Method for evaluating aging gradient of asphalt pavement material in service

Abstract

The application discloses a kind of in-service asphalt pavement material aging gradient evaluation method, comprising the following steps: S1, obtaining service asphalt surface layer mixture sample;S2, using industrial grade X-ray CT scanning technology to collect the continuous fault gray image of service pavement asphalt mixture sample, and using digital image processing technology to identify and calculate the void area and asphalt mortar film thickness of service surface layer mixture sample depth direction;S3, according to the void area and asphalt mortar film thickness, the service asphalt mixture sample is classified, and the service asphalt mixture sample is layered cutting, extraction and distillation according to depth direction, to obtain the representative asphalt sample of different depth positions of sample;S4, using total reflection-Fourier infrared spectrum test and analysis method to semi-quantitatively analyze the oxygen absorption functional group of representative asphalt sample, and the oxidation aging degree of sample is quantitatively characterized.The application can realize the fine evaluation of service asphalt pavement mixture aging gradient.

Description

Technical Field

[0001] This invention relates to the field of road engineering technology, and more specifically to a method for evaluating the aging gradient of in-service asphalt pavement materials. Background Technology

[0002] Aging is a significant factor accelerating pavement deterioration. During long-term service, the pavement surface is in direct contact with the atmosphere, and oxygen continuously penetrates deeper into the pavement through asphalt mortar and micropores, leading to oxidation. Numerous experiments and engineering practices have shown that the porosity characteristics and mixture type of pavement materials have a significant impact on the aging rate. Therefore, it is necessary to accurately quantify the aging process of asphalt pavement materials. Currently, the on-site aging level of pavement is characterized by measuring the overall asphalt aging degree of a specific layer. However, considering the unevenness of aging within the pavement, a single aging degree representation cannot accurately represent the aging trend. It is necessary to refine the aging degree at different depths of the pavement and select reliable methods to further investigate the development of pavement aging. Summary of the Invention

[0003] The purpose of this invention is to disclose a method for evaluating the aging gradient of in-service asphalt pavement materials. By combining X-ray CT scanning technology and infrared spectroscopy technology, continuous tomographic images of the surface layer of in-service asphalt mixtures are captured. The distribution and changes of the void structure in the surface layer of pavement core samples are identified through image processing, the thickness of asphalt mortar is quantitatively characterized, and the degree of oxidation of asphalt at different depths of the surface layer of the pavement is quantitatively analyzed, providing technical support for evaluating the aging gradient of in-service asphalt pavement materials.

[0004] To achieve the above objectives, this invention provides a method for evaluating the aging gradient of in-service asphalt pavement materials, comprising the following steps:

[0005] S1, Obtain samples of in-service asphalt pavement mixture;

[0006] S2. X-ray CT scanning technology was used to acquire continuous fault grayscale images of asphalt mixture samples of in-service pavement, and digital image processing technology was used to identify and calculate the void area and asphalt mortar film thickness in the depth direction of the in-service pavement mixture samples.

[0007] S3. The service asphalt mixture samples are classified according to the void area and the thickness of the asphalt mortar film. The service asphalt mixture samples are then cut, extracted and distilled in layers according to the depth direction to obtain representative asphalt samples at different depth positions.

[0008] S4. The oxygen-absorbing functional groups of representative asphalt samples were semi-quantitatively analyzed using total reflectance-Fourier transform infrared spectroscopy to quantify the degree of oxidative aging of the samples.

[0009] As a further improvement of the present invention, in step S1, the asphalt pavement mixture sample is an asphalt pavement material with different service years in actual use. The method of obtaining the sample is to drill cores on the pavement in the field. The sample size is 150 mm in diameter and the height is the actual pavement thickness, usually 180 mm.

[0010] As a further improvement of the present invention, in step S2, the asphalt mixture is a complex multiphase material containing asphalt, aggregates, and voids. Threshold segmentation is applied to identify and extract void regions. The extracted void regions are then analyzed to calculate the void size, which is ultimately used to evaluate the void size across the entire depth range of the asphalt mixture.

[0011] As a further improvement of the present invention, the calculation of the asphalt mortar film thickness in step S2 includes the following steps:

[0012] First, the acquired image is preprocessed to improve the accuracy of subsequent processing. Possible preprocessing steps include image smoothing, noise removal, and contrast enhancement. Noisy pixels in digital images are often significantly higher or lower than surrounding pixels, which will severely affect image segmentation and reduce the accuracy of identifying the volume composition of asphalt mixtures. Median filtering is used to sort the grayscale values ​​of pixels within a region and then replace the pixel values ​​within the region with the median value to remove noise.

[0013] Secondly, regarding image segmentation threshold selection and edge processing, the tomographic scan image of the asphalt mixture is divided into two parts: one part consisting of coarse aggregate and the other part consisting of asphalt mortar (asphalt plus fine aggregate and voids). Using a local thresholding method, the original image is divided into 16 equally sized rectangles. The threshold is calculated using the Otsu's method (maximum inter-class variance method), as follows:

[0014]

[0015]

[0016]

[0017] 0 Otsu =argmax[ω0(μ0-μ T ) 2 +ω1(μ1-μ T ) 2 (4)

[0018] Where: n i —The number of pixels with a grayscale value of i;

[0019] N—The total number of pixels in the target area;

[0020] L — Gray level 256;

[0021] k — the assumed grayscale threshold;

[0022] θ Otsu —Optimal grayscale threshold;

[0023] Then, the processed images are addressed by processing the minute pores inside the aggregate, the localized interconnections at the aggregate edges, the elongated synapses at the aggregate edges, and noise. Edge detection is performed using the watershed algorithm, as well as dilation and erosion algorithms.

[0024] As a further improvement of the invention, in step S2, the aggregates are segmented and marked, wherein those less than 1.18 mm are defined as the mortar phase. The mortar thickness is obtained at the boundary pixels of the marked aggregates with a search radius of 180 pixels. To quantify the thickness of the asphalt mortar film, T is introduced. m The average thickness of the mortar film is represented by the following calculation method:

[0025]

[0026] Where: i — the number of images used for calculation; (5)

[0027] N—Number of pixels in the coarse aggregate outline of the image;

[0028] T—the distance from a point on one aggregate to another, in mm;

[0029] As a further improvement of the present invention, in step S3, the top 4cm layer of the road core sample is cut into three 1.3cm thin slices, labeled S1, S2, and S3 respectively. The cut slices are then crushed, dissolved, extracted, and distilled to obtain the asphalt binder in the asphalt mixture for subsequent testing.

[0030] As a further improvement of the present invention, in step S3, the organic solvent used for dissolution, extraction and distillation is trichloroethylene.

[0031] As a further improvement of the present invention, in step S4, the carbonyl index is used to quantify the degree of oxidation of asphalt, and the specific calculation method is as follows:

[0032]

[0033]

[0034] In the formula: I C＝O —Carbonyl index;

[0035] — Represents the relative area of ​​the absorption peak near wavenumber 1700;

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows: an evaluation method for aging gradient of in-service asphalt pavement materials. Compared with the traditional on-site aging evaluation method, the pavement layer cutting and extraction method adopted in the present invention can effectively obtain the aging gradient characteristics of the pavement, and provide technical support for obtaining the diffusion and reaction of oxygen in the pavement under on-site environmental conditions.

[0037] Compared with traditional asphalt mixture volume parameter testing, this invention obtains continuous tomographic images of in-service pavement mixtures through X-ray CT scanning, identifies the distribution of void structure and quantifies the thickness of asphalt mortar film through digital image processing and analysis technology, digitally characterizes the volume parameter features that affect the aging development rate, and, combined with aging indicators, clarifies the influence of material volume parameters on pavement aging gradient.

[0038] Compared with traditional indicators for characterizing the aging of asphalt in the field, this invention proposes an indicator that can quantitatively characterize the degree of aging of asphalt in service pavement by analyzing the infrared spectra of asphalt before and after aging and curing, thereby achieving a refined evaluation of the aging gradient of asphalt pavement materials in service. Attached Figure Description

[0039] Figure 1 This invention relates to a sample preparation method and experimental process for an evaluation method of aging gradient of in-service asphalt pavement materials. Detailed Implementation

[0040] The present invention will now be described in detail with reference to the embodiments shown in the accompanying drawings. However, it should be noted that these embodiments are not intended to limit the present invention. Equivalent changes or substitutions in function, method, or structure made by those skilled in the art based on these embodiments are all within the scope of protection of the present invention.

[0041] Please refer to Figure 1 The present invention illustrates a specific embodiment of an aging gradient evaluation method for in-service asphalt pavement materials.

[0042] A method for evaluating the aging gradient of in-service asphalt pavement materials includes the following steps:

[0043] S1, Obtain samples of in-service asphalt pavement mixture.

[0044] The asphalt pavement mixture samples are asphalt pavement materials with different service years. The method of obtaining them is to drill cores on the pavement in the field. The sample size is 150 mm in diameter and the height is the actual pavement thickness.

[0045] In one embodiment, a cylindrical road surface sample is obtained using a core drill barrel with a diameter of 150 mm, based on a pre-selected core section.

[0046] S2 uses X-ray CT scanning technology to acquire continuous fault grayscale images of asphalt mixture samples of in-service pavement, and uses digital image processing technology to identify and calculate the void areas and asphalt mortar film thickness in the depth direction of the in-service pavement mixture samples.

[0047] Because the size of the voids affects the oxygen diffusion rate, and thus the oxidation rate of the pavement, calculating the void region is mainly used to ensure that the samples in the statistical analysis have similar void characteristics. The thickness of the asphalt mortar film serves as an indicator to distinguish different types of asphalt mixtures.

[0048] Industrial-grade X-ray CT scanning technology was used to acquire continuous tomographic grayscale images of road mixture samples; image enhancement, filtering and segmentation algorithms were used to eliminate image noise and identify voids and asphalt mortar areas in the images.

[0049] Specifically, threshold segmentation is applied to identify and extract void regions, and the extracted void regions are analyzed to calculate the void size, which is used to evaluate the void size across the entire depth range of the asphalt mixture.

[0050] The calculation of asphalt mortar film thickness includes: preprocessing the acquired image to improve the accuracy of subsequent processing. Preprocessing steps include image smoothing, noise removal, and contrast enhancement. Spatial filtering algorithms in Matlab are used to remove spike noise from the grayscale image while ensuring the clarity of image edges as much as possible. Median filtering is used to sort the grayscale values ​​of pixels within a region, and the median value is used to replace the pixel values ​​within the region to remove noise. Direct grayscale transformation is used to enhance contrast and improve the image display effect. The Matlab function for enhancing contrast is `imadjust(f,[low_in,high_in],[low_out,high_out])`.

[0051] For image segmentation threshold selection and edge processing, the tomographic scan image of asphalt mixture is divided into two parts: one part is coarse aggregate, and the other part is asphalt mortar. Using a local threshold segmentation method, the original image is divided into 16 equally sized rectangles. The threshold is calculated using the Otsu's method, as follows:

[0052]

[0053]

[0054]

[0055] 0 Otsu =argmax[ω0(μ0-μ T ) 2 +ω1(μ1-μ T) 2 (4)

[0056] Where: n i —The number of pixels with a grayscale value of i;

[0057] N—The total number of pixels in the target area;

[0058] L — Gray level 256;

[0059] k — the assumed grayscale threshold;

[0060] θ Otsu —Optimal grayscale threshold;

[0061] The processed image is addressed by employing image filling algorithms, watershed algorithms, and dilation and erosion algorithms to remove micropores, localized concatenation at aggregate edges, elongated synapses at aggregate edges, and noise. Edge detection is performed using the watershed algorithm and the dilation-erosion algorithm. Specifically, the `bwareaopen(f,area)` function in Matlab is used to remove pore areas. The watershed algorithm in Matlab is used for segmentation, and the parameter `x` of the function `imextendedmin(D,x)` is adjusted appropriately. The `imerode` and `imdilate` functions in Matlab are used for morphological image erosion and dilation operations to remove elongated synapses and noise at aggregate edges.

[0062] Aggregate segmentation and marking are performed, with particles smaller than 1.18 mm defined as the mortar phase. The mortar thickness is obtained at the boundary pixels of the marked aggregates, with a search radius of 180 pixels, and a T is introduced. m The average thickness of the mortar film is represented by the following calculation method:

[0063]

[0064] In the formula: i — the number of images used for calculation;

[0065] N—Number of pixels in the coarse aggregate outline of the image;

[0066] T – The distance from a point on one aggregate to another, in mm.

[0067] S3. The service asphalt mixture samples are classified according to the void area and the thickness of the asphalt mortar film. The service asphalt mixture samples are then cut, extracted and distilled in layers according to the depth direction to obtain representative asphalt samples at different depth positions.

[0068] The top 4cm layer of the sample was divided into three layers, each approximately 1.3cm long. The specimen was immersed in trichloroethylene for at least 6 hours to ensure complete dissolution of the asphalt. Aggregates and mineral powders were removed from the solution using a high-speed centrifuge. Finally, the solution was distilled using a rotary evaporator to obtain the asphalt sample to be tested.

[0069] In one embodiment, the organic solvent used for dissolution, extraction, and distillation is trichloroethylene.

[0070] S4. The oxygen-absorbing functional groups of representative asphalt samples were semi-quantitatively analyzed using total reflectance-Fourier transform infrared spectroscopy to quantify the degree of oxidative aging of the samples.

[0071] The carbonyl index is used to quantify the degree of oxidation of asphalt. The specific calculation method is as follows:

[0072]

[0073]

[0074] In the formula: I C＝O —Carbonyl index;

[0075] — Represents the relative area of ​​the absorption peak near wavenumber n.

[0076] In one embodiment, field-aged samples (S1, S2, S3) with different service times were tested using total reflectance-infrared spectroscopy in a wavenumber range of 600 cm⁻¹. -1 Up to 4000cm -1 Sixteen scans were performed. Each test group included at least two parallel specimens. For better comparison and analysis, the infrared spectra were baseline-calibrated using relevant software, and carbonyl indices were used to quantify the aging level of the samples. Field-aged samples with service lives of 15 and 20 years (denoted as YH and LX) were selected, and the results are shown in Table 1. AK and SMA represent different types of asphalt mixtures; AK represents dense asphalt mixtures, and SMA represents asphalt mastic mixtures. It can be observed that both service life and mixture type significantly affect the degree of pavement oxidation, and the degree of oxidation is also affected by pavement depth, mainly showing a decrease in oxidation level with increasing pavement depth. Due to the significant difference between S1 and S2, the relationship between depth difference and mixture type was further analyzed, and the results are shown in Table 2. It can be observed that the SMA mixture has a larger mortar film thickness than the AK mixture. Furthermore, the larger mortar film thickness leads to a greater variation in the 0-2 cm depth range, indicating that the thicker mortar film inhibits oxygen permeation.

[0077] In summary, the service life and mixture type of asphalt pavement significantly affect the oxidation degree of asphalt pavement. With increasing service life, the oxidation degree of asphalt pavement increases, indicating that the pavement materials are affected by oxidative aging. Furthermore, different types of mixtures also lead to differences in the degree of oxidation. SMA mixtures have a greater mortar film thickness compared to AK mixtures. A thicker mortar film can inhibit oxygen penetration, thereby slowing down the oxidation degree of asphalt pavement. The results of this case study deepen our understanding of the mechanisms and influencing factors of asphalt pavement aging. By assessing and predicting the degree of pavement aging, more effective maintenance strategies can be developed to extend the service life of pavements. In addition, this research provides guidance for optimizing mixture formulations and design.

[0078] Table 1. Aging degree of on-site aging samples

[0079]

[0080] Table 2 Differences between mortar film thickness and road surface depth

[0081]

[0082] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for evaluating the aging gradient of in-service asphalt pavement materials, characterized in that, Includes the following steps: S1, Obtain samples of in-service asphalt pavement mixture; S2. X-ray CT scanning technology was used to acquire continuous fault grayscale images of asphalt mixture samples of in-service pavement, and digital image processing technology was used to identify and calculate the void area and asphalt mortar film thickness in the depth direction of the in-service pavement mixture samples. S3. The service asphalt mixture samples are classified according to the void area and the thickness of the asphalt mortar film. The service asphalt mixture samples are then cut, extracted and distilled in layers according to the depth direction to obtain representative asphalt samples at different depth positions. S4. The oxygen-absorbing functional groups of representative asphalt samples were semi-quantitatively analyzed using total reflectance-Fourier transform infrared spectroscopy to quantify the degree of oxidative aging of the samples. The calculation of the asphalt mortar film thickness in step S2 includes the following steps: The acquired image undergoes preprocessing to improve the accuracy of subsequent processing. Preprocessing steps include image smoothing, noise removal, and contrast enhancement. Median filtering is used to sort the grayscale values ​​of pixels within a region, and the median value is then used to replace the pixel values ​​within the region to remove noise. For image segmentation threshold selection and edge processing, the tomographic scan image of asphalt mixture is divided into two parts: one part is coarse aggregate, and the other part is asphalt mortar. Using a local threshold segmentation method, the original image is divided into 16 equally sized rectangles. The threshold is calculated using the Otsu's method, as follows: （1） （2） （3） （4） In the formula: —The number of pixels with a grayscale value of i; —The total number of pixels in the target area; — 256 gray levels; k — the assumed grayscale threshold; —Optimal grayscale threshold; The processed images are processed using image filling algorithms, watershed algorithms, and dilation and erosion algorithms to address issues such as small holes inside the aggregate, local cascading at the aggregate edges, slender synapses at the aggregate edges, and noise. Edge detection is then performed using the watershed algorithm and the dilation and erosion algorithms. In step S2, the aggregates are segmented and marked, where particles smaller than 1.18 mm are defined as the mortar phase. The mortar thickness is obtained at the boundary pixels of the marked aggregates with a search radius of 180 pixels. The average thickness of the mortar film is represented by the following calculation method: （5） In the formula: —The number of images used for calculation; —Number of pixels in the coarse aggregate outline of the image; — The distance from a point on one aggregate to another, in mm.

2. The method for evaluating the aging gradient of in-service asphalt pavement materials according to claim 1, characterized in that, In step S1, the asphalt pavement mixture samples are asphalt pavement materials with different service years. The method of obtaining the samples is to drill cores on the pavement in the field. The sample size is 150 mm in diameter and the height is the actual pavement thickness.

3. The method for evaluating the aging gradient of in-service asphalt pavement materials according to claim 1, characterized in that, In step S2, threshold segmentation is applied to identify and extract void regions, and the extracted void regions are analyzed to calculate the size of the voids, which is used to evaluate the void size across the entire depth range of the asphalt mixture.

4. The method for evaluating the aging gradient of in-service asphalt pavement materials according to claim 1, characterized in that, In step S3, the 4 cm deep portion of the surface core sample is cut into three thin slices of 1.3 cm each, and each slice is marked. The cut slices are then crushed, dissolved, extracted, and distilled to obtain the asphalt binder in the asphalt mixture for subsequent testing.

5. The method for evaluating the aging gradient of in-service asphalt pavement materials according to claim 4, characterized in that, In step S3, the organic solvent used for dissolution, extraction, and distillation is trichloroethylene.

6. The method for evaluating the aging gradient of in-service asphalt pavement materials according to claim 1, characterized in that, In step S4, the carbonyl index is used to quantify the degree of oxidation of asphalt. The specific calculation method is as follows: （6） （7） In the formula: —Carbonyl index; — Represents the relative area of ​​the absorption peak near wavenumber n.

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