm in height.

[0042] S2. Based on the image information, the depth position and void ratio of each image are calculated according to formula (1) and formula (2), and the synthetic void ratio is calculated according to formula (3):

[0043] h i =p×i (1)

[0044]

[0045] Where:

[0046] h i : The depth position of the i-th image, mm;

[0047] p: vertical resolution of CT scan, mm / layer;

[0048] V i : The void ratio of the i-th picture, %;

[0049] Ai : White area of ​​the ith image, mm 2 ;

[0050] A sum : Area of ​​the sample cross section, mm 2 ;

[0051] n: number of tomographic grayscale images;

[0052] V ave : Sample composite porosity, %;

[0053] Before spraying the surface treatment agent, the sample composite porosity V ave The relative error of the sample void ratio measured by the volume method is no more than 10%. If the relative error exceeds 10%, the threshold needs to be reselected in step (1) for image segmentation and void identification.

[0054] S3. Use formula (4) to calculate the image porosity difference ratio K of the sample before and after spraying the surface treatment agent, and obtain the relationship curve between the porosity difference and the image depth position; use formula (5) to calculate the centroid depth h of the porosity difference in the depth direction ave , and use formula (6) to calculate the centroid depth eccentricity P, where the gap difference centroid depth h ave It is used to characterize the penetration depth, and the void difference centroid depth eccentricity P is used to characterize the penetration uniformity;

[0055]

[0056]

[0057] Where:

[0058] K i : Depth is h i Image void ratio difference ratio at position, %;

[0059] Depth h i Void ratio of the sample image before spraying the surface treatment agent at the position, %;

[0060] Depth h i Void ratio of sample image after spraying surface treatment agent at position, %;

[0061] h ave : Gap difference centroid depth, mm;

[0062] H: thickness of the sample, mm;

[0063] P: Gap difference center of mass eccentricity, %.

[0064] Example 2

[0065] For a commonly used PAC-13 permeable asphalt pavement with a maximum nominal particle size of 13 mm, an indoor molded permeable asphalt mixture sample with a sample diameter of 100 mm and a thickness of 60 mm was calculated and measured using the steps in Example 1.

[0066] The gradation design of permeable asphalt mixture is shown in Table 1. The asphalt adopts SBS modified asphalt that meets the high temperature grade of PG76, and the void ratio of the sample is 23.3%. Indoor damage is applied to the sample through bulk aging and freeze-thaw cycles to simulate the degradation of the material under the combined action of field load and environment. A slow-cracking cationic emulsified asphalt is selected as the surface treatment agent, and its basic properties are shown in Table 2. The spraying amount of the surface treatment agent is 0.4mm / m 2 , 0.6mm / m 2 and 1.2 mm / m 2 , with solid contents of 60%, 40% and 20% respectively. Industrial-grade X-ray CT scanning technology was used to obtain continuous tomographic images of permeable mixture samples before and after surface treatment agent treatment. Before image segmentation, image enhancement and median filtering algorithms were used to eliminate image brightness unevenness and image noise; the threshold method was used to distinguish voids from asphalt mortar and coarse aggregate in permeable asphalt mixtures; the image binarization algorithm was used to define the void area in each grayscale image as white, and the rest as black. The image processing and void identification process is as follows: Figure 1 The X-ray CT scans of the samples before and after spraying had a depth accuracy of 0.1 mm / layer, and the accuracy of each two-dimensional image was 0.67 mm / pixel, with 600 consecutive tomographic images acquired.

[0067] Table 1 Permeable asphalt mixture gradation information

[0068]

[0069]

[0070] Table 2 Basic properties of emulsified asphalt surface treatment agent

[0071]

[0072] The porosity and its corresponding depth position are calculated for each image obtained from the sample before and after spraying. The calculation results are as follows: Figure 2 In addition, the synthetic porosity V of the sample before the surface treatment agent is sprayed is calculated. ave The relative errors of the void ratios of 23.3% measured by the volume method are 0.8%, 2.1% and 9.0%, which are less than 10% and meet the accuracy requirements.

[0073] According to the calculated image porosity data, the image porosity difference ratio K value is further calculated, and the relationship curve between it and the image depth position is obtained, such as Figure 3 The gap difference centroid depth and centroid eccentricity index are calculated using formulas (4)-(6), as shown in Table 3:

[0074] Table 3 Summary of penetration level indicators

[0075] Working conditions <![CDATA[Centroid depth h ave (mm)]]> Center of mass eccentricity P (%) A 17.74 -40.8％ B 24.95 -16.8％ C 42.4 41.3％

[0076] Comparing the three working conditions, it can be found that the centroid depth of working condition C is the largest, which can reach 42.4mm, but this does not mean that the penetration level of working condition C is high. From the centroid deviation rate P index, it can be seen that the centroid deviation rate of working condition C is positive, reaching 41.3%, indicating that although most of the preventive curing agents in working condition C can penetrate the entire sample thickness, most of them are difficult to remain in the gap channel and gather at the bottom of the sample. Comparing working conditions A and B, it can be seen that the centroid depth of working condition B is larger and the absolute value of the centroid deviation rate P is smaller, indicating that the preventive curing agent under working condition C has a higher penetration depth and better penetration uniformity, reflecting the optimal penetration level.

Claims

1. A method for calculating the penetration level of a porous asphalt pavement surface treatment agent, characterized in that: The following steps are involved: S1. Use industrial-grade X-ray CT scanning to obtain continuous tomographic grayscale images of porous asphalt mixture samples before and after spraying the surface treatment agent. Preprocess the images, then use the threshold method to distinguish the voids from the asphalt mortar and coarse aggregate of the porous asphalt mixture, and use the image binarization algorithm to define the void area in each grayscale image as white, and the rest as black; S2. Based on the image information, the depth position and void ratio of each image are calculated according to formula (1) and formula (2), and the synthetic void ratio is calculated according to formula (3): h i =p×i (1) Where: h i : The depth position of the i-th image, mm; p: vertical resolution of CT scan, mm / layer; V i : The void ratio of the i-th picture, %; A i : White area of ​​the ith image, mm 2 ; A sum : Area of ​​the sample cross section, mm 2 ; n: number of tomographic grayscale images; V ave : Sample composite porosity, %; S3. Calculate the image porosity difference ratio K value of the sample before and after spraying the surface treatment agent using formula (4) to obtain a relationship curve between the porosity difference and the image depth position; Formula (5) is used to calculate the centroid depth h of the gap difference in the depth direction: ave , and use formula (6) to calculate the centroid depth eccentricity P, where the gap difference centroid depth h ave It is used to characterize the penetration depth, and the void difference centroid depth eccentricity P is used to characterize the penetration uniformity; Where: K i : Depth is h i Image void ratio difference ratio at position, %; Depth h i Void ratio of the sample image before spraying the surface treatment agent at the position, %; Depth h i Void ratio of sample image after spraying surface treatment agent at position, %; h ave : Gap difference centroid depth, mm; H: thickness of the sample, mm; P: Gap difference center of mass eccentricity, %.

2. The method for calculating the penetration level of a porous asphalt pavement surface treatment agent according to claim 1, characterized in that: In step S1, the accuracy of the planar and vertical images obtained by the X-ray CT scan is less than 0.1 mm / pixel.

3. The method for calculating the penetration level of a porous asphalt pavement surface treatment agent according to claim 1, characterized in that: In step S1, the porous asphalt mixture sample has a diameter of 100±1 mm and a height of 40 mm to 60 mm.

4. The method for calculating the penetration level of a porous asphalt pavement surface treatment agent according to claim 1, characterized in that: In step S1, the preprocessing refers to applying image enhancement and median filtering algorithms to eliminate image brightness unevenness and image noise.

5. The method for calculating the penetration level of a porous asphalt pavement surface treatment agent according to claim 1, 2, 3 or 4, characterized in that: In step S2, before the surface treatment agent is sprayed, the sample synthesis porosity V ave The relative error of the sample void ratio tested by the volume method is not greater than 10%. If the relative error exceeds 10%, it is necessary to reselect the threshold in step S1 for image segmentation and void identification.

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