Digital intelligent compaction system for highway subgrade and pavement

Abstract

The invention discloses a digital intelligent compaction system for a highway subgrade pavement, and belongs to the technical field of compaction degree detection. The system comprises a synchronous data acquisition mechanism, and the synchronous data acquisition mechanism is arranged in a cab of the vibratory roller and is connected with a first compactness detection mechanism, a second compactness detection mechanism, a flatness detection mechanism and a temperature distribution detection mechanism. The data acquisition mechanism is used for acquiring data detected by the first compactness detection mechanism, the second compactness detection mechanism, the flatness detection mechanism and the temperature distribution detection mechanism; and the rolling construction data analysis and storage mechanism is arranged in a cab of the vibratory roller, is connected with the synchronous data acquisition mechanism and is used for receiving and analyzing the data acquired by the synchronous data acquisition mechanism. According to the invention, the traditional result detection mode is changed, the whole compaction process is monitored, and the most comprehensive and real data provides support for quality control.

Description

Technical Field

[0001] The invention relates to the technical field of compaction detection, and in particular to a digital intelligent compaction system for a highway roadbed and pavement. Background Art

[0002] Highways are an important part of the national transportation infrastructure. As the infrastructure of highway projects, roadbed and pavement play an important role in the safety, stability and durability of highways. As an important field of infrastructure construction, highway construction plays a key role in promoting economic development and strengthening transportation. The compaction quality of the roadbed and pavement determines the overall quality of the roadbed and pavement. Highway construction requires high-quality, high-efficiency and sustainable roadbed construction technology. At present, with the rapid development of information technology and the application of intelligent equipment, the application of smart construction technology in highway construction is becoming more and more popular, and the market demand for smart construction technology of highway roadbed and pavement is also increasing. Transparent construction and efficient supervision of rolling construction are crucial to the density and stability of roadbed and pavement. Traditional highway roadbed construction has construction difficulties such as compaction process and compaction quality control being greatly influenced by human factors and low supervision efficiency. Therefore, it is necessary to propose a digital intelligent compaction system for highway roadbed and pavement to solve the engineering problems of under-pressure and over-pressure caused by the large subjective influence of human factors in traditional compaction and detection and the inability to correct deviations in time. Summary of the invention

[0003] The present invention aims to provide a digital intelligent compaction system for highway roadbed and pavement. The method is suitable for the intelligent compaction and detection of highway roadbed and pavement, and can effectively solve the technical problems existing in traditional compaction control technology, such as missed rolling, cross rolling, overspeeding, substandard rolling times, inability to conduct quality inspection on the entire working surface, and inaccurate and untimely feedback control.

[0004] In order to achieve the purpose of the above invention, the present invention adopts the following technical solution: A digital intelligent compaction system for a highway roadbed and pavement, comprising a vibratory roller, and further comprising: A first compaction detection mechanism and a second compaction detection mechanism; the first compaction detection mechanism and the second compaction detection mechanism are arranged on inner frames at both ends of the vibrating wheel of the vibrating roller and are located at the center of the vibrating wheel of the vibrating roller; Two flatness detection mechanisms, the two flatness detection mechanisms are arranged oppositely on both sides of the vibrating wheel of the vibrating roller and installed on the vibrating wheel frame of the vibrating roller; Two temperature distribution detection mechanisms, the two temperature distribution detection mechanisms are arranged on both sides of the vibrating wheel of the vibrating roller and are installed on the vibrating wheel frame of the vibrating roller; a synchronous data acquisition mechanism, which is arranged in the cab of the vibratory roller and is respectively connected to the first compaction detection mechanism, the second compaction detection mechanism, the flatness detection mechanism, and the temperature distribution detection mechanism, and is used to collect data detected by the first compaction detection mechanism, the second compaction detection mechanism, the flatness detection mechanism, and the temperature distribution detection mechanism; A rolling construction data analysis and storage mechanism is arranged in the driving cabin of the vibratory roller and is connected to the synchronous data acquisition mechanism for receiving and analyzing the data collected by the synchronous data acquisition mechanism.

[0005] Furthermore, the vibratory roller is also provided with a Beidou high-precision positioning mechanism and a wireless network communication mechanism, and the Beidou high-precision positioning mechanism and the wireless network communication mechanism are connected to the rolling construction data analysis and storage mechanism.

[0006] Furthermore, the Beidou high-precision positioning mechanism includes a Beidou antenna, a Beidou receiver and a Beidou positioning base station; The Beidou antenna is arranged on the top of the cab of the vibratory roller, the Beidou receiver is arranged in the cab of the vibratory roller, and the Beidou antenna is connected to the Beidou receiver through a signal line; The Beidou positioning base station is set up in an undisturbed location at the construction site to provide a positioning reference for the Beidou receiver.

[0007] Furthermore, the method for the vibratory roller to perform a rolling test comprises the following steps: S1. Create a vibration compaction model. According to the linear elastic vibration theory and the mass-spring-damper system, a two-degree-of-freedom model is used to analyze the interaction between the vibration wheel and the filler. The compaction quality index is analyzed. The peak coefficient CF is obtained through data analysis. CF is used as an indicator to characterize the change in the compaction state of the filler, and the maximum reaction force of the filler on the wheel is evaluated. S2, dividing the test road section into multiple areas with the same length and width by spreading ash; S3, the vibratory roller performs rolling operations with different exciting forces, driving speeds and compaction passes on different areas, and collects compaction process information of different areas; S4. Analyze the test results.

[0008] Furthermore, while the vibratory roller in step S3 is performing the rolling operation, a sand filling method is used to collect the compaction degree of the filler.

[0009] Furthermore, in the vibration compaction model in step S1, the vibratory roller is simplified into a vibrating wheel and an upper frame, and a Kelvin model of a damper and a linear spring in parallel is used to describe the properties of the soil under the assumption that the filler is completely elastic; Among them, the differential equation of elasticity is:

[0010] In the formula, is the elastic stiffness of the filler; is the stiffness of the shock absorber; is the damping of the filler; is the damping of the shock absorber; is the displacement of the vibration wheel; is the displacement of the upper frame; ma is the mass of the vibration wheel; my is the mass of the upper frame; and is the speed and acceleration of the vibration wheel; and is the speed and acceleration of the upper frame; t is the time; w is the rotation speed of the eccentric mass; For the exciting force; The vertical vibration acceleration of the vibratory roller:

[0011] In the formula, ; ; ; ; It can be seen that the vertical vibration acceleration of the vibratory roller is only related to , Since the packing damping and packing stiffness directly reflect the compaction quality of the packing, the vibration wheel acceleration reflects the compaction condition of the packing to a certain extent; the RICM index is obtained through the rolling test.

[0012] Furthermore, the compaction quality index in step S1 is: The peak acceleration value describes the peak change of the vibration acceleration signal. , the calculation formula is as follows:

[0013] In the formula, is the random acceleration value; n is the number of sampling points in a period of time.

[0014] The ratio of the fundamental frequency amplitude to the secondary frequency amplitude is used to calculate the density value CMV to reflect the degree of signal distortion, and CMV is used to characterize the relative value of the compaction of the rolled filler. The calculation formula is as follows:

[0015] In the formula, is the second harmonic amplitude of vibration acceleration; is the fundamental frequency amplitude; C is the correction coefficient, which is generally taken as 300; Acceleration mean square error Reflects the effective vibration acceleration of the wheel during rolling. The calculation formula is as follows:

[0016] The peak factor CF is used to describe the waveform change law of the wheel acceleration signal. The calculation formula is as follows:

[0017] Among them, the peak factor CF is a dimensionless statistical parameter. CF is defined as the ratio of the peak value of the waveform to the root mean square value. CF affects the accuracy of interactive measurement. The CF value is an effective response to the vibration characteristics and change trend of the vibration acceleration signal. It will change significantly with the degree of distortion of the sine wave. Therefore, the peak factor CF is used to describe the waveform change law of the wheel acceleration signal. Beneficial Effects

[0018] 1) Changed the traditional result detection method, realized the monitoring of the whole compaction process, and provided support for quality control with the most comprehensive and real data; 2) Automatically analyze the weak compaction areas on site, make real-time corrections and prevent under-compaction and over-compaction, and provide auxiliary guidance for compaction operations; 3) Provide multi-faceted data support for BIM platforms and third-party platforms; 4) No human intervention is required during the entire process. Data is automatically collected and uploaded without affecting normal construction, minimizing data deviation caused by human interference.

[0019] 5) Realize digital compaction construction including digitization, networking and visualization of all construction process information, and further combine the closed-loop intelligent construction concept of "perception + decision-making + control" to realize intelligent management and control of digital compaction of highway roadbed and pavement. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a structural schematic diagram of a digital intelligent compaction system for highway roadbed and pavement proposed by the present invention; Figure 2 It is a two-degree-of-freedom vibration compaction model; Figure 3is the experimental scheme of Example 4; Figure 4 is the layout diagram of the test area of ​​Example 4; Figure 5 is the acceleration signal time history curve and two-dimensional spectrum diagram of Example 4; Figure 6 is the relationship curve between the RICM parameters and the number of rolling passes of Example 4; Figure 7 is a curve showing a change in the RICM index and the driving speed in Example 4; Figure 8 is the relationship curve between RICM and exciting force of Example 4; Fig. 9 is the relationship curve between the RICM index and the degree of compaction of Example 4; In the figure: 1. Vibratory roller; 2. Wireless network communication mechanism; 3. Beidou high-precision positioning mechanism; 4. Rolling construction data analysis and storage mechanism; 5. Synchronous data acquisition mechanism; 6. First compaction degree detection mechanism; 7. Flatness detection mechanism; 8. Temperature distribution detection mechanism. DETAILED DESCRIPTION Example 1

[0021] refer to Figure 1 , a digital intelligent compaction system for a highway roadbed and pavement, comprising a vibratory roller, and also comprising: A first compaction detection mechanism 6 and a second compaction detection mechanism; the first compaction detection mechanism 6 and the second compaction detection mechanism are arranged on the inner frames at both ends of the vibrating wheel of the vibrating roller 1 and are located at the center of the vibrating wheel of the vibrating roller 1; Two flatness detection mechanisms 7, the two flatness detection mechanisms 7 are relatively arranged on both sides of the vibrating wheel of the vibrating roller 1, and are installed on the vibrating wheel frame of the vibrating roller 1; Two temperature distribution detection mechanisms 8, the two temperature distribution detection mechanisms 8 are relatively arranged on both sides of the vibrating wheel of the vibrating roller 1, and are installed on the vibrating wheel frame of the vibrating roller 1; A synchronous data acquisition mechanism 5, which is arranged in the driving cabin of the vibratory roller 1 and is respectively connected to the first compaction detection mechanism 6, the second compaction detection mechanism, the flatness detection mechanism 7, and the temperature distribution detection mechanism 8, and is used to collect data detected by the first compaction detection mechanism 6, the second compaction detection mechanism, the flatness detection mechanism 7, and the temperature distribution detection mechanism 8; The rolling construction data analysis and storage mechanism 4 is arranged in the driving cabin of the vibratory roller 1 and is connected to the synchronous data acquisition mechanism 5 for receiving and analyzing the data collected by the synchronous data acquisition mechanism 5 . Example 2

[0022] In order to more accurately locate the position of the vibratory roller, this embodiment is further configured on the basis of the first embodiment.

[0023] Preferably, the vibratory roller 1 is also provided with a Beidou high-precision positioning mechanism 3 and a wireless network communication mechanism 2 , and the Beidou high-precision positioning mechanism 3 and the wireless network communication mechanism 2 are connected to the rolling construction data analysis and storage mechanism 4 .

[0024] Preferably, the Beidou high-precision positioning mechanism 3 includes a Beidou antenna, a Beidou receiver and a Beidou positioning base station; The Beidou antenna is arranged on the top of the cab of the vibratory roller, the Beidou receiver is arranged in the cab of the vibratory roller, and the Beidou antenna is connected to the Beidou receiver through a signal line; The Beidou positioning base station is set up in an undisturbed area at the construction site to provide a positioning reference for the Beidou receiver.

[0025] In this embodiment, the construction site is the place where the vibratory roller 1 of the present application is used. Example 3

[0026] This embodiment is a method for a rolling test of the vibratory roller of embodiment 2, and the method comprises the following steps: S1. Create a vibration compaction model. According to the linear elastic vibration theory and the mass-spring-damper system, a two-degree-of-freedom model is used to analyze the interaction between the vibration wheel and the filler. The compaction quality index is analyzed. The peak coefficient CF is obtained through data analysis. CF is used as an indicator to characterize the change in the compaction state of the filler, and the maximum reaction force of the filler on the wheel is evaluated. S2, dividing the test road section into multiple areas with the same length and width by spreading ash; S3, the vibratory roller performs rolling operations with different exciting forces, driving speeds and compaction passes on different areas, and collects compaction process information on different areas; S4. Analyze the test results.

[0027] Preferably, while the vibratory roller in step S3 is performing the rolling operation, a sand filling method is performed to collect the compaction degree of the filler. Example 4

[0028] refer to Figure 2 This embodiment is further configured on the basis of the embodiment 3.

[0029] Preferably, in the vibration compaction model in step S1, the vibratory roller is simplified into a vibrating wheel and an upper frame, and a Kelvin model of a damper and a linear spring in parallel is used to describe the properties of the soil under the assumption that the filler is completely elastic (e.g. Figure 2shown); Among them, the differential equation of elasticity is:

[0030] In the formula, is the elastic stiffness of the filler; is the stiffness of the shock absorber; is the damping of the filler; is the damping of the shock absorber; is the displacement of the vibration wheel; is the displacement of the upper frame; ma is the mass of the vibration wheel; my is the mass of the upper frame; and is the speed and acceleration of the vibration wheel; and is the speed and acceleration of the upper frame; t is the time; w is the rotation speed of the eccentric mass; For the exciting force; Vertical vibration acceleration of vibratory roller:

[0031] In the formula, ; ; ; ; It can be seen that the vertical vibration acceleration of the vibratory roller is only related to , Since the packing damping and packing stiffness directly reflect the compaction quality of the packing, the vibration wheel acceleration reflects the compaction condition of the packing to a certain extent; the RICM index is obtained through the rolling test.

[0032] In this embodiment, according to the corresponding complex relationship between them and the complex nature of soil, , The relationship between the vibration acceleration cannot be expressed by a simple deterministic number; through field compaction tests, the RICM index suitable for the high-performance red clay roadbed of Hengyong Expressway was obtained.

[0033] Preferably, the compaction quality index in step S1 is: The peak acceleration value describes the peak change of the vibration acceleration signal. , the calculation formula is as follows:

[0034] In the formula, is the random acceleration value; n is the number of sampling points in a period of time.

[0035] The compaction density value CMV, which is the ratio of the fundamental frequency amplitude to the secondary frequency amplitude, reflects the degree of signal distortion, and CMV is used to characterize the relative compaction value of the rolled filler. The calculation formula is as follows:

[0036] In the formula, is the second harmonic amplitude of vibration acceleration; is the fundamental frequency amplitude; C is the correction coefficient, which is generally taken as 300; Acceleration mean square error Reflects the effective vibration acceleration of the wheel during rolling. The calculation formula is as follows:

[0037] The peak factor CF is used to describe the waveform change law of the wheel acceleration signal. The calculation formula is as follows:

[0038] Among them, the peak factor CF is a dimensionless statistical parameter. CF is defined as the ratio of the peak value of the waveform to the root mean square value. CF affects the accuracy of interactive measurement. The CF value is an effective response to the vibration characteristics and change trends of the vibration acceleration signal. It will change significantly with the degree of distortion of the sine wave. Therefore, the peak factor CF is used to describe the waveform change law of the wheel acceleration signal. Example 5

[0039] refer to Figure 3-Figure 4 This embodiment is a method for the vibratory roller of embodiment 3 to perform a rolling test, and the digital intelligent compaction test of the red clay high-performance roadbed is selected in the red clay high-performance roadbed test section. The maximum dry density of the red clay filler in the test layer is 1.68 The natural moisture content is 27%, the optimum moisture content is 19%, the liquid limit is 49.3%, the plastic limit is 32.7%, and the plasticity index is 16.6.

[0040] The method comprises the following steps: S1. Create a vibration compaction model. According to the linear elastic vibration theory and the mass-spring-damper system, a two-degree-of-freedom model is used to analyze the interaction between the vibration wheel and the filler. The compaction quality index is analyzed. The peak coefficient CF is obtained through data analysis. CF is used as an indicator to characterize the change in the compaction state of the filler, and the maximum reaction force of the filler on the wheel is evaluated. S2, dividing the test road section into multiple areas with the same length and width by spreading ash; S3, the vibratory roller performs rolling operations with different exciting forces, driving speeds and compaction passes on different areas, and collects compaction process information on different areas; S4. Analyze the test results.

[0041] In this embodiment, four groups of field tests under different working conditions were carried out (such as Figure 3 as shown).

[0042] Preferably, while the vibratory roller in step S3 is performing the rolling operation, a sand filling method is performed to collect the compaction degree of the filler.

[0043] In this embodiment, in working conditions 2 and 4, the compaction degree of the sampling point is detected by the sand filling method after each rolling. The overall layout of the on-site rolling test area is as follows: Figure 4 As shown, Figure 4 Each circle represents a sampling and testing point; each test zone is 10m long and 3m wide, with 2 static pressures and 8 vibration pressures; the adjustment area is set outside the test area to ensure that the adjustment area and the test area are in the same working state. Example 6

[0044] refer to Figure 5-Figure 9 This embodiment is a further configuration of Embodiment 5, and is a test result analysis method in step S4 of a method for rolling test with a vibratory roller: S41, time domain and spectrum analysis; The collected acceleration signals were analyzed in the time domain; Figure 5 (a) is the original time domain curve of the acceleration signal during the eighth rolling process; it can be seen from the original signal that the acceleration signal waveform shows a certain sinusoidal signal characteristic as a whole. As the soil is gradually compacted, the vibration acceleration signal is distorted and contains a large number of spike interference signals; this is because the vibration wheel will generate high-frequency noise interference during the compaction process, which has a great influence on the amplitude and smoothness of the acceleration signal; according to the time domain of the filtering noise reduction process Figure 5 (b) It can be seen that the acceleration curve after filtering is relatively smooth, reflecting that the vibration acceleration signal monitored during the interaction between the filler and the vibration wheel belongs to a standard periodic sine function.

[0045] In order to further reflect the dynamic response characteristics of the vibration wheel, this project uses fast Fourier transform (FFT) to process the vibration acceleration signal in the frequency domain. Figure 5 (c) and Figure 5 (d) are the frequency spectra of the acceleration signals before and after filtering, respectively; they show that the vibration acceleration signal contains fundamental and higher harmonic components; among them, the fundamental and second harmonic components are relatively stable, and other higher harmonic components are relatively stable.

[0046] S42, correlation between rolling times and RICM index; The number of rolling passes reflects the size of the compaction work and is one of the key control parameters in roadbed construction. It has an important impact on the compaction of the roadbed. In order to avoid the influence of the large difference in soil moisture content on the analysis results, two measuring belts were selected, and 5 sampling points were selected in the entire measuring area. The SR22MA 22t vibratory roller was used to perform two static compactions at a speed of 0.83m / s, and then vibrated and rolled 8 times at a constant speed to complete working condition 2. The RICM index after each pass was recorded, and a total of 80 sets of observation data were obtained. Through the equation, y=ax+b; where a and b are regression coefficients. The correlation between the four RICM indicators and the number of compaction passes was analyzed, and a regression model was established to obtain the correlation analysis results ( Figure 6 ).

[0047] Depend on Figure 6 It can be seen that the indicator There is a close relationship between CMV and the number of compaction passes. The correlation between CF and the number of compaction passes is very poor. The correlation between CMV and the number of compaction passes is very strong, with a correlation coefficient of 0.904. It has a significant correlation with the number of compaction passes, with a correlation coefficient of 0.720. The correlation between CF and the number of compaction passes is very small, and their correlation coefficients are 0.393 and 0.202 respectively.

[0048] S43, correlation between RICM index and driving speed; The driving speed has a significant impact on the compaction effect of the soil, and the driving speed determines the action time of the vibrating wheel on the compacted soil per unit area. For this reason, four small rolling areas were selected and rolled according to working conditions 3 and 4.

[0049] Depend on Figure 7 It can be seen that CMV is inversely proportional to the driving speed and increases regularly with the increase in the number of compaction passes; different from the trend of CMV, the other three indicators show an upward trend with the increase in driving speed. According to energy theory analysis, under the condition of the same number of compaction passes, as the driving speed increases, the energy absorbed by the filler per unit volume gradually decreases, and the reaction force of the filler on the vibrating wheel decreases, resulting in a decrease in vibration acceleration. Therefore, the RICM index should show a downward trend with the number of compaction passes, and in fact only the trend of CMV is consistent with the theory.

[0050] S44, correlation between RICM index and exciting force; According to working conditions 2 and 4, field compaction tests were carried out. Based on the test results, the influence of the exciting force on each RICM index and the correlation between the exciting force state and each RICM index were analyzed.

[0051] As can be seen from Figure 8 (a), as the vibration frequency decreases and the amplitude increases, and show an obvious upward trend. As can be seen from Figure 8 (b), when the exciting force remains unchanged, CMV increases with the increase of compaction times. However, when the compaction passes reach a certain level, CMV tends to be stable with the decrease of vibration frequency and the increase of amplitude.

[0052] For the degree of compaction, the change trend of the degree of compaction with the number of rolling passes has obvious regularity. However, with the decrease of vibration frequency and the increase of amplitude, the degree of compaction shows an obvious downward trend. Based on energy analysis, the energy absorbed by the filler per unit volume under low-frequency and high-amplitude vibration conditions is greater than that under high-frequency and low-amplitude vibration conditions. At the same number of compaction passes, the degree of compaction of the filler increases; therefore, the RICM index should show an upward trend; among them, and completely conform to the theoretical situation, the trend of CMV basically conforms to the theoretical situation, and the trend of CF does not conform to the theoretical situation.

[0053] The correlation between S45, RICM and the degree of compaction; In working conditions 2 and 4, the sand replacement method was used to detect the degree of compaction of the rolling layer after each pass of rolling, and the relationship between RICM and the degree of compaction was established ( Fig. 9 ). As can be seen from Fig. 9 , the correlation coefficient values between the RICM index and the degree of compaction, arranged from small to large, are (0.529) < CF (0.537) < (0.644) < CMV (0.846). Obviously, compared with other indexes, the correlation between CMV and the degree of compaction is the highest, and its correlation coefficient is 0.846.

[0054] Further analysis shows that both the RICM index and the degree of compaction have a certain positive correlation and are suitable for highway engineering filling. Considering comprehensively that CMV has a high correlation with the degree of compaction and the coefficient of variation of CMV is low, it shows that CMV can more accurately characterize the compaction quality of red clay and has the characteristics of good stability and low dispersion. Therefore, CMV can be used as the quality control index for continuous compaction.

[0055] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A digital intelligent compaction system for highway roadbed and pavement, comprising a vibratory roller, characterized in that: Also includes: A first compaction degree detection mechanism and a second compaction degree detection mechanism; the first compaction degree detection mechanism and the second compaction degree detection mechanism are arranged on inner frames at both ends of the vibrating wheel of the vibrating roller and are located at the center of the vibrating wheel of the vibrating roller; Two flatness detection mechanisms, the two flatness detection mechanisms are arranged oppositely on both sides of the vibrating wheel of the vibrating roller and are installed on the vibrating wheel frame of the vibrating roller; Two temperature distribution detection mechanisms, the two temperature distribution detection mechanisms are arranged on both sides of the vibrating wheel of the vibrating roller and are installed on the vibrating wheel frame of the vibrating roller; a synchronous data acquisition mechanism, which is arranged in the cab of the vibratory roller and is respectively connected to the first compaction detection mechanism, the second compaction detection mechanism, the flatness detection mechanism, and the temperature distribution detection mechanism, and is used to collect data detected by the first compaction detection mechanism, the second compaction detection mechanism, the flatness detection mechanism, and the temperature distribution detection mechanism; A rolling construction data analysis and storage mechanism is arranged in the driving cabin of the vibratory roller and is connected to the synchronous data acquisition mechanism for receiving and analyzing the data collected by the synchronous data acquisition mechanism.

2. A digital intelligent compaction system for highway roadbed and pavement as claimed in claim 1, characterized in that: The vibratory roller is also provided with a Beidou high-precision positioning mechanism and a wireless network communication mechanism, and the Beidou high-precision positioning mechanism and the wireless network communication mechanism are connected to the rolling construction data analysis and storage mechanism.

3. A digital intelligent compaction system for highway roadbed and pavement as claimed in claim 2, characterized in that: The Beidou high-precision positioning mechanism includes a Beidou antenna, a Beidou receiver and a Beidou positioning base station; The Beidou antenna is arranged on the top of the cab of the vibratory roller, the Beidou receiver is arranged in the cab of the vibratory roller, and the Beidou antenna is connected to the Beidou receiver through a signal line; The Beidou positioning base station is set up in an undisturbed location at the construction site to provide a positioning reference for the Beidou receiver.

4. A digital intelligent compaction system for highway roadbed and pavement as claimed in claim 2, characterized in that: The method for a rolling test of a vibratory roller comprises the following steps: S1. Create a vibration compaction model. According to the linear elastic vibration theory and the mass-spring-damper system, a two-degree-of-freedom model is used to analyze the interaction between the vibration wheel and the filler. The compaction quality index is analyzed. The peak coefficient CF is obtained through data analysis. CF is used as an indicator to characterize the change in the compaction state of the filler, and the maximum reaction force of the filler on the wheel is evaluated. S2, dividing the test road section into multiple areas with the same length and width by spreading ash; S3, the vibratory roller performs rolling operations with different exciting forces, driving speeds and compaction passes on different areas, and collects compaction process information of different areas; S4. Analyze the test results.

5. A digital intelligent compaction system for highway roadbed and pavement as claimed in claim 4, characterized in that: While the vibratory roller in step S3 is performing the rolling operation, the compaction degree of the filler is collected by the sand filling method.

6. A digital intelligent compaction system for highway roadbed and pavement as claimed in claim 4, characterized in that: In the vibration compaction model in step S1, the vibratory roller is simplified into a vibrating wheel and an upper frame. Under the assumption that the filler is completely elastic, a Kelvin model of a damper and a linear spring in parallel is used to describe the properties of the soil; Among them, the differential equation of elasticity is: In the formula, k s is the elastic stiffness of the filler; k p is the stiffness of the shock absorber; c s is the damping of the filler; c f is the damping of the shock absorber; x d is the displacement of the vibration wheel; x f is the displacement of the upper frame; ma is the mass of the vibration wheel; my is the mass of the upper frame; and is the speed and acceleration of the vibration wheel; and is the speed and acceleration of the upper frame; t is time; w is the rotation speed of the eccentric mass; F0 is the exciting force; The vertical vibration acceleration of the vibratory roller: In the formula, A1 = k f -m f ω 2 ; B1=c f ω; C=m d m f ω4-m d k f ω 2 -m f k s ω 2 -c f c s ω 2 +k f k s -m f k f ω 2 ; D=k s c f ω+k f c s ω-m d c f oh 3 -m f c s oh 3 -m f c f oh 3 ; It can be seen that the vertical vibration acceleration of the vibratory roller is only related to k s 、c s Since the packing damping and packing stiffness directly reflect the compaction quality of the packing, the vibration wheel acceleration reflects the compaction condition of the packing to a certain extent; the RICM index is obtained through the rolling test.

7. A digital intelligent compaction system for highway roadbed and pavement as claimed in claim 6, characterized in that: Compaction quality indicators in step S1: The peak value A of the acceleration that describes the peak change of the vibration acceleration signal P , the calculation formula is as follows: A p =max{|a i |}(i=1,2,…,n) In the formula, a i is the random acceleration value; n is the number of sampling points in a period of time; The compaction density value CMV, which is the ratio of the fundamental frequency amplitude to the secondary frequency amplitude, reflects the degree of signal distortion, and CMV is used to characterize the relative compaction value of the rolled filler. The calculation formula is as follows: In the formula, A 2Ω A is the second harmonic amplitude of vibration acceleration; Ω is the fundamental frequency amplitude; C is the correction coefficient, which is generally taken as 300; Acceleration mean square error A rms Reflects the effective vibration acceleration of the wheel during rolling. The calculation formula is as follows: The peak factor CF is used to describe the waveform change law of the wheel acceleration signal. The calculation formula is as follows: Among them, the peak factor CF is a dimensionless statistical parameter. CF is defined as the ratio of the peak value of the waveform to the root mean square value. CF affects the accuracy of interactive measurement. The CF value is an effective response to the vibration characteristics and change trends of the vibration acceleration signal. It will change significantly with the degree of distortion of the sine wave. Therefore, the peak factor CF is used to describe the waveform change law of the wheel acceleration signal.

Images