Asphalt-aggregate interface failure behavior quantitative analysis method based on image processing

Abstract

The invention discloses an asphalt-aggregate interface failure behavior quantitative analysis method based on image processing, and belongs to the field of road engineering.The method comprises the following steps that a pull-out test is conducted on an asphalt-aggregate interface based on a universal testing machine, a stress-strain curve is obtained, evaluation indexes are extracted based on the stress-strain curve, and the asphalt-aggregate interface failure behavior quantitative analysis method is obtained; calculating a cohesiveness failure behavior test result based on the evaluation index; performing image acquisition on a failure interface of the mixed failure test piece by adopting a digital image processing method, and identifying and calculating an area ratio of a cohesiveness failure region to an adhesion failure region based on the acquired image; and based on the cohesiveness failure behavior test result and the area proportion, calculating an evaluation index result of the cohesiveness failure region, and realizing quantitative expression of the asphalt-aggregate interface cohesiveness failure behavior.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of road engineering, and particularly relates to a quantitative analysis method for asphalt-aggregate interface failure behavior based on image processing. BACKGROUND

[0002] Water damage disease of asphalt pavement refers to that in the service process of the asphalt pavement, water on the road surface, snowmelt is pressed into the internal pores of the pavement mixture under the action of automobile wheel load and repeatedly generates hydrodynamic pressure or vacuum negative pressure suction, which causes the original asphalt-aggregate interface bonding behavior to be affected, and the water gradually replaces the asphalt, forming the phenomenon of water-aggregate bonding behavior. Water damage of asphalt pavement is one of the most common early diseases of pavement in hot and humid areas, and is also the key point of prevention and control in pavement design and construction. From the foregoing definition and occurrence process, the core of the asphalt pavement resisting water damage disease is that the asphalt and aggregate interface has firm bonding force, which can better resist the invasion of rainwater, that is, the bonding characteristics of the asphalt-aggregate interface are the key to reflect the water damage resistance of the asphalt mixture.

[0003] Current road technology workers have deeply realized the importance of the bonding characteristics of the asphalt and aggregate interface, and have developed a series of test methods and evaluation indexes to reflect it. The current specification test method of the prior art is water boiling method / water immersion method. The main observation is the peeling of aggregate of a certain particle size from the asphalt interface in micro-boiling or 80 DEG C water. The method requires higher experience of the operator, and the test results can only be qualitatively analyzed.

[0004] Youtchef et al. introduced Pneumatic Adhesion Tensile Testing Instrument (PATTI) from the high polymer coating industry based on the shortcomings of the current water boiling method, and gradually became the mainstream method for studying the bonding characteristics of road asphalt and aggregate. The specific method is to immerse the pull bolt in hot asphalt and quickly bond with the specific lithology aggregate to be tested, and then pull it out using pneumatic pressure after cooling, so as to obtain the bonding performance data. The test method still has the following limitations: first, the method cannot distinguish between cohesive failure and adhesive failure, which does not correspond to the water damage failure mode of the asphalt mixture in the real service environment; second, all test results are considered as valid results, which leads to some large errors being included in the analysis, and the stability and reproducibility of the test results are poor; third, the test process parameters such as test temperature and stretching speed cannot be controlled, and the result is only a numerical value, which lacks the systematicness of scientific research.

[0005] In recent years, with the help of universal testing machine (UTM) and material test system (MTS), the tensile experiment on the asphalt aggregate interface can realize the dynamic control and continuous recording of the test process, but similar to the foregoing test methods, it cannot well distinguish the cohesive failure and adhesive failure of the asphalt and aggregate interface, and cannot give the judgment criterion of whether the test is successful or not.

[0006] From the above review, although the test method for the bonding characteristics of the asphalt and aggregate interface has been studied and improved at present, it still cannot distinguish the bonding failure types of the asphalt and aggregate interface, and cannot give the discrimination standard of whether the test is successful or not, not to mention the test method with stability and reproducibility. SUMMARY

[0007] To solve the above technical problems, the present application provides a quantitative analysis method for the failure behavior of asphalt-aggregate interface based on image processing to solve the problems existing in the prior art.

[0008] To achieve the above purpose, the present application provides a quantitative analysis method for the failure behavior of asphalt-aggregate interface based on image processing, comprising:

[0009] Performing the pull-out test on the asphalt-aggregate interface based on the universal testing machine, obtaining the stress-strain curve, extracting the evaluation index based on the stress-strain curve, and calculating the cohesive failure behavior test result based on the evaluation index;

[0010] Using the digital image processing method to collect the images of the failure interface of the mixed failure test piece, identifying and calculating the area ratio of the cohesive failure area and the adhesive failure area based on the collected images;

[0011] Based on the cohesive failure behavior test result and the area ratio, the evaluation index result of the adhesive failure area is calculated, and the quantitative expression of the bonding failure behavior of the asphalt-aggregate interface is realized.

[0012] Optionally, the process of extracting the evaluation index based on the stress-strain curve comprises:

[0013] Curve fitting is performed on the continuous stress-strain data collected during the pull-out test, and the characteristic points on the curve are identified;

[0014] When the test piece fails by fracture, the tensile modulus is calculated based on the maximum tensile stress corresponding to the peak point of the stress-strain curve and the strain corresponding to the peak point, and the fracture energy is obtained by integrating the stress-strain curve;

[0015] When the test piece yields but does not break, the yield modulus is calculated according to the stress corresponding to the yield platform on the stress-strain curve and the strain corresponding to the stress, and the yield energy is obtained by calculating the integral area under the stress-strain curve from the beginning of the test to the end of the yield stage;

[0016] The strength index is constructed based on the tensile modulus and the yield modulus, and the energy index is constructed based on the fracture energy and the yield energy;

[0017] Based on the properties of the selected asphalt material, at least one strength index and at least one energy index are selected together as evaluation indexes for evaluating the bonding performance of the asphalt-aggregate interface.

[0018] Optionally, the process of identifying and calculating the area ratio of the cohesion failure area and the adhesion failure area based on the collected images comprises:

[0019] After the test of the test piece is completed, the two failure interfaces are placed in an axisymmetric order corresponding to the damage areas and images are collected;

[0020] The collected images are subjected to image enhancement and image binarization processing to obtain gray-scale images;

[0021] Based on the gray-scale images, an adaptive threshold segmentation algorithm is used for image binarization processing to separate the asphalt area and the aggregate area;

[0022] In the binarized images, the asphalt-asphalt contact area is identified as the cohesion failure area, and the asphalt-aggregate contact area is identified as the adhesion failure area;

[0023] The pixel numbers of the cohesion failure area and the adhesion failure area are counted respectively, and the area ratio of the cohesion failure area and the adhesion failure area is calculated.

[0024] Optionally, the process of separating the asphalt area and the aggregate area by using the adaptive threshold segmentation algorithm to obtain the area ratio of the cohesion failure area and the adhesion failure area comprises:

[0025] The two binarized images are placed in an axisymmetric order corresponding to the damage areas;

[0026] A plane coordinate system is established based on the two axisymmetrically placed images, and the plane coordinate positions of each part are obtained;

[0027] The failure results at the symmetric positions of the plane coordinate positions are compared, and when both symmetric positions are asphalt, it is recorded as cohesion failure, and when one of the symmetric positions is an aggregate part, it is recorded as adhesion failure;

[0028] Count the pixel number of the cohesion failure area and the adhesion failure area respectively, and calculate the area ratio of the cohesion failure area and the adhesion failure area.

[0029] Optionally, the collected image is subjected to image enhancement and image binarization processing by using a Matlab image processing platform; the process of processing the image by using the Matlab image processing platform comprises the following steps:

[0030] The collected original color image is subjected to contrast enhancement and noise filtering processing based on a Matlab image processing function, and the enhanced color image is converted into a gray-scale image by using an rgb2gray function.

[0031] Optionally, the process of calculating the evaluation index result of the adhesion failure area based on the cohesion failure behavior test result and the area ratio comprises the following steps:

[0032] The strength index result and the energy index result are calculated based on the cohesion failure behavior test result and the set test area.

[0033] A mathematical relationship between the total evaluation index of the mixed failure and the cohesion failure evaluation index and the adhesion failure evaluation index is established.

[0034] The contribution weight of the cohesion failure mode and the adhesion failure mode in the mixed failure is determined based on the area ratio obtained by digital image processing.

[0035] The cohesion failure behavior test result and the contribution weight of the two failure modes in the mixed failure are substituted into the mathematical relationship of the mixed failure, and the evaluation index result of the adhesion failure area is solved in combination with the mixed failure test result.

[0036] Optionally, the quantitative expression of the asphalt-aggregate interface bonding failure behavior further comprises feasibility verification of the evaluation method after the quantitative expression of the asphalt-aggregate interface bonding failure behavior is realized.

[0037] The stability and reproducibility of the quantitative expression result of the asphalt-aggregate interface bonding failure behavior are analyzed by using a variance analysis method and a two-sample t-test method.

[0038] The application further provides a computer comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor realizes the method when executing the computer program.

[0039] The application further provides a storage medium having a computer program stored thereon, wherein the program is executable on a processor to realize the method.

[0040] Compared with the prior art, the application has the following advantages and technical effects:

[0041] The present application realizes the accurate quantitative analysis of the asphalt-aggregate interface failure behavior by combining the mechanical test and the image processing technology. The method can effectively distinguish the contribution proportion of the cohesion failure and the adhesion failure, and overcomes the defects that the traditional method can only be qualitatively evaluated or cannot distinguish the failure mode. Through the establishment of a scientific quantitative evaluation system, reliable data support is provided for the water damage resistance performance research of the asphalt mixture, and the accuracy, stability and engineering guidance value of the test result are significantly improved. BRIEF DESCRIPTION OF DRAWINGS

[0042] The accompanying drawings, which form a part of the present application, are used to provide further understanding of the present application, and the illustrative embodiments of the present application and their description serve the purpose of explaining the present application. The accompanying drawings do not constitute an inappropriate limitation on the present application. In the drawings:

[0043] Figure 1 The test technical route map of the embodiments of the present application;

[0044] Figure 2 The mixed failure test test steps of the embodiments of the present application;

[0045] Figure 3 Part of the test situation in the cohesion failure test of the embodiments of the present application; wherein (a) is a tensile process diagram, (b) is that the failure interface is not in the test area due to too fast tensile speed, (c) is that the failure interface appears between asphalt-aggregate due to too low tensile temperature, and (d) is that the cohesion test fails due to too large test area;

[0046] Figure 4 The evaluation index of the asphalt-aggregate interface bonding failure process of the embodiments of the present application; wherein (a) is the evaluation when the test piece breaks, and (b) is the evaluation index when the yield failure occurs in the cohesion test;

[0047] Figure 5 The effectiveness discrimination diagram based on the failure result of the test piece in the cohesion test of the embodiments of the present application, wherein (a) is that the asphalt is normally stretched in the test area, (b) is that the asphalt breaks in the test area, and (c) is that the asphalt breaks at the root of the test area;

[0048] Figure 6 The quantitative expression processing flow of the asphalt-aggregate interface bonding failure behavior of the embodiments of the present application;

[0049] Figure 7 The binary image failure type comparison and analysis flow based on the Image J software of the embodiments of the present application;

[0050] Figure 8 The cohesion failure tensile device design diagram in the BTTD tensile device of the embodiments of the present application;

[0051] Figure 9 The fixture design diagram for the BTTD tensile device of the embodiment of the application is used for the cohesiveness test;

[0052] Figure 10 The mixed failure tensile device design diagram in the BTTD tensile device of the embodiment of the application;

[0053] Figure 11 The fixture design diagram for the BTTD tensile device of the embodiment of the application is used for the mixed test. DETAILED DESCRIPTION

[0054] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0055] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0056] Embodiment one

[0057] In view of the above bottleneck, on the basis of the current research, the present application gives the test steps of the failure behavior of the bonding characteristics of the asphalt-aggregate interface, and in combination with the test result analysis and the digital image processing method mentioned in the patent, the cohesiveness failure and the adhesion failure ratio in any mixed failure result can be distinguished; at the same time, according to the test evaluation index result, the cohesiveness failure and the adhesion failure tensile modulus and the energy contribution result are calculated respectively, so as to realize the quantitative analysis of the bonding characteristics of the asphalt-aggregate interface. In addition, the stability and the reproducibility of the test result are verified in the present patent, which shows the accuracy of the test method. The test method mentioned in the present patent can effectively evaluate the bonding characteristics of the asphalt mixture interface, and provides a quantitative analysis means for the in-depth research on the water damage performance of the asphalt mixture.

[0058] In order to quantitatively analyze the bonding failure behavior of the asphalt-aggregate interface, the present application combines the digital image processing technology to establish a contribution degree analysis method of the cohesiveness failure and the adhesion failure in the mixed failure, and forms a quantitative expression test method of the bonding failure behavior of the asphalt-aggregate interface. At the same time, the stability and the reproducibility of the test method are analyzed, and the reliability of the test method is verified.

[0059] As shown in Figure 1 In the present embodiment, a quantitative analysis method of the failure behavior of the asphalt-aggregate interface based on image processing is provided, which includes the following steps:

[0060] Firstly, the asphalt mixture pull-out test is carried out mainly relying on the universal testing machine (UTM), and the evaluation index that can distinguish the test results of different test objects is given combined with the test results. Meanwhile, the discrimination standard of test success and failure in the test process is determined combined with the occurrence of the asphalt-aggregate interface bonding failure behavior in the test process.

[0061] Secondly, after obtaining the asphalt-aggregate interface bonding failure test results, the analysis method of the contribution degree of cohesive failure and adhesive failure in mixed failure needs to be constructed. Through the analysis of cohesive failure based on the BTTD test method, the test results under a specific evaluation index can be obtained. The detailed steps are as follows: (1) taking a photo of the mixed test specimen failure result based on the BTTD test method, and using the digital image processing method, the proportion of cohesive failure and adhesive failure can be given; (2) combining the mixed test failure evaluation index result, the cohesive failure evaluation index result calculated in the first step is brought in, and the adhesive failure evaluation index result can be solved, thereby realizing the quantitative expression of the asphalt-aggregate interface bonding failure behavior.

[0062] Furthermore, the BTTD test device of the embodiment is shown in Figures 8-11 The device is composed of upper and lower pull rods, upper and lower parallel plates, upper and lower bases, and two sets of shaping clamps. The upper and lower pull rods are accessories of the universal tensile testing machine, which are used for connection and tensile testing of the whole test device. The upper and lower parallel plates are self-made stainless steel parallel plates, which provide a platform for the base. The upper and lower bases are the test aggregates (basalt, limestone) to be selected, with a size of 70mm×50mm×15mm. The base and the parallel plate are fixed by stone glue. The two sets of shaping clamps include a set of cohesive failure test clamps with a size of 50mm×50mm×15mm (the size of the test area is initially proposed as 10mm×10mm×7mm) and another set of mixed failure test clamps with a size of 50mm×50mm×1mm.

[0063] The BTTD test device has the following advantages:

[0064] (1) The cohesive failure and mixed failure can be distinguished. This set of BTTD test device includes two sets of clamps, one set of cohesive failure test clamps and one set of mixed failure test clamps. By using this set of device, the cohesive failure and mixed failure can be successfully distinguished, and by determining the proportion of the two failure modes (cohesive and adhesive failure) in the mixed failure, the contribution of cohesive failure and adhesive failure in the mixed failure behavior can be obtained respectively.

[0065] (2) The test temperature, tensile rate and other test parameters can be accurately controlled. The device can accurately control the temperature, tensile rate and other process parameters in the test process by combining with the UTM test device through a specific clamp, realize dynamic control and continuous recording of the whole test process, and make up for the current asphalt-aggregate bonding performance test which is difficult to control the test environment and parameters.

[0066] (3) The test results can be effectively determined. The current test method (such as PATTI) cannot determine the validity of the test results, but all of them are included in the test results. In the test device, the validity of the test results can be determined in combination with the failure position of asphalt-aggregate (such as the failure position in the cohesion failure is in the middle region of the pull object, and the failure is effective, and the root failure is invalid), and the asphalt and the base fall off, which significantly improves the scientificity of the test results.

[0067] Finally, the stability and reproducibility of the proposed test method are analyzed. By selecting different test times and different operators to perform multiple parallel operations on the same test object, different test results are obtained; the significance difference of the test results is analyzed by using the variance analysis method and t-test method to determine the reliability of the test method.

[0068] Since the test must determine the specific test object and test environment in advance, considering the research purpose of the embodiment, the test object selected in this part includes asphalt and aggregate, wherein the asphalt is further divided into 70# base asphalt and SBS modified asphalt, and the aggregate is further divided into basalt and limestone; the test environment is -10°C and 10°C.

[0069] Further, the asphalt-aggregate interface bonding failure quantitative expression test method includes:

[0070] During the test, the cohesion test of the asphalt-aggregate interface and the mixed test operation steps are highly similar, and in this part, only the mixed test is taken as an example to elaborate its operation process. Specifically, the mixed test includes the following key links, such as Figure 2 as shown in

[0071] (1) Preparation before test, including: heating the asphalt to be tested to the appropriate pouring temperature to ensure its fluidity to meet the test requirements; uniformly applying release agent to the bottom plate for containing the test device and the two sets of shaping clamps to prevent the material from sticking to the device during the test; combine the upper and lower parallel plates with the shaping clamps to enclose a test area with a suitable space to provide a stable operating environment for subsequent tests.

[0072] (2) Molding specimen. Pour the asphalt heated to the appropriate temperature into the space enclosed by the parallel plates and the fixture, and then quickly press the two parallel plates until they are in close contact with the shaping fixture.

[0073] (3) Scraping sample. After the poured asphalt is fully cooled, use a scraper to remove the excess binder on the surface to ensure the surface of the specimen is flat.

[0074] (4) Heat preservation. Place the specimen after scraping the sample in the UTM heat preservation box for 3 to 5 hours of constant temperature treatment to ensure that the internal temperature of the specimen is uniform and stable.

[0075] (5) Test. After the heat preservation time ends, quickly install the specimen into the test device and additionally heat for 1 hour, and then start the test process.

[0076] It is worth noting that when the test process for testing the asphalt-aggregate interface bonding properties based on the BTTD stretching device is determined, the key parameters that affect the test results need to be determined to ensure the measurability of the test and the accuracy of the results. In this part, after repeated tests, it is considered that the test temperature, stretching rate and cohesive failure behavior test area in this process are the key test parameters, as shown in Figure 3 , which are described as follows:

[0077] (1) The stretching rate is to meet the test temperature to complete the asphalt-aggregate interface bonding failure behavior test requirements. If the stretching rate is too fast, the failure interface in the cohesive failure behavior test may appear between the asphalt and the aggregate, which cannot achieve the purpose of asphalt-asphalt fracture in the cohesive failure behavior, as shown in Figure 3 (b); if the stretching rate is too slow, the stretching strain is large and the test process is long, which is not conducive to test control or exceeds the UTM test range.

[0078] (2) The test temperature should not be too low or too high. If the temperature is too low, the asphalt tensile modulus is too high, and the failure interface in the cohesive failure behavior test may appear between the asphalt and the aggregate, which cannot achieve the purpose of testing the cohesive failure behavior, as shown in Figure 3 (c); if the temperature is too high, the asphalt tensile strain is too large and the tensile modulus is low, which is not conducive to test operation and may cause test errors.

[0079] (3) The cohesive failure behavior test area is to ensure that the failure interface appears in the middle of the test area under the selected test temperature and stretching rate, rather than between the asphalt and the aggregate or at the root of the test area, as shown in Figure 3 (d).

[0080] For the above three key parameters of test temperature, tensile rate and cohesive failure behavior test area, multiple tests were conducted, and finally it was considered that under the four factors of No. 70 base asphalt, SBS modified asphalt, basalt plate and limestone plate, the test temperature should be -10°C and 10°C. The tensile speed should match the test temperature, so after multiple tests, the tensile speed at -10°C is finally determined to be 2 mm / min, and the tensile speed at 10°C is finally determined to be 5 mm / min. Regarding the selection of the test area size, because the cross-sectional area size directly affects the position of the asphalt cohesion failure under low temperature conditions, too large cross-sectional area size may cause the failure to occur between the asphalt and the base plate. Therefore, the reasonable test area size needs to be determined based on experience or additional tests. In this test, the size of the cohesion test area is determined to be 10 mm x 10 mm x 7 mm under the most unfavorable conditions.

[0081] Further, the process of selecting the quantitative expression evaluation index of asphalt-aggregate interface bonding failure includes:

[0082] After determining the test device and process, a suitable evaluation index needs to be selected to reflect the test results of the asphalt-aggregate interface bonding failure behavior.

[0083] In the selection of evaluation index, since this test relies on the UTM device for testing, it can monitor the changes of stress and strain in real time, so the complete stress-strain curve can be obtained. Based on this curve, the maximum tensile stress and its corresponding tensile strain can be directly extracted, and the maximum tensile modulus can be further obtained by calculation. In addition, for most asphalt samples that finally fail in fracture, the fracture energy consumed at the time of fracture can be calculated by integrating the stress-strain curve. It is worth noting that due to the excellent performance of SBS modified asphalt, it may be difficult to reach the fracture state within the range of cohesive test under the condition of 10°C and 5 mm / min tensile speed, and most of the tested asphalt presents yield point. Therefore, for the cohesive test at 10°C, the stress and strain at the yield point are used as the evaluation basis, and the yield stress, yield strain, yield modulus, and yield energy calculated therefrom are used to evaluate the bonding performance of the asphalt-aggregate interface under the four asphalt / aggregate combinations. In summary, the test test object, test conditions and evaluation index determined in this study are shown in Table 1, and the schematic situation of each evaluation index is shown in Figure 4 .

[0084] Table 1

[0085]

[0086]

[0087] Further, the process of determining the effectiveness of the test results includes:

[0088] After the tensile test of the asphalt-aggregate interface bonding failure behavior is completed, the effectiveness of the test results needs to be determined to determine whether the test results can be used as an effective group for bonding performance analysis. In the past asphalt-aggregate bonding performance test, due to the inability to effectively distinguish between cohesion and mixed tests, there is a lack of clear test success criteria, making it difficult to identify the effectiveness of the test results. In this test, thanks to the introduction of the BTTD device, the cohesion failure and mixed failure modes of asphalt are successfully distinguished, so that a clear criterion for determining whether the test is successful or not can be further determined.

[0089] For the cohesion test, when the asphalt failure or yield occurs inside the test area, as shown in Figure 5 , the test is considered successful; if the failure occurs at the root of the test area, it is considered a failure.

[0090] For the mixed test, since it has both cohesion failure and adhesion failure, it is generally a mixed failure (in extreme cases, asphalt-aggregate failure, which is adhesion failure), so there is generally no test failure. Only the subsequent digital image processing technology is needed to identify and calculate the proportion of cohesion and adhesion failure in the mixed failure behavior.

[0091] Further, as shown in Figure 6 , the process of quantitatively expressing the asphalt-aggregate interface bonding failure behavior based on digital image processing technology includes:

[0092] After obtaining the results of the asphalt-aggregate interface cohesion and mixed tests based on the BTTD device, the next step is to analyze the state of the cohesion and adhesion failure evaluation indicators (tensile / yield modulus, fracture / yield energy) in the mixed test, as well as the contribution (proportion) of the two in the evaluation index value, to further quantitatively express the asphalt-aggregate interface bonding failure behavior.

[0093] In this embodiment, the proportion of cohesion and adhesion failure in the mixed failure interface is analyzed by means of digital image processing, and the adhesion failure state is calculated in combination with the cohesion failure results. The detailed processing steps are introduced as follows:

[0094] (1) For the test results of the cohesion failure behavior, the evaluation index calculation results can be directly based on the determined results.

[0095] (2) For the test results of mixed failure behavior, first, place the two failure interfaces of the test specimen in the order of one-to-one correspondence of the failure area, and take pictures and store them; second, convert the two photo images into grayscale images by means of image enhancement and image binarization processing; third, mark the aggregate part and the asphalt part on each picture by means of threshold segmentation method to determine the corresponding positions; fourth, compare the asphalt / aggregate situation of the corresponding positions under the one-to-one corresponding angle of the two grayscale images, mark the points with asphalt-aggregate as adhesive failure and the points with asphalt-asphalt as cohesive failure; and finally, count the cohesive and adhesive failure areas in a single grayscale image to obtain the proportion of the two failure modes.

[0096] (3) The cohesive failure behavior evaluation index result in step (1) is brought into step (2) to directly solve the adhesive failure evaluation index result, and finally realize the quantitative expression of any mixed failure behavior.

[0097] At the same time, in order to improve the processing quality of the test results, the embodiment is programmed by means of Matlab software to obtain the binarized image, and is imported into Image J software to compare the failure categories (cohesive / adhesive failure) at different positions of the image, and then calculate the proportion of the two failure modes, thereby realizing the efficient processing of the digital image processing process in step (2) above.

[0098] The Matlab programming content is as follows:

[0099] clc; clear all; : clear all contents in the command window and clear all variables in the workspace.

[0100] I1 = imread('D:\Desktop\matlab\1.png'); whos I1; : read the image file and display its information.

[0101] %I1 = rgb2gray(I1); : The commented code is originally used to convert the color image to grayscale image.

[0102] I1 = im2uint8(I1); whos I1; : Convert the image data type to 8-bit unsigned integer.

[0103] figure, imshow(uint8(I1)), title('Original image', 'fontsize', 16); : Display the image I1 and add the title "Original image".

[0104] [m, n] = size(I1); I1 = double(I1); : Get the size of the image I1 and convert the data type to double precision.

[0105] Th = 160; %: Set threshold value Th as 160.

[0106] count = zeros(256, 1); pcount = zeros(256, 1); %: Initialize two 256x1 zero matrices to store the number and proportion of each gray value.

[0107] for i = 1 : m... end: Double loop to traverse each pixel of the image and calculate the number of each gray value.

[0108] count1 = zeros(256, 1); pcount1 = zeros(256, 1); %: Initialize two 256x1 zero matrices to store the number and proportion of each gray value.

[0109] for i = 1 : m... end: Double loop to traverse each pixel of the image and calculate the number of each gray value.

[0110] dw = 0; x = 0; for i = 1 : m... end: Calculate the number of pixels greater than the threshold value Th.

[0111] for i = Th : 255... end: Calculate the proportion of each gray value in the total matrix and calculate the overall gray mean value of the image.

[0112] Th2 = Th; Thbest = 0; dfc = 0; dfcmax = 0; %: Initialize threshold and related variables of inter-class variance.

[0113] while (Th2 >= Th && Th2 <= 255)... end: Loop to find the best threshold value.

[0114] T2 = Thbest; J2 = im2bw(J1, T2 / 255); %: Use the best threshold value for binary processing.

[0115] figure, imshow(J2), title('Aggregate', 'fontsize', 16); %: Display the binary image and add the title "Aggregate".

[0116] Import the Matlab output results into Image J to get the binary image failure type comparison and analysis process based on Image J software as shown in Figure 7 .

[0117] In Figure 7In the image, the original picture and the failure area of the binarization processing picture correspond one by one, and the black and white contrast test area is obtained after binarization processing. Among them, the white part is asphalt, and the black part is aggregate. In the image processed by Image J, the red area is aggregate, and the white area is asphalt. The red area belongs to the adhesion failure zone, and the proportion in d) is 65.45%, so the white area of the figure accounts for 34.55%, which belongs to the cohesive failure zone, so the proportion of adhesion and cohesion in the mixed test can be obtained.

[0118] Further, the process of verifying the feasibility of the quantitative expression test evaluation method of the asphalt-aggregate interface bonding failure behavior includes:

[0119] The effective distinguishability of the test method to the test object is the premise of the acceptance of the test method, and its stability and reproducibility are the key to be widely applied. In this part, the stability and reproducibility of the quantitative expression test method of the asphalt-aggregate interface bonding failure proposed in this embodiment will be tested.

[0120] In order to ensure the reliability of the test results, this part takes the most unfavorable condition for testing, that is, the combination of limestone + matrix asphalt is tested for asphalt-aggregate interface bonding failure at 10°C. At the same time, based on the stability and reproducibility test principle, this test is divided into two groups: one group is five tests performed by two testers in the same test time and test machine; the second group is another five tests performed by one of the testers on another UTM machine at another time, and the differences between the test results of these groups are compared to verify the stability and reproducibility of the test method. The test will obtain 15 groups of bonding performance results, and according to the digital image technology method of Figure 10 The 15 test results are processed by the digital image technology method to obtain 15 test results, and the adhesion failure area proportion results are counted in Table 2. According to the bonding failure results and the coefficient of variation results, it is difficult to determine the reliability of the test results.

[0121] Therefore, the stability and reproducibility of the 15 groups of test results are analyzed by combining the analysis of variance (ANOVA) method and the two-sample t-test method. The analysis of variance (ANOVA) is a statistical method for testing whether there is a significant difference in the mean values of three or more independent samples. The core principle is to decompose the total data variation into group variation (caused by grouping factors) and within-group variation (caused by random errors), and to judge whether the mean difference has statistical significance by comparing the size of the two. The two-sample t-test is a statistical method for comparing the mean values of two independent or paired samples. The core principle is to calculate the ratio of the mean difference and the standard error of the two groups, that is, the t-statistic, to judge whether the difference is caused by random error. At the same time, the 15 groups of data are subjected to variance analysis and variability analysis, and the SPSS software is used for multiple sample t-test and analysis of variance (ANOVA), as shown in Table 2.

[0122] Table 2

[0123]

[0124] The first group and the second group mainly refer to five groups of tests performed by two testers successively under the same test time and test machine. The 5 groups of data can be regarded as 5 groups of samples, each containing 2 repeated data, which is suitable for single-factor analysis of variance (ANOVA). First, test whether there is a significant difference in the mean values of the 5 groups, and if ANOVA is significant, then perform pairwise comparison. The calculation results by the SPSS software are shown in Table 3.

[0125] Table 3

[0126]

[0127] As shown in Table 3, the between-group mean square (SSB) is 519.30, the within-group sum of squares (SSW) is 241.42, the between-group mean square (MSB) is 129.83, and the within-group mean square (MSW) is 48.28. The F value is the ratio of MSB and MSW, i.e. F = MSB / MSW = 2.69. According to the F distribution table, n1 = 4, n2 = 5, the critical value F0.05(4.5) = 5.19 (α = 0.05), the actual F = 2.69 < 5.19, and the P value > 0.05. The ANOVA result shows that there is no significant difference in the mean values of the 5 groups of data at the α = 0.05 level, so there is no need for further pairwise T-test, which indicates that the reproducibility of the test is good and the data reliability is high.

[0128] The second group and the third group mainly refer to the same tester performing five same tests on different UTM machines at different times, and a two-sample t test can be used, and the calculated t value is 0.37, and the degree of freedom is 8. According to the t distribution table, the critical value of the two-sided test at the level of alpha=0.05 is 2.306, and since the calculated t value (0.37) is less than the critical value, the corresponding P value is greater than 0.05, so at the significance level of alpha=0.05, the mean values of the two groups of data do not have significant differences, which indicates that the test stability and reproducibility in this case are good.

[0129] The technical key of the application is: (1) Establish a quantitative evaluation system of failure behavior. Based on the characteristics of stress-strain curve, a multi-dimensional evaluation index system is constructed: the failure strength is represented by parameters such as fracture modulus and fracture energy, and the viscoelastic response is evaluated by yield modulus and yield energy. Further combined with the digital image processing technology of Matlab threshold segmentation + ImageJ area statistics, the solving method of the contribution degree of cohesiveness and adhesion in mixed failure is analyzed, and the fine quantitative analysis of interface failure behavior is realized. (2) Establish a failure position driven test effectiveness criterion: for cohesive test, it is clearly stipulated that failure occurs inside the test area; for mixed test, the failure contribution ratio is directly quantified through image analysis. It solves the defect that traditional methods cannot distinguish failure types and accept invalid data. At the same time, the test reproducibility is verified, and the data results in ANOVA and t-test test are p>0.05, showing no significant difference, and the coefficient of variation is controlled in the engineering acceptable range of 4.69%~15.31%. It is proved that the method has good stability and reproducibility.

[0130] The positive effect of the application is: based on the UTM test, the selection standard of raw materials (matrix asphalt, SBS modified asphalt and basalt, limestone) is determined, and the key parameter system such as temperature field (-10℃ to 10℃), tensile rate (2-5mm / min) and test area is established. By constructing multi-dimensional evaluation indexes such as stress-strain curve, tensile modulus and fracture energy, and combining with digital image processing technology, a standardized test analysis method is proposed, which can distinguish mixed failure mode and determine the proportion of cohesive failure and adhesive failure in mixed failure, which lays a foundation for accurate evaluation of interface bonding performance. The main conclusions are as follows:

[0131] (1)Establish a quantitative evaluation system of failure behavior. Based on the characteristics of stress-strain curve, a multi-dimensional evaluation index system is constructed: the failure strength is characterized by fracture modulus, fracture energy, etc., and the viscoelastic response is evaluated by yield modulus and yield energy. Further combining the digital image processing technology of Matlab threshold segmentation + ImageJ area statistics, the calculation method of the contribution degree of cohesion and adhesion in mixed failure is analyzed, and the fine quantitative analysis of the interface failure behavior is realized.

[0132] (2)Establish a failure position driven test effectiveness criterion: for cohesive tests, it is clearly stipulated that failure occurs inside the test area; for mixed tests, the failure contribution ratio is directly quantified through image analysis. The defect of traditional methods that cannot distinguish failure types and accept invalid data is solved. At the same time, the test reproducibility is verified, and the data results are p>0.05 in ANOVA and t-test test, showing no significant difference, and the coefficient of variation is controlled in the engineering acceptable range of 4.69%~15.31%. It is proved that the method has good stability and reproducibility.

[0133] The application further provides a computer comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the method when executing the computer program.

[0134] The application further provides a storage medium having a computer program stored thereon, wherein the program is executable on a processor to implement the method.

[0135] The above is only the preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed in the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A quantitative analysis method for asphalt-aggregate interface failure behavior based on image processing, characterized in that, Includes the following steps: Pull-out tests were conducted on the asphalt-aggregate interface using a universal testing machine to obtain stress-strain curves. Evaluation indices were then extracted based on the stress-strain curves, and the cohesive failure behavior test results were calculated based on the evaluation indices. Digital image processing methods were used to acquire images of the failure interface of hybrid failure specimens. Based on the acquired images, the area ratio of cohesive failure region to adhesive failure region was identified and calculated. Based on the test results of the cohesive failure behavior and the area ratio, the evaluation index results of the adhesive failure area are calculated, so as to realize the quantitative expression of the asphalt-aggregate interface bonding failure behavior.

2. The method for quantitative analysis of asphalt-aggregate interface failure behavior based on image processing according to claim 1, characterized in that, The process of extracting evaluation indicators based on stress-strain curves includes: The continuous stress-strain data collected during the pull-out test were recorded as curves, and the characteristic points on the curves were identified. When the specimen fails by fracture, the tensile modulus is calculated using the maximum tensile stress and strain corresponding to the peak point of the stress-strain curve, and the fracture energy is obtained by integrating the stress-strain curve. When the specimen yields but does not fracture, the yield modulus is calculated by the stress corresponding to the yield plateau on the stress-strain curve and the strain corresponding to the stress, and the yield energy is obtained by calculating the integral area under the stress-strain curve from the beginning of the test to the end of the yielding stage. Strength indices are constructed based on the tensile modulus and yield modulus, and energy indices are constructed based on the fracture energy and yield energy. Based on the characteristics of the selected asphalt material, at least one strength index and at least one energy index are selected as evaluation indicators for the asphalt-aggregate interfacial bonding performance.

3. The method for quantitative analysis of asphalt-aggregate interface failure behavior based on image processing according to claim 1, characterized in that, The process of identifying and calculating the area ratio of cohesive failure regions to adhesive failure regions based on the acquired images includes: After the test specimen completes the test, the two failure interfaces are arranged in an axisymmetric order corresponding to the damage areas and images are collected. The acquired image is enhanced and binarized to obtain a grayscale image; Based on the grayscale image, an adaptive threshold segmentation algorithm is used to perform image binarization processing to separate the asphalt area from the aggregate area; In the binarized image, the asphalt-asphalt contact area is identified as the cohesive failure area, and the asphalt-aggregate contact area is identified as the adhesive failure area. The number of pixels in the cohesive failure region and the adhesive failure region are counted separately, and the area ratio of the cohesive failure region to the adhesive failure region is calculated.

4. The method for quantitative analysis of asphalt-aggregate interface failure behavior based on image processing according to claim 3, characterized in that, The process of using an adaptive threshold segmentation algorithm for image binarization to separate the asphalt region from the aggregate region and obtain the area ratio of the cohesive failure region to the adhesion failure region includes: The two binarized images are arranged in an axisymmetric order that corresponds one-to-one with the damaged areas; A planar coordinate system is established based on two images placed symmetrically, and the planar coordinate positions of each part are obtained; Compare the failure results of plane coordinate positions that are symmetrical. When both symmetrical positions are asphalt, it is recorded as cohesive failure. When one of the symmetrical positions is an aggregate part, it is recorded as adhesive failure. The number of pixels in the cohesive failure region and the adhesive failure region are counted separately, and the area ratio of the cohesive failure region to the adhesive failure region is calculated.

5. The method for quantitative analysis of asphalt-aggregate interface failure behavior based on image processing according to claim 3, characterized in that, The acquired images were enhanced and binarized using the Matlab image processing platform. The process of processing images using the Matlab image processing platform includes: The original color image was enhanced for contrast and filtered for noise using Matlab image processing functions. The enhanced color image was then converted to a grayscale image using the rgb2gray function.

6. The method for quantitative analysis of asphalt-aggregate interface failure behavior based on image processing according to claim 2, characterized in that, The process of calculating the evaluation index results of the adhesion failure region based on the test results of the cohesive failure behavior and the area ratio includes: Based on the test results of the cohesive failure behavior and the area of ​​the test area, the strength index and energy index results were calculated. Establish the mathematical relationship between the overall evaluation index of hybrid failure and the evaluation indices of cohesive failure and adhesive failure; The contribution weights of cohesive failure mode and adhesive failure mode in hybrid failure are determined based on the area ratio obtained from digital image processing. By substituting the test results of cohesive failure behavior and the contribution weights of the two failure modes in mixed failure into the mathematical relationship of mixed failure, and combining the test results of mixed failure, the evaluation index results of the adhesive failure region are obtained.

7. The method for quantitative analysis of asphalt-aggregate interface failure behavior based on image processing according to claim 1, characterized in that, After achieving a quantitative expression of the asphalt-aggregate interface bond failure behavior, the evaluation method feasibility verification is also included. Among them, the stability and reproducibility of the quantitative expression results of the asphalt-aggregate interface bonding failure behavior were analyzed using the analysis of variance method and the two-sample t-test method.

8. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in claim 1.

9. A storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in claim 1.

Images