阅读说明：本技术 一种混合料自愈合性能检测方法、装置及存储介质 (Method and device for detecting self-healing performance of mixture and storage medium ) 是由 赵文政 张苏龙 徐衍亮 李华 朱宏亮 毛益佳 陈广辉 王捷 方芳 潘芳 王青 于 2019-10-22 设计创作，主要内容包括：本申请提供一种混合料自愈合性能检测方法、装置及存储介质,包括：获取第一测试件的多张第一断面图、第二测试件的多张第二断面图以及第三测试件的多张第三断面图；第一测试件为利用沥青混合料制备的小梁试件；第二测试件是第一测试件通过四点弯曲试验后获得的；第三测试件是第二测试件通过自愈合试验后获得的；断面图是根据CT扫描技术对测试件扫描后获得；根据多张第一断面图确定第一测试件的第一空隙率；根据多张第二断面图确定第二测试件的第二空隙率；根据多张第三断面图确定第三测试件的第三空隙率；根据第一空隙率、第二空隙率以及第三空隙率确定沥青混合料的自愈合性能指数。(The application provides a method and a device for detecting self-healing performance of a mixture and a storage medium, and the method comprises the following steps: acquiring a plurality of first cross-sectional views of a first test piece, a plurality of second cross-sectional views of a second test piece and a plurality of third cross-sectional views of a third test piece; the first test piece is a trabecular test piece prepared by using the asphalt mixture; the second test piece is obtained after the first test piece is subjected to a four-point bending test; the third test piece is obtained after the second test piece passes the self-healing test; the section diagram is obtained after the test piece is scanned according to the CT scanning technology; determining a first porosity of the first test piece according to the plurality of first section diagrams; determining a second porosity of the second test piece according to the plurality of second section diagrams; determining a third porosity of the third test piece according to the plurality of third section diagrams; and determining the self-healing performance index of the asphalt mixture according to the first void ratio, the second void ratio and the third void ratio.)

1. A method for detecting self-healing performance of a mixture is characterized by comprising the following steps:

acquiring a plurality of first cross-sectional views of a first test piece, a plurality of second cross-sectional views of a second test piece and a plurality of third cross-sectional views of a third test piece; the first test piece is a trabecular test piece prepared by using the asphalt mixture; the first section is obtained after a first test piece is scanned according to the CT scanning technology; the second test piece is obtained after the first test piece is subjected to a four-point bending test; the second section is obtained after a second test piece is scanned according to the CT scanning technology; the third test piece is obtained after the second test piece passes a self-healing test; the third section is obtained after the third test piece is scanned according to the CT scanning technology;

determining a first porosity of the first test piece according to the plurality of first section diagrams; determining a second porosity of the second test piece according to the plurality of second section diagrams; determining a third porosity of the third test piece according to the third section diagrams;

and determining the self-healing performance index of the asphalt mixture according to the first porosity, the second porosity and the third porosity.

2. The method of claim 1, wherein said determining a first porosity of said first test piece from said plurality of first profiles comprises:

carrying out gray level processing on the plurality of first cross-sectional views to obtain a plurality of gray-level processed first cross-sectional views;

performing gray value analysis on the plurality of first cross-sectional diagrams after the gray processing to determine a first void ratio of the first test piece;

the determining a second gap of the second test piece according to the plurality of second cross-sectional diagrams includes:

carrying out gray level processing on the plurality of second cross-sectional views to obtain a plurality of gray-level processed second cross-sectional views;

performing gray value analysis on the plurality of second cross-sectional diagrams after the gray processing to determine a second void ratio of the second test piece;

the determining a third porosity of the third test piece according to the plurality of third cross-sectional views includes:

carrying out gray level processing on the plurality of third cross-sectional views to obtain a plurality of gray-level processed third cross-sectional views;

and performing gray value analysis on the plurality of third cross-sectional diagrams after the gray processing to determine a third void ratio of the third test piece.

3. The method of claim 2, wherein the performing gray scale value analysis on the plurality of gray scale processed first cross-sectional maps to determine the first porosity of the first test piece comprises:

determining the percentage of each gray value in each gray-scale processed first cross-sectional diagram to the corresponding gray-scale processed first cross-sectional diagram according to each gray-scale processed first cross-sectional diagram;

adding the percentage of each gray value in a first preset gray value range to the corresponding gray-processed first cross-sectional diagram to obtain the void ratio of each first cross-sectional diagram;

calculating a first porosity of the first test piece according to the porosity of each of the plurality of first cross-sectional diagrams;

the determining the second porosity of the second test piece by performing gray value analysis on the plurality of second cross-sectional diagrams after the gray processing comprises:

determining the percentage of each gray value in each gray-scale processed second cross-sectional diagram to the corresponding gray-scale processed second cross-sectional diagram according to each gray-scale processed second cross-sectional diagram;

adding the percentage of each gray value in a second preset gray value range to the corresponding gray-processed second cross-sectional diagram to obtain the void ratio of each second cross-sectional diagram;

calculating a second porosity of the second test piece according to the porosity of each of the second cross-sectional views;

the determining the third porosity of the third test piece by performing gray value analysis on the plurality of third cross-sectional diagrams after the gray processing includes:

determining the percentage of each gray value in each gray-scale processed third cross-sectional view to the corresponding gray-scale processed third cross-sectional view according to each gray-scale processed third cross-sectional view;

adding the percentage of each gray value in a third preset gray value range to the corresponding gray-processed third cross-sectional diagram to obtain the void ratio of each third cross-sectional diagram;

and calculating the third porosity of the third test piece according to the porosity of each of the third cross-sectional views.

4. The method according to claim 1, wherein determining the self-healing performance index of the asphalt mixture according to the first, second, and third void fractions comprises:

obtaining a self-healing performance index of the asphalt mixture according to a first difference value divided by a second difference value, wherein the first difference value is the difference between the second porosity and the third porosity; the second difference is a difference between the second porosity and the first porosity.

5. The method according to claim 1, wherein after the determining the self-healing performance index of the asphalt mix according to the first, second, and third voidages, the method further comprises:

obtaining a plurality of self-healing performance indexes;

and calculating the average value of the self-healing performance indexes.

6. The method of claim 1, wherein the four-point bending test comprises: the first test piece was subjected to four-point bending loading 10000 times under 400 microstrain.

7. The method according to claim 1, wherein the self-healing test comprises: and placing the second test piece in an environment box with the temperature of 25 ℃ and the humidity of 30% for 24 hours.

8. The utility model provides a mixture self-healing performance detection device which characterized in that, the device includes:

the acquisition module is used for acquiring a plurality of first cross-sectional views of the first test piece, a plurality of second cross-sectional views of the second test piece and a plurality of third cross-sectional views of the third test piece; the first test piece is a trabecular test piece prepared by using the asphalt mixture; the first section is obtained after the first test piece is scanned according to the CT scanning technology; the second test piece is obtained after the first test piece is subjected to a four-point bending test; the second section is obtained after a second test piece is scanned according to the CT scanning technology; the third test piece is obtained after the second test piece passes a self-healing test; the third section is obtained after the third test piece is scanned according to the CT scanning technology;

the determining module is used for determining a first void ratio of the first test piece according to the first section graphs; determining a second porosity of the second test piece according to the plurality of second section diagrams; determining a third porosity of the third test piece according to the third section diagrams; and determining the self-healing performance index of the asphalt mixture according to the first porosity, the second porosity and the third porosity.

9. An electronic device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.

Technical Field

The application relates to the technical field of performance testing, in particular to a method and a device for detecting self-healing performance of a mixture and a storage medium.

Background

The asphalt pavement can cause cracks under the action of load and environmental factors, and asphalt as a viscoelastic material can be heated and softened when the temperature rises, so that the asphalt mixture has certain self-healing performance aiming at the cracks, and the asphalt pavement has important significance.

At present, a macroscopic mechanical experiment is mainly adopted for detecting the self-healing performance of the asphalt mixture crack, the self-healing performance of the mixture is indirectly reflected through the change conditions of indexes such as ductility and modulus, and the problem that the precision and reliability of a detection result obtained through the macroscopic mechanical experiment are not high exists.

Disclosure of Invention

The embodiment of the application aims to provide a method and a device for detecting the self-healing performance of a mixture and a storage medium, and aims to solve the problem that the precision and the reliability of the detection result of the self-healing performance of the mixture obtained through a macroscopic mechanical experiment are not high at present.

In order to achieve the above object, the present application provides the following technical solutions:

in a first aspect: the application provides a method for detecting self-healing performance of a mixture, which comprises the following steps: acquiring a plurality of first cross-sectional views of a first test piece, a plurality of second cross-sectional views of a second test piece and a plurality of third cross-sectional views of a third test piece; the first test piece is a trabecular test piece prepared by using the asphalt mixture; the first section is obtained after a first test piece is scanned according to the CT scanning technology; the second test piece is obtained after the first test piece is subjected to a four-point bending test; the second section is obtained after a second test piece is scanned according to the CT scanning technology; the third test piece is obtained after the second test piece passes a self-healing test; the third section is obtained after the third test piece is scanned according to the CT scanning technology; determining a first porosity of the first test piece according to the plurality of first section diagrams; determining a second porosity of the second test piece according to the plurality of second section diagrams; determining a third porosity of the third test piece according to the third section diagrams; and determining the self-healing performance index of the asphalt mixture according to the first porosity, the second porosity and the third porosity.

In the scheme of the design, a plurality of first section diagrams of the first test piece, a plurality of second section diagrams of the second test piece and a plurality of third section diagrams of the third test piece are obtained through the CT scanning technology, more accurate void ratio indexes inside the test piece in different stages are determined according to the plurality of first section diagrams, the plurality of second section diagrams and the plurality of third section diagrams, then the mixture self-healing performance indexes are detected according to the more accurate void ratio indexes, the mixture self-healing performance is visually detected, the problems that the precision and the reliability of the mixture self-healing performance detection result obtained through a macroscopic mechanics experiment are not high at present are solved, and the precision and the reliability of the mixture self-healing performance detection result are improved.

In an alternative embodiment of the first aspect, the determining the first porosity of the first test piece according to the plurality of first cross-sectional views comprises: carrying out gray level processing on the plurality of first cross-sectional views to obtain a plurality of gray-level processed first cross-sectional views; performing gray value analysis on the plurality of first cross-sectional diagrams after the gray processing to determine a first void ratio of the first test piece; the determining a second gap of the second test piece according to the plurality of second cross-sectional diagrams includes: carrying out gray level processing on the plurality of second cross-sectional views to obtain a plurality of gray-level processed second cross-sectional views; performing gray value analysis on the plurality of second cross-sectional diagrams after the gray processing to determine a second void ratio of the second test piece; the determining a third porosity of the third test piece according to the plurality of third cross-sectional views includes: carrying out gray level processing on the plurality of third cross-sectional views to obtain a plurality of gray-level processed third cross-sectional views; and performing gray value analysis on the plurality of third cross-sectional diagrams after the gray processing to determine a third void ratio of the third test piece.

In an optional implementation manner of the first aspect, the determining the first porosity of the first test piece by performing gray-scale value analysis on the plurality of gray-scale processed first cross-sectional views includes: determining the percentage of each gray value in each gray-scale processed first cross-sectional diagram to the corresponding gray-scale processed first cross-sectional diagram according to each gray-scale processed first cross-sectional diagram; adding the percentage of each gray value in a first preset gray value range to the corresponding gray-processed first cross-sectional diagram to obtain the void ratio of each first cross-sectional diagram; calculating a first porosity of the first test piece according to the porosity of each of the plurality of first cross-sectional diagrams; the determining the second porosity of the second test piece by performing gray value analysis on the plurality of second cross-sectional diagrams after the gray processing comprises: determining the percentage of each gray value in each gray-scale processed second cross-sectional diagram to the corresponding gray-scale processed second cross-sectional diagram according to each gray-scale processed second cross-sectional diagram; adding the percentage of each gray value in a second preset gray value range to the corresponding gray-processed second cross-sectional diagram to obtain the void ratio of each second cross-sectional diagram; calculating a second porosity of the second test piece according to the porosity of each of the plurality of second cross-sectional views; the determining the third porosity of the third test piece by performing gray value analysis on the plurality of third cross-sectional diagrams after the gray processing includes: determining the percentage of each gray value in each gray-scale processed third cross-sectional view to the corresponding gray-scale processed third cross-sectional view according to each gray-scale processed third cross-sectional view; adding the percentage of each gray value in a third preset gray value range to the corresponding gray-processed third cross-sectional diagram to obtain the void ratio of each third cross-sectional diagram; and calculating the third porosity of the third test piece according to the porosity of each of the third cross-sectional views.

In an optional embodiment of the first aspect, the determining the self-healing performance index of the asphalt mixture according to the first void fraction, the second void fraction and the third void fraction comprises: obtaining a self-healing performance index of the asphalt mixture according to a first difference value divided by a second difference value, wherein the first difference value is the difference between the second porosity and the third porosity; the second difference is a difference between the second porosity and the first porosity.

In the three design embodiments, the section obtained after three-dimensional scanning of the CT is subjected to gray level processing and gray level analysis, and then the void ratio of one section is determined according to the sum of the percentage of each gray level value in a preset gray level range in the section after gray level processing, so as to obtain a first void ratio, a second void ratio and a third void ratio.

In an optional embodiment of the first aspect, after the determining the self-healing performance index of the asphalt mix according to the first, second, and third void fractions, the method further comprises: obtaining a plurality of self-healing performance indexes; calculating an average value of the plurality of self-healing performance indexes, wherein the average value represents the self-healing performance of the asphalt mixture.

In the embodiment of the design, the average value of the mixture self-healing performance index is calculated through a plurality of self-healing performance indexes, so that the finally obtained mixture self-healing performance is more accurate.

In an alternative embodiment of the first aspect, the four-point bend test comprises: the first test piece was subjected to four-point bending loading 10000 times under 400 microstrain.

In an alternative embodiment of the first aspect, the self-healing test comprises: and placing the second test piece in an environment box with the temperature of 25 ℃ and the humidity of 30% for 24 hours.

In a second aspect: the application provides a mixture self-healing performance detection device, the device includes: the acquisition module is used for acquiring a plurality of first cross-sectional views of the first test piece, a plurality of second cross-sectional views of the second test piece and a plurality of third cross-sectional views of the third test piece; the first test piece is a trabecular test piece prepared by using the asphalt mixture; the first section is obtained after the first test piece is scanned according to the CT scanning technology; the second test piece is obtained after the first test piece is subjected to a four-point bending test; the second section is obtained after a second test piece is scanned according to the CT scanning technology; the third test piece is obtained after the second test piece passes a self-healing test; the third section is obtained after the third test piece is scanned according to the CT scanning technology; the determining module is used for determining a first void ratio of the first test piece according to the first section graphs; determining a second porosity of the second test piece according to the plurality of second section diagrams; determining a third porosity of the third test piece according to the third section diagrams; and determining the self-healing performance index of the asphalt mixture according to the first porosity, the second porosity and the third porosity.

In the device of above-mentioned design, obtain many first section diagrams of first test piece through CT scanning technique, many second section diagrams of second test piece and many third section diagrams of third test piece, according to many first section diagrams, many second section diagrams and many third section diagrams survey the inside more accurate void fraction index of different stages test piece, and then detect mixture self-healing performance index according to more accurate void fraction index, detect mixture self-healing performance directly perceived, the problem that the mixture self-healing performance testing result precision and reliability that obtains through the macroscopic mechanics experiment at present have all been solved, the precision and the reliability of the mixture self-healing performance testing result that the mixture self-healing performance testing result is not high have been improved.

In an optional implementation manner of the second aspect, the determining module is specifically configured to perform gray scale processing on the multiple first cross-sectional views to obtain multiple gray-scale processed first cross-sectional views; performing gray value analysis on the plurality of first cross-sectional diagrams after the gray processing to determine a first void ratio of the first test piece; carrying out gray level processing on the plurality of second cross-sectional views to obtain a plurality of gray-level processed second cross-sectional views; performing gray value analysis on the plurality of second cross-sectional diagrams after the gray processing to determine a second void ratio of the second test piece; carrying out gray level processing on the plurality of third cross-sectional views to obtain a plurality of gray-level processed third cross-sectional views; and performing gray value analysis on the plurality of third cross-sectional diagrams after the gray processing to determine a third void ratio of the third test piece.

In an optional implementation manner of the second aspect, the determining module is further specifically configured to determine, according to each of the grayscale processed first cross-sectional views, a percentage of each grayscale value in each of the grayscale processed first cross-sectional views to the corresponding grayscale processed first cross-sectional view; adding the percentage of each gray value in a first preset gray value range to the corresponding gray-processed first cross-sectional diagram to obtain the void ratio of each first cross-sectional diagram; calculating a first porosity of the first test piece according to the porosity of each of the plurality of first cross-sectional diagrams; determining the percentage of each gray value in each gray-scale processed second cross-sectional diagram to the corresponding gray-scale processed second cross-sectional diagram according to each gray-scale processed second cross-sectional diagram; adding the percentage of each gray value in a second preset gray value range to the corresponding gray-processed second cross-sectional diagram to obtain the void ratio of each second cross-sectional diagram; calculating a second porosity of the second test piece according to the porosity of each of the plurality of second cross-sectional views; determining the percentage of each gray value in each gray-scale processed third cross-sectional view to the corresponding gray-scale processed third cross-sectional view according to each gray-scale processed third cross-sectional view; adding the percentage of each gray value in a third preset gray value range to the corresponding gray-processed third cross-sectional diagram to obtain the void ratio of each third cross-sectional diagram; and calculating the third porosity of the third test piece according to the porosity of each of the third cross-sectional views.

In an optional implementation manner of the second aspect, the determining module is further specifically configured to obtain a self-healing performance index of the asphalt mixture according to a first difference value divided by a second difference value, where the first difference value is a difference between the second porosity and the third porosity; the second difference is a difference between the second porosity and the first porosity.

In an optional implementation manner of the second aspect, the apparatus further includes an obtaining module, configured to obtain a plurality of self-healing performance indexes; and the calculation module is used for calculating the average value of the self-healing performance indexes, and the average value represents the self-healing performance of the asphalt mixture.

In a third aspect: the present application further provides an electronic device, including: a processor, a memory connected to the processor, the memory storing a computer program that, when executed by the computing device, is executed by the processor to perform the method of the first aspect, any of the alternative implementations of the first aspect.

In a fourth aspect: the present application provides a computer readable storage medium having stored thereon a computer program for performing the method of the first aspect, any of the alternative implementations of the first aspect, when the computer program is executed by a processor.

In a fifth aspect: the present application provides a computer program product which, when run on a computer, causes the computer to perform the method of the first aspect, any of the alternative implementations of the first aspect.

Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and drawings.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.

Fig. 1 is a schematic view of a first process of a method for detecting self-healing performance of a mixture according to a first embodiment of the present application;

fig. 2 is a second process schematic diagram of a method for detecting a self-healing performance of a mixture according to a first embodiment of the present application;

fig. 3 is a third flow diagram of a method for detecting self-healing performance of a mixture according to a first embodiment of the present application;

fig. 4 is a fourth flowchart illustrating a method for detecting a self-healing performance of a mixture according to a first embodiment of the present application;

fig. 5 is a schematic structural diagram of a device for detecting self-healing performance of a mixture according to a second embodiment of the present application;

fig. 6 is a schematic structural diagram of an electronic device according to a third embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

First embodiment

As shown in fig. 1, the present application provides a method for detecting a self-healing performance of a mixture, where the method may be applied to a server, and the method specifically includes the following steps:

step S100: and acquiring a plurality of first cross-sectional views of the first test piece, a plurality of second cross-sectional views of the second test piece and a plurality of third cross-sectional views of the third test piece.

Step S102: determining a first porosity of the first test piece according to the plurality of first section diagrams; determining a second porosity of the second test piece according to the plurality of second section diagrams; and determining a third porosity of the third test piece according to the plurality of third section diagrams.

Step S104: and determining the self-healing performance index of the asphalt mixture according to the first void ratio, the second void ratio and the third void ratio.

In step S100, the first test piece is a trabecular test piece prepared from an asphalt mixture, and specifically, the test piece used for the four-point bending test may be manufactured according to an asphalt mixture four-point bending fatigue test procedure (T0739-2011) in "road engineering asphalt and mixture test procedure". The trabecular test piece can be 380mm +/-5 mm in length, 50mm +/-6 mm in height and 63mm +/-6 mm in width. The second test piece is obtained by carrying out a four-point bending test on the first test piece; the third test piece is obtained after the second test piece is subjected to a self-healing test.

The second test piece is obtained by performing a four-point bending test on the first test piece, the four-point bending means that a sample is placed on two stress points (the lower half part of a four-point bending fixture) with a certain distance, two points (the upper half part of the four-point bending fixture) above the stress points apply pressure to the sample, and the upper point and the lower point are respectively a stress point and a stress point. The four-point bending test performed on the first test piece in the scheme of the application may specifically be: under the condition of 400 microstrain, four-point bending loading 10000 times are carried out to the first test piece, and the specific microstrain condition and the loading times can be properly adjusted according to the actual situation.

The third test piece obtains for this second test piece after carrying out the self-healing test, and the self-healing test represents the experiment for simulation test piece crack self-healing process, and the self-healing test specifically can be in this application scheme: the second test piece is placed in an environment box with the temperature of 25 ℃ and the humidity of 30% for 24 hours, and the specific temperature, humidity and time length setting can be properly adjusted according to actual conditions.

The parameter settings of the four-point bending test and the self-healing test are only for facilitating the understanding of the scheme of the present application, and should not limit the protection scope of the present application.

The multiple first cross-sectional views in the step 100 are obtained by scanning the first test piece through a CT three-dimensional scanning technology; the plurality of second cross-sectional diagrams are obtained by scanning the second test piece through a CT three-dimensional scanning technology; and the plurality of third cross-sectional diagrams are obtained by scanning the third test piece through a CT three-dimensional scanning technology. The number of the first cross-sectional diagram, the second cross-sectional diagram and the third cross-sectional diagram can be obtained by setting an interlayer scanning interval of the CT three-dimensional scanning technology, taking the first cross-sectional diagram as an example, assuming that the length of the first test piece is 380mm, the interlayer scanning interval of the CT three-dimensional scanning technology can be set to be 0.1mm, and thus 3800 first cross-sectional diagram can be obtained after the first test piece is scanned by the CT three-dimensional scanning technology. The number of second and third profiles can also be obtained by this method. In addition, the basic working principle of the CT three-dimensional scanning technology is as follows: and transmitting the fault of the test piece to be tested from multiple directions by using X rays in a scanning manner, and collecting the rays attenuated after transmission by using a detector to finally obtain a CT scanning sectional view of the test piece to be tested.

In addition, since the execution subject of the method may be a server, the way for the server to obtain the plurality of first cross-sectional views, the plurality of second cross-sectional views and the plurality of third cross-sectional views may be that after the CT three-dimensional scanning scans the corresponding test piece to obtain the corresponding cross-sectional view, the plurality of corresponding cross-sectional views obtained by the scanning may be transmitted to the server connected to the server. For example, after a CT three-dimensional scan scans a first test piece to obtain a plurality of first cross-sectional views, the plurality of first cross-sectional views are transmitted to a server connected to the server, and after the server obtains the plurality of first cross-sectional views, the server may store or directly use the plurality of obtained first cross-sectional views. Likewise, the second and third cross-sectional views yield the same principles.

It has been explained above that after the server obtains the plurality of first cross-sectional views, the obtained plurality of first cross-sectional views may be stored or directly utilized, and the corresponding step S102 determines the first porosity of the first test piece according to the plurality of first cross-sectional views; determining a second porosity of the second test piece according to the plurality of second section diagrams; determining a third porosity of the third test piece according to the plurality of third cross-sectional diagrams, wherein the specific experimental process comprises the following two situations:

firstly, after the first test piece is scanned by using a CT three-dimensional scanning technology, a server receives a plurality of first section diagrams, and determines a first void ratio of the first test piece by directly using the plurality of first section diagrams; then, the first test piece is subjected to a four-point bending test to obtain a second test piece, the second test piece is scanned by using a CT three-dimensional scanning technology, then the server receives a plurality of second section diagrams, and the second void ratio of the second test piece is determined by directly using the plurality of second section diagrams; then, carrying out a self-healing test on the second test piece to obtain a third test piece, scanning the third test piece by using a CT three-dimensional scanning technology, receiving a plurality of third section diagrams by using a server, and directly determining a third void ratio of the third test piece by using the plurality of third section diagrams; finally, the first porosity, the second porosity and the third porosity are obtained.

Secondly, after the first test piece is scanned by using the CT three-dimensional scanning technology, the server receives a plurality of first cross-sectional views, and stores the plurality of first cross-sectional views after receiving the plurality of first cross-sectional views; then, the first test piece is subjected to a four-point bending test to obtain a second test piece, the second test piece is scanned by using a CT three-dimensional scanning technology, and the server receives and stores a plurality of second section diagrams; then, carrying out a self-healing test on the second test piece to obtain a third test piece, scanning the third test piece by using a CT three-dimensional scanning technology, and receiving a plurality of third section diagrams by using a server; after the server receives the third cross-sectional views, the server determines a first void ratio by using the first cross-sectional views at one time; determining a second porosity by using the plurality of second section diagrams; determining a third porosity by using a plurality of third section diagrams; finally, the first porosity, the second porosity and the third porosity are obtained.

After the first void fraction, the second void fraction and the third void fraction are obtained in step S102, step S104 is executed to determine a self-healing performance index of the mixed material according to the first void fraction, the second void fraction and the third void fraction.

In the scheme, a plurality of first section diagrams of the first test piece, a plurality of second section diagrams of the second test piece and a plurality of third section diagrams of the third test piece are obtained through a CT scanning technology, more accurate void ratio indexes inside the test piece in different stages are determined according to the plurality of first section diagrams, the plurality of second section diagrams and the plurality of third section diagrams, then the mixture self-healing performance indexes are detected according to the more accurate void ratio indexes, the mixture self-healing performance is intuitively detected, the problem that the precision and the reliability of the mixture self-healing performance detection result obtained through a macroscopic mechanics experiment at present are not high is solved, and the precision and the reliability of the mixture self-healing performance detection result are improved.

In an optional implementation manner of this embodiment, in step S102, the first porosity of the first test piece is determined according to the plurality of first cross-sectional diagrams; determining a second porosity of the second test piece according to the plurality of second section diagrams; determining a third porosity of the third test piece according to the plurality of third cross-sectional diagrams, specifically as shown in fig. 2, including the following steps:

step S1020: and performing gray value analysis on the plurality of first cross-sectional diagrams to determine the first void ratio of the first test piece.

Step S1022: and performing gray scale processing on the plurality of second cross-sectional views to obtain a plurality of gray scale processed second cross-sectional views, and performing gray scale value analysis on the plurality of gray scale processed second cross-sectional views to determine a second void ratio of the second test piece.

Step S1024: and performing gray scale processing on the plurality of third cross-sectional views to obtain a plurality of gray-scale processed third cross-sectional views, and performing gray scale value analysis on the plurality of gray-scale processed third cross-sectional views to determine a third void ratio of the third test piece.

In the above step, the gray-scale processing is performed on each of the plurality of first cross-sectional views, the plurality of second cross-sectional views, and the plurality of third cross-sectional views, and the gray-scale analysis is performed on each of the plurality of gray-scale processed first cross-sectional views, the plurality of gray-scale processed second cross-sectional views, and the plurality of gray-scale processed third cross-sectional views, to determine the first porosity, the second porosity, and the third porosity.

In an optional implementation manner of this embodiment, the determining the first porosity of the first test piece by performing gray-scale value analysis on the multiple gray-scale processed first cross-sectional views in step S1020 may specifically include, as shown in fig. 3, the following steps:

step S10200: and determining the percentage of each gray value in each gray-scale processed first cross-sectional diagram to the corresponding gray-scale processed first cross-sectional diagram according to each gray-scale processed first cross-sectional diagram.

Step S10202: and adding the percentage of each gray value in the first preset gray value range in the corresponding gray-processed first cross-sectional diagram to obtain the void ratio of each first cross-sectional diagram.

Step S10204: and calculating the first porosity of the first test piece according to the porosity of each of the plurality of first cross-sectional diagrams.

In step S10200, the gray-scale processed first cross-sectional image can be input into Origin software to determine the percentage of each gray-scale value in each gray-scale processed first cross-sectional image in the corresponding gray-scale processed first cross-sectional image. Further, step S10202 is performed to preset a gray value range, and the percentage of each gray value in the gray value range is added to obtain the void ratio of the first cross-sectional view. For example, assuming that the gray value of the gap is within 50, the corresponding percentages of the gray values of 0-50 are selected and added, and finally the void ratio of a cross-sectional diagram can be obtained. The porosity of each of the plurality of first cross-sectional views can be obtained by the above-mentioned methods of steps S10200 to S10202, and further, step S10204 is executed to calculate the first porosity of the first test piece according to the porosity of each of the first cross-sectional views, specifically, the total porosity obtained by adding the porosities of each of the first cross-sectional views is divided by the number of the first cross-sectional views.

The method for determining the second air gap ratio of the second test piece and the method for determining the third air gap ratio of the third test piece in the foregoing steps S1022 and S1024 are similar to the method for determining the first air gap ratio of the first test piece in the foregoing steps S10200 to S10204, and are not repeated here.

In an optional implementation manner of this embodiment, the determining the self-healing performance index of the asphalt mixture according to the first void ratio, the second void ratio and the third void ratio in step S104 is specifically as shown in fig. 4, and includes the following steps:

step S1040: obtaining a self-healing performance index of the asphalt mixture according to the first difference value divided by the second difference value, wherein the first difference value is the difference between the second porosity and the third porosity; the second difference is the difference between the second porosity and the first porosity.

In step S1040, the first difference is expressed as a difference between the second void fraction and the third void fraction, the second difference is expressed as a difference between the second void fraction and the first void fraction, and the self-healing performance index of the asphalt mixture is expressed as a quotient of the first difference and the second difference, which may be expressed by the following formula:

wherein HR is self-healing performance index, VV, of the asphalt mixture_i1A first porosity; VV_i2A second porosity; VV_i3Is the third porosity.

In the three design embodiments, the section obtained after three-dimensional scanning of the CT is subjected to gray level processing and gray level analysis, and then the void ratio of one section is determined according to the sum of the percentage of each gray level value in a preset gray level range in the section after gray level processing, so as to obtain a first void ratio, a second void ratio and a third void ratio.

In an alternative embodiment of the present embodiment, a plurality of test pieces may be prepared from the same asphalt mixture, and the above-described steps S100 to S104 may be performed simultaneously to obtain a plurality of self-healing performance indexes of the asphalt mixture, and the self-healing performance index average value of the asphalt mixture may be obtained from the self-healing performance indexes of the asphalt mixture, and the self-healing performance index average value of the asphalt mixture may be used as the normal self-healing performance index of the asphalt mixture. Wherein, the quantity of a plurality of test pieces of going on simultaneously can be no less than 4, can make the self-healing performance index that final calculation obtained more accurate like this.

In addition to obtaining the self-healing performance index in the normal case of the asphalt mixture by preparing a plurality of test pieces using the same asphalt mixture, the self-healing performance indexes of different asphalt mixtures may be compared by preparing test pieces using different asphalt mixtures and performing the above-described steps S100 to S104. For example, the SMA-13 and AC-13 types of mixed materials commonly used in the road industry may be selected, the two types of mixed materials are respectively manufactured into test pieces, then the test pieces are calculated by using the methods of the foregoing steps S100 to S104, the first void fraction, the second void fraction, the third void fraction and the self-healing performance index of the SMA-13 type and the AC-13 type are respectively obtained, and then the two types are compared. For example, the first porosity, the second porosity and the third porosity of the SMA-13 are respectively 4.04%, 4.32% and 4.17% through a plurality of experimental results, and the self-healing performance index of the mixture of the SMA-13 type can be calculated to be 53.57%; the first, second and third void fractions of the AC-13 are obtained to be 4.21%, 4.74% and 4.52%, respectively, and the self-healing performance index of the AC-13 type mixture can be calculated to be 41.51%. Therefore, the self-healing performance of the SMA-13 mixture is stronger than that of the AC-13 mixture as can be seen from the experimental results.

Second embodiment

Fig. 5 shows a schematic structural block diagram of a mix self-healing performance detection device provided by the present application, and it should be understood that the device corresponds to the above-mentioned method embodiments of fig. 1 to 4, and can perform the steps involved in the method of the first embodiment, and the specific functions of the device may be referred to the above description, and a detailed description is appropriately omitted here to avoid repetition. The device includes at least one software function that can be stored in memory in the form of software or firmware (firmware) or solidified in the Operating System (OS) of the device. Specifically, the apparatus includes: an obtaining module 200, configured to obtain multiple first cross-sectional views of a first test piece, multiple second cross-sectional views of a second test piece, and multiple third cross-sectional views of a third test piece; the first test piece is a trabecular test piece prepared by using the asphalt mixture; the first section is obtained after the first test piece is scanned according to the CT scanning technology; the second test piece is obtained after the first test piece is subjected to a four-point bending test; the second section is obtained after scanning a second test piece according to the CT scanning technology; the third test piece is obtained after the second test piece passes the self-healing test; the third section is obtained after scanning the third test piece according to the CT scanning technology; the determining module 202 is configured to determine a first porosity of the first test piece according to the plurality of first cross-sectional views; determining a second porosity of the second test piece according to the plurality of second section diagrams; determining a third porosity of the third test piece according to the plurality of third section diagrams; and determining the self-healing performance index of the asphalt mixture according to the first porosity, the second porosity and the third porosity.

In the device of above-mentioned design, obtain many first section diagrams of first test piece through CT scanning technique, many second section diagrams of second test piece and many third section diagrams of third test piece, according to many first section diagrams, many second section diagrams and many third section diagrams survey the inside more accurate void fraction index of different stages test piece, and then detect mixture self-healing performance index according to more accurate void fraction index, detect mixture self-healing performance directly perceived, the problem that the mixture self-healing performance testing result precision and reliability that obtains through the macroscopic mechanics experiment at present have all been solved, the precision and the reliability of the mixture self-healing performance testing result that the mixture self-healing performance testing result is not high have been improved.

In an optional implementation manner of this embodiment, the determining module 202 is specifically configured to perform gray processing on the multiple first cross-sectional views to obtain multiple gray-processed first cross-sectional views; performing gray value analysis on the multiple gray-processed first cross-sectional diagrams to determine a first void ratio of the first test piece; carrying out gray level processing on the plurality of second cross-sectional views to obtain a plurality of gray-level processed second cross-sectional views; performing gray value analysis on the plurality of second cross-sectional diagrams after the gray processing to determine a second void ratio of the second test piece; carrying out gray level processing on the plurality of third cross-sectional views to obtain a plurality of gray-level processed third cross-sectional views; and performing gray value analysis on the plurality of third cross-sectional diagrams after the gray processing to determine a third porosity of the third test piece.

In an optional implementation manner of this embodiment, the determining module 202 is further specifically configured to determine, according to each of the grayscale processed first cross-sectional views, a percentage of each grayscale value in each of the grayscale processed first cross-sectional views to the corresponding grayscale processed first cross-sectional view; adding the percentage of each gray value in a first preset gray value range to the corresponding gray-processed first cross-sectional diagram to obtain the void ratio of each first cross-sectional diagram; calculating a first porosity of the first test piece according to the porosity of each of the plurality of first cross-sectional diagrams; determining the percentage of each gray value in each gray-scale processed second cross-sectional diagram to the corresponding gray-scale processed second cross-sectional diagram according to each gray-scale processed second cross-sectional diagram; adding the percentage of each gray value in a second preset gray value range to the corresponding gray-processed second cross-sectional diagram to obtain the void ratio of each second cross-sectional diagram; calculating a second porosity of the second test piece according to the porosity of each of the plurality of second cross-sectional diagrams; determining the percentage of each gray value in each gray-scale processed third cross-sectional view to the corresponding gray-scale processed third cross-sectional view according to each gray-scale processed third cross-sectional view; adding the percentage of each gray value in a third preset gray value range to the corresponding gray-processed third cross-sectional diagram to obtain the void ratio of each third cross-sectional diagram; and calculating the third porosity of the third test piece according to the porosity of each of the third cross-sectional views.

In an optional implementation manner of this embodiment, the determining module 202 is further specifically configured to obtain a self-healing performance index of the asphalt mixture according to a first difference value divided by a second difference value, where the first difference value is a difference between the second void fraction and the third void fraction; the second difference is a difference between the second porosity and the first porosity.

In an optional implementation manner of this embodiment, the obtaining module 200 is further configured to obtain a plurality of self-healing performance indexes; and the calculating module 204 is configured to calculate an average value of the multiple self-healing performance indexes, where the average value represents the self-healing performance of the asphalt mixture.

Third embodiment

As shown in fig. 6, the present application provides an electronic device 3 including: the processor 301 and the memory 302, the processor 301 and the memory 302 being interconnected and communicating with each other via a communication bus 303 and/or other form of connection mechanism (not shown), the memory 302 storing a computer program executable by the processor 301, the processor 301 executing the computer program when the computing device is running to perform the method of the first embodiment, any alternative implementation of the first embodiment.

The present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method of the first embodiment, any of the alternative implementations of the first embodiment.

The storage medium may be implemented by any type of volatile or nonvolatile storage device or combination thereof, such as a Static Random Access Memory (SRAM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), an Erasable Programmable Read-Only Memory (EPROM), a Programmable Read-Only Memory (PROM), a Read-Only Memory (ROM), a magnetic Memory, a flash Memory, a magnetic disk, or an optical disk.

The present application provides a computer program product which, when run on a computer, causes the computer to perform the method of the first embodiment, any of its alternative implementations.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the modules is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.

Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.

The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.