Marshall Compaction of Asphalt Mixture, Manufacturing Method, System, Equipment and Medium

Abstract

The present invention discloses a Marshall compaction method, manufacturing method, system, device and medium for asphalt mixture. The compaction method includes: obtaining dynamic response parameters of the asphalt mixture during Marshall compaction; the dynamic response parameters are used to characterize the internal state of the asphalt mixture corresponding to the number of compaction times; determining whether the degree of change of the dynamic response parameters is stable; if so, determining the compaction number corresponding to when the degree of change of the dynamic response parameters reaches stability as the target compaction number. The compaction method, by obtaining the dynamic response parameters of the asphalt mixture and determining the target compaction number when the degree of change of the dynamic response parameters reaches stability, automatically and intelligently determines the compaction number, and the degree of change of the dynamic response parameters directly reflects the compaction state inside the asphalt mixture, thereby improving the accuracy of determining the compaction number and avoiding the crushing of coarse aggregates caused by overcompaction or the porosity not meeting the requirements caused by undercompaction.

Description

Technical Field

[0001] The present invention relates to the technical field of road engineering, and particularly relates to a Marshall compaction method, manufacturing method, system, equipment and medium for asphalt mixture. Background Art

[0002] The Marshall design method is widely used in the design of asphalt mixture. The specimen forming method is compaction forming. Although this forming method has certain limitations in aspects such as simulating field compaction and the correlation with road traffic volume, due to its simplicity, strong applicability, and low equipment price, it is still one of the main methods for the mix proportion design of asphalt mixture at present.

[0003] During the compaction forming process of asphalt mixture, there is a critical state of the internal skeleton structure of the system. Before reaching the critical state, the compaction effect can effectively increase the density of the asphalt mixture, and the compaction effect is significant; after reaching the critical state, that is, the coarse aggregates are in contact with each other after compaction to form a stable skeleton structure and are interlocked with each other, and the coarse and fine aggregates and the coated asphalt share the load to reach a stable state. Further compaction will significantly increase the risk of aggregate crushing, change the original gradation of the mixture, and have an adverse impact on its road performance. Therefore, the current Marshall specimen forming method with a fixed number of compaction times lacks a judgment standard for the internal compaction state of the mixture. Combining relevant practical experience, for the Marshall specimen with 75 double-sided compactions, it often leads to the crushing of coarse aggregates due to over-compaction. On the one hand, it changes the original gradation of the mixture, and on the other hand, the new broken surface cannot be coated with asphalt to form a mottled material, thus affecting the effectiveness of the performance test results of the Marshall specimen formed indoors. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the defect that when designing the mix proportion of asphalt mixture, using a fixed number of compactions for specimens leads to the crushing of coarse aggregates due to over-compaction, and to provide a Marshall compaction method, manufacturing method, system, equipment and medium for asphalt mixture.

[0005] The present invention solves the above technical problem by the following technical solutions:

[0006] The present invention provides a Marshall compaction method for asphalt mixture, and the compaction method includes:

[0007] Obtaining the dynamic response parameters of the asphalt mixture during the Marshall compaction process;

[0008] The dynamic response parameters are used to characterize the internal state of the asphalt mixture corresponding to the number of compactions;

[0009] Judging whether the change degree of the dynamic response parameters is stable;

[0010] If so, determine the compaction number corresponding to when the change degree of the dynamic response parameter reaches stability as the target compaction number.

[0011] Preferably, the steps of obtaining the dynamic response parameter of the asphalt mixture during the Marshall compaction process include:

[0012] Embed sensors at preset positions inside the asphalt mixture to obtain the dynamic response parameter of the asphalt mixture during the compaction process.

[0013] Preferably, the steps of embedding sensors at preset positions inside the asphalt mixture to obtain the dynamic response parameter of the asphalt mixture during the compaction process include:

[0014] Uniformly embed a preset number of multi-index integrated intelligent sensors along the central axis of the asphalt mixture;

[0015] Take the average value of the values of the same dynamic response parameter respectively obtained by the preset number of multi-index integrated intelligent sensors during the compaction process as the dynamic response parameter of the asphalt mixture during the compaction process.

[0016] Preferably, the steps of judging whether the change degree of the dynamic response parameter is stable include:

[0017] Determine the dynamic response parameter change rate according to the dynamic response parameter;

[0018] The dynamic response parameter change rate is used to characterize the change degree of the dynamic response parameter;

[0019] Judge whether the change degree of the dynamic response parameter is stable according to the dynamic response parameter change rate and a preset stability threshold.

[0020] Preferably, the dynamic response parameter includes the contact stress, acceleration and rotation angle of the internal particles of the asphalt mixture;

[0021] Determine the dynamic response parameter change rate according to the dynamic response parameter and the following formula:

[0022]

[0023] Wherein, n represents the current compaction number, R n represents the dynamic response parameter change rate corresponding to n times of compaction; SD σ 、SD α and SD δ are respectively the standard deviations of the peak values of the contact stress σ, acceleration α and rotation angle δ of the last adjacent preset times of compaction; Δσ, Δα and Δδ are respectively the change values of the peak values of the contact stress σ, acceleration α and rotation angle δ measured in the last adjacent two times of compaction;

[0024] If so, the step of determining the compaction times corresponding to the stable change degree of the dynamic response parameter as the target compaction times includes:

[0025] When the dynamic response parameter corresponding to the current compaction times is less than the stable threshold and the dynamic response parameter corresponding to the previous adjacent compaction times is greater than the stable threshold, the current compaction times is used as the target compaction times.

[0026] The present invention also provides a method for manufacturing an asphalt mixture, and the manufacturing method includes:

[0027] Determine the preliminary ratio of the asphalt mixture;

[0028] Determine the compaction times of the asphalt mixture according to the Marshall compaction method of the asphalt mixture as described above, perform compaction treatment on the asphalt mixture according to the compaction times, and perform performance tests on the compacted asphalt mixture;

[0029] Determine whether the preliminary ratio is the target ratio according to whether the first index obtained by the compaction treatment and the second index obtained by the performance test meet the standards.

[0030] The present invention also provides a Marshall compaction system for an asphalt mixture, and the compaction system includes:

[0031] A dynamic response parameter acquisition module, configured to acquire the dynamic response parameter of the asphalt mixture during the Marshall compaction process;

[0032] The dynamic response parameter is used to characterize the internal state of the asphalt mixture corresponding to the compaction times;

[0033] A change degree judgment module, configured to judge whether the change degree of the dynamic response parameter is stable;

[0034] A compaction times determination module, configured to determine the compaction times corresponding to the stable change degree of the dynamic response parameter as the target compaction times.

[0035] Preferably, the dynamic response parameter acquisition module is specifically configured to bury sensors at preset positions inside the asphalt mixture to acquire the dynamic response parameter of the asphalt mixture during the compaction process.

[0036] Preferably, the dynamic response parameter acquisition module is specifically configured to uniformly bury a preset number of multi-index integrated intelligent sensors on the central axis of the asphalt mixture;

[0037] The dynamic response parameter acquisition module is specifically configured to take the average value of the values of the same dynamic response parameter respectively obtained by the preset number of multi-index integrated intelligent sensors during the compaction process as the dynamic response parameter of the asphalt mixture during the compaction process.

[0038] Preferably, the change degree judgment module is specifically configured to determine the dynamic response parameter change rate according to the dynamic response parameter;

[0039] The dynamic response parameter change rate is used to characterize the change degree of the dynamic response parameter;

[0040] The change degree judgment module is specifically configured to judge whether the change degree of the dynamic response parameter is stable according to the dynamic response parameter change rate and a preset stability threshold.

[0041] Preferably, the dynamic response parameter includes the contact stress, acceleration and rotation angle of the internal particles of the asphalt mixture;

[0042] The change degree judgment module is specifically configured to determine the dynamic response parameter change rate according to the dynamic response parameter and the following formula:

[0043]

[0044] where n represents the current compaction times, and R n represents the dynamic response parameter change rate corresponding to n times of compaction; SD σ , SD α and SD δ are the standard deviations of the peak values of the contact stress σ, acceleration α and rotation angle δ of the last adjacent preset times of compaction respectively; Δσ, Δα and Δδ are the change values of the peak values of the contact stress σ, acceleration α and rotation angle δ measured in the last adjacent two times of compaction respectively;

[0045] The compaction times determination module is specifically configured to use the current compaction times as the target compaction times when the dynamic response parameter corresponding to the current compaction times is less than the stability threshold and the dynamic response parameter corresponding to the previous adjacent compaction times is greater than the stability threshold.

[0046] The present invention also provides a production system for asphalt mixture, and the production system includes:

[0047] A pre-ratio determination module, configured to determine the pre-ratio of the asphalt mixture;

[0048] A compaction test module, configured to determine the compaction times of the asphalt mixture according to the Marshall compaction system of the asphalt mixture as described above, perform compaction treatment on the asphalt mixture according to the compaction times, and perform performance tests on the compacted asphalt mixture;

[0049] The index analysis module is used to determine whether the preliminary proportion is the target proportion according to whether the first index obtained by compaction treatment and the second index obtained by performance test meet the standards.

[0050] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the Marshall compaction method of the asphalt mixture or the production method of the asphalt mixture as described above is implemented.

[0051] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the Marshall compaction method of the asphalt mixture or the production method of the asphalt mixture as described above is implemented.

[0052] The positive and progressive effects of the present invention are as follows:

[0053] In the Marshall compaction method of the asphalt mixture provided by the present invention, by obtaining the dynamic response parameters characterizing the internal state of the asphalt mixture corresponding to the number of compaction times, when the change degree of the dynamic response parameters reaches stability, the target compaction times are determined. The compaction times of the asphalt mixture are determined automatically and intelligently, and the change degree of the dynamic response parameters of the internal state of the asphalt mixture corresponding to the number of compaction times directly reflects the compaction state inside the asphalt mixture, which is more accurate than indirectly determining the compaction state through external parameters (such as the acceleration response of the compaction hammer). Furthermore, the accuracy of determining the compaction times of asphalt mixtures with different proportions and different gradation types is improved, avoiding the crushing of coarse aggregates caused by over-compaction or the porosity not meeting the requirements caused by under-compaction, and improving the quality of the asphalt mixture. Description of the Drawings

[0054] Figure 1 It is the first flow chart of the Marshall compaction method of the asphalt mixture in Embodiment 1 of the present invention.

[0055] Figure 2 It is the second flow chart of the Marshall compaction method of the asphalt mixture in Embodiment 1 of the present invention.

[0056] Figure 3 It is a schematic diagram of the buried position of the intelligent sensor and the compaction method in Embodiment 1 of the present invention.

[0057] Figure 4 It is a display diagram of the test results of the internal temperature of the mixture in Embodiment 1 of the present invention.

[0058] Figure 5 It is a flow chart of the production method of the asphalt mixture in Embodiment 2 of the present invention.

[0059] Figure 6 It is a schematic structural diagram of the Marshall compaction system for the asphalt mixture in Embodiment 3 of the present invention.

[0060] Figure 7 It is a schematic structural diagram of the production system for the asphalt mixture in Embodiment 4 of the present invention.

[0061] Figure 8 It is a schematic structural diagram of the electronic device in Embodiment 5 of the present invention. Specific embodiments

[0062] The present invention will be further described below by way of embodiments, but the present invention is not limited to the scope of the described embodiments.

[0063] Embodiment 1

[0064] Please refer to Figure 1 , which is the first flowchart of the Marshall compaction method for the asphalt mixture in this embodiment. Specifically, the compaction method includes:

[0065] S101. Obtain the internal dynamic response parameters of the specimen during the Marshall compaction of the asphalt mixture; the dynamic response parameters are used to characterize the internal state of the asphalt mixture corresponding to the compaction times. Specifically, compared with determining the compaction state of the asphalt mixture through external data or parameters, the dynamic response parameters in this embodiment are to characterize the internal state of the asphalt mixture corresponding to the compaction times, and more directly and truly reflect the compaction state of the asphalt mixture.

[0066] S102. Judge whether the change degree of the dynamic response parameters is stable. Specifically, it is reflected by the change of the dynamic response parameters (including the inter-particle contact stress σ, acceleration a, and rotation angle δ) with the compaction times. The response laws of asphalt mixtures of different gradation types (including but not limited to AC, SMA, OGFC, etc.) are different. Among them, SMA (Stone Mastic Asphalt) refers to stone mastic asphalt mixture, OGFC (Open-graded Friction Courses) refers to open-graded drainage wearing course mixture, and AC (Asphalt Concrete) refers to dense-graded asphalt mixture.

[0067] S103. If so, determine the compaction times corresponding to when the change degree of the dynamic response parameters reaches stability as the target compaction times. In an optional implementation manner, the critical compaction times with the change rate of the dynamic response parameters less than the preset stability threshold are used as the target compaction times.

[0068] In an optional implementation manner, step S101 includes:

[0069] Sensors are buried at preset positions inside the asphalt mixture to obtain the dynamic response parameters of the asphalt mixture during the compaction process.

[0070] The following further explains in combination with the Marshall compaction test.

[0071] In this embodiment, AC-20C type asphalt mixture is used, the asphalt used is 70# base asphalt, the asphalt-aggregate ratio is 4.5%, and the synthetic gradation of the mineral aggregate is shown in Table 1.

[0072] Table 1

[0073]

[0074] In this embodiment, a standard Marshall compactor is used. The inner diameter of the test mold is 101.06 mm ± 0.2 mm (millimeters), the height is 87 mm, the diameter of the base is about 120.6 mm, the diameter of the compaction hammer is 98.5 mm ± 0.5 mm, the weight is 4536 g ± 9 g (grams), and the drop height is 457.2 mm ± 1.5 mm.

[0075] Please refer to Figure 2 , which is the second flow chart of the Marshall compaction method for the asphalt mixture in this embodiment. Specifically, as Figure 2 shown, the steps of setting sensors at preset positions inside the asphalt mixture to obtain the dynamic response parameters of the asphalt mixture during the compaction process include:

[0076] S1011. Uniformly bury a preset number of multi-index integrated intelligent sensors along the central axis of the asphalt mixture. As Figure 3 shown, multi-index integrated intelligent sensors are buried at the central axis of the Marshall specimen (h is the height of the Marshall specimen) position to collect the internal particle contact stress σ, acceleration α, rotation angle δ, and temperature t of the asphalt mixture during the Marshall compaction process. A large number of test data show that compared with other buried positions, multi-index integrated multi-source intelligent sensors are buried at the central axis at position, and the test signals are the most stable and the test results are the best.

[0077] The specific method is as follows: After checking the equipment such as the Marshall compactor control box and compaction hammer without errors, prepare to bury the multi-index integrated intelligent sensor. Add asphalt mixture into the Marshall test mold. When it is added to one-third of the required amount, after preliminary leveling, bury the multi-index integrated intelligent sensor at the center position of the cross-section of the test mold; continue to add materials. When it is added to two-thirds of the required amount, after preliminary leveling, bury the multi-index integrated intelligent sensor at the center position of the cross-section of the test mold; add the remaining asphalt mixture. Then, compact it 75 times on one side, and simultaneously collect and record the contact stress σ, acceleration a, rotation angle δ, and temperature t between the particles inside the mixture during the Marshall compaction process in real time. Turn over the Marshall specimen that has been compacted 75 times on one side and continue to compact it until it reaches the compaction stable state, and simultaneously collect and record the contact stress σ, acceleration a, rotation angle δ, and temperature t between the particles inside the mixture during the Marshall compaction process in real time. The temperature results are as Figure 4 shown. Since the temperature is related to the contact stress σ between the particles, the temperature value is measured simultaneously as a reference.

[0078] S1012. Take the average value of the numerical values of the same dynamic response parameter respectively obtained by a preset number of multi-index integrated intelligent sensors during the compaction process as the dynamic response parameter of the asphalt mixture during the compaction process.

[0079] In an optional implementation manner, step S102 includes:

[0080] S1021. Determine the dynamic response parameter change rate according to the dynamic response parameter; the dynamic response parameter change rate is used to characterize the change degree of the dynamic response parameter.

[0081] S1022. Judge whether the change degree of the dynamic response parameter is stable according to the dynamic response parameter change rate and a preset stable threshold.

[0082] In this embodiment, the dynamic response parameters include the contact stress, acceleration, and rotation angle of the internal particles of the asphalt mixture; the dynamic response parameter change rate is determined according to the dynamic response parameter and the following formula:

[0083]

[0084] Among them, n represents the current compaction times, and R n represents the dynamic response parameter change rate corresponding to n times of compaction; SD σ , SD α and SD δ are respectively the standard deviations of the peak values of the contact stress σ, acceleration α, and rotation angle δ of the last adjacent preset times of compaction; Δσ, Δα, and Δδ are respectively the change values of the peak values of the contact stress σ, acceleration α, and rotation angle δ measured in the last adjacent two times of compaction; with R n-1 > ε, R n<ε is used as the termination condition of Marshall compaction, where ε is a preset threshold value, and usually ε is taken as 0.03.

[0085] Table 2 shows the test results of the dynamic response parameters of the mixture internal particles during the Marshall compaction in one test. When the compaction reaches 132 times, the dynamic response parameters tend to be stable. The dynamic response parameters measured by 2 multi-index integrated intelligent sensors embedded during the 127th - 132nd Marshall compaction are shown in the following table:

[0086] Table 2

[0087]

[0088] In this example, SD σ 、SD α and SD δ are the standard deviations of the peak values of the contact stress σ, acceleration α, and rotation angle δ in the last adjacent 5 compactions respectively; Δσ, Δα, and Δδ are the change values of the peak values of the contact stress σ, acceleration α, and rotation angle δ measured in the last adjacent two compactions respectively. Furthermore, R 131 = 0.831, R 132 = 0.027. Among them, taking the contact stress corresponding to the 127th compaction as an example, the values obtained by the two sensors are 504.5 KPa (kilopascal) and 503.9 KPa respectively, and the average value is 504.2 KPa.

[0089] Step S103 includes:

[0090] S1031. When the dynamic response parameter corresponding to the current compaction number is less than the stable threshold value and the dynamic response parameter corresponding to the adjacent previous compaction number is greater than the stable threshold value, take the current compaction number as the target compaction number. Specifically, R 131 = 0.831 > 0.03, R 132 = 0.027 < 0.03, that is, it is considered that when the compaction reaches 132 times, the Marshall specimen reaches the compaction stable state, terminate the compaction, and take 132 times as the target compaction number.

[0091] Repeat the above steps to conduct another 3 groups of parallel tests, and the obtained compaction termination times are 128 times, 131 times, and 126 times respectively. Take the maximum value of the compaction termination times, which is 132 times, as the Marshall compaction times for forming AC - 20C type asphalt mixture in this embodiment.

[0092] The Marshall compaction method for asphalt mixture provided by the present invention determines the target compaction times by obtaining the dynamic response parameters characterizing the internal state of the asphalt mixture corresponding to the compaction times. When the change rate of the dynamic response parameters reaches the preset stable threshold, the compaction times of the asphalt mixture are determined automatically and intelligently. Moreover, the degree of change of the dynamic response parameters of the internal state of the asphalt mixture corresponding to the compaction times directly reflects the compaction state inside the asphalt mixture, which is more accurate than indirectly determining the compaction state through external parameters (such as the acceleration response of the compaction hammer). Furthermore, the accuracy of determining the compaction times for asphalt mixtures with different ratios and different gradation types is improved, avoiding the crushing of coarse aggregates caused by over-compaction or the porosity not meeting the requirements caused by under-compaction, and improving the quality of the asphalt mixture.

[0093] Example 2

[0094] Please refer to Figure 5 , which is the flow chart of the production method of the asphalt mixture in this embodiment.

[0095] Specifically, the production method includes:

[0096] S201. Determine the preliminary ratio of the asphalt mixture; specifically, in this embodiment, AC-20C type asphalt mixture is used, the asphalt used is 70# base asphalt, the asphalt-aggregate ratio is 4.5%, and the synthetic gradation of the mineral aggregate is shown in Table 1.

[0097] S202. Determine the compaction times of the asphalt mixture according to the Marshall compaction method of the asphalt mixture in Example 1, perform compaction treatment on the asphalt mixture according to the compaction times, and conduct performance tests on the compacted asphalt mixture;

[0098] S203. Determine whether the preliminary ratio is the target ratio according to whether the first index obtained from the compaction treatment and the second index obtained from the performance test meet the standards. Conduct verification on the volume parameters and conventional performances of the AC-20C type asphalt mixture obtained in step S202. The results are shown in Table 3. The Marshall test indexes (the first index) and various road performance indexes (the second index) all meet the specification requirements, indicating the applicability and effectiveness of this method.

[0099] Table 3

[0100]

[0101]

[0102] The method for preparing the asphalt mixture provided in this embodiment determines the compaction times of the asphalt mixture by using the Marshall compaction method for the above asphalt mixture, compacts the asphalt mixture according to the determined compaction times, and conducts performance tests on the compacted asphalt mixture. If both the first index obtained from the compaction treatment and the second index obtained from the performance test meet the standards, the preliminary proportion is determined as the target proportion. The target proportion of the asphalt mixture is determined automatically and intelligently, improving the accuracy of determining the compaction times for asphalt mixtures with different proportions and different gradation types, avoiding the crushing of coarse aggregates caused by over-compaction or the failure to meet the porosity requirements due to under-compaction, and thus improving the quality of the asphalt mixture.

[0103] Example 3

[0104] Please refer to Figure 6 , which is a schematic structural diagram of the Marshall compaction system for the asphalt mixture in this embodiment. Specifically, the compaction system includes:

[0105] The dynamic response parameter acquisition module 1 is used to acquire the internal dynamic response parameters of the specimen during the Marshall compaction of the asphalt mixture; the dynamic response parameters are used to characterize the internal state of the asphalt mixture corresponding to the compaction times. Specifically, compared with determining the compaction state of the asphalt mixture through external data or parameters, the dynamic response parameters in this embodiment are used to characterize the internal state of the asphalt mixture corresponding to the compaction times, more directly and truly reflecting the compaction state of the asphalt mixture.

[0106] The change degree judgment module 2 is used to judge whether the change degree of the dynamic response parameters is stable; specifically, it is reflected by the change of the dynamic response parameters (including the inter-particle contact stress σ, acceleration a, and rotation angle δ) with the compaction times. The response laws of asphalt mixtures with different gradation types (including but not limited to AC, SMA, OGFC, etc.) are different. Among them, SMA (Stone Mastic Asphalt) refers to stone mastic asphalt mixture, OGFC (Open-graded Friction Courses) refers to open-graded drainage wearing course mixture, and AC (Asphalt Concrete) refers to dense-graded asphalt mixture.

[0107] The compaction times determination module 3 is used to determine the compaction times corresponding to when the change degree of the dynamic response parameters reaches stability as the target compaction times. In an optional implementation manner, the critical compaction times with the change rate of the dynamic response parameters less than the preset stability threshold are used as the target compaction times.

[0108] In an optional implementation manner, the dynamic response parameter acquisition module 1 is specifically used to bury sensors at preset positions inside the asphalt mixture to acquire the dynamic response parameters of the asphalt mixture during the compaction process.

[0109] The following further elaborates in conjunction with the Marshall compaction test.

[0110] In this embodiment, AC-20C type asphalt mixture is used, the asphalt used is 70# base asphalt, the asphalt-aggregate ratio is 4.5%, and the synthetic gradation of the mineral aggregate is shown in Table 1.

[0111] In this embodiment, a standard Marshall compactor is used. The inner diameter of the test mold is 101.06 mm ± 0.2 mm (millimeters), the height is 87 mm, the diameter of the base is about 120.6 mm, the diameter of the compaction hammer is 98.5 mm ± 0.5 mm, the weight is 4536 g ± 9 g (grams), and the drop height is 457.2 mm ± 1.5 mm.

[0112] Specifically, the dynamic response parameter acquisition module 1 is specifically configured to uniformly embed a preset number of multi-index integrated intelligent sensors along the central axis of the asphalt mixture; as Figure 3 shown, multi-index integrated intelligent sensors are buried at the position of the central axis of the Marshall specimen (h is the height of the Marshall specimen) to collect the internal particle contact stress σ, acceleration α, rotation angle δ, and temperature t of the asphalt mixture during the Marshall compaction process. A large number of test data show that compared with other embedding positions, the test signals are the most stable and the test results are the best when multi-index integrated multi-source intelligent sensors are respectively buried at the position of the central axis. The specific method is as follows: After checking equipment such as the control box of the Marshall compactor and the compaction hammer, and preparing to embed multi-index integrated intelligent sensors, add asphalt mixture into the Marshall test mold. When it is added to one-third of the required amount, after preliminary leveling, bury multi-index integrated intelligent sensors at the center position of the cross-section of the test mold; continue to add materials. When it is added to two-thirds of the required amount, after preliminary leveling, bury multi-index integrated intelligent sensors at the center position of the cross-section of the test mold; add the remaining asphalt mixture. Then, compact it unidirectionally 75 times, and simultaneously collect and record the internal particle contact stress σ, acceleration a, rotation angle δ, and temperature t of the mixture during the Marshall compaction process in real time. Turn over the Marshall specimen compacted unidirectionally 75 times and continue to compact it until it reaches the compaction stable state, and simultaneously collect and record the internal particle contact stress σ, acceleration a, rotation angle δ, and temperature t of the mixture during the Marshall compaction process in real time. The temperature results are as

[0113] shown. Since the temperature is related to the internal particle contact stress σ, the temperature value is measured simultaneously as a reference. Figure 4 The dynamic response parameter acquisition module 1 is specifically configured to take the average value of the numerical values of the same dynamic response parameter respectively obtained by a preset number of multi-index integrated intelligent sensors during the compaction process as the dynamic response parameter of the asphalt mixture during the compaction process.

[0114] ​

[0115] In an alternative embodiment, the change degree determination module 2 is specifically configured to determine the change rate of the dynamic response parameter according to the dynamic response parameter; the change rate of the dynamic response parameter is used to characterize the change degree of the dynamic response parameter; the change degree determination module 2 is specifically configured to determine whether the change degree of the dynamic response parameter is stable according to the change rate of the dynamic response parameter and a preset stability threshold.

[0116] In this embodiment, the dynamic response parameters include the contact stress, acceleration, and rotation angle of the internal particles of the asphalt mixture; the change degree determination module 2 is specifically configured to determine the change rate of the dynamic response parameter according to the dynamic response parameter and the following formula:

[0117]

[0118] where n represents the current compaction times, and R n represents the change rate of the dynamic response parameter corresponding to n times of compaction; SD σ , SD α , and SD δ are the standard deviations of the peak values of the contact stress σ, acceleration α, and rotation angle δ of the last adjacent preset compaction times, respectively; Δσ, Δα, and Δδ are the change values of the peak values of the contact stress σ, acceleration α, and rotation angle δ measured in the last adjacent two compaction times; taking R n-1 > ε, R n < ε as the condition for terminating the Marshall compaction, where ε is a preset threshold, and usually ε is taken as 0.03.

[0119] Table 2 shows the test results of the dynamic response parameters of the internal particles of the mixture during the Marshall compaction in one test. When the compaction reaches 132 times, the dynamic response parameters tend to be stable. The dynamic response parameters measured by the two multi-index integrated intelligent sensors embedded during the 127th - 132nd Marshall compaction are shown in Table 2.

[0120] In this example, SD σ , SD α , and SD δ are the standard deviations of the peak values of the contact stress σ, acceleration α, and rotation angle δ of the last adjacent 5 compaction times, respectively; Δσ, Δα, and Δδ are the change values of the peak values of the contact stress σ, acceleration α, and rotation angle δ measured in the last adjacent two compaction times. Then, R 131 = 0.831, and R 132 = 0.027.

[0121] The compaction times determination module 3 is specifically configured to use the current compaction times as the target compaction times when the dynamic response parameter corresponding to the current compaction times is less than the stability threshold and the dynamic response parameter corresponding to the previous adjacent compaction times is less than the stability threshold. Specifically, R131 = 0.831 > 0.03, R132 = 0.027 < 0.03, that is, it is considered that when the Marshall specimen is compacted 132 times, it reaches the compaction stability state, the compaction is terminated, and 132 times is used as the target compaction times.

[0122] Repeat the above operations to conduct another 3 groups of parallel tests. The obtained compaction termination times are 128 times, 131 times, and 126 times respectively. Take the maximum value of 132 times of the compaction termination times as the Marshall compaction times for the AC-20C type asphalt mixture formed in this embodiment.

[0123] The Marshall compaction system for asphalt mixture provided by the present invention determines the target compaction times when the change rate of the dynamic response parameter reaches the preset stability threshold by obtaining the dynamic response parameter representing the internal state of the asphalt mixture corresponding to the compaction times, automatically and intelligently determines the compaction times of the asphalt mixture, and the change degree of the dynamic response parameter of the internal state of the asphalt mixture corresponding to the compaction times directly reflects the compaction state inside the asphalt mixture, which is more accurate than indirectly determining the compaction state through external parameters (such as the acceleration response of the compaction hammer). Furthermore, it improves the accuracy of determining the compaction times for asphalt mixtures with different ratios and different gradation types, avoids the crushing of coarse aggregates caused by over-compaction or the porosity not meeting the requirements caused by under-compaction, and improves the quality of the asphalt mixture.

[0124] Example 4

[0125] Please refer to Figure 7 , which is the structural schematic diagram of the production system of the asphalt mixture in this embodiment.

[0126] Specifically, the production system includes:

[0127] The pre-ratio determination module 4 is used to determine the pre-ratio of the asphalt mixture; specifically, in this embodiment, AC-20C type asphalt mixture is used, the asphalt used is 70# base asphalt, and the asphalt-aggregate ratio is 4.5%. The synthetic gradation of the mineral aggregate is shown in Table 1.

[0128] The compaction test module 5 is used to determine the compaction times of the asphalt mixture according to the Marshall compaction system of the asphalt mixture as described above, perform compaction treatment on the asphalt mixture according to the compaction times, and conduct performance tests on the compacted asphalt mixture.

[0129] The index analysis module 6 is used to determine whether the preliminary ratio is the target ratio according to whether the first index obtained by compaction treatment and the second index obtained by performance test meet the standards. The volume parameters and conventional performance of the AC-20C asphalt mixture obtained by the compaction test module 5 are verified. The results are shown in Table 3. The Marshall test indexes (the first index) and various road performance indexes (the second index) all meet the specification requirements, indicating the applicability and effectiveness of this method.

[0130] The asphalt mixture production system provided in this embodiment determines the compaction times of the asphalt mixture by using the above-mentioned Marshall compaction system for asphalt mixture, conducts compaction treatment on the asphalt mixture according to the determined compaction times, and conducts performance tests on the compacted asphalt mixture. If both the first index obtained by compaction treatment and the second index obtained by performance test meet the standards, it is determined that the preliminary ratio is the target ratio, automatically and intelligently determining the target ratio of the asphalt mixture, improving the accuracy of determining the compaction times for asphalt mixtures with different ratios and different gradation types, avoiding the crushing of coarse aggregates caused by over-compaction or the porosity not meeting the requirements caused by under-compaction, and thus improving the quality of the asphalt mixture.

[0131] Embodiment 5

[0132] Figure 8 This is a schematic structural diagram of an electronic device provided in Embodiment 5 of the present invention. The electronic device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the Marshall compaction method for asphalt mixture in Embodiment 1 or the production method for asphalt mixture in Embodiment 2. Figure 8 The displayed electronic device 30 is merely an example and should not impose any limitations on the functions and usage scope of the embodiments of the present invention.

[0133] As Figure 8 shown, the electronic device 30 can be presented in the form of a general computing device, for example, it can be a server device. The components of the electronic device 30 may include, but are not limited to: at least one of the above-mentioned processors 31, at least one of the above-mentioned memories 32, and a bus 33 connecting different system components (including the memory 32 and the processor 31).

[0134] The bus 33 includes a data bus, an address bus, and a control bus.

[0135] The memory 32 may include volatile memory, such as a random access memory (RAM) 321 and / or a cache memory 322, and may further include a read-only memory (ROM) 323.

[0136] The memory 32 may also include a program / utilities 325 having a set (at least one) of program modules 324. Such program modules 324 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment.

[0137] The processor 31 executes various functional applications and data processing by running computer programs stored in the memory 32, such as the Marshall compaction method of asphalt mixture in Embodiment 1 or the production method of asphalt mixture in Embodiment 2 of the present invention.

[0138] The electronic device 30 may also communicate with one or more external devices 34 (such as a keyboard, pointing device, etc.). Such communication may be carried out through the input / output (I / O) interface 35. Moreover, the model generation device 30 may also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through the network adapter 36. As shown in the figure, the network adapter 36 communicates with other modules of the model generation device 30 through the bus 33. It should be understood that although not shown in the figure, other hardware and / or software modules may be used in conjunction with the model generation device 30, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.

[0139] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present invention, the features and functions of two or more of the above-described units / modules may be embodied in one unit / module. Conversely, the features and functions of one unit / module described above may be further divided and embodied by multiple units / modules.

[0140] Embodiment 6

[0141] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the Marshall compaction method of asphalt mixture in Embodiment 1 or the production method of asphalt mixture in Embodiment 2.

[0142] Among them, the more specific computer-readable storage medium may include, but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0143] In a possible implementation manner, the present invention can also be implemented in the form of a program product, which includes program code. When the program product runs on a terminal device, the program code is used to cause the terminal device to execute the Marshall compaction method for asphalt mixture in Embodiment 1 or the production method for asphalt mixture in Embodiment 2.

[0144] Among them, the program code for executing the present invention can be written in any combination of one or more programming languages. The program code can be completely executed on the user device, partially executed on the user device, executed as an independent software package, partially executed on the user device and partially executed on a remote device, or completely executed on a remote device.

[0145] Although the specific implementation manners of the present invention have been described above, those skilled in the art should understand that this is only an example. The protection scope of the present invention is defined by the appended claims. Without departing from the principles and essence of the present invention, those skilled in the art can make various changes or modifications to these implementation manners, but these changes and modifications all fall within the protection scope of the present invention.

Claims

1. A Marshall compaction method for asphalt mixture, characterized in that, The compaction method includes: Obtaining the dynamic response parameters of the asphalt mixture during the Marshall compaction process; The dynamic response parameters are used to characterize the internal state of the asphalt mixture corresponding to the number of compaction times; Judging whether the change degree of the dynamic response parameters is stable; If so, determining the compaction number corresponding to when the change degree of the dynamic response parameters reaches stability as the target compaction number; The step of judging whether the change degree of the dynamic response parameters is stable includes: Determining the dynamic response parameter change rate according to the dynamic response parameters; The dynamic response parameter change rate is used to characterize the change degree of the dynamic response parameters; Judging whether the change degree of the dynamic response parameters is stable according to the dynamic response parameter change rate and a preset stability threshold; The dynamic response parameters include the contact stress, acceleration and rotation angle of the internal particles of the asphalt mixture; Determining the dynamic response parameter change rate according to the dynamic response parameters and the following formula: where n represents the current compaction number, and R n represents the change rate of the dynamic response parameter corresponding to the n - th compaction; SD σ , SD α and SD δ are the standard deviations of the peak values of the contact stress σ, acceleration α, and rotation angle δ for the last adjacent preset compactions, respectively; Δσ, Δα, and Δδ are the change values of the peak values of the contact stress σ, acceleration α, and rotation angle δ measured for the last adjacent two compactions, respectively; If so, the step of determining the compaction number corresponding to when the change degree of the dynamic response parameters reaches stability as the target compaction number includes: When the dynamic response parameter corresponding to the current compaction number is less than the stability threshold and the dynamic response parameter corresponding to the adjacent previous compaction number is greater than the stability threshold, taking the current compaction number as the target compaction number.

2. The compaction method according to claim 1, wherein The step of obtaining the dynamic response parameters of the asphalt mixture during the Marshall compaction process includes: Embedding sensors at preset positions inside the asphalt mixture to obtain the dynamic response parameters of the asphalt mixture during the compaction process.

3. The compaction method according to claim 2, wherein The step of embedding sensors at preset positions inside the asphalt mixture to obtain the dynamic response parameters of the asphalt mixture during the compaction process includes: Uniformly embedding a preset number of multi-index integrated intelligent sensors on the central axis of the asphalt mixture to obtain at least one type of dynamic response parameter of the asphalt mixture during the compaction process; Taking the average value of the numerical values of the same dynamic response parameter respectively obtained by the preset number of multi-index integrated intelligent sensors during the compaction process as the dynamic response parameter of the asphalt mixture during the compaction process.

4. A method for making an asphalt mixture, characterized in that, The production method includes: Determining the preliminary ratio of the asphalt mixture; Determining the compaction number of the asphalt mixture according to the Marshall compaction method of the asphalt mixture according to any one of claims 1-3, compacting the asphalt mixture according to the compaction number, and performing a performance test on the compacted asphalt mixture; Determining whether the preliminary ratio is the target ratio according to whether the first index obtained by the compaction treatment and the second index obtained by the performance test meet the standards.

5. A Marshall compaction system for asphalt mixture, characterized in that, The compaction system includes: A dynamic response parameter acquisition module for acquiring the dynamic response parameters of the asphalt mixture during the Marshall compaction process; The dynamic response parameters are used to characterize the internal state of the asphalt mixture corresponding to the number of compaction times; A change degree judgment module for judging whether the change degree of the dynamic response parameters is stable; A compaction number determination module for determining the compaction number corresponding to when the change degree of the dynamic response parameters reaches stability as the target compaction number; The degree-of-change determination module is specifically configured to determine the change rate of the dynamic response parameter according to the dynamic response parameter; The change rate of the dynamic response parameter is used to characterize the degree of change of the dynamic response parameter; The degree-of-change determination module is specifically configured to determine whether the change degree of the dynamic response parameter is stable according to the change rate of the dynamic response parameter and a preset stability threshold; The dynamic response parameters include the contact stress, acceleration, and rotation angle of the internal particles of the asphalt mixture; The degree-of-change determination module is specifically configured to determine the change rate of the dynamic response parameter according to the dynamic response parameter and the following formula: where n represents the current compaction number, and R n represents the change rate of the dynamic response parameter corresponding to the n-th compaction; SD σ , SD α and SD δ are the standard deviations of the peak values of the contact stress σ, acceleration α, and rotation angle δ of the last adjacent preset compactions, respectively; Δσ, Δα, and Δδ are the change values of the peak values of the contact stress σ, acceleration α, and rotation angle δ measured in the last adjacent two compactions, respectively; If so, the step of determining the compaction number corresponding to the stable degree of change of the dynamic response parameter as the target compaction number includes: The compaction-number determination module is specifically configured to use the current compaction number as the target compaction number when the dynamic response parameter corresponding to the current compaction number is less than the stability threshold and the dynamic response parameter corresponding to the adjacent previous compaction number is greater than the stability threshold.

6. A production system for asphalt mixture, characterized in that, The manufacturing system includes: A pre-ratio determination module, configured to determine the pre-ratio of the asphalt mixture; A compaction test module, configured to determine the compaction number of the asphalt mixture according to the Marshall compaction system of the asphalt mixture as claimed in claim 5, perform compaction treatment on the asphalt mixture according to the compaction number, and perform a performance test on the compacted asphalt mixture; An index analysis module, configured to determine whether the pre-ratio is the target ratio according to whether the first index obtained from the compaction treatment and the second index obtained from the performance test meet the standards.

7. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the Marshall compaction method of the asphalt mixture as described in any one of claims 1-3 or the manufacturing method of the asphalt mixture as described in claim 4.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the Marshall compaction method of the asphalt mixture as described in any one of claims 1-3 or the manufacturing method of the asphalt mixture as described in claim 4.

Images