An intelligent compaction control integration system and its evaluation method

Abstract

The present invention relates to the technical field of road engineering, and specifically to an intelligent compaction control integration system and an evaluation method thereof. The technical solution includes: an operation positioning module, which is installed on the roller body and is used to sense and obtain the current operation position of the roller. An acceleration signal acquisition module, which is installed on the roller body and is used to sense and obtain in real time the vibration acceleration data feedback from the road structure layer at the current working position of the roller. A deflection detection module, which is installed on the roller body and is used to intermittently detect the roller operation road to obtain dynamic deflection values. A data processing module is electrically connected to the operation positioning module, the data storage module, the acceleration signal acquisition module, and the deflection detection module. The compaction index value detected in real time by the acceleration signal acquisition module is judged against the compaction index threshold value. The compaction index value can be obtained by real-time detection, and the judgment is comprehensive. The judgment threshold value can be automatically updated in real time according to the road conditions.

Description

Technical Field

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

[0002] Road compaction refers to a process in road engineering where various types of subgrade materials are evenly laid and reach the design strength after a certain degree of compaction. The compaction quality of the road directly affects the safety, comfort, and service life of road traffic. The following are the main factors affecting road compaction quality: 1. Subgrade condition: The subgrade 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 method of the roller will also affect the compaction quality of the subgrade road. 5. Construction technology: Technical parameters such as the uniformity of the mixture, the number of compaction passes, and the compaction sequence should be controlled according to the specifications. To ensure the compaction quality of the road, some measures usually need to be taken: 1. Select a suitable roller: Select an appropriate roller according to factors such as the thickness, width, and compaction requirements of the working layer. 2. Strictly control the construction technology: Construct strictly according to the specifications and technical points, including the mixture ratio, mixing uniformity, and the number of compaction passes. 3. Strengthen construction management: Strengthen the quality monitoring of the construction process, and promptly discover and solve existing problems. 4. Strengthen training and education: Conduct technical training and management for construction personnel to enable them to master construction skills proficiently. In short, reasonable road compaction is of great significance for ensuring the stability and comfort of the road structure, and 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. Degree of compaction: The most direct indicator to measure the compaction quality, that is, the change in the water content of the subgrade soil after compaction. It can be measured by professional instruments, and generally, it is required to reach the specified minimum degree of compaction value. 2. Surface defects: Mainly check whether there are quality problems such as looseness and deformation on the compacted road. 3. Internal quality: For example, conduct radar uniformity detection on the gravel soil subgrade, and take core samples of the integral materials of the road to evaluate whether their physical and mechanical properties meet the design requirements, such as density, void ratio, strength, etc. 4. Appearance quality: The appearance quality includes the roadbed, base course, 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 meets 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 re-compacted, or whether further quality control measures are required.

[0004] For detecting the existing road compaction quality, a falling weight deflectometer is generally used. Its working principle is as follows: Under computer control, a gravity hammer of a certain mass is lifted to a certain height by a hydraulic transmission device and then freely falls. The impact force acts on the bearing plate and is transmitted to the road, thereby applying a pulse load to the road, causing an instantaneous deformation on the road surface. Sensors distributed at different distances from the measuring point detect the deformation on 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 action of the dynamic load are measured. The test data can be used to back-calculate the modulus of the road structural layer, so as to scientifically evaluate the bearing capacity of the road. The traditional falling weight deflectometer detection can only perform sampling detection on the road surface, resulting in insufficient road evaluation ability. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides an intelligent compaction control integration system for compaction detection of the road structural layer under construction, especially for pebble roadbeds, road structural layers, etc., and conducts related evaluations of compaction quality. The intelligent compaction control integration system may include:

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

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

[0008] A deflection detection module, installed on the roller body, which is used to intermittently detect the operation 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] A data processing module, which is used to obtain the vibration acceleration data fed back by the road structural layer at the current working position; determine whether the distance between the current working position and the detection position of the dynamic deflection value l d-1 is greater than or equal to a preset detection standard spacing L 标 , if so, detect the current working position to obtain the dynamic deflection value l d and the compaction index value CCV corresponding to the detection point numbered d d ; if not, do not perform dynamic deflection value detection; fit and construct the relationship between CCV d and l d and the coefficient eigenvalue K1 and the constant eigenvalue K2; and determine the compaction index threshold CCV T ; calculate the obtained compaction index value CCV and the compaction index threshold CCV TThe relationship between; determine whether the compaction quality of the current compacted structural layer is qualified. If it is qualified, no marking is performed; if it is unqualified, the current operation position is marked. And send the current operation position to the data display module for display, and the operation position can be recompacted. When there are many unqualified operation positions, the entire road section can be fully compacted.

[0011] Preferably: The method for obtaining the current operation position includes: constructing a plane coordinate system, and directly implanting the map of the operation area into the coordinate system, so that the coordinate points of the current operation position in the coordinate system can be obtained.

[0012] Preferably: The method for obtaining the current operation position includes: constructing a plane coordinate system, where the abscissa of the plane coordinate system can be the length of the road, and the ordinate can be the width of the road. The distances of the current position of the press relative to the coordinate axes are used as the abscissa and ordinate of the coordinates, so as to obtain its coordinate points in the coordinate system. The information of the operation position obtained by this method can be used to evaluate and analyze the road, facilitating the rapid positioning of each coordinate point in the road and facilitating 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 the non-rotating area of the wheel frame of the roller.

[0015] Preferably: The non-rotating area of the wheel frame can be on the two side frames of the compacting roller of the roller. In this area, the vibration acceleration data of the compacted road structural layer can be sensed to the maximum extent. The non-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, which can effectively obtain the vibration acceleration signal without being affected by other interferences.

[0016] Preferably: The deflection detection module can be a falling weight deflectometer or an automatic deflectometer, etc.

[0017] Preferably: The deflection detection module is a falling weight deflectometer.

[0018] Preferably: The falling weight deflectometer can be installed at the tail position of the roller.

[0019] Preferably: A protective baffle can be fixedly arranged at the tail of the roller. The protective baffle can be of a steel frame structure. The protective baffle can be used to protect and install and support the roller tires and the falling weight deflectometer of the roller. Specifically, the falling weight deflectometer can be installed on the protective baffle through a fixed bracket.

[0020] Preferably, a damping component is installed on the fixed support. The damping component is located above the retracted position of the gravity hammer of the falling weight deflectometer. The damping component 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 upward inertia.

[0021] Preferably, the data processing module is arranged in the cab of the road roller and can 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] Preferably, the compaction index value CCV corresponding to the detection point numbered d d and the dynamic deflection value l d have the relationship , 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, and CCV d is the compaction index value of the detection position of the deflection detection module numbered d. k1 is the calculated coefficient value and k2 is the calculated constant value.

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

[0025] Preferably, mathematical statistics is to calculate the compaction index value CCV corresponding to the detection point numbered d from the vibration acceleration data of the detection position of the deflection detection module d and the dynamic deflection value l d and substitute them into the formula relationship , so as to obtain multiple groups of calculated coefficient values k1 and calculated constant values k2. Establish correlation relationships for statistical analysis and 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 to minimize the error between the predicted compaction degree value of the model and the actual measured value. Verification and adjustment: Verify the model through actual engineering data and adjust K1 and K2 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 accurate evaluation of compaction quality. This method combines experimental data and mathematical statistics techniques to improve the accuracy and efficiency of compaction quality control.

[0026] Preferably, the obtaining of the coefficient eigenvalue K1 and the constant eigenvalue K2 may also include: by using the compaction index value CCV corresponding to the detection point numbered d of the detection position of the deflection detection module d and the dynamic deflection value ld Substitute into the relational expression , thus multiple sets of coefficient calculation values can be obtained and constant calculation values , where d is the number of the detection position of the deflection detection module, is the coefficient calculation value 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, is the constant calculation value 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 is the total number of current detections of the deflection detection module, d = 2, 3…, D. Then the coefficient eigenvalue , the constant eigenvalue , where ɑ is the base number of subgrade deviation, and its value is generally 1 - 10. is the d-th power of the base number of subgrade deviation. ε is the deviation adjustment factor, and its value is generally 0, 1 - 10, and generally can be taken as 1. is the coefficient calculation value 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, is the constant calculation value 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. By calculating the coefficient eigenvalue and the constant eigenvalue through this method, the differences in road section materials, construction, and environment can be considered. It can be seen from the formula that the earlier the detection position number, the smaller the proportion it occupies, and the less impact it has on the determination of the current point. In such a case, we can increase the proportion of the calculation 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 calculates more accurately and can better and more accurately evaluate the road compaction structural layer.

[0027] Preferably: 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 numbered d, A i is the i-th harmonic amplitude of the detection position of the deflection detection module numbered d, I is the total number of wave amplitude orders, i = 1, 2,…, I. β is the amplitude coefficient, and its value is generally 200.

[0028] Preferably: .

[0029] Preferably: The compaction index threshold , where K1 is the coefficient eigenvalue, K2 is the constant eigenvalue, l T is the dynamic deflection design value.

[0030] Preferably: The dynamic deflection design value , — Design value of subgrade resilient modulus, — Load on the bearing plate of the falling weight deflectometer, — Radius of the falling weight bearing plate, is a design coefficient, and its value is 150 - 200, preferably 176. By calculating the compaction index threshold value in this way, the test data can be well distinguished and judged. The calculation is convenient, and the coefficient characteristic value and the constant characteristic value are updated and optimized periodically to ensure the accuracy of the judgment threshold value.

[0031] Preferably: The method for judging the relationship between the compaction index value CCV and the compaction index threshold value CCV T may include: judging whether the optimized compaction reduction value C is less than a preset standard reduction ratio C 标 , and whether the current compaction index value CCV n is greater than δ times of the compaction index threshold value CCV T . If both are true, it is judged as qualified; otherwise, it is judged as unqualified.

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

[0033] Preferably: The preset standard reduction ratio C 标 is generally 10% - 30%.

[0034] Preferably: The optimal value is 20%.

[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 includes the following steps:

[0036] S1. Obtain the vibration acceleration data feedback from the road structure layer at the current working position.

[0037] S2. Determine whether the distance between the current working position and the detection position of the previous dynamic deflection value l d-1 is greater than or equal to a preset detection standard spacing L 标 . If so, execute S3; if not, 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. According to the vibration acceleration data feedback from the road structure layer at the current working position and the dynamic deflection value l d , fit and construct the compaction index value CCV corresponding to the detection point numbered d d and the dynamic deflection value l dRelationship, and calculate the coefficient eigenvalue K1 and the constant eigenvalue K2.

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

[0041] S6. Obtain the relationship between the compaction index value CCV obtained by detecting and calculating the current working position and the compaction index threshold CCV T to determine whether the compaction quality of the current compacted structural layer is qualified. If it is qualified, no marking is performed. If it is unqualified, the current working position is marked.

[0042] The technical effects and advantages of the present invention: During the working process, in the prior art, a falling weight deflectometer is generally used to detect roads. However, this detection is a single-point detection and takes time, and it cannot be detected in real time. Due to the differences in the specific conditions of each position point of the road structural layer. For example, due to uneven moisture content caused by staged feeding, uneven paving thickness, or uneven mixing of paving materials, it is impossible to achieve the same road compaction quality, and it is very easy to cause misalignment between the detection points and the unqualified points, resulting in an incomplete evaluation of road compaction and thus affecting the road quality. The compaction index value CCV detected in real time through the acceleration signal acquisition module and the compaction index threshold CCV T are used for determination. The compaction index value can be detected in real time, so that each working position can be determined. Such determination is comprehensive and can completely ensure that there will be no missed unqualified working positions, ensuring the comprehensiveness of the compaction detection of the road structural layer. If the unqualified position can be filled and compacted in time, the compaction quality of the road can be ensured. The compaction index threshold CCV T can be corrected by the dynamic deflection value obtained by intermittently detecting through the deflection detection module, so as to avoid incorrect threshold setting caused by changes in road conditions. The compaction index threshold obtained by this method is a dynamically corrected dynamic data at stages, and the data is updated in time, improving the accuracy of determination. In the actual detection process, we need the roller to compact the road structural layer and obtain the current working position and vibration acceleration data. The current working position and vibration acceleration data are obtained in real time, and this data detection does not require an operation interval, which can greatly reduce the damage to the road and is convenient for detection. Description of the Drawings

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

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

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

[0046] Figure 4 Schematic flow chart of a method for evaluating intelligent compaction control proposed by the present invention.

[0047] Figure 5 For the compaction index value CCV and the compaction index threshold CCV in an intelligent compaction control integration system proposed by the present invention T Schematic flow chart of the determination method.

[0048] Figure 6 Amplitude acceleration signal curve of a method for evaluating intelligent compaction control proposed by the present invention.

[0049] Figure 7 Correlation curve between the dynamic deflection value and the continuous compaction index of a method for evaluating intelligent compaction control proposed by the present invention.

[0050] Explanation of reference numerals: Operation positioning module 1, data processing module 2, compaction roller 3, non-wheel-rotating area 4 of the wheel frame, acceleration signal acquisition module 5, protective baffle 6, fixed bracket 7, vibration damping component 8, deflection detection module 9, road roller tire 10. Detailed implementation manners

[0051] The embodiments of the present disclosure will be described in detail below. Examples of the embodiments are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present disclosure and should not be construed as limiting the present disclosure. On the contrary, the embodiments of the present disclosure include all changes, modifications, and equivalents falling within the spirit and scope of the appended claims.

[0052] Embodiment 1

[0053] Refer to Figure 1 , in this embodiment, an intelligent compaction control integration system is proposed for performing compaction detection on the road structure layer under construction, especially on the crushed pebble roadbed and road layer, and performing relevant evaluations on the compaction quality. The intelligent compaction control integration system may include:

[0054] The operation positioning module 1 is installed on the road roller body and is used to sense and obtain the current operation position of the road roller. The specific structure of the road roller is prior art and will not be elaborated herein. The specific structure of the operation positioning module 1 is prior art and can sense the position 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, and can be specifically evaluated according to the actual requirements. When it is necessary to construct data on the influence 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, generally a plane coordinate system is appropriate, which can greatly reduce the data storage amount. Taking the plane coordinate system as an example here, the plane coordinate system can be a coordinate system covering the terrain of the entire operation area, that is, the abscissa is the length of an operation direction, and the ordinate is the length of the operation direction perpendicular to the abscissa. In this way, we can directly implant the map of the operation position into the coordinate system, and the implantation method is prior art and will not be elaborated herein. For example, the abscissa points to the due east, the unit length is 1 meter, the ordinate points to the due south, and its unit length is also 1 meter, and the information of the current operation position is converted into the corresponding coordinate point in the coordinate system, so that the position information of each operation point can be obtained. Specifically, it can be obtained through relevant navigation systems such as GPS, which is prior art and will not be elaborated herein. The coordinate system established by this method can be evaluated and maintained from the overall perspective of road construction, which is convenient for the overall observation of the road and the overall interference analysis between the road and other related projects. The coordinate system can also be constructed through the road itself. The abscissa of the coordinate system can be the length of the road, and its unit length can be 1 meter. The ordinate can be the width of the road, and its unit length can also be 1 meter. We use the distances of the current position of the road roller from the coordinate axes within the road range as the abscissa and ordinate of the coordinates, so as to obtain its coordinate point in the coordinate system. The coordinate axes can be the center line and the starting line of the road, which will not be elaborated herein. The information of the operation position obtained by this method can be used for evaluation and analysis of the road, which is convenient for quickly positioning each coordinate point in the road and is convenient for maintenance. Reference Figure 2 , the operation positioning module 1 can be installed on the top of the road roller cab. Of course, it does not exclude being installed in other positions. Installing in this position is convenient for signal transmission and can avoid damage and touch, etc., which will not be elaborated herein.

[0055] The acceleration signal acquisition module 5 is installed on the road roller body and is used to sense and obtain in real time the vibration acceleration data fed back by the road structure layer at the current working position of the road roller. The specific structure of the acceleration signal acquisition module 5 is prior art and will not be elaborated herein. The acceleration signal acquisition module 5 filters the acquired acceleration signals through a band-pass filter with a filtering interval of 3 - 220 Hz to remove high-frequency noise and low-frequency interference, and improve the accuracy and reliability of the signals. Reference Figure 2, the acceleration signal acquisition module 5 can be installed on the non-wheel-rotating area 4 of the wheel frame of the road roller. Of course, installation in other positions is not excluded. Installing in other positions may be affected by the vibration during the operation of the road roller itself. Of course, we can artificially remove the vibration signal during the operation from the detected signal. However, since the vibration is large during the operation, this filtering method is likely to cause the detected signal to be distorted. During the operation, the road roller itself vibrates and emits a vibration signal. This vibration signal is affected by the compaction state of the road structure layer, and then is fed back and detected by the acceleration signal acquisition module 5. This signal can carry data on the compaction quality of the road structure layer. The present invention is based on this for detection. The non-wheel-rotating area 4 of the wheel frame can be on the vehicle frames on both sides of the compaction roller 3 of the road 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 vehicle frame by screws passing through the fixed clamping blocks fixed at its edge. The fixing and dismounting are convenient and it is easy to repair. Of course, it can also be fixed by welding, which will not be elaborated here specifically.

[0056] The deflection detection module 9 is installed on the vehicle body of the road roller and is used for intermittently detecting the road structure layer of the road roller during operation to obtain the dynamic deflection value l d , where d is the number of the detection position of the deflection detection module 9. The deflection detection module 9 can be a falling weight deflectometer or an automatic deflectometer. Of course, other detection components are not excluded. Among them, the falling weight deflectometer is the most practical. Refer to Figure 2, the deflection detection module 9 can be installed at the tail position of the roller. After the roller compacts the road structure layer, the falling weight deflectometer can detect the compacted road structure layer. The falling weight deflectometer can control the detection and obtain the detection data. Specifically, it is prior art and will not be elaborated here. A protective baffle 6 can be fixedly arranged 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 and support the roller tires 10 of the roller and the falling weight deflectometer. Specifically, the falling weight deflectometer can be installed on the protective baffle 6 through a fixing bracket 7. When it is necessary to detect the road structure layer, the gravity hammer of the falling weight deflectometer drops, and the impact load generated by the free fall of the heavy hammer is used to measure the deflection, which belongs to dynamic deflection, and the resilient deflection modulus of the road structure layer can be back-calculated, which is fast and continuous. When in use, it is calibrated and converted by the Benkelman beam method. The specific detection process is prior art and will not be elaborated here. When detection is not required, the gravity hammer of the falling weight deflectometer is retracted. A vibration damping component 8 is installed on the fixing bracket 7. The vibration damping component 8 is above the retracted position of the gravity hammer of the falling weight deflectometer. The vibration damping component 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 falling weight deflectometer can be installed on the fixing bracket 7. The four corners of the fixing bracket 7 are fixedly installed on the protective baffle 6 through bolts, so as to facilitate the installation and maintenance of the falling weight deflectometer. The vibration damping component 8 can be a spring, an elastic pad or a combined structure of a spring and an elastic pad, which will not be elaborated here specifically.

[0057] A data storage module, which is used to receive and store historical detection data. The historical detection data includes the vibration acceleration data corresponding to the operation position and the working position and the dynamic deflection value l d , and implant each data corresponding to its position information and determination result into the coordinate system and save it, so as to facilitate extraction when using the data 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 specifically.

[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 needs to perform wireless transmission, the intelligent compaction control integration system can also include a wireless signal transmission module, which is used to obtain the vibration acceleration data at the current operation position, the current working position and the dynamic deflection value, and transmit them to the data processing module 2. The data processing module 2 obtains the vibration acceleration data at the current operation position, the current working position and the dynamic deflection value; determines whether the distance between the current working position and the previous dynamic deflection value l d-1 The distance between the detection positions is greater than or equal to a preset detection standard spacing L 标 , if so, detect the current working position to obtain the dynamic deflection value ld If not, the dynamic deflection value detection is not performed. The preset detection standard spacing L 标 , which can be determined according to the actual situation. If the influencing coefficient eigenvalue K1 and the constant eigenvalue K2 change greatly, their values need to be set shorter; if the change is not significant, they can be set longer. The values are generally between 50 - 200 m, and 100 m is generally selected. According to the vibration acceleration data and the dynamic deflection value l d fed back by the road structure layer at the current working position, a relational expression is fitted and constructed, and the coefficient eigenvalue K1 and the constant eigenvalue K2 are calculated. The compaction index threshold CCV is determined according to the coefficient eigenvalue K1 and the constant eigenvalue K2 T . The relationship between the compaction index value CCV obtained by detection and calculation at the current working position and the compaction index threshold CCV T is determined to judge whether the compaction quality of the current compacted structure layer is qualified. If it is qualified, no marking is required, and the current working position does not need to be recompacted. If it is unqualified, the current working position is marked, and the current working position is sent to the data display module for display, and the current working position can be recompacted. When there are many unqualified working positions, the entire road structure layer section can be fully compacted. The data processing module 2 can be set in the driver's cab of the roller. Of course, the data processing module 2 can also be a remote control center. Remote control can be achieved through the remote control center, and remote control is suitable for driverless operation, which will not be elaborated here. The data display module can be installed on the display screen in the driver's cab of the roller or on the monitor of the remote control center, which will not be elaborated here. During the working process, in the prior art, a falling weight deflectometer is generally used to detect the road structure layer. However, this detection is a single-point detection and takes time, and cannot be detected in real time. Due to the differences in the specific conditions of each position point of the road structure layer. For example, due to uneven moisture content caused by staged feeding, uneven paving thickness, or uneven mixing of paving materials, it is impossible to achieve the same compaction quality of the road structure layer, and it is very easy to cause misalignment between the detection points and the unqualified points, resulting in an incomplete evaluation of the road structure layer, thereby affecting the quality of the road structure layer. By using the compaction index value CCV detected in real time by the acceleration signal acquisition module 5 and the compaction index threshold CCV T for judgment, the compaction index value can be detected in real time, so that each working position can be judged. Such judgment is comprehensive and can fully ensure that there will be no missed unqualified working positions, ensuring a comprehensive road detection. If there are unqualified positions, they can be recompacted in time, thereby ensuring the compaction quality of the road. The compaction index threshold CCV TIt can be corrected by the dynamic deflection value obtained through intermittent detection by the deflection detection module 9, so as to avoid incorrect threshold setting caused by changes in road conditions. The compaction index threshold obtained by this method is dynamic data with phased correction, and the data is updated in a timely manner, improving the accuracy of determination. During the actual detection process, we need the 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, and this data detection does not require an operation interval or destructive testing of the road, and the detection is convenient. The information of the current operation is obtained by detecting through the operation positioning module 1, and the vibration acceleration data is obtained by detecting 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, it can also include other data, such as speed, acceleration, equipment attitude, travel distance, etc., which will not be elaborated here. The vibration acceleration data and the dynamic deflection value l d are fitted to construct the relationship between the dynamic deflection value and the compaction index value CCV corresponding to the detection point numbered d d as , 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, and CCV d 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 coefficient value and k2 is the calculated constant value. K1 is the coefficient eigenvalue and K2 is the constant eigenvalue, and these two values can be obtained through model fitting. The magnitude of these values is not only related to factors such as the filler type and filler height of the subgrade, but also related to soil parameters (water content, gradation, etc.), compaction process parameters (speed of the roller, excitation force, number of passes, etc.), and number of compaction passes (different numbers of compaction passes may affect the values of K1 and K2). Generally, we do not calculate these two values based on the properties of the subgrade, because there are too many variables and it is easy to cause inaccurate data calculation, but it does not rule out the possibility of determining them based on the properties of the subgrade. The determination method is to calculate multiple sets of calculated coefficient values k1 and calculated constant values k2 through the pairwise combination of the dynamic deflection values l d of the detection positions of each deflection detection module 9 and the compaction index value CCV d corresponding to the detection point numbered d, and then we perform optimization processing to obtain the coefficient eigenvalue K1 and the constant eigenvalue K2. Refer to Figure 3 , and the optimization method can include mathematical statistics, establishment of correlation relationships, parameter optimization, and verification and statistics. Mathematical statistics is to calculate the compaction index value CCV d corresponding to the detection point numbered d and the dynamic deflection value l dSubstitute into the formula relationship , so that multiple sets of coefficient calculation values k1 and constant calculation values k2 can be obtained. The correlation relationship 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 compactness value predicted by the model and the actual measured value is minimized. Verification and adjustment: Verify the model through actual engineering data, and adjust K1 and K2 according to the verification results to adapt to different types of soil and compaction requirements. The specific numerical calculation is too cumbersome and will not be exemplified here. Through the above process, k1 and k2 are determined and used in the compaction quality evaluation formula to achieve accurate evaluation of compaction quality. This method combines experimental data and mathematical statistics techniques, improving the accuracy and efficiency of compaction quality control. The coefficient eigenvalue K1 and the constant eigenvalue K2 can also be obtained by direct calculation, and the obtaining methods include mathematical statistics and numerical calculation. Mathematical statistics is to calculate the compaction index value CCV corresponding to the detection point numbered d from the vibration acceleration data of the detection positions of the pairwise deflection detection modules 9 d and the dynamic deflection value l d Substitute into the relationship , so that multiple sets of coefficient calculation values and constant calculation values can be obtained, where d is the number of the detection position of the deflection detection module 9, is the coefficient calculation value 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, is the constant calculation value 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 is the total number of current detections of 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, etc. 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 start counting again, which will not be elaborated here. Then the coefficient eigenvalue , the constant eigenvalue , where ɑ is the base number of subgrade deviation, and its value is generally 1 - 10, which can be assigned by experience. The differences in the influencing coefficient eigenvalue K1 and the constant eigenvalue K2 factors can also be artificially divided into 10 levels. When they are exactly the same, the base number of subgrade deviation ɑ is 1; when the difference is the largest, the base number of subgrade deviation ɑ is 10. Then a numerical classification assignment table is constructed. We can look up the numerical classification assignment table through the current various factors to obtain the current base number of subgrade deviation. For the same road section, its numerical change is generally not very large. The specific content of the numerical classification assignment table is not the protected subject of this application and will not be elaborated here. is the d-th power of the base number of subgrade deviation. ε is the deviation adjustment factor, and its value is generally 0, 1 - 10, and generally takes the value of 1, which will not be elaborated here. is the coefficient calculation value obtained by the combined calculation of the detection position of the deflection detection module 9 numbered d and the detection position of the deflection detection module 9 numbered d - 1. is the constant calculation value obtained by the combined calculation of the detection position of the deflection detection module 9 numbered d and the detection position of the deflection detection module 9 numbered d - 1, where d = 2, 3…, D. By calculating the coefficient eigenvalue and the constant eigenvalue in this way, the differences in road section materials, construction, and environment can be considered. It can be seen from the formula that the earlier the detection position number, the smaller the proportion it occupies, and the less impact it has on the determination of the current point. In such a case, we can increase the proportion of the calculation values of the position points adjacent to the current position point, so as to reduce the deviation caused by factors such as time and distance. This method of calculation is more accurate and can better and more accurately evaluate the road structure layer. The relational expression the compaction index value CCV corresponding to the detection point numbered d d does not directly use 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 of the detection position of the deflection detection module 9 numbered d, I is the total number of wave amplitudes, and i = 1, 2, …, I. β is the amplitude coefficient, and its value is generally 200. Refer to Figure 6 , generally, the number of I is 3, that is , of course, other calculation methods are not excluded and will not be elaborated here. The compaction index threshold CCV T The determination method can include the compaction index threshold , where K1 is the coefficient eigenvalue, K2 is the constant eigenvalue, which are the values obtained by the above calculation, and l Tis the dynamic deflection design value, and its specific value can be obtained by the staff through speculation based on equipment and subgrade data. Of course, this situation is highly subjective and requires extremely rich experience of the staff. The dynamic deflection design value can also be obtained through calculation. , —the design value of the subgrade resilient modulus, —the load of the falling weight deflectometer bearing plate (Mpa), —the radius of the falling weight bearing plate (mm). These values can be obtained according to the road structure layer design standard and equipment parameters, and will not be elaborated here. is the design coefficient, and its value is 150 - 200, with 176 being appropriate. The compaction index threshold obtained by this method can well distinguish and judge the test data, is convenient for calculation, and updates and optimizes the coefficient characteristic value and constant characteristic value periodically to ensure the accuracy of the judgment threshold. The compaction index value CCV and the compaction index threshold CCV T are judged by the method that can directly compare the current compaction index value CCV n with the compaction index threshold CCV T . Here, n is the number of roller passes at the current operation position, which can be obtained from historical data and will not be elaborated here. The current compaction index value CCV n is the vibration acceleration data calculated from the acceleration signal collected by the acceleration signal acquisition module 5 at the previous operation position. If the current compaction index value CCV n is greater than δ times of the compaction index threshold CCV T , it is judged as qualified. δ is the judgment ratio coefficient, and its value can be 0.7 - 1, which specifically depends on the road quality requirements and generally takes the value of 0.9 and will not be elaborated here. Refer to Figure 5 and Figure 7 . Of course, the judgment method of the compaction index value CCV and the compaction index threshold CCV T can also include: judging whether the optimized compaction reduction value C is less than a preset standard reduction ratio C 标 , and whether the current compaction index value CCV n is greater than δ times of the compaction index threshold CCV T . If both are true, it is judged as qualified; if there is one false, it is judged as unqualified. The optimized compaction reduction value can be , where n is the number of compaction passes. Generally, the number of compaction passes of the road structure layer is greater than 3, and for every 100m evaluation length of the roller tire, 10m is the calculation length, so as to facilitate timely additional compaction. Of course, other numerical settings are not excluded and will not be elaborated 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 empirical values, with 20% being the optimal. By making judgments through this method, not only can the compaction changes at the same working position be used for judgment, but also the quality can be controlled through thresholds. There are various forms of judgment, so as to control from the necessity of optimizing the quality of the road structure layer and various aspects of road quality, thereby improving the evaluation effect of the road structure layer quality.

[0059] Embodiment 2

[0060] Reference 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 includes the following steps:

[0061] S1. Obtain the vibration acceleration data feedback from the road structure layer at the current working position.

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

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

[0064] S4. According to the vibration acceleration data feedback from the road structure layer at the current working position and the dynamic deflection value l d , fit and construct a relational expression, and calculate the coefficient eigenvalue K1 and the constant eigenvalue K2.

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

[0066] S6. Determine the relationship between the compaction index value CCV obtained by detecting and calculating at the current working position and the compaction index threshold CCV T . Determine whether the compaction quality of the current compaction structure layer is qualified. If it is qualified, no marking is performed; if it is unqualified, the current working position is marked.

[0067] It should be understood that various forms of the above-mentioned processes can be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved. No limitations are imposed herein.

[0068] The above specific embodiments do not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present disclosure should be included within 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 based on the coefficient eigenvalue K1 and the constant eigenvalue K2 T ; Calculate the compaction index value CCV and the compaction index threshold CCV T and determine whether the compaction quality of the current compacted structure layer is qualified. If qualified, no mark is made; if unqualified, the current operation position is marked; Coefficient eigenvalue Constant eigenvalue Where ɑ is the base of roadbed deviation; α d is the dth power of the base of the roadbed deviation; ε is the deviation adjustment factor; 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.

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 CCV d =k1l d +k2, 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.

9. The intelligent compaction control integrated system according to claim 1, characterized in that: Compaction indicator threshold CCV T =K1l T +K2, 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; Coefficient eigenvalue Constant eigenvalue Where ɑ is the base of roadbed deviation; α d is the dth power of the base of the roadbed deviation; ε is the deviation adjustment factor; 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; 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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