Intelligent compaction control integrated system and evaluation method thereof

Abstract

The invention relates to the technical field of road engineering, in particular to an intelligent compaction control integrated system and an evaluation method thereof. According to the technical scheme, the device comprises an operation positioning module which is installed on a road roller body and used for sensing and obtaining the current operation position of the road roller; and the acceleration signal acquisition module is mounted on the road roller body and is used for sensing and acquiring vibration acceleration data fed back by the road structure layer at the current working position of the road roller in real time. And the deflection detection module is mounted on the road roller body and is used for intermittently detecting the working road of the road roller to obtain a dynamic deflection value. And the data processing module is electrically connected with the operation positioning module, the data storage module, the acceleration signal acquisition module and the deflection detection module. The compaction index value and the compaction index threshold value detected in real time through the acceleration signal acquisition module are judged, the compaction index value can be obtained through real-time detection, judgment is comprehensive, and the judgment threshold value can be automatically updated in real time according to the road condition.

Description

Technical Field

[0001] The present invention relates to the technical field of road engineering, and in particular to an intelligent compaction control integrated system and an evaluation method thereof. Background Art

[0002] Road compaction refers to the process of evenly laying various types of roadbed materials in road engineering and achieving the designed strength after a certain degree of compaction. The compaction quality of roads directly affects the safety, comfort and service life of road traffic. The following are the main factors affecting the quality of road compaction: 1. Roadbed condition: The roadbed is the foundation of the road, and its flatness, strength and stability will directly affect the quality of the surface layer. 2. Material type: Different road materials have different density requirements. For example, crushed pebble fillers need to reach a certain degree of compaction to ensure their anti-deformation ability. 3. Construction environment: Factors such as climatic conditions and traffic conditions will affect the speed and efficiency of paving and compaction. 4. Equipment performance: The type, specification and operation mode of the roller will also affect the compaction quality of the roadbed. 5. Construction process: Technical parameters such as mixture uniformity, compaction times, and compaction sequence should be controlled in accordance with specifications. In order to ensure the compaction quality of the road, some measures are usually required: 1. Select a suitable roller: Select an appropriate roller according to factors such as working layer thickness, width, and compaction requirements. 2. Strictly control the construction process: strictly follow the specifications and technical points for construction, including the proportion of mixed materials, mixing uniformity, compaction times, etc. 3. Strengthen construction management: strengthen the quality monitoring of the construction process, and promptly discover and solve existing problems. 4. Strengthen training and education: provide technical training and management for construction personnel so that they can master construction skills. In short, reasonable road compaction is of great significance to ensure the stability and comfort of the road structure. Relevant standards and specifications must be strictly implemented to ensure the compaction quality of each layer of materials.

[0003] The evaluation of road compaction can be carried out from multiple aspects, mainly including the following points: 1. Compaction: The most direct indicator to measure the compaction quality, that is, the change in the water content of the soil base after compaction. It can be measured by professional instruments, and generally requires to reach the specified minimum compaction value. 2. Surface defects: Mainly check whether the compacted road has quality problems such as looseness and deformation. 3. Internal quality: For example, radar uniformity detection of gravel soil roadbed, core sampling of road integrity materials, and evaluation of whether its physical and mechanical properties meet the design requirements, such as density, porosity, strength, etc. 4. Appearance quality: Appearance quality includes the roadbed, base layer and surface layer of the road, especially the smoothness and cleanliness of the road surface layer. 5. Progress and cost: Evaluate whether the construction progress of the road is in line with the plan, and whether the corresponding investment cost is reasonable. Based on the evaluation results of the above aspects, it can be judged whether the compaction quality of the road is qualified, whether it needs to be reworked and re-compacted, or whether further quality control measures are needed.

[0004] The existing road compaction quality testing instrument generally uses a drop-hammer deflectometer, whose working principle is: under computer control, a gravity hammer of a certain mass is lifted to a certain height by a hydraulic transmission device and then falls freely. The impact force acts on the bearing plate and is transmitted to the road, thereby applying a pulse load to the road, causing instantaneous deformation of the road surface. Sensors distributed at different distances from the measuring point detect the deformation of the surface of the structural layer, and the recording system transmits the signal to the computer, that is, the dynamic deflection and deflection basin generated under the dynamic load are measured. The test data can be used to inversely calculate the modulus of the road structure layer, thereby scientifically evaluating the bearing capacity of the road. The traditional drop-hammer deflectometer test can only perform sampling tests on the road surface, resulting in insufficient road surface evaluation capabilities. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides an intelligent compaction control integrated system for performing compaction detection on a road structure layer under construction, especially a crushed pebble roadbed, a road structure layer, etc., and performing compaction quality-related evaluation. The intelligent compaction control integrated system may include:

[0006] An operation positioning module is installed on the roller body and is used to obtain the current operation position of the roller;

[0007] The acceleration signal acquisition module is installed on the roller body and is used to sense and obtain the vibration acceleration data of the road structure layer at the current working position in real time;

[0008] The deflection detection module is installed on the roller body and is used to intermittently detect the working road to obtain the dynamic deflection value l d , where d is the number of the detection position;

[0009] A data storage module, which is used to store historical detection data;

[0010] The data processing module is used to obtain the vibration acceleration data fed back by the road structure layer at the current working position; determine the current working position and the dynamic deflection value l d-1 Check whether the distance between the detection positions is greater than or equal to a preset detection standard distance L 标 If yes, the current working position is tested to obtain the dynamic deflection value l d And the compaction index value CCV corresponding to the detection point numbered d d ; If not, no dynamic deflection value detection is performed; Fitting to construct CCV d With l d Relationship, coefficient eigenvalue K1 and constant eigenvalue K2; and determine the compaction index threshold CCV T ; Calculate the compaction index value CCV and the compaction index threshold CCV Tand determine whether the compaction quality of the current compacted structure layer is qualified. If qualified, no mark is made; if unqualified, the current working position is marked. The current working position is sent to the data display module for display, and the working position can be recompacted. When there are many unqualified working positions, the entire road section can be fully compacted.

[0011] Preferably, the method for obtaining the current working position includes: constructing a plane coordinate system, and directly implanting the map of the working area into the coordinate system, so as to obtain the coordinate point of the current working position in the coordinate system.

[0012] Preferably, the method for obtaining the current working position includes: constructing a plane coordinate system, wherein the horizontal coordinate of the plane coordinate system can be the length of the road, and the vertical coordinate can be the width of the road, and the distance of the current position of the press relative to the coordinate axis is used as the horizontal coordinate and the vertical coordinate of the coordinate, so as to obtain its coordinate point in the coordinate system. The information of the working position obtained by this method can be used to evaluate and analyze the road, so as to facilitate the rapid positioning of each coordinate point in the road and facilitate maintenance.

[0013] Preferably, the operation positioning module can be installed on the top of the roller cab.

[0014] Preferably, the acceleration signal acquisition module can be installed in a non-wheel-rotating area of ​​the wheel frame of the roller.

[0015] Preferably, the non-wheel-rotating area of ​​the wheel frame can be located on the two side frames of the compacting roller of the road roller, and the vibration acceleration data of the compacted road structure layer can be sensed to the maximum extent in this area. The non-wheel-rotating area of ​​the wheel frame refers to the area that vibrates synchronously with the vibrating wheel but does not rotate with the vibrating wheel, and the vibration acceleration signal can be effectively obtained without being interfered by other factors.

[0016] Preferably, the deflection detection module may be a drop weight deflectometer or an automatic deflectometer, etc.

[0017] Preferably, the deflection detection module is a drop weight deflectometer.

[0018] Preferably, the drop weight deflectometer can be installed at the tail of the roller.

[0019] Preferably: a protective baffle can be fixedly provided at the rear of the roller, and the protective baffle can be a steel frame structure. The protective baffle can be used to protect and install the roller tire and the drop weight deflectometer of the roller. Specifically, the drop weight deflectometer can be installed on the protective baffle through a fixed bracket.

[0020] Preferably: the fixed bracket is equipped with a vibration reduction assembly, which is located above the retracted position of the gravity hammer of the drop-weight deflectometer. The vibration reduction assembly is used to block and buffer the rising gravity hammer to prevent the gravity hammer from colliding with the protective baffle under the action of rising inertia.

[0021] Preferably, the data processing module is arranged in the driving cabin of the road roller and may be a flat-panel control display.

[0022] Preferably: the vibration acceleration data may include the fundamental frequency amplitude A0 and the harmonic amplitude A i , where i is the harmonic amplitude order.

[0023] Preferred: The compaction index value CCV corresponding to the detection point numbered d d and dynamic deflection value l d The relationship is , where d is the number of the detection position of the deflection detection module, l d is the dynamic deflection value corresponding to the detection position of the deflection detection module numbered d, CCV d is the compaction index value of the detection position of the deflection detection module numbered d. k1 is the coefficient calculation value, and k2 is the constant calculation value.

[0024] Preferably, the method for obtaining the coefficient eigenvalue K1 and the constant eigenvalue K2 may include: mathematical statistics, correlation relationship establishment, parameter optimization, verification and statistics.

[0025] Preferably, mathematical statistics is to calculate the compaction index value CCV corresponding to the detection point numbered d by using the vibration acceleration data of the detection position of the deflection detection module d and dynamic deflection value l d Substitute the formula relationship , so that multiple sets of coefficient calculation values ​​k1 and constant calculation values ​​k2 can be obtained, the correlation is established for statistical analysis, and a mathematical model between them is established. Parameter optimization: Use optimization algorithms (such as gradient descent, least squares method, etc.) to determine the optimal values ​​of K1 and K2 so that the error between the compaction value predicted by the model and the actual measured value is minimized. Verification and adjustment: The model is verified through actual engineering data, and K1 and K2 are adjusted according to the verification results to adapt to different types of soil and compaction requirements. Through the above process, k1 and k2 are determined and used in the compaction quality evaluation formula to achieve an accurate assessment of the compaction quality. This method combines experimental data and mathematical statistics techniques to improve the accuracy and efficiency of compaction quality control.

[0026] Preferably, the acquisition of the coefficient characteristic value K1 and the constant characteristic value K2 may also include: by assigning the compaction index value CCV corresponding to the detection point numbered d at the detection position of the deflection detection module to d and dynamic deflection value ld Bring in the relation , so that multiple sets of coefficient calculation values ​​can be obtained and constant calculation value , where d is the number of the detection position of the deflection detection module, The coefficient calculation value is obtained by jointly calculating the detection position of the deflection detection module numbered d and the detection position of the deflection detection module numbered d-1. The constant calculation value is obtained by combining the detection position of the deflection detection module numbered d and the detection position of the deflection detection module numbered d-1, where D is the total number of current detections by the deflection detection module, d=2, 3…, D. Then the coefficient eigenvalue , constant eigenvalue , where ɑ is the base of the roadbed deviation, and its value is generally 1-10. It is the dth power of the base of the roadbed deviation. ε is the deviation adjustment factor, and its value is generally 0, 1-10, and can generally be 1. The coefficient calculation value is obtained by jointly calculating the detection position of the deflection detection module numbered d and the detection position of the deflection detection module numbered d-1. The constant calculation value is obtained by jointly calculating the detection position of the deflection detection module numbered d and the detection position of the deflection detection module numbered d-1, d=2, 3…, D. The coefficient eigenvalue and the constant eigenvalue are calculated by this method, and the differences in road materials, construction and environment can be taken into account. It can be seen from the formula that the smaller the proportion of the detection position with the front number, the smaller the influence on the judgment of the current point. In this case, we can increase the proportion of the calculated value of the position point adjacent to the current position point, so as to reduce the deviation caused by factors such as time and distance. This method is more accurate in calculation and can make a better and more accurate assessment of the compacted structure layer of the road.

[0027] Preferred: Compaction index value , where i is the harmonic amplitude order, A0 is the fundamental frequency amplitude of the detection position of the deflection detection module numbered d, and A i is the i-th harmonic amplitude at the detection position of the deflection detection module numbered d, I is the total number of amplitude values, i=1, 2, ..., I. β is the amplitude coefficient, and its value is generally 200.

[0028] Preferred: .

[0029] Preferred: Compaction indicator threshold , where K1 is the coefficient eigenvalue, K2 is the constant eigenvalue, l T is the design value of dynamic deflection.

[0030] Preferably: the dynamic deflection design value , —Design value of roadbed rebound modulus, —Drop weight instrument load plate, — Radius of the drop weight bearing plate, is the design coefficient, and its value is 150-200, with 176 being the most appropriate. The compaction index threshold calculated by this method can well distinguish and judge the detection data, and the calculation is convenient. The coefficient eigenvalue and constant eigenvalue are updated and optimized in stages to ensure the accuracy of the judgment threshold.

[0031] Optimum: Compaction Index Value CCV and Compaction Index Threshold CCV T The method for determining the relationship between the optimized compaction reduction value C and the optimized compaction reduction value C may include: determining whether the optimized compaction reduction value C is less than a preset standard reduction ratio C 标 , and the current compaction index value CCV n Is it greater than the compaction index threshold CCV? T δ times of , if they are both , it is judged as qualified, otherwise, it is judged as unqualified.

[0032] Preferably: the optimized compaction reduction value can be , where n is the number of compaction passes.

[0033] Preferably: the preset standard reduction ratio C 标 Generally it is 10%-30%.

[0034] Preferred: 20% is the best.

[0035] The present invention also proposes an intelligent compaction control evaluation method for evaluating the compaction quality of a compacted road structure layer. The intelligent compaction control evaluation method comprises the following steps:

[0036] S1. Obtain vibration acceleration data fed back by the road structure layer at the current working position.

[0037] S2. Determine the current working position and the previous dynamic deflection value l d-1 Check whether the distance between the detection positions is greater than or equal to a preset detection standard distance L 标 If yes, execute S3, if no, do not perform dynamic deflection value detection.

[0038] S3, then detect the current working position to obtain the dynamic deflection value l d .

[0039] S4, based on the vibration acceleration data and dynamic deflection value l of the road structure layer feedback at the current working position d Fitting construction number d corresponding to the compaction index value CCV d and dynamic deflection value l drelation, and calculate the coefficient eigenvalue K1 and the constant eigenvalue K2.

[0040] S5. Determine the compaction index threshold CCV based on the coefficient eigenvalue K1 and the constant eigenvalue K2 T .

[0041] S6. Calculate and obtain the compaction index value CCV and the compaction index threshold CCV through current operation position detection T The relationship between them is used to determine whether the compaction quality of the current compacted structural layer is qualified. If qualified, no mark is made; if unqualified, the current working position is marked.

[0042] The technical effects and advantages of the present invention: During the working process, the prior art generally uses a drop-weight deflectometer to detect the road, but this detection is a single-point detection, which takes time and cannot be detected in real time, because the specific conditions of each position point in the road structure layer are different. For example, due to uneven moisture content, uneven paving thickness, or uneven mixing of paving materials caused by staged feeding, it is impossible to achieve the same road compaction quality, and it is very easy to cause the detection point and the unqualified point to be misaligned, resulting in an incomplete evaluation of road compaction, thereby affecting the road quality. The compaction index value CCV and the compaction index threshold CCV detected in real time by the acceleration signal acquisition module T The compaction index value can be detected and obtained in real time, so that each working position can be judged. Such a comprehensive judgment can fully ensure that there will be no unqualified working positions missed, and ensure the comprehensive compaction detection of the road structure layer. If the unqualified position can be re-compacted in time, the compaction quality of the road can be guaranteed. The compaction index threshold CCV T The dynamic deflection value obtained through intermittent detection by the deflection detection module can be corrected to avoid threshold setting errors caused by changes in road conditions. The compaction index threshold obtained by this method is a dynamic data with staged corrections. The data is updated in a timely manner, which improves the accuracy of the judgment. In the actual detection process, we need a roller to compact the road structure layer and obtain the current working position and vibration acceleration data. The current working position and vibration acceleration data are obtained in real time. This data detection does not require an operation interval, which can greatly reduce damage to the road and facilitate detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a structural block diagram of an intelligent compaction control integrated system proposed in the present invention.

[0044] Figure 2 This is a schematic diagram of the installation structure of an intelligent compaction control integrated system proposed by the present invention.

[0045] Figure 3This is a flow chart of a method for obtaining coefficient eigenvalue K1 and constant eigenvalue K2 in an intelligent compaction control integrated system proposed by the present invention.

[0046] Figure 4 A schematic flow chart of an intelligent compaction control evaluation method proposed in the present invention.

[0047] Figure 5 The compaction index value CCV and the compaction index threshold CCV in the intelligent compaction control integrated system proposed by the present invention are as follows: T Schematic diagram of the flow chart of the determination method.

[0048] Figure 6 This is an amplitude acceleration signal curve of an intelligent compaction control evaluation method proposed in the present invention.

[0049] Figure 7 This is a correlation curve between the dynamic deflection value and the continuous compaction index of the intelligent compaction control evaluation method proposed in the present invention.

[0050] Explanation of the reference numerals: operation positioning module 1, data processing module 2, compaction roller 3, non-wheel-rotating area of ​​the wheel frame 4, acceleration signal acquisition module 5, protective baffle 6, fixed bracket 7, vibration reduction assembly 8, deflection detection module 9, roller tire 10. DETAILED DESCRIPTION

[0051] Embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present disclosure, and are not to be construed as limitations of the present disclosure. On the contrary, the embodiments of the present disclosure include all changes, modifications, and equivalents that fall within the spirit and connotation of the appended claims.

[0052] Example 1

[0053] refer to Figure 1 In this embodiment, an intelligent compaction control integrated system is proposed for performing compaction detection on the road structure layer under construction, especially the crushed pebble roadbed and road layer, and performing compaction quality related evaluation. The intelligent compaction control integrated system may include:

[0054] The operation positioning module 1 is installed on the body of the roller and is used to sense the current operation position of the roller. The specific structure of the roller is a prior art and will not be described in detail here. The specific structure of the operation positioning module 1 is a prior art and can sense the location information of the current operation position at all times. Specifically, a coordinate system can be constructed. The coordinate system can be a spatial coordinate system or a plane coordinate system. It can be evaluated according to actual needs. When it is necessary to construct data on the impact of the road structure layer height, a three-dimensional plane coordinate system can be constructed. If the road structure layer height does not need to be considered, a plane coordinate system is generally appropriate, which can greatly reduce the amount of data storage. Here, the plane coordinate system is taken as an example. The plane coordinate system can be a coordinate system covering the terrain of the entire operation area, that is, the horizontal coordinate is a length in the operation direction, and the vertical coordinate is the length in the operation direction perpendicular to the horizontal coordinate. In this way, we can directly implant the map of the operation position into the coordinate system. The implantation method is a prior art and will not be described in detail here. For example, the horizontal coordinate points to the east, with a unit length of 1 meter, and the vertical coordinate points to the south, with a unit length of one meter. The information of the current working position is converted into the corresponding coordinate point in the coordinate system, so that the location information of each working point can be obtained. Specifically, it can be obtained through GPS and other related navigation systems. It is a prior art and will not be described in detail here. The coordinate system established by this method can be evaluated and maintained from the overall perspective of road construction, which is convenient for overall observation of the road and overall interference analysis between the road and other related projects. The coordinate system can also be constructed by the road itself. The horizontal coordinate of the coordinate system can be the length of the road, with a unit length of 1 meter, and the vertical coordinate can be the width of the road, with a unit length of 1 meter. We use the distance of the coordinate axis of the current position of the press within the range of the road as the horizontal and vertical coordinates of the coordinate, so as to obtain its coordinate point in the coordinate system. The coordinate axis can be the center line and the starting line of the road, which will not be described in detail here. The information of the working position obtained by this method can be used to evaluate and analyze the road, which is convenient for quickly locating each coordinate point in the road and facilitating maintenance. Reference Figure 2 The operation positioning module 1 can be installed on the top of the roller cab, and of course it does not exclude installation at other locations. Installation at this location facilitates signal transmission and can avoid damage and contact, etc. The details will not be repeated here.

[0055] The acceleration signal acquisition module 5 is installed on the roller body and is used to sense and obtain the vibration acceleration data of the road structure layer at the current working position of the roller in real time. The specific structure of the acceleration signal acquisition module 5 is a prior art and will not be described in detail here. The acceleration signal acquisition module 5 filters the collected acceleration signal through a bandpass filter with a filtering range of 3 to 220 Hz to remove high-frequency noise and low-frequency interference, thereby improving the accuracy and reliability of the signal. Figure 2, the acceleration signal acquisition module 5 can be installed on the non-wheel-rotating area 4 of the wheel frame of the roller. Of course, it is not excluded to be installed in other positions. If it is installed in other positions, it may be disturbed by the vibration of the roller itself during operation. Of course, we can artificially remove the vibration signal during the operation of the detection signal, but the vibration during the operation is large, and this filtering method is very likely to cause the detection signal distortion. During the operation, the roller itself vibrates and sends out a vibration signal. This vibration signal is affected by the compaction state of the road structure layer, and then fed back and detected by the acceleration signal acquisition module 5. This signal can carry the data of the compaction quality of the road structure layer. The present invention also performs detection based on this. The non-wheel-rotating area 4 of the wheel frame can be on the two side frames of the compaction roller 3 of the roller. In this area, the vibration acceleration data of the compacted road structure layer can be sensed to the maximum extent. The acceleration signal acquisition module 5 can be fixed to the frame by screws through the fixed block fixed at its edge. It is convenient to fix and disassemble, and easy to repair. Of course, it can also be welded, and the details are not repeated here.

[0056] The deflection detection module 9 is installed on the roller body and is used to intermittently detect the road structure layer of the roller to obtain the dynamic deflection value l d , d is the number of the detection position of the deflection detection module 9. The deflection detection module 9 can be a drop-weight deflectometer or an automatic deflectometer, and other detection components are certainly not excluded, among which the drop-weight deflectometer is the most practical. Figure 2The deflection detection module 9 can be installed at the tail of the roller. When the roller compacts the road structure layer, the drop-hammer deflectometer can detect the compacted road structure layer. The drop-hammer deflectometer can realize control detection and obtain detection data. This is a prior art and will not be described in detail here. A protective baffle 6 can be fixedly provided at the tail of the roller. The protective baffle 6 can be a steel frame structure. The protective baffle 6 can be used to protect and install the roller tire 10 and the drop-hammer deflectometer of the roller. The specific drop-hammer deflectometer can be installed on the protective baffle 6 through a fixed bracket 7. When it is necessary to detect the road structure layer, the gravity hammer of the drop-hammer deflectometer falls, and the deflection is measured by the impact load generated by the free fall of the heavy hammer. This is a dynamic deflection, and the rebound deflection modulus of the road structure layer can be inversely calculated. It is fast and continuous, and the Beckman beam method is used for calibration and conversion when used. The specific detection process is a prior art and will not be described in detail here. When detection is not needed, the gravity hammer of the drop-hammer deflectometer is retracted. The fixed bracket 7 is equipped with a vibration reduction assembly 8, and the vibration reduction assembly 8 is located above the retracted position of the gravity hammer of the drop-hammer deflectometer. The vibration reduction assembly 8 is used to block and buffer the rising gravity hammer to prevent the gravity hammer from colliding with the protective baffle 6 under the action of rising inertia. Specifically, the drop-hammer deflectometer can be installed on the fixed bracket 7, and the four corners of the fixed bracket 7 are fixed to the protective baffle 6 by bolts, so as to facilitate the installation and maintenance of the drop-hammer deflectometer. The vibration reduction assembly 8 can be a spring, an elastic pad, or a combination of a spring and an elastic pad, and the details are not repeated here.

[0057] The data storage module is used to receive and store historical detection data. The historical detection data includes the vibration acceleration data and dynamic deflection value corresponding to the operation position and the working position. d And each data corresponding to its position information and judgment result is implanted into the coordinate system and saved, so as to facilitate the extraction when the data is used later. The data storage module can be a hard disk or cloud storage, and the specific situation needs to be determined according to the actual situation, which will not be elaborated here.

[0058] The data processing module 2 is electrically connected to the operation positioning module 1, the data storage module, the acceleration signal acquisition module 5 and the deflection detection module 9. When the data processing module 2 requires wireless transmission, the intelligent compaction control integrated system may further include a wireless signal transmission module, which is used to obtain the vibration acceleration data of the current operation position, the current operation position and the dynamic deflection value, and transmit them to the data processing module 2. The vibration acceleration data of the current operation position obtained by the data processing module 2, the current operation position and the dynamic deflection value; determine whether the current operation position is different from the previous dynamic deflection value l d-1 Check whether the distance between the detection positions is greater than or equal to a preset detection standard distance L 标 If yes, the current working position is tested to obtain the dynamic deflection value ld If not, the dynamic deflection value detection is not performed. The preset detection standard spacing L 标 , can be determined according to the actual situation. If the influence coefficient characteristic value K1 and the constant characteristic value K2 factors change greatly, their values ​​need to be set shorter, and if the change is not large, they should be set longer. The value is generally between 50-200m, and 100m is generally selected. According to the vibration acceleration data and dynamic deflection value l fed back by the road structure layer at the current working position d Fit and construct the relationship, and calculate the coefficient eigenvalue K1 and the constant eigenvalue K2. Determine the compaction index threshold CCV based on the coefficient eigenvalue K1 and the constant eigenvalue K2 T The compaction index value CCV and the compaction index threshold CCV are obtained by detecting and calculating the current working position. T The relationship between the data processing module 2 and the data processing module 2 is used to determine whether the compaction quality of the current compacted structural layer is qualified. If qualified, no marking is performed, and the working position may not be subjected to additional compaction. If unqualified, the current working position is marked, and the current working position is sent to the data display module for display, and additional compaction may be performed on the working position. When there are many unqualified working positions, the entire road structure layer section may be fully compacted. The data processing module 2 may be arranged in the cab of the roller. Of course, the data processing module 2 may also be a remote control center, and remote control may be achieved through the remote control center. Remote control is suitable for unmanned operation, and the details are not described here. The data display module may be installed on a display screen in the cab of the roller, or it may be a display of a remote control center, and the details are not described here. During the working process, a drop hammer deflectometer is generally used in the prior art to detect the road structure layer, but this detection is a single-point detection, and the detection takes time, and cannot be detected in real time, because the specific conditions of each position point of the road structure layer are different. For example, if the moisture content is uneven, the paving thickness is uneven, or the paving material is unevenly mixed due to the staged feeding, it is impossible to achieve the same compaction quality of the road structure layer, which is very easy to cause the detection point and the unqualified point to be misplaced, resulting in an incomplete evaluation of the road structure layer, thereby affecting the quality of the road structure layer. The compaction index value CCV and the compaction index threshold CCV detected in real time by the acceleration signal acquisition module 5 T The compaction index value can be detected and obtained in real time, so that each working position can be judged. Such a comprehensive judgment can completely ensure that there will be no unqualified working positions missed, ensuring comprehensive road detection. If the unqualified position can be re-compacted in time, the compaction quality of the road can be guaranteed. The compaction index threshold CCV TThe dynamic deflection value obtained through intermittent detection by the deflection detection module 9 can be corrected to avoid threshold setting errors caused by changes in road conditions. The compaction index threshold obtained by this method is a dynamic data with staged corrections. The data is updated in a timely manner, which improves the accuracy of the judgment. In the actual detection process, we need a roller to compact the road structure layer and obtain the current working position and vibration acceleration data. The current working position and vibration acceleration data are obtained in real time. This data detection does not require an operation interval or destructive detection of the road, and the detection is convenient. The current operation information is obtained through the operation positioning module 1, and the vibration acceleration data is obtained through the acceleration signal acquisition module 5. The vibration acceleration data can include the fundamental frequency amplitude A0 and the harmonic amplitude A i , where i is the harmonic amplitude order. Of course, other data may also be included, such as speed, acceleration, equipment posture, travel distance, etc., which will not be described in detail here. Vibration acceleration data and dynamic deflection value l d Fitting to construct the dynamic deflection value and the compaction index value CCV corresponding to the detection point numbered d d The relationship between , where d is the number of the detection position of the deflection detection module 9, l d is the vibration acceleration data corresponding to the detection position of the deflection detection module 9 numbered d, CCV d It is the compaction index value of the acceleration signal acquisition module 5 at the detection position of the deflection detection module 9 numbered d. k1 is the calculated value of the coefficient and k2 is the calculated value of the constant. K1 is the coefficient characteristic value and K2 is the constant characteristic value. The two values ​​can be obtained through model fitting. The size of the values ​​is not only related to factors such as the filler type and filler height of the roadbed, but also to soil parameters (water content, gradation, etc.), compaction process parameters (roller speed, exciting force, number of passes, etc.), and compaction passes (different compaction passes may affect the values ​​of K1 and K2). We generally do not calculate these two values ​​through the properties of the roadbed, as there are too many variables, which may easily cause inaccurate data calculations. However, the possibility of determining them through the properties of the roadbed is not ruled out. The determination method is to use the dynamic deflection values ​​l of the two combinations of the detection positions of each deflection detection module 9. d The compaction index value CCV corresponding to the detection point numbered d d Calculate multiple groups of coefficient calculation values ​​k1 and constant calculation values ​​k2, and then perform optimization to obtain coefficient eigenvalues ​​K1 and constant eigenvalues ​​K2. Figure 3 The optimization method may include mathematical statistics, correlation establishment, parameter optimization, verification and statistics. Mathematical statistics is to calculate the compaction index value CCV corresponding to the detection point numbered d by the vibration acceleration data of the detection position of the two deflection detection modules 9. d and dynamic deflection value l dSubstitute the formula relationship , so that multiple sets of coefficient calculation values ​​k1 and constant calculation values ​​k2 can be obtained, and the correlation relationship is established for statistical analysis to establish a mathematical model between them. Parameter optimization: Use optimization algorithms (such as gradient descent, least squares method, etc.) to determine the optimal values ​​of K1 and K2, so that the error between the compaction value predicted by the model and the actual measured value is minimized. Verification and adjustment: The model is verified by actual engineering data, and K1 and K2 are adjusted according to the verification results to adapt to different types of soil and compaction requirements. The specific numerical calculation is too cumbersome and is not given as an example here. Through the above process, k1 and k2 are determined and used in the compaction quality evaluation formula to achieve an accurate assessment of the compaction quality. This method combines experimental data and mathematical statistics technology to improve the accuracy and efficiency of compaction quality control. The coefficient characteristic value K1 and the constant characteristic value K2 can also be obtained by direct calculation, and the acquisition method includes mathematical statistics and numerical calculation. Mathematical statistics is to calculate the compaction index value CCV corresponding to the detection point numbered d by the vibration acceleration data of the detection position of the two-by-two deflection detection module 9. d and dynamic deflection value l d Bring in the relation , so that multiple sets of coefficient calculation values ​​can be obtained and constant calculation value , where d is the number of the detection position of the deflection detection module 9, The coefficient calculation value is obtained by jointly calculating the detection position of the deflection detection module 9 numbered d and the detection position of the deflection detection module 9 numbered d-1, The constant calculation value is obtained by combining the detection position of the deflection detection module 9 numbered d and the detection position of the deflection detection module 9 numbered d-1. D is the total number of current detections by the deflection detection module 9, d=2, 3..., D. In the actual working process, we will start counting from a preset working section, such as a specific road section, time period or road section with the same number of rolling passes. The parameters affecting K1 and K2 in this road section, time period or road section with the same number of rolling passes do not change much. If the parameters change greatly, we can restart the counting, which will not be described in detail here. Then the coefficient eigenvalue , constant eigenvalue , where ɑ is the base number of the roadbed deviation, and its value is generally 1-10, which we can assign based on experience. We can also artificially divide the differences between the influencing coefficient eigenvalue K1 and the constant eigenvalue K2 into 10 levels. When they are exactly the same, the base number of the roadbed deviation ɑ is 1, and when the difference is the largest, the base number of the roadbed deviation ɑ is 10. Then, we construct a numerical classification assignment table. We can find the numerical classification assignment table through the current factors to obtain the current base number of the roadbed deviation. For the same road section, the numerical changes are generally not very large. The specific content of the numerical classification assignment table is not the subject of protection of this application, and will not be elaborated here. It is the dth power of the base of the roadbed deviation. ε is the deviation adjustment factor, and its value is generally 0, 1-10, and is generally taken as 1. The specific details are not described here. The coefficient calculation value is obtained by jointly calculating the detection position of the deflection detection module 9 numbered d and the detection position of the deflection detection module 9 numbered d-1, The constant calculation value is obtained by jointly calculating the detection position of the deflection detection module 9 numbered d and the detection position of the deflection detection module 9 numbered d-1, d=2, 3..., D. The coefficient eigenvalues ​​and constant eigenvalues ​​are calculated by this method, and the differences in road materials, construction and environment can be taken into account. It can be seen from the formula that the smaller the proportion of the detection position with the front number, the smaller the influence on the judgment of the current point. In this case, we can increase the proportion of the calculated values ​​of the position points adjacent to the current position point, thereby reducing the deviation caused by factors such as time and distance. This method is more accurate in calculation and can make better and more accurate assessments of the road structure layer. The relationship The compaction index value CCV corresponding to the detection point numbered d d Instead of directly using the vibration acceleration data of the acceleration signal acquisition module 5, the compaction index value , where i is the harmonic amplitude order, A0 is the fundamental frequency amplitude of the detection position of the deflection detection module 9 numbered d, and A i is the i-th harmonic amplitude at the detection position of the deflection detection module 9 numbered d, where I is the total number of amplitude values, i=1, 2, ..., I. β is the amplitude coefficient, which is generally 200. Figure 6 , generally speaking, the number of I is 3, that is Of course, other calculation methods are not excluded, and the details are not described here. T The determination method may include a compaction indicator threshold , where K1 is the coefficient eigenvalue, K2 is the constant eigenvalue, which is the value obtained by the above calculation, l TIt is the dynamic deflection design value. Its specific value can be obtained by staff through experience through equipment and roadbed data. Of course, this situation is highly subjective and requires staff to have extremely rich experience. The dynamic deflection design value can also be obtained by calculation. , —Design value of roadbed rebound modulus, —Drop weight instrument load plate (Mpa), —Drop weight bearing plate radius (mm). These values ​​can be obtained based on the road structure layer design standards and equipment parameters, and will not be elaborated here. is the design coefficient, and its value is 150-200, with 176 being the most appropriate. The compaction index threshold calculated by this method can well distinguish and judge the detection data, and the calculation is convenient. In addition, the coefficient eigenvalue and constant eigenvalue are updated and optimized in stages to ensure the accuracy of the judgment threshold. T The judgment method can be directly based on the current compaction index value CCV n Compaction indicator threshold CCV T Compare the size, where n is the number of times the roller rolls at the current working position, which can be obtained through historical data. The details are not described here. The current compaction index value CCV n It is the calculated vibration acceleration data detected by the acceleration signal acquisition module 5 at the front working position. n Greater than the compaction indicator threshold CCV T If the road is δ times of the road quality, it is considered qualified. δ is the judging proportional coefficient, and its value can be 0.7-1. The specific value depends on the road quality requirements. The general value is 0.9, which will not be elaborated here. Figure 5 and Figure 7 Of course, the compaction index value CCV and the compaction index threshold CCV T The determination method may also include: determining whether the optimized compaction reduction value C is less than a preset standard reduction ratio C 标 , and the current compaction index value CCV n Is it greater than the compaction index threshold CCV? T δ times, if both are true, it is determined to be qualified, if one is not, it is determined to be unqualified. The optimized compaction reduction value can be , where n is the number of compaction passes. In general, the number of compaction passes of the road structure layer is greater than 3, and each roller tire has an evaluation length of 100m and a calculation length of 10m, so as to facilitate timely compaction. Of course, other numerical settings are not excluded, and the specific details are not repeated here. The preset standard reduction ratio C 标It can be set according to actual needs, and the value is generally 10%-30%. It can be determined according to road requirements and experience values, with 20% being the best. This method can be used to determine not only the compaction changes at the same operating position, but also the quality control through thresholds. The judgment forms are diverse, so the necessity of optimizing the quality of the road structure layer and the road quality can be controlled from multiple aspects, thereby improving the evaluation effect of the quality of the road structure layer.

[0059] Example 2

[0060] refer to Figure 4 The present invention also proposes an intelligent compaction control evaluation method for evaluating the compaction quality of a compacted road structure layer. The intelligent compaction control evaluation method comprises the following steps:

[0061] S1. Obtain vibration acceleration data fed back by the road structure layer at the current working position.

[0062] S2. Determine the current working position and the previous dynamic deflection value l d-1 Check whether the distance between the detection positions is greater than or equal to a preset detection standard distance L 标 If yes, execute S3, if no, do not perform detection.

[0063] S3, then detect the current working position to obtain the dynamic deflection value l d .

[0064] S4, based on the vibration acceleration data and dynamic deflection value l of the road structure layer feedback at the current working position d The fitting relationship is constructed and the coefficient eigenvalue K1 and the constant eigenvalue K2 are calculated.

[0065] S5. Determine the compaction index threshold CCV based on the coefficient eigenvalue K1 and the constant eigenvalue K2 T .

[0066] S6. Calculate and obtain the compaction index value CCV and the compaction index threshold CCV through current operation position detection T The relationship between them is used to determine whether the compaction quality of the current compacted structural layer is qualified. If qualified, no mark is made; if unqualified, the current working position is marked.

[0067] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0068] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. An intelligent compaction control integrated system, characterized in that: include: An operation positioning module is installed on the roller body and is used to obtain the current operation position of the roller; The acceleration signal acquisition module is installed on the roller body and is used to sense and obtain the vibration acceleration data of the road structure layer at the current working position in real time; The deflection detection module is installed on the roller body and is used to intermittently detect the working road to obtain the dynamic deflection value l d , where d is the number of the detection position; A data storage module, which is used to store historical detection data; The data processing module is used to obtain the vibration acceleration data fed back by the road structure layer at the current working position; determine the current working position and the dynamic deflection value l d-1 Check whether the distance between the detection positions is greater than or equal to a preset detection standard distance L 标 If yes, the current working position is tested to obtain the dynamic deflection value l d And the compaction index value CCV corresponding to the detection point numbered d d ; If not, no dynamic deflection value detection is performed; Fitting to construct CCV d With l d Relationship, coefficient eigenvalue K1 and constant eigenvalue K2; and determine the compaction index threshold CCV T ; Calculate the compaction index value CCV and the compaction index threshold CCV T The relationship between them; determine whether the compaction quality of the current compacted structural layer is qualified. If qualified, no mark is made; if unqualified, the current working position is marked.

2. According to claim 1, the intelligent compaction control integrated system is characterized in that: The operation positioning module is installed on the top of the roller cab.

3. According to claim 1, the intelligent compaction control integrated system is characterized in that: The acceleration signal acquisition module is installed in the non-wheel-rotating area of ​​the wheel frame of the roller.

4. The intelligent compaction control integrated system according to claim 1, characterized in that: The deflection detection module is a drop weight deflectometer.

5. The intelligent compaction control integrated system according to claim 1, characterized in that: A protective baffle is fixedly arranged at the rear of the roller, and the deflection detection module is installed on the protective baffle through a fixed bracket.

6. The intelligent compaction control integrated system according to claim 5, characterized in that: The fixed bracket is equipped with a vibration reduction assembly, which is located above the retracted position of the gravity hammer of the drop-weight deflectometer.

7. The intelligent compaction control integrated system according to claim 1, characterized in that: The data processing module is arranged in the driving cabin of the road roller.

8. The intelligent compaction control integrated system according to claim 1, characterized in that: The compaction index value CCV corresponding to the detection point numbered d d and dynamic deflection value l d The relationship is , where d is the number of the detection position of the deflection detection module, l d is the dynamic deflection value corresponding to the detection position of the deflection detection module numbered d, CCV d is the compaction index value of the detection position of the deflection detection module numbered d, k1 is the calculated value of the coefficient, and k2 is the calculated value of the constant.

9. The intelligent compaction control integrated system according to claim 1, characterized in that: Compaction indicator threshold , where K1 is the coefficient eigenvalue, K2 is the constant eigenvalue, l T is the design value of dynamic deflection.

10. An intelligent compaction control evaluation method, characterized in that: The intelligent compaction control evaluation method comprises the following steps: S1. Obtain vibration acceleration data fed back by the road structure layer at the current working position; S2. Determine the current working position and the previous dynamic deflection value l d-1 Check whether the distance between the detection positions is greater than or equal to a preset detection standard distance L 标 ; If yes, then S3 is executed; if no, then the dynamic deflection value detection is not performed; S3. Detect the current working position to obtain the dynamic deflection value l d ; S4, based on the vibration acceleration data and dynamic deflection value l of the road structure layer feedback at the current working position d Fitting construction number d corresponding to the compaction index value CCV d and dynamic deflection value l d Relationship, and calculate the coefficient eigenvalue K1 and the constant eigenvalue K2; S5. Determine the compaction index threshold CCV based on the coefficient eigenvalue K1 and the constant eigenvalue K2 T ; S6. Calculate and obtain the compaction index value CCV and the compaction index threshold CCV through current operation position detection T The relationship between them is used to determine whether the compaction quality of the current compacted structural layer is qualified. If qualified, no mark is made; if unqualified, the current working position is marked.

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