A method and system for evaluating aging characteristics of road petroleum asphalt and storage medium

Abstract

The present invention discloses a method and system for evaluating the aging characteristics of road petroleum asphalt, as well as a storage medium. The method includes the following steps: obtaining standard asphalt samples of varying degrees of aging and dissolving them in equal volumes of a color-developing solvent to obtain corresponding asphalt sample solutions; aspirating each asphalt sample solution and dropping it onto the center of a paper-based carrier 1 to obtain a paper-based carrier 2 having the corresponding asphalt sample solution diffused thereon; capturing images of the diffusion regions on the surfaces of each paper-based carrier 2, calculating the diffusion characteristic parameters of the corresponding diffusion regions, and determining an aging characteristic evaluation model based on each diffusion characteristic parameter using multiple linear regression analysis; determining an aging index (AI) corresponding to the asphalt sample to be tested by obtaining a diffusion characteristic image of the asphalt sample to be tested and calculating the diffusion characteristic parameters of the diffusion region; and determining the aging degree of the asphalt sample to be tested based on the aging index range. The present invention aims to rapidly obtain the aging characteristics of the asphalt sample to be tested.

Description

Technical Field

[0001] The present invention relates to the technical field of road materials, and in particular to a method and system for evaluating aging characteristics of road petroleum asphalt, and a storage medium. Background Art

[0002] Asphalt pavement materials inevitably age during use. Aging increases asphalt brittleness and deteriorates aggregate adhesion, ultimately leading to pavement defects such as cracking and potholes. Currently, commonly used asphalt aging evaluation methods include the following: First, evaluation methods based on changes in physical properties, such as the penetration aging index in the American Society for Testing and Materials (ASTM) standard D5-13 (based on the ratio of penetration before and after aging, typically required to be no less than 55%) and the softening point increment in ASTM D36 (required to be no less than 8°C). These methods are simple to use but have limited sensitivity. Sample preparation and testing typically take 3-24 hours (including time spent extracting, recovering, and drying the sample), and the equipment costs range from 50,000 to 100,000 yuan. Second, evaluation methods based on changes in rheological properties, such as the dynamic shear rheometer (DSR) test (AASHTOT315) specified in the US SHRP program, calculate the rutting factor aging index by measuring changes in the complex shear modulus G and phase angle δ before and after aging. This method has high sensitivity but has strict requirements on sample preparation, long test cycle (3-24 hours) (including the time spent on mixture extraction and sample drying), and high equipment cost (300,000-500,000 yuan). The third evaluation method is based on the change of chemical composition: such as the Fourier transform infrared spectroscopy (FTIR) carbonyl aging index (calculation of 1700cm before and after aging). - ¹) and gel permeation chromatography (GPC) molecular weight distribution changes. These methods directly reflect changes at the molecular level, but are complex and require specialized personnel. The equipment is expensive (approximately 300,000-400,000 RMB for FTIR and 800,000-1,000,000 RMB for GPC), and the testing cycle is long (typically 5-24 hours), including time spent extracting, recovering, and drying the sample.

[0003] In summary, the main problems with existing technologies include: long evaluation cycles, which make it difficult to meet the needs of rapid on-site testing; high equipment costs, which limit their promotion and application; complex operations, and high technical requirements for personnel; and some methods lack sensitivity and cannot accurately reflect the early aging status.

[0004] The existing invention patent with patent publication number CN119023559A discloses a method for evaluating the longitudinal aging behavior of asphalt pavement materials. This method is innovative in the quantitative analysis of longitudinal aging behavior, but uses a hollow double-cylindrical test mold structure. The test mold structure is complex and difficult to manufacture and assemble. It is prone to problems such as poor sealing and uneven distribution of regeneration agents, which makes the test mold processing cost high, the experimental repeatability is difficult to ensure, and it is difficult to promote and apply in actual projects. In addition, the ultraviolet aging conditions are disconnected from the actual environment, so that the experimental results may overestimate or underestimate the actual degree of aging and lack the ability to predict long-term aging behavior. At the same time, the definition of "continuous aging zone" and "stable aging zone" relies on subjective judgment of curve trends and lacks quantitative standards. The evaluation results may deviate due to operator experience or different data processing methods, making the evaluation accuracy low and unable to meet the needs of asphalt pavement anti-aging performance evaluation. Summary of the Invention

[0005] The main purpose of the present invention is to provide a method and system for evaluating the aging characteristics of road petroleum asphalt, and a storage medium, aiming to solve the technical problem that the existing asphalt pavement anti-aging performance evaluation method is not cost-effective.

[0006] To achieve the above object, the present invention provides a method for evaluating the aging characteristics of road petroleum asphalt, the method comprising the following steps: Step 1, obtaining standard asphalt samples of different aging degrees and dissolving them in the same volume of a chromogenic solvent to obtain corresponding asphalt sample solutions, wherein the mass volume ratio of each standard asphalt sample to the chromogenic solvent is (1-5) g:100 mL;

[0007] Step 2: aspirate a preset amount of each asphalt sample solution and drop it onto the center of the paper-based carrier 1. Let it stand for 20±5 minutes to allow each sample droplet to fully migrate on the corresponding paper-based carrier. Finally, dry it at room temperature to obtain a paper-based carrier 2 with the corresponding asphalt sample solution diffused thereon.

[0008] Step 3: Capture images of the diffusion areas on the surface of each paper-based carrier 2 and calculate the diffusion characteristic parameters of the diffusion areas corresponding to each paper-based carrier 2. The diffusion characteristic parameters include diffusion area ratio, color gradient value, and edge fractal dimension.

[0009] Step 4: Determine the aging characteristic evaluation formula based on the diffusion characteristic parameters of the diffusion area corresponding to each paper-based carrier 2 according to the multivariate linear regression analysis to obtain the weight coefficient corresponding to each parameter, so as to determine the aging characteristic evaluation model. The aging characteristic evaluation model is: AI = w1 × diffusion area ratio + w2 × color gradient value + w3 × edge fractal dimension, where w1, w2, and w3 are the weight coefficients of each parameter, respectively, and AI is the aging index;

[0010] In step 5, the diffusion characteristic image of the asphalt sample to be tested is obtained using steps 1-3, and the diffusion characteristic parameters of the diffusion area are calculated. The diffusion characteristic parameters are substituted into the aging characteristic evaluation model in step 4 to determine the aging index AI corresponding to the asphalt sample to be tested, and the aging degree of the asphalt sample to be tested is determined according to the aging index range, wherein the aging index range is mapped to the aging degree.

[0011] Optionally, in step 1, the color-developing solvent is prepared by uniformly mixing a color developer and a dissolving agent, the color developer is oil-soluble Sudan red, and the dissolving agent is one or two of trichloroethylene, carbon disulfide, and tetrahydrofuran.

[0012] Optionally, in step 2, each paper-based carrier 1 is a cellulose filter paper with a pore size of 10±1 μm and a thickness of 0.2±0.02 mm.

[0013] Optionally, before step 2, the method further includes: placing each paper-based carrier 1 in a constant temperature and humidity insulation cover with a temperature of 25±1° C. and a relative humidity of 50±5% for equilibration for 20±5 minutes.

[0014] Optionally, in step 3, the diffusion area ratio is the diffusion area of different aged asphalt samples divided by the theoretical maximum diffusion area, wherein the diffusion area of different aged asphalt samples is obtained by binarizing the corresponding collected images and counting the pixels, and the theoretical maximum diffusion area is the diffusion area of the unaged asphalt sample with the same solvent volume under the same conditions.

[0015] Optionally, in step 3, the color gradient value is obtained by converting the corresponding RGB image into the HSV color space and calculating the square of the standard deviation of the H channel within the diffusion area.

[0016] Optionally, in step 3, the edge fractal dimension is calculated by the box counting method, and the calculation formula is: D=-lim[log(N(ε)) / log(ε)], where N(ε) is the number of boxes required to cover the edge, and ε is the box size.

[0017] Optionally, in step 5, the mapping relationship between the aging index AI range and the aging degree is AI<0.3 indicating no aging or slight aging, 0.3≤AI<0.5 indicating moderate aging, 0.5≤AI<0.8 indicating severe aging, and AI≥0.8 indicating extreme aging.

[0018] In addition, in order to achieve the above-mentioned purpose, the present invention also provides a road petroleum asphalt aging characteristics evaluation system, which stores a road petroleum asphalt aging characteristics evaluation program. When the road petroleum asphalt aging characteristics evaluation program is executed by a processor, the processor executes the steps of the road petroleum asphalt aging characteristics evaluation method as described in any one of the above-mentioned items.

[0019] In addition, in order to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, which stores a road petroleum asphalt aging characteristics evaluation program. When the road petroleum asphalt aging characteristics evaluation program is executed by a processor, the processor executes the steps of the road petroleum asphalt aging characteristics evaluation method as described in any one of the above-mentioned items.

[0020] Beneficial effects:

[0021] The present invention provides a method for evaluating the aging characteristics of road petroleum asphalt. This method involves dissolving different aged asphalt samples in a color-developing solvent and allowing them to migrate and diffuse under constant temperature, humidity, and windless conditions. An aging characteristics evaluation model is then created based on the diffusion characteristic information, ultimately enabling rapid acquisition of the aging characteristics of the asphalt sample to be tested. This method is based on the molecular aggregation characteristics of solution-type aged asphalt and its microfluidic diffusion characteristics on a paper-based carrier. By measuring multidimensional parameters such as diffusion area ratio, color gradient value, and edge fractal dimension, a comprehensive evaluation model for the degree of asphalt aging is established. Compared to traditional evaluation methods, the present invention offers significant advantages such as high evaluation efficiency, low equipment and testing costs, and high evaluation accuracy. Furthermore, it is portable and flexible, has a wide range of applications, is easy to operate, and allows for multidimensional evaluation. This provides low-cost and efficient technical support for asphalt material performance development, pavement maintenance decisions, and waste pavement recycling. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The present invention provides a flow chart of an embodiment of a method for evaluating aging characteristics of road petroleum asphalt;

[0023] Figure 2 for Figure 1 The process is shown in a simplified diagram.

[0024] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0025] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0026] like Figure 1-2 As shown, the present invention provides a flow chart of an embodiment of a method for evaluating aging characteristics of road petroleum asphalt, wherein the method comprises the following steps:

[0027] Step 1: Obtain standard asphalt samples of varying degrees of aging and dissolve them in equal volumes of a color-developing solvent to obtain corresponding asphalt sample solutions. The mass-to-volume ratio of each standard asphalt sample to color-developing solvent is (1-5) g:100 mL. Preferably, the asphalt sample solution is uniformly stirred clockwise at 60±5 rpm using a glass rod for 3±0.5 minutes and moderately shaken for 30±5 seconds. The mixed solution is then placed in an ultrasonic cleaner (frequency 40±2 kHz, temperature 30±2°C) for 20±2 minutes to form a uniform, stable solution of the aged asphalt sample. The color-developing solvent is prepared by uniformly mixing a color developer and a solvent. The color developer is oil-soluble Sudan Red, and the solvent is one or two of trichloroethylene, carbon disulfide, or tetrahydrofuran, preferably trichloroethylene, or a mixture of trichloroethylene and carbon disulfide in a volume ratio of 3:1.

[0028] Step 2: Take a preset amount of each asphalt sample solution and drop it on the center of the paper-based carrier 1. Let it stand for 20±5 minutes to allow each sample droplet to fully migrate on the corresponding paper-based carrier. Finally, dry it at room temperature for 10 minutes to obtain a paper-based carrier 2 with the corresponding asphalt sample solution diffused. Before step 2, each paper-based carrier 1 needs to be placed in a constant temperature and humidity insulation cover with a temperature of 25±1°C and a relative humidity of 50±5% for equilibration for 20±5 minutes. Each paper-based carrier 1 is a cellulose filter paper with a pore size of 10±1μm and a thickness of 0.2±0.02mm. The migration and diffusion of the aged asphalt solution is carried out under constant temperature, humidity and windless conditions, and a micropipette is used to accurately take 20±0.5μL of solution-type aged asphalt sample droplets, which are vertically and lightly dropped on the precise center position of the paper-based carrier 1. Then, let it stand for 20±5 minutes to allow the droplets to fully diffuse and migrate on the paper-based carrier 1.

[0029] Step 3: Capture images of the diffusion areas on the surface of each paper-based carrier 2 and calculate the diffusion characteristic parameters of the corresponding diffusion areas on each paper-based carrier 2. These diffusion characteristic parameters include the diffusion area ratio, color gradient value, and edge fractal dimension. The diffusion area ratio is the diffusion area of the different aged asphalt samples divided by the theoretical maximum diffusion area. The diffusion area of the different aged asphalt samples is obtained by binarizing the corresponding captured images and counting pixels. The theoretical maximum diffusion area is the diffusion area of an unaged asphalt sample with the same solvent volume under the same conditions. The color gradient value is obtained by converting the corresponding RGB image to the HSV color space and calculating the square of the standard deviation of the H channel within the diffusion area. The edge fractal dimension is calculated using the box counting method using the formula: D = -lim[log(N(ε)) / log(ε)], where N(ε) is the number of boxes required to cover the edge and ε is the box size. Preferably, images of the diffusion areas on the paper-based carrier 2 are captured using a high-resolution digital microscope at 50±5x magnification, with an image resolution of no less than 300 dpi. Image analysis software is used to quantitatively analyze the sample diffusion characteristics.

[0030] Step 4: The diffusion characteristic parameters of the diffusion areas corresponding to each paper-based carrier 2 are analyzed using a multiple linear regression analysis to determine an aging characteristic evaluation formula to obtain weight coefficients corresponding to each parameter, thereby determining an aging characteristic evaluation model. The aging characteristic evaluation model is: AI = w1 × diffusion area ratio + w2 × color gradient value + w3 × edge fractal dimension, where w1, w2, and w3 are weight coefficients for each parameter, respectively, and AI is the aging index. Preferably, if standard asphalt samples with different degrees of aging, such as unaged, short-term aging (TFOT - 5h / 7.5h / 10h), long-term thermal oxidative aging (PAV - 10h / 20h / 40h), and long-term ultraviolet aging (UV - 6d / 12d / 24d), are used, the diffusion characteristic parameter values of the samples with different aging degrees are analyzed, and the weight coefficients of each parameter are determined through multiple linear regression analysis, an aging characteristic evaluation model is established as AI = 0.45 × diffusion area ratio + 0.35 × color gradient value + 0.20 × edge fractal dimension.

[0031] In step 5, the diffusion characteristic image of the asphalt sample to be tested is obtained by adopting steps 1-3, and the diffusion characteristic parameters of the diffusion area are calculated, and the diffusion characteristic parameters are substituted into the aging characteristic evaluation model in step 4 to determine the aging index AI corresponding to the asphalt sample to be tested, and the aging degree of the asphalt sample to be tested is determined according to the aging index range, wherein the aging index range is in a mapping relationship with the aging degree, that is, the mapping relationship between the aging index AI range and the aging degree is AI<0.3 indicates no aging or slight aging, good road performance, and no special treatment is required; 0.3≤AI<0.5 indicates moderate aging, road performance begins to decline, and preventive maintenance is required; 0.5≤AI<0.8 indicates severe aging, road performance significantly deteriorates, and restorative maintenance is required; AI≥0.8 indicates extreme aging, road performance has been seriously damaged, and replacement or regeneration is required.

[0032] The present invention provides a method for evaluating the aging characteristics of road petroleum asphalt. This method involves dissolving different aged asphalt samples in a color-developing solvent and allowing them to migrate and diffuse under constant temperature, humidity, and windless conditions. An aging characteristics evaluation model is then created based on the diffusion characteristic information, ultimately enabling rapid acquisition of the aging characteristics of the asphalt sample to be tested. This method is based on the molecular aggregation characteristics of solution-type aged asphalt and its microfluidic diffusion characteristics on a paper-based carrier. By measuring multidimensional parameters such as diffusion area ratio, color gradient value, and edge fractal dimension, a comprehensive evaluation model for the degree of asphalt aging is established. Compared to traditional evaluation methods, the present invention offers significant advantages such as high evaluation efficiency, low equipment and testing costs, and high evaluation accuracy. Furthermore, it is portable and flexible, has a wide range of applications, is easy to operate, and allows for multidimensional evaluation. This provides low-cost and efficient technical support for asphalt material performance development, pavement maintenance decisions, and waste pavement recycling.

[0033] Furthermore, in order to better illustrate the process steps of the present invention, the following is a detailed description through specific examples.

[0034] Example 1

[0035] S1: Weigh the sample and dissolve the color developing reagent.

[0036] (1) Using an electronic balance with an accuracy of 0.001g, 0.1g of standard asphalt samples of different aging degrees (including unaged, short-term aged (TFOT - 5h / 7.5h / 10h), long-term thermal oxidative aged (PAV - 10h / 20h / 40h) and long-term ultraviolet aged (UV - 6d / 12d / 24d) standard asphalt samples of different aging degrees) were weighed respectively; (2) Using a measuring cylinder, 10mL of trichloroethylene was accurately measured as a solvent; (3) Using an electronic balance with an accuracy of 0.001g, 0.05g of oil-soluble Sudan red was weighed as a color developer; (4) In a clean beaker, the color developer and the dissolving agent were mixed and stirred thoroughly to prepare a dissolved color developer; (5) The weighed standard asphalt samples of different aging degrees were placed in a beaker containing a dissolving agent. (6) Use a glass rod with a diameter of 5 mm to stir the asphalt sample at a speed of 60 rpm in a clockwise direction for 3 minutes; (7) Cover the container and shake it moderately for 30 seconds to ensure that the asphalt sample is initially dispersed; (8) Place the mixed solution in an ultrasonic cleaner (frequency 40 kHz, temperature 30°C) for 20 minutes; (9) Take out the container and let it stand for 5 minutes to observe whether a uniform and stable solution-type aged asphalt sample is formed. If there is precipitation or suspended matter, the ultrasonic treatment time needs to be extended.

[0037] S2: Migration and diffusion under constant temperature, humidity and windless conditions.

[0038] (1) Select quantitative cellulose filter paper with a pore size of 10 μm, a thickness of 0.2 mm, and a diameter of 90 mm as the carrier for the diffusion of aged asphalt solution; (2) Before the test, use a pencil to gently mark the center point on the back of the paper-based carrier; (3) Place the paper-based carrier in a constant temperature and humidity insulation cover at a temperature of 25°C and a relative humidity of 50% for 20 minutes; (4) Use a micropipette with a range of 10-100 μL to accurately draw a 20 μL droplet of solution-type aged asphalt sample; (5) Place the micropipette perpendicular to the surface of the paper-based carrier, 5±1 mm away from the paper surface, and gently drop the droplet on the precise center position of the paper-based carrier; (6) Let it stand for 20 minutes, during which time the environmental parameters of the insulation cover are kept stable to allow the droplet to fully diffuse and migrate on the paper-based carrier; (7) After the diffusion is completed, carefully remove the paper-based carrier and let it dry naturally at room temperature for 10 minutes.

[0039] S3: Diffusion characteristic information record.

[0040] (1) Use a high-resolution digital microscope at 50x magnification to capture images of the diffusion area on the paper-based support, ensuring that the image resolution is no less than 300 dpi; (2) Save the captured images in a lossless format and transfer them to a computer; (3) Use professional image analysis software (such as ImageJ) to quantitatively analyze the diffusion characteristics of the sample; (4) The specific analysis parameters are calculated as follows:

[0041] a) Diffusion area ratio = (measured diffusion area / theoretical maximum diffusion area) × 100%, where the measured diffusion area is obtained by counting pixels after image binarization, and the theoretical maximum diffusion area is determined based on the diffusion area of an unaged asphalt sample with the same solvent volume under the same conditions.

[0042] b) Color gradient value = variance of H channel in HSV color space. By converting the RGB image to HSV color space, the square of the standard deviation of H channel in the diffusion area is calculated;

[0043] c) Edge Fractal Dimension = Diffusion Edge Fractal Dimension Calculated Using the Box-Counting Method The fractal dimension D of the diffusion edge is calculated using the box-counting method. The formula is: D = lim[log(N(ε)) / log(ε)], where N(ε) is the number of boxes required to cover the edge and ε is the box size.

[0044] S4: Aging characteristics evaluation model.

[0045] (1) According to the diffusion characteristic parameter values of samples of different aging degrees obtained in S3, the weight coefficients of each parameter were determined by multivariate linear regression analysis, and an aging characteristic evaluation model was established: AI = 0.45 × diffusion area ratio + 0.35 × color gradient value + 0.20 × edge fractal dimension.

[0046] (2) Establish a standard aging database to record the AI value range of asphalt samples with different aging degrees as a reference standard for evaluating the aging degree of the samples to be tested.

[0047] S5: Rapid acquisition of aging characteristics of asphalt samples.

[0048] (1) For any sample to be tested, use steps S1 to S3 to obtain its diffusion characteristic image and calculate the diffusion area ratio, color gradient value and edge fractal dimension of the sample to be tested according to the image analysis method; (2) Substitute the calculated parameters into the aging characteristic evaluation model to obtain the sample's aging index AI; (3) Determine the aging degree of the sample based on the AI value range. Among them, AI < 0.3: no aging or slight aging, indicating that the asphalt still has good road performance and does not require special treatment; 0.3 ≤ AI < 0.5: moderate aging, indicating that the asphalt performance has begun to decline and preventive maintenance is required; 0.5 ≤ AI < 0.8: severe aging, indicating that the asphalt performance has significantly deteriorated and restorative maintenance is required; AI ≥ 0.8: extreme aging, indicating that the asphalt has lost its basic road performance and needs to be replaced or regenerated.

[0049] Example 2: Solvent type optimization example.

[0050] In order to determine the best solvent type, based on Example 1, comparative experiments were conducted using different solvents:

[0051] (1) Solvent A: pure trichloroethylene; (2) Solvent B: pure carbon disulfide; (3) Solvent C: pure tetrahydrofuran; (4) Solvent D: a mixture of trichloroethylene and carbon disulfide (volume ratio 3:1).

[0052] Using the same batch of SK70# base asphalt, we prepared samples at three different ages: unaged, aged after 10 hours of TFOT, and aged after 20 hours of PAV. These three asphalt samples were dissolved in the four aforementioned solvents, and diffusion experiments were conducted according to steps S1-S3 of Example 1, with the diffusion characteristic parameters analyzed.

[0053] The results showed that solvents A (trichloroethylene) and D (a mixture of trichloroethylene and carbon disulfide) had the highest degree of differentiation in the diffusion characteristics of asphalt samples of varying degrees of aging, with differences in diffusion area ratio exceeding 45%, color gradient values exceeding 55%, and edge fractal dimensions exceeding 25%. Solvents B and C, on the other hand, had relatively low differentiation, with differences in diffusion characteristic parameters below 30%.

[0054] Therefore, considering both performance and safety, solvent A (trichloroethylene) is recommended as the preferred solvent. When further improvement of the evaluation sensitivity is required, solvent D (a mixture of trichloroethylene and carbon disulfide) can be used.

[0055] Example 3: Paper-based carrier optimization example.

[0056] In order to determine the best paper-based carrier type, based on Example 1, a comparative experiment was conducted using paper-based carriers of different specifications:

[0057] (1) Paper-based carrier A: cellulose filter paper with a pore size of 5 μm and a thickness of 0.15 mm; (2) Paper-based carrier B: cellulose filter paper with a pore size of 10 μm and a thickness of 0.2 mm; (3) Paper-based carrier C: cellulose filter paper with a pore size of 15 μm and a thickness of 0.25 mm; (4) Paper-based carrier D: quartz filter paper with a pore size of 10 μm and a thickness of 0.2 mm.

[0058] Using the same batch of SK70# base asphalt, we prepared samples at three different ages: unaged, 10-hour TFOT-aged, and 20-hour PAV-aged. Diffusion experiments were performed on the four paper-based carriers using these three different aged asphalt samples according to steps S1-S4 of Example 1, and the diffusion characteristic parameters were analyzed.

[0059] The results showed that paper-based carrier B (cellulose filter paper with a pore size of 10 μm and a thickness of 0.2 mm) provided the best diffusion feature differentiation. The diffusion area ratio difference between the three aged samples reached over 50%, the color gradient value difference reached over 60%, and the edge fractal dimension difference reached over 30%. The other three paper-based carriers had relatively low differentiation, either because of slow diffusion (paper-based carrier A), too fast diffusion resulting in unclear features (paper-based carrier C), or uneven material resulting in poor repeatability (paper-based carrier D).

[0060] Therefore, it is recommended to use paper-based carrier B (cellulose filter paper with a pore size of 10 μm and a thickness of 0.2 mm) as the standard carrier.

[0061] Example 4: Example of determining weight coefficient.

[0062] In order to determine the optimal weight coefficients of each parameter in the aging characteristics evaluation model, multiple batches of experimental studies were conducted based on Example 1:

[0063] SK70#, Jinling 70# and Karamay 70# base asphalts from three different origins were selected, and 12 samples with different aging degrees were prepared, including unaged, TFOT aged (5h / 7.5h / 10h), PAV aged (10h / 20h / 40h) and UV aged (6d / 12d / 24d). Each sample was tested according to steps S1 to S3 of Example 1 to obtain three parameters: diffusion area ratio, color gradient value and edge fractal dimension.

[0064] At the same time, the same samples were tested using the traditional DSR rutting factor aging index (AASHTO T315), FTIR carbonyl aging index and needle penetration aging index. A multiple linear regression model was established with the comprehensive evaluation results of the three traditional methods as the dependent variable and the three diffusion characteristic parameters as the independent variables. The weight coefficients were determined through regression analysis.

[0065] The data analysis results based on 30 groups of samples (3 types of matrix asphalt × 10 aging states) show that the importance of the three parameters of diffusion area ratio, color gradient value and edge fractal dimension for aging evaluation is ranked as follows: diffusion area ratio > color gradient value > edge fractal dimension, and the optimal solution of the specific weight coefficients is: w1=0.45, w2=0.35, w3=0.20.

[0066] The correlation coefficient between the aging index AI calculated using this weight coefficient and the comprehensive result of the traditional evaluation method is as high as 0.94 (p<0.01), indicating that this weight ratio can better reflect the degree of asphalt aging.

[0067] Example 5: Example for determining the aging index grading standard.

[0068] In order to determine a reasonable grading standard for the aging index AI, extensive sample verification studies were conducted based on Examples 1 and 4:

[0069] SK70#, Jinling 70# and Karamay 70# base asphalts from three different origins, SBS modified asphalt and rubber powder modified asphalt, as well as asphalt samples extracted from asphalt pavements with different service years (0 years, 3 years, 6 years, 9 years and 12 years) were selected, totaling 50 asphalt samples of different types and different degrees of aging. The samples were tested according to steps S1 to S4 of Example 1 to obtain the aging index AI of each sample.

[0070] At the same time, all samples were tested using traditional indicators such as the DSR rutting factor aging index, needle penetration aging index, and softening point increment. Combined with the requirements for asphalt aging performance in the "Technical Specifications for Highway Asphalt Pavement Construction" (JTG F40) and actual engineering experience, the degree of asphalt aging was divided into four levels: no aging or slight aging, moderate aging, severe aging, and extreme aging.

[0071] By statistically analyzing the correspondence between the AI values and aging grades of 50 samples, the following grading standards were obtained: AI < 0.3: no aging or slight aging, indicating that the asphalt still has good road performance and no special treatment is required; 0.3 ≤ AI < 0.5: moderate aging, indicating that the asphalt performance begins to decline and preventive maintenance is required; 0.5 ≤ AI < 0.8: severe aging, indicating that the asphalt performance has significantly deteriorated and restorative maintenance is required; AI ≥ 0.8: extreme aging, indicating that the asphalt has lost its basic road performance and needs to be replaced or regenerated.

[0072] The accuracy of the grading standard was verified by its consistency with actual engineering maintenance decisions, and the results showed a consistency rate of 92.5%, indicating that the standard has high practical value.

[0073] Example 6: Accuracy verification example.

[0074] To verify the accuracy of the method of the present invention, based on Example 1, evaluation experiments were conducted on SK70# matrix asphalt samples with different aging degrees, and compared with three traditional evaluation methods:

[0075] Sample types: (1) Sample A: unaged SK70# matrix asphalt; (2) Sample B: SK70# matrix asphalt aged for 5 hours by TFOT; (3) Sample C: SK70# matrix asphalt aged for 10 hours by TFOT; (4) Sample D: SK70# matrix asphalt aged for 5 hours by TFOT + 20 hours by PAV; (5) Sample E: SK70# matrix asphalt aged for 5 hours by TFOT + 40 hours by PAV.

[0076] The aging evaluation of the above samples was carried out using the method of the present invention, the DSR rutting factor aging index, the FTIR carbonyl aging index and the GPC molecular weight growth rate. Each method was tested 5 times and the average value was taken. The results are shown in Table 1 below:

[0077] Table 1 - Comparison of different aging indices

[0078]

[0079] Through Pearson correlation coefficient analysis, the correlation coefficient between the AI value of the present invention and the DSR rutting factor aging index is 0.95 (p < 0.01), the correlation coefficient with the FTIR carbonyl aging index is 0.93 (p < 0.01), and the correlation coefficient with the GPC molecular weight growth rate is 0.91 (p < 0.01), indicating that the method of the present invention is highly consistent with the traditional evaluation method.

[0080] The coefficient of variation (CV = standard deviation / mean) analysis showed that the coefficient of variation of the method of the present invention was 7.8%, which was slightly higher than the DSR rutting factor aging index (6.5%), but lower than the FTIR carbonyl aging index (8.9%) and the GPC molecular weight growth rate (9.7%), indicating that the method of the present invention has good accuracy and repeatability.

[0081] Example 7: Universality verification example.

[0082] To verify the universality of the method of the present invention, based on Example 1, evaluation experiments were conducted on different types of asphalt samples:

[0083] Sample types: (1) Sample F: unaged SK70# base asphalt; (2) Sample G: unaged Karamay 70# base asphalt; (3) Sample H: unaged Jinling 70# base asphalt; (4) Sample I: unaged SBS modified asphalt (4.5% SBS content); (5) Sample J: unaged rubber powder modified asphalt (15% rubber powder content); (6) Sample K: asphalt extracted from unaged asphalt mixture.

[0084] First, the unaged samples were subjected to aging evaluation according to steps S1-S5 of Example 1. Then, the samples were subjected to TFOT aging for 5 h and PAV aging for 20 h, and the aging degree of the aged samples was evaluated again using the method of the present invention. The results are shown in Table 2 below:

[0085] Table 2 - Aging AI values of different samples

[0086]

[0087] The results show that the proposed method can effectively evaluate the aging degree of different asphalt samples and reflect the differences in aging sensitivity among different asphalt types. Specifically, the aging sensitivity of base asphalt is higher than that of modified asphalt and asphalt extracted from mixtures, which is consistent with the conclusions of traditional evaluation methods.

[0088] In addition, by subjecting Sample I and Sample J to different degrees of aging treatment (unaged, TFOT-5h, TFOT-10h, TFOT-5h+PAV-10h, TFOT-5h+PAV-20h, TFOT-5h+PAV-40h), the change in AI value was evaluated using the method of the present invention. The results showed that the AI value increased monotonically with the increase in the degree of aging, with good sensitivity and monotonicity, further demonstrating the universality of the method of the present invention for different types of asphalt samples.

[0089] Example 8: Field practicality verification example.

[0090] To verify the field practicability of the method of the present invention, cores were taken from asphalt pavements with service years of 0, 3, 6, 9, and 12 years, and asphalt was extracted. The degree of aging was evaluated using the method of the present invention:

[0091] (1) First, the equipment required for the method of the present invention (micropipette, paper-based carrier, ultrasonic cleaner, small thermal shield, portable microscope and tablet computer) were integrated into a portable field evaluation device with a total weight of <5 kg;

[0092] (2) On-site coring was conducted on a certain highway, with three core samples taken from asphalt pavements of different ages;

[0093] (3) Extracting bitumen from core samples using solvent extraction;

[0094] (4) evaluating the aging degree of the extracted asphalt using steps S1-S5 of the method of the present invention;

[0095] (5) At the same time, some of the extracted asphalt samples were brought back to the laboratory and evaluated using the traditional DSR rutting factor aging index method as a reference.

[0096] The results of the on-site evaluation are shown in Table 3 below:

[0097] Table 3 - Aging evaluation of asphalt samples of pavement of different ages

[0098]

[0099] Results demonstrate that the proposed method can efficiently evaluate asphalt aging on-site, taking an average of approximately two hours, compared to approximately 48 hours for conventional laboratory methods (including extraction, recovery, and drying). The correlation between the on-site and laboratory evaluation results reached a high of 0.94, demonstrating the efficiency and reliability of the proposed method in field applications.

[0100] Based on the on-site evaluation results, a basis can be quickly provided for pavement maintenance decisions: 0-3 year old sections only require routine maintenance, 6 year old sections require preventive maintenance, 9 year old sections require restorative maintenance, and 12 year old sections require consideration of overlay or regeneration treatment.

[0101] Example 9: Comparison example of equipment cost and test cost.

[0102] To verify the low-cost advantage of the method of the present invention, the equipment and testing costs required by the method of the present invention are compared with those of traditional evaluation methods:

[0103] The main equipment and cost details required for the method of the present invention are as follows: (1) precision electronic balance (0.001g accuracy): about 500 yuan; (2) ultrasonic cleaner (40kHz): about 400 yuan; (3) micropipette (10-100μL): about 300 yuan; (4) digital microscope (50x magnification): about 1500 yuan; (5) small constant temperature and humidity insulation cover: about 800 yuan; (6) tablet computer (including image analysis software): about 1200 yuan; (7) auxiliary equipment (beaker, measuring cylinder, etc.): about 300 yuan.

[0104] The total cost of the equipment for the method of the present invention is about 5,000 yuan, and the cost of each test is as follows: (1) paper-based carrier: about 0.5 yuan / piece; (2) reagents (solvent, color developer): about 1.5 yuan / time; (3) electricity and other consumption: about 0.5 yuan / time.

[0105] The total cost of each test of the method of the present invention is about 2.5 yuan.

[0106] Cost of equipment and testing for traditional methods: (1) DSR rheometer method: equipment costs approximately RMB 300,000, and each test costs approximately RMB 50; (2) FTIR carbonyl index method: equipment costs approximately RMB 350,000, and each test costs approximately RMB 60; (3) GPC molecular weight method: equipment costs approximately RMB 550,000, and each test costs approximately RMB 300.

[0107] Comparison shows that the method of the present invention reduces equipment costs by more than 99% and testing costs by more than 95% compared with traditional methods. At the same time, it is comparable to traditional methods in terms of accuracy (correlation coefficient>0.9), fully verifying the low-cost and high-efficiency advantages of the present invention.

[0108] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0109] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0110] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for evaluating the aging characteristics of road petroleum asphalt, characterized in that: The method comprises the following steps: Step 1: Obtain standard asphalt samples of different aging degrees and dissolve them in the same volume of chromogenic solvent to obtain corresponding asphalt sample solutions. The mass volume ratio of each standard asphalt sample to the chromogenic solvent is (1-5) g:100 mL. Step 2: aspirate a preset amount of each asphalt sample solution and drop it onto the center of the paper-based carrier (1), let it stand for 20±5 minutes to allow each sample droplet to fully migrate on the corresponding paper-based carrier, and finally dry it at room temperature to obtain a paper-based carrier (2) with the corresponding asphalt sample solution diffused thereon; Step 3, respectively collect images of the diffusion area on the surface of each paper-based carrier (2), and calculate the diffusion characteristic parameters of the diffusion area corresponding to each paper-based carrier (2), the diffusion characteristic parameters including diffusion area ratio, color gradient value, and edge fractal dimension, wherein the diffusion area ratio is the diffusion area of different aged asphalt samples divided by the theoretical maximum diffusion area, the diffusion area of different aged asphalt samples is obtained by binarizing the corresponding collected images and counting the pixels, the theoretical maximum diffusion area is the diffusion area of the unaged asphalt sample with the same solvent volume under the same conditions, the color gradient value is obtained by converting the corresponding RGB image into the HSV color space and calculating the square of the standard deviation of the H channel in the diffusion area, and the edge fractal dimension is calculated by the box counting method, and the calculation formula is: D=-lim[log(N(ε)) / log(ε)], wherein N(ε) is the number of boxes required to cover the edge, and ε is the box size; Step 4, the diffusion characteristic parameters of the diffusion area corresponding to each paper-based carrier (2) are determined by multivariate linear regression analysis to obtain the weight coefficient corresponding to each parameter to determine the aging characteristic evaluation formula, and the aging characteristic evaluation model is: AI=w1×diffusion area ratio+w2×color gradient value+w3×edge fractal dimension, wherein w1, w2 and w3 are the weight coefficients of each parameter respectively, and AI is the aging index; In step 5, the diffusion characteristic image of the asphalt sample to be tested is obtained using steps 1-3, and the diffusion characteristic parameters of the diffusion area are calculated. The diffusion characteristic parameters are substituted into the aging characteristic evaluation model in step 4 to determine the aging index AI corresponding to the asphalt sample to be tested, and the aging degree of the asphalt sample to be tested is determined according to the aging index range, wherein the aging index range is mapped to the aging degree.

2. The method for evaluating aging characteristics of road petroleum asphalt according to claim 1, wherein: In step 1, the color-developing solvent is prepared by uniformly mixing a color developer and a dissolving agent, the color developer is oil-soluble Sudan red, and the dissolving agent is one or two of trichloroethylene, carbon disulfide, and tetrahydrofuran.

3. The method for evaluating aging characteristics of road petroleum asphalt according to claim 1, wherein: In step 2, each paper-based carrier (1) is a cellulose filter paper with a pore size of 10±1 μm and a thickness of 0.2±0.02 mm.

4. The method for evaluating aging characteristics of road petroleum asphalt according to claim 1, wherein: Before step 2, the method further includes placing each paper-based carrier (1) in a constant temperature and humidity insulation cover at a temperature of 25±1° C. and a relative humidity of 50±5% for equilibration for 20±5 minutes.

5. The method for evaluating aging characteristics of road petroleum asphalt according to claim 1, wherein: In step 5, the mapping relationship between the aging index AI range and the aging degree is: AI < 0.3 indicates no aging or slight aging, 0.3 ≤ AI < 0.5 indicates moderate aging, 0.5 ≤ AI < 0.8 indicates severe aging, and AI ≥ 0.8 indicates extreme aging.

6. A road petroleum asphalt aging characteristics evaluation system, characterized in that: The system stores a road petroleum asphalt aging characteristics evaluation program, and when the road petroleum asphalt aging characteristics evaluation program is executed by a processor, the processor executes the steps of the road petroleum asphalt aging characteristics evaluation method according to any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that The medium stores a road petroleum asphalt aging characteristics evaluation program, and when the road petroleum asphalt aging characteristics evaluation program is executed by the processor, the processor executes the steps of the road petroleum asphalt aging characteristics evaluation method according to any one of claims 1 to 5.

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