Intelligent regenerant spraying method and system

Abstract

The invention relates to the technical field of recycling of recycled asphalt pavement materials, in particular to an intelligent spraying method and system for a regenerant. The method comprises the following steps: detecting the actual penetration depth of a regenerant in mixture particles, the radius of the mixture particles and the real-time temperature of the mixture in real time; calculating a penetration depth ratio according to the actual penetration depth and the mixture particle radius; determining the spraying sub-stage of the current spraying in the spraying process according to the penetration depth ratio; and adjusting the spraying amount and temperature of spraying equipment according to the real-time temperature of the mixture based on the spraying sub-stage. The problems that in the prior art, when a recycled asphalt pavement material is regenerated, the surface layer of the material can rapidly adsorb a regenerant to form a compact saturated layer, so that the regenerant is prevented from further permeating into particles, then core aged asphalt is not effectively softened, and performance recovery is insufficient are solved. And the regeneration performance of the recycled asphalt pavement material is improved.

Description

Technical Field

[0001] This invention relates to the field of recycling technology for asphalt pavement materials, specifically a smart spraying method and system for regenerating agents. Background Technology

[0002] In recent years, with the continuous increase in traffic density and the extension of road service life, a large number of asphalt pavements have entered the maintenance stage. Reclaimed asphalt pavement (RAP), as a resource with both environmental and economic advantages, is being widely used in recycled asphalt mixtures. Especially in hot recycling technology, adding recycling agents to soften and restore the performance of aged asphalt in RAP is an effective means to achieve material recycling, reduce costs, and reduce carbon emissions, which meets the strategic needs of green transportation and sustainable development.

[0003] Despite the rapid development of recycling technology, numerous challenges remain in practical engineering. One of the most prominent issues is the method of adding recycling agents. Traditional processes typically involve a single spraying of the recycling agent, followed by thorough mixing during the stirring process. This method has two drawbacks: firstly, the surface of the RAP particles rapidly absorbs the recycling agent, forming a saturated zone, preventing the aged asphalt in the core from fully contacting the recycling agent and resulting in insufficient activation; secondly, the entire spraying process lacks a temperature and dosage control mechanism, making the recycling agent prone to deactivation or decomposition at high temperatures, reducing its actual effectiveness.

[0004] Meanwhile, the types of regenerators widely used in the market are becoming increasingly diversified, including vegetable oils (such as soybean oil and palm oil), petroleum-based regenerators (such as REOB), and composite SBS modified interface agents. These materials differ significantly in physicochemical properties, reaction temperatures, and penetration rates, which necessitates precise matching of their spraying methods, timing, and environmental conditions. Clearly, a single spraying method and constant parameter control are no longer sufficient to meet the current comprehensive requirements for regeneration depth, fusion efficiency, and stability.

[0005] Furthermore, in actual regeneration processes, the lack of responsiveness in the regenerant spraying control system often prevents it from dynamically adjusting spraying behavior based on differences in RAP sources (aging degree, content, particle structure) and process fluctuations (temperature changes, time delays). This leads to uncertainty and dispersion in the regeneration process, severely affecting the uniformity and engineering adaptability of the recycled mixture. Therefore, a more intelligent and scientific spraying method is urgently needed to improve the regeneration effect. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a smart method and system for spraying rejuvenating agents. This solves the problem that in existing technologies, when recycling asphalt pavement materials, the surface of the material quickly absorbs the rejuvenating agent, forming a dense saturated layer that hinders its further penetration into the particles. Consequently, the aged asphalt in the core is not effectively softened, resulting in insufficient performance recovery.

[0007] To achieve the above objectives, one aspect of the present invention provides a method for intelligent spraying of regenerants, comprising: real-time detection of the actual penetration depth of the regenerant within the mixed material particles, the radius of the mixed material particles, and the real-time temperature of the mixed material; calculating a penetration depth ratio based on the actual penetration depth and the radius of the mixed material particles; determining the current spraying sub-stage in the spraying process based on the penetration depth ratio; and adjusting the spraying volume and temperature of the spraying equipment based on the spraying sub-stage and the real-time temperature of the mixed material.

[0008] This invention monitors the recycling agent penetration depth, mixture particle radius, and temperature in real time, divides the spraying into sub-stages based on the penetration depth ratio, and then dynamically adjusts the spraying parameters according to the temperature. This model precisely adapts to the recycling agent penetration pattern, making the spraying process more refined and intelligent. It allows the recycling agent to fully and uniformly penetrate within the mixture particles, improving the recycling effect of old materials, ensuring the performance of recycled materials, and enhancing the performance of recycled asphalt pavement materials.

[0009] Optionally, the spraying sub-stages include an initial penetration spraying stage, a mid-term activation spraying stage, and a final fusion spraying stage. Determining the current spraying sub-stage based on the penetration depth ratio includes: setting threshold ranges for the initial penetration spraying stage, the mid-term activation spraying stage, and the final fusion spraying stage; comparing the penetration depth ratio with the threshold ranges; and determining the current spraying sub-stage based on the comparison result.

[0010] This invention subdivides the spraying process into three sub-stages: initial penetration, intermediate activation, and final fusion, and sets a penetration depth ratio threshold range for each stage. This achieves precise division of the regenerant spraying process. By comparing the real-time penetration depth ratio with the threshold range, the current stage can be clearly identified, allowing the spraying strategy to adapt to the characteristics of each stage. This avoids the coarseness of traditional uniform adjustment, making the regenerant spraying more in line with the penetration law, and improving the utilization efficiency of the regenerant and the quality of the mixed material regeneration.

[0011] Optionally, the threshold interval includes an initial threshold interval corresponding to the initial penetration spraying stage, a mid-term threshold interval corresponding to the mid-term activation spraying stage, and a final threshold interval corresponding to the final fusion spraying stage, wherein the initial threshold interval satisfies The intermediate threshold interval satisfies The final threshold interval satisfies ,in, This represents the penetration depth ratio.

[0012] This invention sets clear penetration depth ratio threshold ranges for the three spraying sub-stages, making the division of each stage more precise. The system can then clearly determine the current spraying process, ensuring that the strategy of focusing on penetration in the initial stage, enhancing activation in the middle stage, and ensuring fusion in the final stage is accurately implemented, avoiding blind adjustments, and improving the utilization efficiency of regenerators and the quality of mixture regeneration.

[0013] Optionally, adjusting the spraying volume and temperature of the spraying equipment based on the real-time temperature of the mixture in the spraying sub-stage includes: obtaining the target temperature corresponding to the spraying sub-stage; and adjusting the spraying volume and temperature of the spraying equipment based on the target temperature and the real-time temperature of the mixture.

[0014] This invention sets target temperatures for each spraying sub-stage and adjusts the spraying volume and temperature in real time, making the control more closely match the characteristics of each stage. This avoids the limitations of uniform adjustment and improves the penetration effect of the regenerator, the quality of the mixture, and the efficiency of spraying.

[0015] Optionally, adjusting the spraying volume and temperature of the spraying equipment based on the target temperature and the real-time temperature of the mixture includes: constructing a temperature difference sequence based on the target temperature and the real-time temperature of the mixture and obtaining the current temperature difference; obtaining a proportional gain and calculating a proportional term based on the proportional gain and the current temperature difference; obtaining an integral gain, summing the temperature difference sequence, and calculating an integral term based on the summation result and the integral gain; obtaining a differential gain, performing adjacent difference operations on the temperature difference sequence, and calculating a differential term based on the adjacent difference operation result and the differential gain; calculating a control output quantity based on the proportional term, the integral term, and the differential term; and using the control output quantity as an adjustment command of the PID controller to adjust the spraying volume and temperature of the spraying equipment.

[0016] This invention constructs a temperature difference sequence and combines proportional, integral, and derivative operations to achieve PID control. The proportional term responds to the current temperature difference, the integral term eliminates steady-state error, and the derivative term predicts the trend of change. The three terms work together to calculate and control the output, making the spraying volume and temperature adjustment of the spraying equipment more precise. It not only meets the target temperature requirements of each sub-stage, but also dynamically adapts to real-time temperature changes, avoiding over-adjustment or lag, and improving the penetration efficiency of regenerator and the stability of the mixture quality.

[0017] Optionally, obtaining the proportional gain includes: performing statistical analysis on the regeneration levels of various recycled asphalt pavement materials to obtain a benchmark carbonyl index value; obtaining an aging weighting factor and a first initial control gain; and calculating the proportional gain based on the benchmark carbonyl index value, the aging weighting factor, and the first initial control gain.

[0018] This invention determines the benchmark carbonyl index value by statistically analyzing the regeneration level of various recycled asphalt pavement materials, and calculates the proportional gain by combining the aging weight factor and the first initial control gain, so that the proportional gain can be adapted to the aging characteristics of different materials, thereby improving the accuracy of the proportional gain calculation.

[0019] Optionally, the statistical analysis of the recycling levels of various recycled asphalt pavement materials to obtain a baseline carbonyl index value includes: measuring various recycled asphalt pavement materials using Fourier transform infrared spectroscopy to obtain a sample carbonyl index set; removing outliers from the carbonyl index set to obtain a corrected carbonyl index set; and conducting a recycling test based on the corrected carbonyl index set to determine the baseline carbonyl index value.

[0020] This invention measures various recycled asphalt materials using Fourier transform infrared spectroscopy to obtain a sample carbonyl index set and remove outliers. Then, a regeneration test is conducted to determine the benchmark carbonyl index value, thereby improving the representativeness and accuracy of the benchmark carbonyl index value.

[0021] Optionally, obtaining the integral gain includes: obtaining a temperature difference attenuation factor and a second initial control gain; and calculating the integral gain based on the current temperature difference, the temperature difference attenuation factor, and the second initial control gain.

[0022] This invention combines the current temperature difference, temperature difference attenuation factor, and second initial control gain to calculate the integral gain, enabling the integral term to adapt to real-time temperature changes, avoiding integral saturation, and improving the accuracy of integral gain calculation.

[0023] Optionally, obtaining the differential gain includes: obtaining a fine-tuning time factor, a third initial control gain, and a spray response time; and calculating the differential gain based on the fine-tuning time factor, the third initial control gain, and the spray response time.

[0024] This invention combines the fine-tuning time factor, the third initial control gain, and the spray response time to calculate the differential gain, which allows the differential gain to dynamically adapt to the time characteristics of the spraying process, thus improving the accuracy of the differential gain calculation.

[0025] Another aspect of the present invention provides a regenerant intelligent spraying system, comprising: a processor, an input device, an output device, and a memory, wherein the processor, the input device, the output device, and the memory are interconnected, wherein the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to invoke the program instructions to execute a regenerant intelligent spraying method according to any of the preceding aspects of the present invention.

[0026] The present invention provides a regenerant intelligent spraying system with a compact structure, stable performance, high integration and simple composition. It can stably execute the regenerant intelligent spraying method provided in the preceding aspect of the present invention, further improving the overall applicability and practical application capability of the present invention. Attached Figure Description

[0027] Figure 1 This is a flowchart of a smart regenerant spraying method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a smart regenerant spraying system according to an embodiment of the present invention. Detailed Implementation

[0028] Specific embodiments of the present invention will now be described in detail. It should be noted that the embodiments described herein are for illustrative purposes only and are not intended to limit the invention. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that these specific details are not necessary to practice the invention. In other instances, well-known circuits, software, or methods have not been specifically described to avoid obscuring the invention.

[0029] Throughout this specification, references to "an embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with that embodiment or example is included in at least one embodiment of the invention. Therefore, the phrases "in an embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily refer to the same embodiment or example. Furthermore, specific features, structures, or characteristics can be combined in one or more embodiments or examples in any suitable combination and / or sub-combination. Moreover, those skilled in the art will understand that the illustrations provided herein are for illustrative purposes and are not necessarily drawn to scale.

[0030] Please see Figure 1 In order to solve the problems in the prior art, in an alternative embodiment, such as Figure 1 The intelligent spraying method for regenerant shown includes the following steps: Step S1: Real-time detection of the actual penetration depth of the regenerant inside the mixture particles, the radius of the mixture particles, and the real-time temperature of the mixture.

[0031] In this embodiment, the spraying system is designed first, and the system mainly consists of the following modules: Main support structure: including brackets, operating platform and multi-level installation interfaces, used to fix each module and adapt to experimental or small-scale engineering environments.

[0032] Dual-tank feeding module: Equipped with two independent tanks to store different functional regenerant components, such as a penetrating low-viscosity oil phase and a high-polarity activator; expandable to three tanks if necessary to achieve independent supply of fusion-promoting components (such as SBS modifier). Each tank is equipped with independent heating and temperature control and liquid level monitoring functions to ensure the stability of the solution before spraying.

[0033] Temperature-controlled spraying module: Each spraying branch is equipped with a miniature electric heating unit, temperature sensor and insulated nozzle. Together with the PID feedback control system, it realizes real-time heating and adjustment before spraying, ensuring that the sprayed liquid is stably output within the range of 130℃-160℃, and avoiding the failure of active components due to overheating.

[0034] Multi-stage spraying structure: Three sets of independent nozzles are arranged along the mixing tank or mixing channel, corresponding to the three spraying stages of "initial-intermediate-final". The system can set the start time, duration, dosage and temperature parameters of each stage to meet the process requirements of penetration, activation and fusion.

[0035] Intelligent control and data feedback system: Using a microcontroller as the control core, it receives temperature sensor signals and dynamically adjusts the on / off state of each nozzle and the temperature control output. The control terminal has a visual user interface, allowing users to input material characteristics and call preset spraying programs, enabling rapid switching and customized regeneration strategies.

[0036] During the spraying process, one to two typical asphalt pavement material particles (8mm-16mm in diameter, ensuring coverage of the main particle size range) are randomly selected from the mixed material and their accurate radii are recorded. They are then immediately placed in liquid nitrogen for rapid freezing (this ensures that the internal aged asphalt is embrittled to obtain a clear cross-section while shortening the freezing time). After removal, the particles are gently tapped with mechanical force to break along their natural weak surfaces, exposing the internal cross-section. A 0.05%-0.1% concentration of Rhodamine B fluorescent dye solution is then quickly and evenly sprayed onto the cross-section (this concentration allows for rapid binding with the regenerator penetration area without affecting the detection accuracy). Once the dye is fully adsorbed, the cross-section is placed under an ultraviolet fluorescence microscope with an excitation wavelength of 540nm and an emission wavelength of 580nm-610nm. The fluorescence color development area is captured in real time using the microscope's automated microscopic measurement software, and the maximum penetration depth of the regenerator inside the particles, i.e., the actual penetration depth, is directly read.

[0037] The real-time temperature of the mixture is obtained using a combination of dual-channel thermocouple calibration and multi-point monitoring. Two independent thermocouples are placed at key locations such as the inner wall of the mixing container or the mixing arm to form dual-channel monitoring. At the same time, an infrared temperature measurement module can be used to realize real-time acquisition of the mixture temperature. The dual-channel thermocouples are calibrated by comparing the temperature difference in real time, calculating the average value, or automatically switching the backup channel to ensure the accuracy and reliability of the temperature data. The infrared temperature measurement module assists in monitoring the temperature of key areas, ensuring the accuracy and reliability of the temperature data throughout the spraying process.

[0038] Step S2: Calculate the penetration depth ratio based on the actual penetration depth and the particle radius of the mixture.

[0039] In this embodiment, the penetration depth ratio satisfies the following formula: in, The penetration depth ratio, This represents the actual penetration depth of the regenerant within the mixture particles. The radius of the mixture particles.

[0040] This index quantifies the penetration and coverage of the recycling agent on aged asphalt, and is a key physical parameter for measuring recycling depth and efficiency. When the penetration depth ratio is close to 1, it indicates that the recycling agent has fully penetrated into the interior of the particles. If the penetration depth ratio is low, it indicates that the recycling agent mainly remains on the surface, and the aged asphalt inside has not been effectively repaired.

[0041] Step S3: Determine the current spraying sub-stage in the spraying process based on the penetration depth ratio.

[0042] The spraying sub-stages include the initial penetration spraying stage, the intermediate activation spraying stage, and the final fusion spraying stage.

[0043] Determining the current spraying sub-stage based on the penetration depth ratio specifically includes the following sub-steps: Step S301: Set threshold ranges for the initial penetration spraying stage, the intermediate activation spraying stage, and the final fusion spraying stage, respectively.

[0044] The threshold range includes the initial threshold range corresponding to the initial penetration spraying stage, the intermediate threshold range corresponding to the intermediate activation spraying stage, and the final threshold range corresponding to the final fusion spraying stage. The initial threshold range satisfies... The intermediate threshold interval satisfies The final threshold interval satisfies ,in, This represents the penetration depth ratio.

[0045] In this embodiment, during the initial penetration stage, the regenerant primarily achieves surface wetting. This reflects the initial state of the regenerant covering the particle surface, laying the foundation for subsequent deep penetration; in the intermediate activation stage, the regenerant needs to penetrate through the surface into the particle and activate the aged colloid. The 0.2-0.6 range corresponds to the uniform activation process of the rejuvenator on the aged asphalt in the middle layer, ensuring the effective action of the polar components, and the final fusion stage. This indicates that the rejuvenator has fully penetrated into the core area of ​​the particles, meeting the requirements for the fusion of the new and old asphalt interfaces. The advantage of this division is that it clarifies the objectives of each stage and provides a basis for phased spraying, making it easier to dynamically adjust spraying parameters in conjunction with parameters such as temperature and carbonyl index.

[0046] Step S302: Compare the penetration depth ratio with the threshold range, and determine the current spraying sub-stage in the spraying process based on the comparison result.

[0047] In this embodiment, the penetration depth ratio is compared with the threshold range. If the penetration depth ratio is within a certain range... This is considered the initial penetration spraying stage. This stage corresponds to the regenerant just completing surface wetting and initially penetrating to the shallow layer of particles. Rapid surface coverage is necessary to break down the subsequent penetration barrier. If the penetration depth is less than... This is determined to be the mid-term activation spraying stage. This stage indicates that the rejuvenator has penetrated the surface layer, reached the middle layer of the particles, and begun to activate the internal aged asphalt. At this time, it is necessary to ensure the uniform effect of the polar components on the internal aged colloids. If the penetration depth is higher than that... The system is determined to be in the final fusion spraying stage. The greater the penetration depth ratio, the more the rejuvenator penetrates into the core area of ​​the particles, meeting the fusion requirements of the new and old asphalt interfaces. Through this interval matching that is closely related to the penetration characteristics and control requirements of each stage, the system can clearly identify the current sub-stage of spraying, providing a quantitative basis for subsequent precise control and ensuring that the role of the rejuvenator is maximized at each stage.

[0048] Step S4: Based on the spraying sub-stage, adjust the spraying volume and temperature of the spraying equipment according to the real-time temperature of the mixture.

[0049] The adjustment of the spraying volume and temperature of the spraying equipment based on the real-time temperature of the mixture in the spraying sub-stage specifically includes the following sub-steps: Step S401: Obtain the target temperature corresponding to the spraying sub-stage.

[0050] In this embodiment, the core of the initial penetration spraying stage is to achieve rapid wetting of the surface of the asphalt pavement material particles by the recycling agent. This requires matching the temperature conditions that facilitate the material's penetration. The target temperature is set at 135°C. This temperature ensures the fluidity of the recycling agent to promote shallow penetration while avoiding early volatilization due to excessively high temperatures. The intermediate activation spraying stage needs to enhance the activation effect of polar components on the internal aged asphalt. It needs to be within the optimal range of asphalt softening reaction. The target temperature is set at 150°C. This temperature can enhance the reactivity of aged colloids and recycling agents, ensuring uniform activation. The final fusion spraying stage focuses on the stable bonding of the new and old asphalt interfaces. It is necessary to ensure sufficient fusion while avoiding overheating. The target temperature is set at 145°C. This temperature can maintain the interfacial activity of the recycling agent while reducing damage to the fusion interface caused by high temperatures.

[0051] Step S402: Adjust the spraying volume and temperature of the spraying equipment according to the target temperature and the real-time temperature of the mixture.

[0052] The adjustment of the spraying volume and temperature of the spraying equipment based on the target temperature and the real-time temperature of the mixture specifically includes the following sub-steps: Step S40201: Construct a temperature difference sequence based on the target temperature and the real-time temperature of the mixture, and obtain the current temperature difference.

[0053] In this embodiment, the system collects the current temperature of the mixture in real time through dual-channel thermocouples, and constructs a temperature difference sequence based on the time axis and temperature change pattern of each sub-stage. For the initial penetration stage (target temperature 135℃), the intermediate activation stage (target temperature 150℃), and the final fusion stage (target temperature 145℃), the system continuously records the difference between the target temperature at the current moment and the real-time collected temperature in each stage, forming a difference dataset (i.e., temperature difference sequence) arranged in chronological order, where the current temperature difference is the latest item in the sequence.

[0054] Step S40202: Obtain the proportional gain and calculate the proportional term based on the proportional gain and the current temperature difference.

[0055] Obtaining the proportional gain specifically includes the following sub-steps: Step S4020201 involves statistically analyzing the recycling levels of various recycled asphalt pavement materials to obtain a benchmark carbonyl index value.

[0056] The statistical analysis of the recycling levels of various recycled asphalt pavement materials to obtain the benchmark carbonyl index value specifically includes the following sub-steps: Step S402020101: Fourier transform infrared spectroscopy is used to measure various recycled asphalt pavement materials to obtain a sample carbonyl index set.

[0057] In this embodiment, a variety of representative recycled asphalt pavement materials were selected, covering milled pavement materials with different service years, climate regions, and aging degrees, to ensure that the samples can reflect the aging state range of recycled asphalt pavement materials in actual engineering projects. Subsequently, Fourier transform infrared spectroscopy was used to test each recycled asphalt pavement material sample, specifically extracting samples at 1680 cm⁻¹. 1 -1750cm⁻ 1 The carbonyl peak area within the range (this band corresponds to the characteristic absorption of the carbonyl functional group C=O in asphalt, directly reflecting the degree of oxidative aging), and the reference band (1350 cm⁻) is also extracted. 1 –1500cm⁻ 1 Using the peak area of ​​the reference band as a benchmark, the carbonyl peak area of ​​each sample is divided by the peak area of ​​the reference band to obtain the carbonyl index of that sample. The carbonyl index values ​​of all samples are summarized to form a sample carbonyl index set containing the characteristics of recycled asphalt pavement materials with different aging degrees.

[0058] Step S402020102: Remove outliers from the carbonyl index set to obtain a corrected carbonyl index set.

[0059] In this embodiment, based on all data in the sample carbonyl index set, outliers are identified using statistical methods. A reasonable data distribution range can be determined by calculating the interquartile range (IQR) or standard deviation of the dataset (values ​​exceeding ±3 times the mean or 1.5 times the IQR are considered outliers). Extreme carbonyl index values ​​that significantly deviate from the overall distribution, possibly due to sample contamination, testing errors, or atypical aging conditions, are identified as outliers. These outliers are then removed, and the remaining data constitutes the corrected carbonyl index set. This processing step aims to eliminate interference from non-representative data in subsequent analysis, ensuring that the corrected dataset accurately reflects the typical aging conditions of most recycled asphalt pavement materials, providing a more reliable data foundation for recycling tests and the determination of benchmark carbonyl index values.

[0060] Step S402020103: Conduct a regeneration test based on the modified carbonyl index set to determine the baseline carbonyl index value.

[0061] In this embodiment, staged regenerant spraying tests were conducted on different carbonyl index samples from the modified carbonyl index set, and the regeneration effect indicators at each stage were monitored in real time, including the regenerant penetration depth ratio, the adhesion between new and old asphalt interfaces, the uniformity of the mixture, and the degree of performance recovery of aged asphalt (such as rheological recovery effect). By comparing the regeneration effects corresponding to samples with different carbonyl index values, the correlation between carbonyl index values ​​and suitable regeneration levels was analyzed. That is, when the carbonyl index value is too high, even with enhanced spraying, the regenerant may not be able to fully penetrate and activate due to excessive aging (the penetration depth ratio is likely to be lower than the threshold). When the carbonyl index value is too low, light spraying can achieve the required penetration depth ratio and sufficient interface fusion. Excessive spraying will lead to resource waste. Finally, the carbonyl index value that can stably achieve the required regeneration effect at each stage (such as the penetration depth ratio meeting the stage threshold and sufficient interface fusion) in the regeneration test is determined as the benchmark carbonyl index value. This value serves as the zero-deviation reference point for spraying control. In an optional embodiment, the benchmark carbonyl index value is 0.3.

[0062] Step S4020202: Obtain the aging weight factor and the first initial control gain.

[0063] In this embodiment, to obtain the aging weight factor, asphalt pavement material samples covering typical values ​​of the modified carbonyl index set are first selected. The regenerator penetration rate, interface activation effect and rheological recovery degree corresponding to different carbonyl index values ​​are tested respectively. The range in which the regenerator response rate increases most significantly when the benchmark carbonyl index value (the difference between the actual carbonyl index value and the benchmark value of 0.30) increases is screened out. The initial range of the aging weight factor (e.g., 0.8–1.5) is determined in this way, and the median value of 1.2 is used as the initial value. Then, the subsequent response curve fitting is optimized to ensure that it can accurately reflect the influence of the degree of aging on the spraying response intensity.

[0064] To obtain the first initial control gain, a basic spraying test needs to be carried out under the appropriate regeneration level state corresponding to the benchmark carbonyl index value (benchmark carbonyl index value = 0.3). The initial adjustment effect of the proportional term on the temperature deviation is monitored. That is, when the mixture temperature is in the target range and the carbonyl index value is the benchmark value, the initial gain is adjusted so that the proportional output of the PID control can stably maintain the balance between spraying flow and penetration efficiency. Finally, the initial value that can ensure the basic spraying accuracy without causing system overshoot is determined as the first initial control gain.

[0065] Step S4020203: Calculate the proportional gain based on the benchmark carbonyl index value, the aging weighting factor, and the first initial control gain.

[0066] The proportional gain satisfies the following formula: in, For proportional gain, The first initial control gain, As an aging weighting factor, This is the benchmark carbonyl index value.

[0067] The above formula is based on the initial control gain under the baseline state, and dynamically adjusts the proportional gain by combining the aging weighting factor and the baseline carbonyl index value. The quasi-carbonyl index value reflects the typical aging degree of the recycled asphalt pavement material, and the aging weighting factor quantifies the influence of the aging degree on the spraying response. When the baseline carbonyl index value is larger (i.e., the more severe the material aging), The larger the value of the term, the greater the proportional gain, thereby enhancing the response strength of the proportional term in PID control to temperature deviation, ensuring more suitable spraying control for more severely aged materials, and achieving precise matching between regenerator spraying and material aging state.

[0068] The proportional term satisfies the following formula: in, For the proportion term, For proportional gain, for Temperature difference between the two samples.

[0069] The above formula uses proportional gain Multiply by the current Temperature difference of the second sample The ability to quickly adjust based on the current temperature deviation is a fundamental aspect of PID control, enabling the control system to rapidly respond to the current deviation.

[0070] Step S40203: Obtain the integral gain, sum the temperature difference sequence, and calculate the integral term based on the summation result and the integral gain.

[0071] The specific steps for obtaining the integral gain are as follows: Step S4020301: Obtain the temperature difference attenuation factor and the second initial control gain.

[0072] When obtaining the temperature difference attenuation factor, the focus should be on suppressing system overshoot or hysteresis caused by the accumulation of temperature deviation in the integral term (Ki): First, conduct experiments in the typical temperature difference range of 5°C–10°C, monitor the uniformity and penetration depth of the regenerator spraying under different temperature differences, analyze the correlation between the accumulated amount of the integral term and the temperature difference, and fit the law of attenuation of the integral amount as the temperature difference increases. For example, the larger the temperature difference, the stronger the attenuation is needed to avoid excessive growth of the integral. Then, combine the temperature fluctuation characteristics of each spraying sub-stage (initial penetration, mid-term activation, and final fusion) (such as the more active temperature difference changes in the mid-term activation stage) to determine the initial value (β=0.05 is recommended). Subsequently, dynamically adjust by testing the control accuracy of the target temperature deviation (such as whether it can quickly converge to within ±2°C) to ensure that the integral overshoot is effectively punished when the temperature difference is large, and that moderate integral adjustment is retained when the temperature difference is small.

[0073] To obtain the second initial control gain, a basic experiment needs to be conducted under the reference conditions (such as the mixture temperature being stable at the ideal value and the carbonyl index being the reference value of 0.30): by adjusting the initial gain, observe the ability of the integral term to eliminate the steady-state temperature difference, and determine the initial value that ensures that the integral adjustment is neither excessive (avoiding overshoot) nor insufficient (ensuring the elimination of steady-state error) as the reference for calculating the integral gain.

[0074] Step S4020302: Calculate the integral gain based on the current temperature difference, the temperature difference attenuation factor, and the second initial control gain.

[0075] The integral gain satisfies the following formula: in, For integral gain, This is the second initial control gain. For time Real-time temperature of the mixture With target temperature The absolute difference.

[0076] The above formula uses the initial control gain Based on this, by introducing a correction term related to the absolute difference between the real-time temperature of the mixture and the target temperature, the integral gain is dynamically adjusted with the temperature deviation. The larger the deviation, the smaller the gain, thus avoiding overshoot caused by excessive integral action and ensuring control stability.

[0077] The integral term satisfies the following formula: in, for The integral term of the next sampling, For integral gain, This represents the current number of samples. for Temperature difference between the two samples for Second sampling and The time interval between samplings.

[0078] The above formula multiplies the temperature difference of each sampling (from the initial to the tth time) by the corresponding sampling interval (the time interval between the previous sampling and the previous sampling) and sums them up, and then multiplies them by the integral gain. This process accumulates the influence of historical temperature deviations, eliminates long-term steady-state errors, and makes the control more precise.

[0079] Step S40204: Obtain the differential gain, perform adjacent difference operation on the temperature difference sequence, and calculate the differential term based on the result of the adjacent difference operation and the differential gain.

[0080] The specific steps for obtaining the differential gain are as follows: Step S4020401: Obtain the fine-tuning time factor, the third initial control gain, and the spray response time.

[0081] In this embodiment, when obtaining the fine-tuning time factor, it is necessary to combine the duration of the regenerant spraying process and the rate of temperature change of the mixture. With the goal of improving the system's ability to resist fluctuations, it is set in the range of [0.95, 0.99] to achieve smooth decay. By testing the temperature stability at different time points, the decay law of the derivative term over time can be fitted, and finally, a specific value that can balance the response speed and system stability (such as the initial suggestion of 0.97) can be determined. The theoretical basis is the smooth control requirement of time on the derivative term in the classical PID control theory.

[0082] To obtain the third initial control gain, a basic differential adjustment test needs to be conducted under baseline conditions (e.g., a baseline carbonyl index of 0.3 and a mixture temperature stable at the ideal spraying temperature). The initial suppression effect of the differential term on temperature abrupt changes should be monitored. By adjusting the initial value, the differential output can respond quickly to temperature fluctuations (e.g., suppressing sudden temperature rises during the mid-stage activation) without causing spray volume oscillations due to over-adjustment. Finally, a baseline initial value that balances disturbance rejection and stability should be determined. The spray response time is the real-time time progression starting from the spray initiation moment. It needs to be recorded in real-time by a system timer, and its value range should match the duration of each spraying sub-stage to dynamically reflect the impact of time on the decay of the differential term, ensuring greater system stability in the later stages of spraying.

[0083] Step S4020402: Calculate the differential gain based on the fine-tuning time factor, the third initial control gain, and the spraying response time.

[0084] The differential gain satisfies the following formula: in, For differential gain, The third initial control gain, To fine-tune the time factor, This refers to the spray response time.

[0085] Differential gain With initial control gain Based on this, by fine-tuning the time factor With spray response time The exponential correlation dynamically adapts to system requirements, allowing the adjustment intensity of the differential element to change precisely with the response characteristics, thereby enhancing the adaptability and stability of the control.

[0086] The differential term satisfies the following formula: in, for The differential term of the next sampling, For differential gain, for Temperature difference between the two samples for Temperature difference between the two samples for Second sampling and The time interval between samplings.

[0087] The above formula first takes the first... The second and the previous The temperature difference between the two samples is divided by the time interval between the two samples to obtain the rate of change of temperature deviation. This rate of change is then multiplied by the differential gain to reflect the trend of temperature deviation, allowing the control system to respond in advance and improve the timeliness and stability of spray adjustment.

[0088] Step S40205: Calculate the control output quantity based on the proportional term, the integral term, and the derivative term.

[0089] The control output quantity satisfies the following formula: in, To control the output, other variables remain the same as defined above.

[0090] The above formula controls the output quantity by directly responding to the current temperature deviation through the proportional term, accumulating historical deviations to eliminate steady-state errors through the integral term, and capturing the rate of change of deviation to achieve proactive adjustment. The three work together to allow the PID controller to output appropriate adjustment commands, precisely control the spraying equipment, and make the temperature of the mixture stably approach the target value.

[0091] Step S40206: The control output quantity is used as the adjustment command of the PID controller to adjust the spraying quantity and temperature of the spraying equipment.

[0092] In this embodiment, based on this output, the controller dynamically adjusts the spraying amount of the regenerant by changing the volume or mass of the regenerant sprayed per unit time to adapt to the deviation between the real-time temperature of the mixture and the target temperature. On the other hand, it synchronously controls the spraying temperature, for example, by adjusting the power of the heating module or the flow rate of the cooling circuit, so that the temperature of the sprayed regenerant and the temperature of the mixture can form a reasonable interaction, ultimately achieving precise control of the temperature of the mixture. This allows the entire regenerant spraying process to stably and efficiently approach the target temperature under PID control logic, ensuring that the performance of the recycled mixture meets the standards.

[0093] like Figure 2 As shown, another intelligent regenerant spraying system includes: a processor, an input device, an output device, and a memory. The processor, the input device, the output device, and the memory are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to call the program instructions to execute the relevant steps of a relevant embodiment of the intelligent regenerant spraying method of the present invention.

[0094] This invention provides an intelligent regenerant spraying system. The functional components can be integrated into a single processing unit, or each component can exist independently, or two or more components can be integrated into one unit. The integrated components can be implemented in hardware or software.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for intelligent spraying of regenerant, characterized in that, The method includes: Real-time monitoring of the actual penetration depth of the regenerant inside the mixture particles, the radius of the mixture particles, and the real-time temperature of the mixture; The penetration depth ratio is calculated based on the actual penetration depth and the particle radius of the mixture. The current spraying sub-stage is determined based on the penetration depth ratio. Based on the spraying sub-stage, the spraying volume and temperature of the spraying equipment are adjusted according to the real-time temperature of the mixture.

2. The intelligent spraying method for regenerant according to claim 1, characterized in that, The spraying sub-stages include an initial penetration spraying stage, a mid-term activation spraying stage, and a final fusion spraying stage. Determining the current spraying sub-stage based on the penetration depth ratio includes: Threshold ranges are set for the initial penetration spraying stage, the intermediate activation spraying stage, and the final fusion spraying stage, respectively; The penetration depth ratio is compared with the threshold range, and the spraying sub-stage at which the current spraying is in the spraying process is determined based on the comparison result.

3. The intelligent spraying method for regenerant according to claim 2, characterized in that, The threshold range includes the initial threshold range corresponding to the initial penetration spraying stage, the intermediate threshold range corresponding to the intermediate activation spraying stage, and the final threshold range corresponding to the final fusion spraying stage. The initial threshold range satisfies... The intermediate threshold interval satisfies The final threshold interval satisfies ,in, This represents the penetration depth ratio.

4. The intelligent spraying method for regenerant according to claim 1, characterized in that, The adjustment of the spraying volume and temperature of the spraying equipment based on the real-time temperature of the mixture in the spraying sub-stage includes: Obtain the target temperature corresponding to the spraying sub-stage; The spraying volume and temperature of the spraying equipment are adjusted according to the target temperature and the real-time temperature of the mixture.

5. The intelligent spraying method for regenerant according to claim 4, characterized in that, The adjustment of the spraying volume and temperature of the spraying equipment based on the target temperature and the real-time temperature of the mixture includes: A temperature difference sequence is constructed based on the target temperature and the real-time temperature of the mixture, and the current temperature difference is obtained. Obtain the proportional gain, and calculate the proportional term based on the proportional gain and the current temperature difference; Obtain the integral gain, sum the temperature difference sequence, and calculate the integral term based on the summation result and the integral gain; Obtain the differential gain, perform adjacent difference operations on the temperature difference sequence, and calculate the differential term based on the result of the adjacent difference operations and the differential gain; The control output is calculated based on the proportional term, the integral term, and the derivative term. The control output is used as the adjustment command of the PID controller to adjust the spraying volume and temperature of the spraying equipment.

6. The intelligent spraying method for regenerant according to claim 5, characterized in that, The acquisition of the proportional gain includes: Statistical analysis was conducted on the recycling levels of various recycled asphalt pavement materials to obtain a benchmark carbonyl index value; Obtain the aging weighting factor and the first initial control gain; The proportional gain is calculated based on the benchmark carbonyl index value, the aging weighting factor, and the first initial control gain.

7. The intelligent spraying method for regenerant according to claim 6, characterized in that, The statistical analysis of the recycling levels of various recycled asphalt pavement materials yielded the following benchmark carbonyl index values: Fourier transform infrared spectroscopy was used to measure various recycled asphalt pavement materials to obtain a sample carbonyl index set; The carbonyl index set is modified by removing outliers. Regeneration tests were conducted based on the modified carbonyl index set to determine the baseline carbonyl index value.

8. The intelligent spraying method for regenerant according to claim 5, characterized in that, The acquisition of integral gain includes: Obtain the temperature difference attenuation factor and the second initial control gain; The integral gain is calculated based on the current temperature difference, the temperature difference attenuation factor, and the second initial control gain.

9. The intelligent spraying method for regenerant according to claim 5, characterized in that, The acquisition of differential gain includes: Obtain the fine-tuning time factor, the third initial control gain, and the spray response time; The differential gain is calculated based on the fine-tuning time factor, the third initial control gain, and the spray response time.

10. A smart regenerant spraying system, characterized in that, include: The system includes a processor, an input device, an output device, and a memory, all interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to invoke the program instructions to execute a smart regenerant spraying method as described in any one of claims 1 to 9.

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