Real-time feedback control system and method for asphalt pavement compaction degree based on multi-source data

Abstract

The application discloses a real-time feedback control system and method for asphalt pavement compactness based on multi-source data, and relates to the technical field of road engineering construction control. The real-time feedback control method for asphalt pavement compactness based on multi-source data acquires the compactness state data of a plurality of pavement measurement points of the asphalt pavement in real time, including pavement vibration, pavement temperature and pavement structure response data, and pre-processes and analyzes the compactness state index set of the plurality of pavement measurement points, comprehensively analyzes the compactness index of the asphalt pavement, and matches and judges the preset plurality of compactness intervals, and each compactness interval corresponds to a control strategy; when the compactness index falls into a preset compactness interval, the corresponding feedback control strategy is executed. The application acquires the compactness state data of a plurality of pavement measurement points in real time, and the data sources include three types of content, i.e. vibration response, temperature response and structure response, so as to help comprehensively reflect the instant stress state, thermal state and internal structure reaction of the asphalt pavement.

Description

Technical Field

[0001] This invention relates to the field of road engineering construction control technology, specifically to a real-time feedback control system and method for asphalt pavement compaction based on multi-source data. Background Technology

[0002] The construction quality of asphalt pavement directly affects the service life, structural safety, and driving comfort of roads. Compaction, as a key process in asphalt pavement construction, is always a crucial aspect of road engineering construction management. After paving, the asphalt mixture must be compacted within a suitable temperature range using appropriate rolling techniques to achieve the predetermined density requirements, thereby ensuring the strength, rigidity, and durability of the pavement.

[0003] In traditional construction processes, compaction quality is mainly adjusted by control parameters such as the number of rolling passes, compaction temperature, and rolling speed. Construction workers usually judge whether the compaction requirements have been met based on experience, or use simple measuring tools to sample and test the surface density. This method has a certain degree of lag and randomness, and it is difficult to accurately reflect the true compaction state of the road surface in different areas and at different depths.

[0004] The limitations of existing technologies include at least the following problems: during the compaction process of asphalt pavement, its compaction state is affected by a variety of factors such as pavement temperature, vibration characteristics and structural response, and there are obvious differences between different regions. However, existing compaction control technologies usually do not establish a unified way of expressing the compaction state, lack the ability to systematically evaluate different pavement states, and do not achieve direct correlation between evaluation results and control strategies.

[0005] In practical applications, existing methods often only set construction parameters in one direction, lacking the logic of judging intervals based on the actual compaction state. The control strategy is difficult to adjust automatically with changes in road surface conditions, which can easily lead to insufficient or excessive compaction. At the same time, due to the lack of a unified judgment standard and strategy matching method, the compaction control process is difficult to achieve precision and real-time performance, affecting construction efficiency and quality stability. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a real-time feedback control system and method for asphalt pavement compaction based on multi-source data, which solves the problem that existing technologies lack a mechanism for graded identification and corresponding adjustment of compaction states.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a real-time feedback control method for asphalt pavement compaction based on multi-source data, comprising the following steps: acquiring compaction state data of several pavement measurement points in real time, including pavement vibration, pavement temperature, and pavement structure response data, and preprocessing them; analyzing the compaction state index set of several pavement measurement points based on the preprocessed compaction state data, including pavement vibration, pavement temperature, and pavement structure response indices; analyzing the compaction degree index of the asphalt pavement based on the compaction state index set of several pavement measurement points, and matching it with several preset compaction degree intervals, with each compaction degree interval corresponding to a control strategy; and executing the corresponding feedback control strategy when the compaction degree index falls into a preset compaction degree interval.

[0008] Further, the specific steps for analyzing the compaction index of asphalt pavement are as follows: read the pavement vibration, pavement temperature, and pavement structure response indices at several pavement measurement points, and perform comprehensive analysis to obtain the set of average compaction state indices of asphalt pavement, including the average response indices of pavement vibration, pavement temperature, and pavement structure; perform comprehensive analysis on the set of average compaction state indices of asphalt pavement to obtain the corresponding compaction index.

[0009] Furthermore, the specific formula for calculating the compaction index of asphalt pavement is as follows: Where YsD, LzP, LwP, and LjP are the compaction index, average vibration response index, average temperature response index, and average structural response index of asphalt pavement, respectively; e is a natural constant; and λ1, λ2, and λ3 are the pavement vibration response coefficient, pavement temperature response coefficient, and pavement structural response coefficient stored in the database, respectively, with λ1+λ2+λ3=1.

[0010] Furthermore, the road surface vibration response data includes the vertical rebound acceleration of the ground surface, the horizontal response acceleration of the ground surface, and the response delay time of the ground surface.

[0011] Furthermore, the specific steps for analyzing the road vibration response index of each road surface measurement point of the asphalt pavement are as follows: Obtain reference data of the road vibration response of the asphalt pavement, including reference values ​​of vertical rebound acceleration, horizontal response acceleration, and response delay time; combine the road vibration response data of each road surface measurement point with the reference data of the road vibration response of the asphalt pavement to conduct a comprehensive analysis, and obtain the road vibration response index of each road surface measurement point of the asphalt pavement.

[0012] Furthermore, the road surface temperature response data includes the asphalt surface temperature value and the asphalt sublayer temperature value.

[0013] Further, the specific steps for analyzing the pavement temperature response index at each pavement measurement point of the asphalt pavement are as follows: Obtain the pavement temperature response reference data of the asphalt pavement, including the target value of the asphalt surface temperature, the asphalt surface temperature response tolerance value, the target value of the asphalt sub-layer temperature, the asphalt sub-layer temperature response tolerance value, and the temperature difference limit between the upper and lower asphalt layers; Combine the pavement temperature response data of each pavement measurement point of the asphalt pavement with the pavement temperature response reference data of the asphalt pavement for comprehensive analysis to obtain the pavement temperature response index of each pavement measurement point of the asphalt pavement.

[0014] Furthermore, the pavement structure response data includes wave incident amplitude, wave reflection amplitude, and echo delay time.

[0015] Furthermore, the specific steps for analyzing the pavement structure response index of each pavement measurement point of the asphalt pavement are as follows: obtain the echo delay time limit of the asphalt pavement; combine the pavement structure response data of each pavement measurement point of the asphalt pavement with the echo delay time limit of the asphalt pavement for comprehensive analysis to obtain the pavement structure response index of each pavement measurement point of the asphalt pavement.

[0016] The real-time feedback control system for asphalt pavement compaction based on multi-source data includes: a real-time data acquisition unit, used to acquire compaction state data of several pavement measurement points in real time, including pavement vibration, pavement temperature, and pavement structure response data, and perform preprocessing; a data response analysis unit, used to analyze the compaction state index set of several pavement measurement points based on the preprocessed compaction state data of several pavement measurement points, including pavement vibration, pavement temperature, and pavement structure response indices; a compaction state analysis unit, used to analyze the compaction index of the asphalt pavement based on the compaction state index set of several pavement measurement points; and a matching control unit, used to match and judge the compaction index of the asphalt pavement with several preset compaction intervals, and each compaction interval corresponds to a control strategy. When the compaction index falls into a preset compaction interval, the corresponding feedback control strategy is executed.

[0017] The present invention has the following beneficial effects:

[0018] (1) The real-time feedback control method for asphalt pavement compaction based on multi-source data can collect compaction state data from multiple pavement measurement points in real time. The data sources include three categories: vibration response, temperature response, and structural response. This helps to comprehensively reflect the instantaneous stress state, thermal state, and internal structural response of the asphalt pavement. Compared with the traditional method that relies solely on control parameters such as the number of passes and speed to judge compaction quality, this method can provide more detailed and accurate compaction state information. By clarifying the data collection content and performing preprocessing, this method can uniformly manage and standardize different types of data, reducing the risk of misjudgment caused by a single indicator. Especially in large-area continuous construction scenarios, it can support dynamic tracking of compaction effect, which is conducive to timely detection and location of local compaction deviations.

[0019] (2) The real-time feedback control method for asphalt pavement compaction based on multi-source data constructs pavement vibration, pavement temperature and pavement structure response indices respectively, and calculates the overall average state index based on data from multiple measurement points, and then further forms the final compaction index. Unlike the previous method that relied on manual experience or single-point judgment, this modeling method based on the index system can transform complex and multi-source physical response information into clear and comparable quantitative results, improving the clarity of the judgment of compaction degree. On this basis, the method sets several compaction degree intervals, so that the judgment process is no longer a fuzzy estimate, but a standardized classification based on numerical intervals. The compaction state can be clearly divided into several levels, providing a clear judgment basis for subsequent control strategies under different degrees, and also facilitating recording, tracking and verification, reducing the uncertainty caused by human judgment.

[0020] (3) The real-time feedback control method for asphalt pavement compaction based on multi-source data, after the compaction index is determined, matches it with the preset compaction interval and executes the feedback control strategy corresponding to the interval. This method makes compaction control no longer dependent on manual intervention or fixed process, but can automatically adjust according to the current state. The control strategy matched by each interval is targeted and can automatically trigger different levels of response control according to different levels of compaction state, such as adjusting rolling parameters or performing local compaction. This mechanism not only enhances the dynamic response capability of the compaction process, but also makes the control process more flexible and can adapt to the changing requirements of different materials, climate and construction rhythm. Especially in the case of multiple simultaneous operations, the state of each measurement point can be independently evaluated and the strategy can be judged, which improves the overall control accuracy and reduces the quality risk caused by control lag.

[0021] (4) The real-time feedback control system for asphalt pavement compaction based on multi-source data establishes a complete structural chain for compaction feedback control by clearly dividing four functional units: data acquisition, index analysis, compaction judgment, and control execution. Each unit is functionally independent but interconnected in terms of process, which can effectively support closed-loop control of the entire process from data perception to state decision-making and strategy execution. The real-time data acquisition unit faces the pavement site and is responsible for multi-point synchronous collection and preliminary data processing to ensure the integrity and timeliness of the data. The data response analysis unit extracts key indicators based on the acquisition results. The compaction state analysis unit undertakes the tasks of index fusion and compaction calculation, and has good logical continuity. The matching control unit matches the control strategy according to the compaction results and has the ability to output control commands. Through the above structural division, the system can realize layered deployment of hardware and software, which is convenient for flexible integration in different construction platforms and has good scalability and engineering adaptability. At the same time, the modular structure is conducive to system maintenance, debugging and functional upgrades, and can support the digital, visual and intelligent operation of the compaction process.

[0022] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0023] Figure 1 This is a flowchart of the real-time feedback control method for asphalt pavement compaction based on multi-source data according to the present invention.

[0024] Figure 2 This is a flowchart illustrating the specific steps involved in analyzing the pavement vibration response index at each pavement measurement point in the real-time feedback control method for asphalt pavement compaction based on multi-source data, as described in this invention.

[0025] Figure 3 This is a block diagram of the real-time feedback control system for asphalt pavement compaction based on multi-source data according to the present invention. Detailed Implementation

[0026] Please see Figure 1This invention provides a technical solution: a real-time feedback control method for asphalt pavement compaction based on multi-source data, comprising the following steps: real-time acquisition of compaction state data from several pavement measurement points, including pavement vibration, pavement temperature, and pavement structure response data, and preprocessing (including outlier detection processing of the raw compaction state data of each measurement point, specifically: performing multi-point statistical analysis on surface vertical rebound acceleration, surface horizontal response acceleration, surface response delay time, asphalt surface temperature, asphalt sublayer temperature, wave incident amplitude, wave reflection amplitude, and echo delay time, identifying and removing outliers using the mean ± 3 standard deviations; and using linear interpolation or sliding interpolation for time series data (such as acceleration, temperature, etc.). The mean method is used for time-based completion (specifically, the average of two consecutive valid values ​​is used to replace outliers); based on the compaction state data of several preprocessed pavement measurement points, the compaction state index set of several pavement measurement points is analyzed, including pavement vibration, pavement temperature, and pavement structure response index; based on the compaction state index set of several pavement measurement points, the compaction degree index of the asphalt pavement is analyzed and matched with several preset compaction degree intervals, and each compaction degree interval corresponds to a control strategy; when the compaction degree index falls into a preset compaction degree interval, the corresponding feedback control strategy is executed to adjust the current compaction process. Specifically, a hierarchical collaborative control architecture is adopted, dividing the control logic into two levels: the main strategy control layer and the compensation strategy control layer.

[0027] The main strategy control layer determines the overall compaction state based on the matching relationship between the current compaction index and the preset compaction range, and triggers the corresponding level of compaction control strategy.

[0028] The compensation strategy control layer is used to identify local abnormal responses and make fine-tuning interventions based on the state indices (road vibration, road temperature, and road structure response index) of each measurement point.

[0029] The control scheme includes, but is not limited to, the following numerical control examples:

[0030] When the compaction index is ≤0.4 (extremely under-compacted), the main strategy control layer will trigger a strong feedback compaction mode, the control content of which includes:

[0031] The vibration frequency of the road roller was adjusted to 65Hz (30% higher than the conventional 50Hz);

[0032] Reduce the compaction speed to no more than 1.2 km / h;

[0033] Set the target number of compaction passes to ≥4 passes and activate the forced re-compaction area marker;

[0034] The system records the status of the area in real time and reports it to the cloud, marking it as a "deep pressure compensation area".

[0035] When the compaction index ∈ (0.4, 0.6] (slightly under-compacted), the main strategy control layer executes a medium-intensity adjustment strategy, and the adjustment parameters include:

[0036] The excitation frequency is maintained within a fluctuation range of 50–55 Hz;

[0037] The travel speed is set to 1.8–2.2 km / h;

[0038] The system automatically prompts the driver that the area needs to be compacted 1-2 more times.

[0039] Simultaneously record the road surface vibration response index. If it remains below 0.6 for an extended period, the compensation strategy will switch to a local excitation mode.

[0040] When the compaction index ∈ (0.6, 0.85] (appropriate compaction range), the main strategy control layer does not make any adjustments and keeps the current compaction parameters unchanged;

[0041] The compensation strategy layer continues to monitor the road surface temperature and road structure response index at each measuring point. If any index is below 0.5, temporary low-speed compaction compensation is triggered (for example, temporarily reducing the speed to 1.5 km / h and compacting the area once more).

[0042] When the compaction index > 0.85 (possibly due to overpressure or heat loss), the control system executes a reduced feedback mode.

[0043] The excitation frequency automatically drops to ≤45Hz;

[0044] Increase the travel speed to 2.8–3.2 km / h to avoid repeated compaction;

[0045] If the road surface temperature response index is higher than 0.9 and the lower layer temperature exceeds 140℃, a "heat damage risk" warning will be issued, and compaction will be suspended.

[0046] Typical examples of compensation strategies include, but are not limited to:

[0047] When the vibration delay time at a certain road surface measurement point is >0.25s (significant response hysteresis), the local excitation power is increased by 20%, and the speed is forcibly reduced by 30% to perform one additional compaction.

[0048] If the temperature difference between the upper and lower layers is ≥25℃ and the road surface temperature response index is ≤0.4, the compaction operation will be suspended immediately and the system will automatically delay for 2 minutes to wait for the thermal balance to recover.

[0049] If the wave reflection amplitude remains below 40% of the incident amplitude, the system marks "abnormal structural energy absorption" and indicates that the "weak support risk" area needs to be manually reviewed.

[0050] Specifically, the steps for analyzing the compaction index of asphalt pavement are as follows: Read the pavement vibration, pavement temperature, and pavement structure response indices from several pavement measurement points, and perform comprehensive analysis on each (i.e., perform mean analysis on the pavement vibration, pavement temperature, and pavement structure response indices for each pavement measurement point) to obtain the set of average compaction state indices for the asphalt pavement, including the average response indices of pavement vibration, pavement temperature, and pavement structure; perform comprehensive analysis on the set of average compaction state indices for the asphalt pavement to obtain the corresponding compaction index.

[0051] The specific formula for calculating the compaction index of asphalt pavement is as follows: Wherein, YsD, LzP, LwP, and LjP are the compaction index, average vibration response index, average temperature response index, and average structural response index of the asphalt pavement, respectively; e is a natural constant, which is taken as 2.71 in this embodiment; λ1, λ2, and λ3 are the pavement vibration response coefficient, pavement temperature response coefficient, and pavement structural response coefficient stored in the database, respectively; and λ1+λ2+λ3=1.

[0052] It should be explained that the compaction index is established based on the following approach:

[0053] In current construction practices, the assessment of compaction quality typically relies on multiple physical response parameters (such as vibration, temperature, and structural wave reflection), but these parameters have the following problems:

[0054] The physical responses have different units and dimensions, making direct addition and comparison impossible;

[0055] The influence of response parameters on compaction effect exhibits a non-linear, increasing relationship; for example, when the structural response signal is weak, it may still be in a state of severe undercompression.

[0056] The lack of a unified standard for judging the compaction state makes it difficult to trigger subsequent feedback control and divide the compaction zone.

[0057] To overcome the above problems, this invention proposes to integrate three different types of response indices (LzP: vibration response, LwP: temperature response, LJP: structural response) to establish a unified compaction index YsD, and design it as a Sigmoid function structure.

[0058] The logical basis for establishing this structure is as follows:

[0059] The three physical response dimensions reflect the mechanical contact state of compaction, the adequacy of thermal action, and the degree of structural density, respectively. All three must be considered together to fully reflect the current compaction effect.

[0060] The actual response of the compaction effect is not a linear superposition relationship, but rather exhibits a "bottleneck amplification" effect. For example, when the structural response is low, even if the temperature and vibration are good, compaction may still fail. Therefore, an exponential structure is used to enhance the influence of key dimensions and ensure that the model has nonlinear amplification sensitivity.

[0061] The output value of the Sigmoid function is always between (0,1), which is naturally suitable for constructing an "interval compaction state division model". For example, the compaction intervals set in this invention (such as <0.4 for under-compaction, 0.6-0.85 for moderate-compaction, etc.) can be directly defined based on the YsD value, which is conducive to the automation and standardization of subsequent feedback control decisions.

[0062] The previous steps have standardized and normalized the three response indices LzP, LwP, and LJP. Therefore, a weighted summation term can be constructed as the Sigmoid input to achieve a unified compaction evaluation mapping after dimensional fusion.

[0063] The Sigmoid function structure has good mathematical continuity and numerical stability, avoiding risks such as sudden output changes and jumps, making it suitable for deployment in embedded real-time systems or construction platform terminals.

[0064] The steps for determining λ1, λ2, and λ3 are as follows:

[0065] We initially assume that the initial values ​​of λ1, λ2, and λ3 are 1 / 3, that is:

[0066] λ1 = 1 / 3: Vibration response coefficient;

[0067] λ² = 1 / 3: Temperature response coefficient;

[0068] λ3 = 1 / 3: Structural response coefficient;

[0069] When the initial setting is 1 / 3, it means that the impact of each response on the compaction is equal at the beginning. This setting provides a balanced starting point for subsequent adjustments and ensures fair treatment of each physical response.

[0070] This assumption is simple and meets the initial requirements for a comprehensive assessment of compaction effectiveness, facilitating subsequent fine-tuning and optimization.

[0071] In practical engineering, the effects of vibration, temperature, and structure are different, so λ1, λ2, and λ3 need to be adjusted according to the impact of each physical response on the compaction effect.

[0072] Adjustment of λ1 (road vibration response coefficient):

[0073] Physical background: Vibration usually has a significant impact on compaction, especially in environments with strong vibration, where vibration can cause a large compaction effect on the road surface.

[0074] Adjustment method: If field data shows that vibration load contributes significantly to compaction, λ1 can be increased, for example, by setting λ1 = 0.4, to enhance the contribution of vibration to compaction.

[0075] Example: If the road surface vibration response is strong during construction, λ1 should be increased, for example, by setting it to 0.4, to increase the impact of vibration on YsD.

[0076] λ2 (Road surface temperature response coefficient) adjustment:

[0077] Physical background: Temperature has a direct impact on the compaction of asphalt pavement, especially in high-temperature and large-temperature-difference environments, where temperature fluctuations can significantly affect the compaction effect.

[0078] Adjustment method: If the on-site temperature fluctuates greatly and the temperature response contributes significantly to the compaction effect, λ2 can be appropriately increased, for example, by setting λ2 = 0.5, to ensure that the influence of temperature on YsD is fully reflected.

[0079] Example: In environments with drastic temperature changes, the effect of temperature on compaction is more significant. λ2 should be adjusted to 0.5 to enhance the influence of temperature response.

[0080] Adjustment of λ3 (road structure response coefficient):

[0081] Physical background: The density of the road structure has a direct relationship with the compaction effect. Especially when the structure is poorly dense, even if the vibration and temperature response is good, compaction may still fail.

[0082] Adjustment method: When the pavement structure has poor compaction, λ3 needs to be increased, for example, by setting λ3 = 0.6, to emphasize the contribution of structural response to YsD.

[0083] Example: If the structure has low density and good temperature and vibration response, but compaction problems still exist, λ3 should be increased, for example, by setting it to 0.6, to enhance the structure's influence on the compaction effect.

[0084] Coefficients and Constraints: The adjusted coefficients, based on actual conditions, must still satisfy the constraint λ1+λ2+λ3=1. This constraint ensures a reasonable balance among the three coefficients, preventing any one response index from having an excessively dominant effect on YsD.

[0085] During construction, coefficients λ1, λ2, and λ3 can be fine-tuned based on real-time monitoring data such as vibration, temperature, and structural response. For example, if the impact of a certain response on the compaction effect exceeds expectations, the corresponding coefficient can be adjusted to reflect the actual construction effect.

[0086] Example values ​​for the coefficient:

[0087] Example 1 (Vibration has a greater impact, while temperature has a smaller impact):

[0088] λ1 = 0.4, λ2 = 0.3, λ3 = 0.3 (strong vibration response, relatively balanced temperature and structural response).

[0089] Example 2 (significant temperature variation, substantial impact on structure):

[0090] λ1 = 0.2, λ2 = 0.5, λ3 = 0.3 (temperature fluctuations are large, and the structural influence is strong).

[0091] Example 3 (Structural response has a significant impact):

[0092] λ1=0.2, λ2=0.2, λ3=0.6 (Structural compactness has a significant impact on compaction degree).

[0093] In this implementation plan, by establishing a set of compaction state indices based on mean analysis and introducing an exponential function structure to fuse the three-dimensional indices, the accuracy and rationality of compaction state assessment can be effectively improved. Compared with traditional linear weighting or empirical judgment methods, this method not only makes full use of distributed data from different measurement points to reflect the overall compaction trend, but also performs nonlinear amplification processing on the fluctuations of various response indices through exponential functions, so that changes in key indicators can have a more sensitive impact on the final compaction degree index. At the same time, by introducing response coefficients stored in the database as weight adjustment parameters, the calculation logic can be flexibly adjusted according to different pavement structures, construction environments, or material properties, enhancing the adaptability and scalability of the model. This structure has the advantages of being quantifiable and adjustable, and also ensures the stability of compaction degree calculation and working condition matching ability, which helps to achieve more engineering-value-based compaction quality judgment results.

[0094] Specifically, the road surface vibration response data includes the vertical rebound acceleration of the ground surface, the horizontal response acceleration of the ground surface, and the response delay time of the ground surface.

[0095] To obtain the actual vibration response information of the asphalt pavement during compaction, the road roller is equipped with several acceleration sensors for real-time data acquisition. The device for measuring the vertical rebound acceleration of the ground surface includes a vertical acceleration sensor, which is mounted on a rigid fixed frame at the front of the compaction wheel. This frame is a non-rotating structure, and the sensor is close to the compaction wheel body but does not contact the rolling surface. The device for measuring the horizontal response acceleration of the ground surface includes a horizontal acceleration sensor, which is mounted on the non-rotating connection between the road roller body and the compaction wheel axle or on the side wall of the vehicle body support, ensuring that it remains stationary with the entire vehicle body.

[0096] In this invention, "under the wheel" does not refer to the sensor being directly mounted on the tire's rolling surface. Rather, it means that the sensor is spatially aligned with the road surface area along the wheel's path. Specifically, before the roller passes the measuring point or during the compaction period, the sensor's fixed position is directly facing this area, enabling the acquisition of vibration signals directly beneath the compaction path. Because the sensor is fixed to a non-rotating structure, it does not rotate with the wheel during operation, ensuring measurement stability and sampling continuity.

[0097] The sensor has a sampling frequency of no less than 200Hz, enabling it to record minute vibration signal changes. For identifying the surface response delay time, this invention establishes the following judgment criteria:

[0098] Let A(t) be the continuous sampling sequence before compaction, and calculate its mean μ0 and standard deviation σ0;

[0099] Set the response judgment threshold T = μ0 + k·σ0, where the recommended value for k is 2 to 3;

[0100] The time point t1 when the sampling curve first satisfies A(t)≥T is considered the moment when the road surface first produces a "significant response";

[0101] If the excitation start time is denoted as t0, then the road surface response delay time Td = t1 - t0.

[0102] The surface response delay time value refers to the time interval between the moment the excitation signal of the road roller is issued and the moment when the asphalt pavement first shows a significant acceleration response. It can be obtained by measuring the difference between the timestamp of the exciter and the sensor.

[0103] like Figure 2 and 3 As shown, the specific steps for analyzing the road vibration response index of each road surface measurement point of the asphalt pavement are as follows: Obtain the road vibration response reference data of the asphalt pavement, including the reference value of the vertical rebound acceleration of the ground surface, the reference value of the horizontal response acceleration of the ground surface, and the reference value of the response delay time of the ground surface; Combine the road vibration response data of each road surface measurement point of the asphalt pavement with the road vibration response reference data of the asphalt pavement to obtain the road vibration response index of each road surface measurement point of the asphalt pavement.

[0104] The specific formula for calculating the pavement vibration response index at a certain pavement measurement point is as follows: Where LzX, CfJ, SpJ, and XyY are the road vibration response index, vertical rebound acceleration, horizontal response acceleration, and response delay time of a certain road measurement point on the asphalt pavement, respectively; CfC, SpC, and XyC are the reference values ​​of vertical rebound acceleration, horizontal response acceleration, and response delay time of the asphalt pavement, respectively; α1, α2, and α3 are the weighting coefficients of vertical rebound acceleration, horizontal response acceleration, and response delay time stored in the database, respectively; and α1 + α2 + α3 = 1.

[0105] It needs to be explained that the logic for establishing the road surface vibration response index is as follows:

[0106] The vertical rebound acceleration, horizontal response acceleration, and response delay time of the ground surface represent the vibration response intensity and hysteresis behavior of the road surface in different directions. However, their numerical distributions are inconsistent and need to be normalized using their respective reference values ​​(CfC, SpC, XyC) to eliminate dimensional differences.

[0107] Since each response item has a different impact on compaction quality, coefficients α1, α2, and α3 are introduced as weighting parameters, and their values ​​are determined based on the following:

[0108] The proportions of the three results in the formula are analyzed separately, and the results of the proportion analysis are the corresponding coefficients.

[0109] The exponential structure of the road vibration response index:

[0110] The various exponential calculations are used to enhance the weight changes of each parameter under abnormal operating conditions and strengthen the differences in nonlinear responses;

[0111] After multiplying multiple exponents, nonlinear compression is performed by taking the square root of the product to avoid the product value approaching 0. This exponential structure is used to reverse the correspondence between the degree of compaction and the exponential value: that is, the more sufficient the response, the larger the product value and the smaller LzX, indicating that the road surface condition is good; if the response is abnormal, the product value is small and LzX is large, indicating that there is a vibration problem.

[0112] The reference value of vertical rebound acceleration of the ground surface refers to the upper limit of vertical rebound acceleration of the ground surface under ideal compaction conditions. It can be obtained by statistical analysis of the maximum value in test section measurements, construction experience, or historical data.

[0113] The reference value of surface horizontal response acceleration refers to the reference value of surface horizontal response acceleration under standard compaction conditions. It is used for normalization processing and can be obtained by taking the maximum or average value from historical measurement point data.

[0114] The reference value for surface response delay time refers to the maximum allowable range or standard value of surface response delay time. It is used to determine whether the response delay is abnormal and can be obtained from construction technical specifications or field data.

[0115] In this implementation plan, by clearly decomposing and quantifying the vibration response-related parameters, the mechanical response characteristics during the compaction process can be expressed in a specific and structured way. By introducing three core indicators—vertical rebound acceleration, horizontal response acceleration, and response delay time—the system can more intuitively reflect the real-time interaction between the compaction equipment and the asphalt pavement. At the same time, normalization analysis combined with reference values ​​helps to eliminate environmental interference during construction, improve the stability and comparability of compaction state judgment, and the weights of each indicator can be flexibly adjusted according to on-site needs or historical experience, enhancing the model's adaptability to different construction scenarios.

[0116] Specifically, the road surface temperature response data includes the asphalt surface temperature value and the asphalt sublayer temperature value.

[0117] Among them, the asphalt surface temperature value refers to the instantaneous temperature of the asphalt pavement surface (usually 0-3cm deep) at the time of compaction, which can be obtained by measuring the infrared temperature sensor installed at the front of the roller or under the wheel.

[0118] The temperature of the lower layer of asphalt refers to the instantaneous temperature of the lower layer (about 3-5 cm deep) in the asphalt pavement structure, which can be measured by a pin-type thermocouple or a point-measured infrared temperature sensor.

[0119] The specific steps for analyzing the pavement temperature response index at each pavement measurement point of the asphalt pavement are as follows: Obtain reference data on the pavement temperature response of the asphalt pavement, including the target value of the asphalt surface temperature, the tolerance value of the asphalt surface temperature response, the target value of the asphalt sub-layer temperature, the tolerance value of the asphalt sub-layer temperature response, and the temperature difference limit between the upper and lower asphalt layers; Combine the pavement temperature response data of each pavement measurement point with the pavement temperature response reference data of the asphalt pavement for comprehensive analysis to obtain the pavement temperature response index of each pavement measurement point of the asphalt pavement.

[0120] The specific formula for calculating the pavement temperature response index at a certain pavement measurement point is as follows: Wherein, LwX, BwD, and XwD are the pavement temperature response index, asphalt surface temperature value, and asphalt sublayer temperature value at a certain pavement measurement point, respectively; BwM, BwR, XwM, XwR, and SxW are the asphalt surface temperature target value, asphalt surface temperature response tolerance value, asphalt sublayer temperature target value, asphalt sublayer temperature response tolerance value, and asphalt upper and lower layer temperature difference limit value, respectively; and e is a natural constant, which is taken as 2.71 in this embodiment.

[0121] It should be explained that there is a close relationship between pavement temperature changes and compaction effect; temperature differences directly affect the compaction degree and stability of asphalt pavement. To accurately assess the impact of temperature changes on the compaction process, this invention designs a pavement temperature response index. By comprehensively considering the temperature difference between the surface and underlying layers, the deviation of the target temperature value, and its tolerance, it can quantitatively assess the behavior of asphalt pavement under different environmental conditions.

[0122] First exponent term BwD and BwM represent the actual measured temperature and target temperature of the asphalt surface, respectively. BwR is the temperature response tolerance value, indicating the fluctuation range of the target temperature. This term calculates the temperature deviation of the asphalt surface and amplifies the impact of temperature differences through exponential calculation. The squared term design makes the influence of temperature differences on the pavement temperature response index more non-linear; that is, the greater the temperature deviation, the more significant the increase in the pavement temperature response index value. This design can more sensitively reflect the impact of temperature differences on pavement compaction, especially in environments with large temperature fluctuations.

[0123] The second exponential term Similar to the first exponential term, this term calculates the deviation of the asphalt sublayer temperature, where XwD is the actual sublayer temperature, XwM is the target sublayer temperature, and XwR is the temperature response tolerance value. This term also strengthens the influence of the deviation between the sublayer temperature and the target temperature on the pavement temperature response index through exponential calculation, so that the contribution of the sublayer temperature deviation to the pavement temperature response index is nonlinearly amplified, further improving the sensitivity of the pavement response to temperature differences.

[0124] Temperature difference limit This parameter limits the impact of excessive temperature differences between the surface and underlying layers. Large temperature differences significantly affect the compaction of asphalt pavement; therefore, a maximum temperature difference limit (SxW) is set to prevent unreasonable pavement temperature response index calculations due to excessive temperature variations. When the temperature difference between the surface and underlying layers is too large, LwX is suppressed to ensure that the temperature difference does not have an extreme impact on the calculation results.

[0125] The effect of temperature on pavement compaction is nonlinear. Therefore, an exponential calculation is used to amplify the effect of temperature differences, so that larger temperature deviations will have a greater impact on the pavement temperature response index, reflecting more stringent compaction requirements.

[0126] The exponential structure of the road surface temperature response index:

[0127] This invention focuses on temperature response deviations, which not only exhibit numerical differences but also possess nonlinear characteristics in their behavioral impact. In actual compaction processes, the relationship between asphalt temperature deviation and compaction quality is not linear. Especially when the deviation exceeds a certain tolerance range, its impact on compaction quality increases dramatically. Therefore, the pavement temperature response index first squares the temperature deviation (the difference between the actual temperature and the target temperature) and then uses it as the exponent term in the exponential function. This squaring operation ensures that the impact of the temperature deviation, whether positive or negative, on the compaction effect is treated equally, while avoiding the phenomenon of positive and negative deviations canceling each other out. Furthermore, the exponential operation strengthens the nonlinear influence of the deviation value, making slight deviations have a smaller impact, while larger deviations rapidly amplify their influence on the LwX value.

[0128] This design realizes a non-linear temperature assessment mechanism that "responds slowly when the temperature difference is small and responds violently when the temperature difference is large," which is more in line with the actual construction requirements for temperature control on compaction effect, thereby ensuring that the pavement temperature response index of this invention can accurately reflect the degree of response of temperature fluctuations to construction behavior.

[0129] The target temperature of asphalt surface layer refers to the design temperature target of surface asphalt material under optimal compaction conditions. It is usually set based on material characteristics and construction process standards, and can be preset by construction parameters.

[0130] The surface temperature response tolerance value of asphalt refers to the maximum temperature difference range that the surface temperature is allowed to deviate from the target value. It is used to construct the thermal response curve and can be obtained by setting the compaction sensitivity or by calibrating based on field experience.

[0131] The target temperature of the asphalt sublayer refers to the target temperature of the asphalt structure when it is heated and has structural support capabilities. It is usually lower than the target temperature of the surface layer and can be preset by the construction specifications.

[0132] The temperature response tolerance value of the asphalt subbase refers to the maximum range in which the temperature of the subbase is allowed to deviate from the target value. It is used to determine whether the subbase has reached the effective response range and can be obtained through process requirements or field tests.

[0133] The temperature difference limit between the upper and lower asphalt layers refers to the maximum allowable temperature difference between the asphalt surface layer and the lower layer during compaction. It is used to avoid "hot layer pressing cold layer" causing delamination. It can be obtained through experience setting or structural quality standard setting.

[0134] In this implementation plan, by collecting and analyzing the temperature of the asphalt surface and underlying layers in layers, the accuracy of identifying the thermal state distribution is improved, which helps to determine whether the material is in a suitable temperature range for compaction. The introduction of target values ​​and response tolerances provides clear boundaries for the judgment criteria, facilitating automatic analysis and control by the system. At the same time, the addition of temperature difference limits between upper and lower layers effectively avoids quality hazards such as hollowing and delamination caused by excessive temperature differences between layers. All temperature parameters can be acquired in real time using conventional sensors on site, demonstrating good feasibility and allowing for personalized adjustments based on different materials and processes. Overall, this method ensures the accuracy of temperature acquisition while enhancing the structure and practicality of temperature response analysis, providing a key foundation for precise control of compaction effects.

[0135] Specifically, the pavement structure response data includes wave incident amplitude, wave reflection amplitude, and echo delay time.

[0136] Among them, the wave incident amplitude value refers to the initial amplitude when the excitation wave of the road roller vibrator enters the asphalt structure, which can be measured by a vibration sensor installed at the output end of the vibrator or on the surface of the structure.

[0137] The amplitude of wave reflection refers to the amplitude of the excitation wave reflected back to the sensor after propagating in the structure. It can be measured and obtained by a road embedded vibration sensor or a structure echo module.

[0138] The echo delay time value refers to the time interval between the emission of the excitation wave and the first reception of the reflected wave, which can be calculated from the timestamps of the transmitting / receiving sensors.

[0139] The specific steps for analyzing the pavement structure response index of each pavement measurement point of the asphalt pavement are as follows: obtain the echo delay time limit of the asphalt pavement; combine the pavement structure response data of each pavement measurement point of the asphalt pavement with the echo delay time limit of the asphalt pavement for comprehensive analysis to obtain the pavement structure response index of each pavement measurement point of the asphalt pavement.

[0140] The specific formula for calculating the pavement structure response index at a certain pavement measurement point of an asphalt pavement is as follows: Wherein, LjX, RsF, FsF, and HbY are the pavement structure response index, wave incident amplitude, wave reflection amplitude, and echo delay time of a certain pavement measurement point, respectively; HbX is the echo delay time limit of the asphalt pavement; ε is the amplitude adjustment factor stored in the database to prevent the denominator from being 0; and π is pi, which is taken as 3.14 in this embodiment.

[0141] It should be explained that the pavement structure response index is used to measure the structural response index of asphalt pavement under fluctuating response conditions, reflecting the adaptability of the pavement structure to fluctuations.

[0142] When asphalt pavements are subjected to external fluctuations (such as traffic loads and ground vibrations), the structural response of the pavement directly affects its durability and service life. To accurately assess the structural response of asphalt pavements under fluctuating loads, this invention designs the LjX structural response index, which quantifies the pavement structure's response to fluctuations by comprehensively considering wave incident amplitude, wave reflection amplitude, and echo delay time.

[0143] In the pavement structure response index:

[0144] Amplitude difference item RsF represents the incident wave amplitude, and FsF represents the reflected wave amplitude. The difference in amplitude between the incident and reflected waves is calculated. This term measures the road surface's responsiveness to waves, i.e., the relationship between the reflection and incident waves after they pass through the road surface. The greater the difference, the stronger the road surface's response to the waves.

[0145] The stability of the calculation is ensured by using proportional calculations and adjusting the factor ε to avoid extreme results when the amplitude difference is too large.

[0146] echo delay term HbY represents the actual echo delay time, and HbX represents the limit value of the echo delay time. This term reflects the influence of echo delay on the structural response using a cosine function. A longer echo delay indicates that the pavement structure reacts slowly to fluctuations, thus affecting the assessment of compaction degree.

[0147] The use of a cosine function in the design makes the effect of the echo delay on the structural response smoother and avoids over-amplifying the effect of the echo delay.

[0148] Amplitude difference is an important factor affecting the impact of fluctuations on pavement structure. Using this amplitude difference calculation can accurately reflect the pavement's ability to respond to external fluctuations.

[0149] Echo delay time affects the dynamic response of the road surface. Designing a cosine function can smoothly account for this factor and avoid the interference of extreme values ​​on the results.

[0150] By measuring amplitude differences and echo delay, and using a cosine function to balance the impact of fluctuations on the structure, a scientific assessment of the structural response of asphalt pavement under fluctuating loads is achieved.

[0151] The echo delay time limit refers to the maximum allowable range of echo delay time. If the echo delay time is exceeded, the structure is considered loose or the response is insufficient. It can be set based on standard compaction conditions or experience in judging compaction quality.

[0152] In this implementation scheme, by extracting and analyzing three parameters—wave incident amplitude, wave reflection amplitude, and echo delay time—the integrity and compactness characteristics of the asphalt structural layer under vibration can be reflected. Evaluation is conducted using the wave propagation behavior within the structure, avoiding errors that may arise from judging only surface parameters. By comparing with echo delay time limits, problems such as voids, delamination, or insufficient compaction in the structural layer can be quickly identified. Furthermore, by introducing a comprehensive calculation method combining amplitude ratio and delay time, the sensitivity of the structural response index in identifying abnormal areas is enhanced. This method can be implemented using conventional vibration sensors and time synchronization equipment, possessing good feasibility and precision control capabilities. It helps to promptly detect deep structural anomalies during compaction, improving the depth and reliability of overall quality control.

[0153] Please see Figure 3 This invention provides a technical solution: a real-time feedback control system for asphalt pavement compaction based on multi-source data, comprising: a real-time data acquisition unit, used to acquire compaction state data of several pavement measurement points in real time, including pavement vibration, pavement temperature, and pavement structure response data, and perform preprocessing; a data response analysis unit, used to analyze the compaction state index set of several pavement measurement points based on the preprocessed compaction state data of several pavement measurement points, including pavement vibration, pavement temperature, and pavement structure response index; a compaction state analysis unit, used to analyze the compaction index of the asphalt pavement based on the compaction state index set of several pavement measurement points; and a matching control unit, used to match and judge the compaction index of the asphalt pavement with several preset compaction intervals, and each compaction interval corresponds to a control strategy. When the compaction index falls into a preset compaction interval, the corresponding feedback control strategy is executed.

[0154] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0155] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A real-time feedback control method for asphalt pavement compaction degree based on multi-source data, characterized in that, Includes the following steps: Real-time acquisition of compaction status data from several pavement measurement points on the asphalt pavement, including pavement vibration, pavement temperature, and pavement structure response data, and preprocessing of these data; Based on the compaction state data of several preprocessed pavement measurement points, the compaction state index set of several pavement measurement points of asphalt pavement is analyzed, including pavement vibration, pavement temperature and pavement structure response index. Based on the compaction state index set of several road measurement points, the compaction index of asphalt pavement is analyzed and matched with several preset compaction intervals. Each compaction interval corresponds to a control strategy. When the compaction index falls into a preset compaction range, the corresponding feedback control strategy is executed.

2. The real-time feedback control method for asphalt pavement compaction degree based on multi-source data according to claim 1, characterized in that, The specific steps for analyzing the compaction index of asphalt pavement are as follows: The pavement vibration, pavement temperature, and pavement structure response index of several pavement measurement points are read and comprehensively analyzed to obtain the set of average compaction state indices of the asphalt pavement, including pavement vibration, pavement temperature, and pavement structure average response index. A comprehensive analysis of the set of average compaction state indices for asphalt pavement was conducted to obtain the corresponding compaction degree index.

3. The real-time feedback control method for asphalt pavement compaction degree based on multi-source data according to claim 2, characterized in that, The specific formula for calculating the compaction index of asphalt pavement is as follows: Where YsD, LzP, LwP, and LjP are the compaction index, average vibration response index, average temperature response index, and average structural response index of asphalt pavement, respectively; e is a natural constant; and λ1, λ2, and λ3 are the pavement vibration response coefficient, pavement temperature response coefficient, and pavement structural response coefficient stored in the database, respectively, with λ1+λ2+λ3=1.

4. The real-time feedback control method for asphalt pavement compaction degree based on multi-source data according to claim 1, characterized in that, Road surface vibration response data includes vertical rebound acceleration, horizontal response acceleration, and response delay time.

5. The real-time feedback control method for asphalt pavement compaction degree based on multi-source data according to claim 4, characterized in that, The specific steps for analyzing the pavement vibration response index at each measurement point of an asphalt pavement are as follows: Obtain reference data on the vibration response of asphalt pavement, including reference values ​​for vertical rebound acceleration, horizontal response acceleration, and surface response delay time. The road vibration response data of each road surface measurement point of the asphalt pavement are combined with the road vibration response reference data of the asphalt pavement for comprehensive analysis to obtain the road vibration response index of each road surface measurement point of the asphalt pavement.

6. The real-time feedback control method for asphalt pavement compaction degree based on multi-source data according to claim 1, characterized in that, The road surface temperature response data includes the temperature values ​​of the asphalt surface layer and the asphalt sublayer.

7. The real-time feedback control method for asphalt pavement compaction degree based on multi-source data according to claim 6, characterized in that, The specific steps for analyzing the pavement temperature response index at each pavement measurement point in asphalt pavement are as follows: Obtain reference data on the temperature response of asphalt pavement, including the target temperature value of the asphalt surface layer, the temperature response tolerance value of the asphalt surface layer, the target temperature value of the asphalt sublayer, the temperature response tolerance value of the asphalt sublayer, and the temperature difference limit between the upper and lower asphalt layers. The pavement temperature response data of each pavement measurement point is combined with the pavement temperature response reference data of the asphalt pavement for comprehensive analysis to obtain the pavement temperature response index of each pavement measurement point.

8. The real-time feedback control method for asphalt pavement compaction degree based on multi-source data according to claim 1, characterized in that, The pavement structure response data includes wave incident amplitude, wave reflection amplitude, and echo delay time.

9. The real-time feedback control method for asphalt pavement compaction degree based on multi-source data according to claim 8, characterized in that, The specific steps for analyzing the pavement structure response index at each pavement measurement point of an asphalt pavement are as follows: Obtain the echo delay time limit of asphalt pavement; The pavement structure response data of each pavement measurement point in the asphalt pavement are comprehensively analyzed in conjunction with the echo delay time limit of the asphalt pavement to obtain the pavement structure response index of each pavement measurement point in the asphalt pavement.

10. A real-time feedback control system for asphalt pavement compaction degree based on multi-source data, employing the real-time feedback control method for asphalt pavement compaction degree based on multi-source data as described in any one of claims 1-9, characterized in that, include: The real-time data acquisition unit is used to acquire compaction status data of several pavement measurement points in real time, including pavement vibration, pavement temperature and pavement structure response data, and perform preprocessing. The data response analysis unit is used to analyze the compaction state index set of several pavement measurement points based on the preprocessed compaction state data of several pavement measurement points, including pavement vibration, pavement temperature and pavement structure response index. The compaction state analysis unit is used to analyze the compaction index of asphalt pavement based on a set of compaction state indices from several pavement measurement points. The matching control unit is used to match the compaction index of the asphalt pavement with several preset compaction intervals. Each compaction interval corresponds to a control strategy. When the compaction index falls into a preset compaction interval, the corresponding feedback control strategy is executed.

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