2668 results about "Asphalt pavement" patented technology

The invention discloses an asphalt pavement health state monitoring system and method, and belongs to the technical field of traffic infrastructure monitoring. The system comprises the following modules: a multi-source data acquisition module used for realizing real-time acquisition of pavement state parameters; the data processing module is used for performing space-time alignment, quality evaluation, exception handling and standardization on the acquired multi-source data; the multi-scale feature extraction module is used for extracting features from the microscopic diseases, the road section states and the network level, and constructing a multi-scale feature representation system; the dynamic graph analysis module is used for constructing a layered dynamic graph structure and realizing unified modeling and analysis of the road network health state; the health assessment module is used for realizing real-time assessment, deterioration trend prediction and risk early warning of the road surface health state; and the decision visualization module is used for displaying the monitoring data, the prediction result and the early warning information, and automatically generating maintenance decision suggestions based on the evaluation result.

The invention discloses an asphalt pavement fatigue damage model calibration method based on AI and digital twinning, and relates to the technical field of damage detection. Compared with the prior art, the problems that traditional asphalt pavement design depends on empirical formulas and static parameters, material aging, environmental coupling and load uncertainty are difficult to dynamically reflect, and cross-scale correlation between microscopic interface behaviors and macroscopic structure performance is lacked are solved; the method comprises the following steps: collecting and preprocessing multi-source heterogeneous data in real time through a multi-modal data fusion and dynamic sensing system, simulating and accurately quantifying asphalt-aggregate interface binding energy and adhesion work in combination with molecular dynamics, and constructing a cross-scale damage evolution model; a physical information neural network is used for embedding an improved Paris formula, actually measured data and a physical rule are deeply fused, and the locality hypothesis of a traditional model is effectively corrected.

The invention provides an intelligent asphalt pavement segregation detection method based on multi-source data analysis, and relates to the technical field of road engineering detection.The method comprises the steps that a to-be-detected road section is determined, and multi-source data of the to-be-detected road section is obtained; preprocessing the multi-source data; constructing a double-branch neural network detection model which comprises a first branch detection model and a second branch detection model, and inputting the preprocessed optical data and laser point cloud data into the pre-trained first branch detection model to obtain a grading segregation distribution result; inputting the preprocessed thermal imaging data into a pre-trained second branch detection model to obtain a temperature segregation distribution result; performing conjoint analysis on the grading segregation distribution result and the temperature segregation distribution result to generate a comprehensive segregation index; and outputting a detection result according to the comprehensive segregation index. According to the invention, comprehensive, accurate and automatic detection of the segregation degree of the asphalt pavement can be realized, and a scientific basis is provided for pavement quality evaluation and maintenance.

The invention discloses rubber powder grafted nano material composite modifier modified asphalt, a preparation method thereof and an asphalt mixture, and belongs to the technical field of modified asphalt. The modified asphalt is prepared by modifying a carboxylated nano material grafted with aminated rubber powder. According to the invention, the rubber powder and the nano material are grafted, so that the advantages of the rubber powder and the nano material can be fully played, the high temperature, low temperature, water stability and other properties of asphalt and asphalt mixtures are remarkably improved, and a new solution is provided for high performance and sustainable development of asphalt pavements; therefore, the method has good application prospect and value in the field of road engineering.

The invention provides a hot in-place recycling asphalt mixture and a construction method, and relates to the technical field of asphalt mixtures, and the hot in-place recycling asphalt mixture is obtained by recycling old asphalt pavement materials in a high proportion, reducing new material consumption and carbon emission, realizing resource recycling and green construction and introducing a regenerant to recover the performance of aged asphalt. The high-temperature rut resistance, the low-temperature crack resistance, the fatigue resistance and the interface bonding strength of the mixture are synergistically improved by matching with the styrene butadiene rubber modifier, the basalt fiber, the nano silicon dioxide and other functional materials, and the mixture is ensured to be uniform and free of segregation through precise feeding sequence, high-pressure atomization spraying and forced stirring parameter control. The defects of gray materials, oil balls and the like are avoided, the compactness, the flatness and the overall structure stability of the regenerated pavement are improved, and the problems of performance degradation and insufficient durability of a traditional regenerated mixture are solved.

The invention relates to the technical field of asphalt pavement paving, and discloses an asphalt pavement 3D intelligent paving cooperative control system and method based on BIM + GIS, and the system comprises a data fusion layer, a real-time control layer, a multi-machine cooperation and task distribution layer, and a quality closed-loop layer. The real-time control layer comprises multi-source data acquisition (positioning / temperature / compaction degree and the like) and three types of core decisions carried out by the cloud center, and the three types of core decisions carried out by the cloud center comprise feeding demand prediction (based on paving speed + thickness) of a dumper, thickness / speed adaptive adjustment of a paver and dynamic planning of a rolling path of a road roller. According to the method, real-time correction of transverse deviation and elevation deviation is achieved through combination of PID control and fuzzy control, the expansion amount of a hydraulic cylinder of the ironing plate is dynamically adjusted by associating the paving speed, the multi-source sensing technology of Beidou, IMU, laser ranging and infrared imaging is adopted, time sequence consistency data synchronization is achieved through 5G communication, and the real-time correction of the transverse deviation and the elevation deviation is achieved. And the precision and the closed-loop optimization effect can be controlled in real time.

The invention relates to the technical field of measurement and monitoring of road engineering variables, in particular to an asphalt pavement paving quality management system, which comprises a data acquisition module configured to acquire real-time meteorological data, mixture temperature parameters and pavement quality monitoring data; the viscosity analysis module is used for determining the dynamic viscosity adjustment range of the asphalt material based on the real-time meteorological data and the temperature parameters of the mixture; the temperature control module is used for regulating and controlling the mixing temperature according to the viscosity change of the asphalt material and generating a target paving temperature curve; the power optimization module is used for matching a dynamic adjustment strategy of the heating power of the screed of the paver based on the target paving temperature curve; by means of the system, meteorological and construction data are monitored in real time, parameters such as asphalt viscosity and screed power are dynamically regulated and controlled, closed-loop optimization is achieved, the paving quality is improved, and intelligent construction is achieved.

The invention discloses an asphalt pavement disease identification method based on unmanned aerial vehicle scanning, and relates to the field of asphalt pavement disease identification, and the method comprises the steps: employing an unmanned aerial vehicle to carry a multispectral imager, obtaining an orthoimage of a whole road segment through a preset route, and carrying out the preliminary feature extraction and suspected region identification; a flight path is optimized according to a suspicion degree and spatial distribution by intelligently planning a recheck route for a suspicion area, and spectral reflectivity data of a specific wave band is collected for secondary verification; color features, glossiness features and texture features are explicitly extracted for a target asphalt pavement area, quantitative extraction is carried out on disease related physical features through brightness and saturation distribution, highlight area detection, texture structure analysis and other means, the accuracy and reliability of oil flooding disease recognition are improved, meanwhile, the disease degree grade is generated, and the recognition efficiency is improved. And accurate data support is provided for asphalt pavement maintenance decision making.

The invention discloses an asphalt pavement internal disease detection method, which comprises the following steps: acquiring antenna attitude data, and correcting the antenna attitude data; acquiring acquisition parameters of the ground penetrating radar according to the corrected antenna attitude data; acquiring an original electromagnetic signal through the ground penetrating radar according to the acquisition parameters; performing feature extraction on the original electromagnetic signal to obtain a reflection feature; the reflection features are judged, abnormal reflection points are obtained, and the position and intensity data of the abnormal reflection points are extracted; obtaining an abnormal reflection point distribution diagram according to the positions and the intensities of the abnormal reflection points, and obtaining disease types of the abnormal reflection points according to the abnormal reflection point distribution diagram; generating a disease distribution diagram according to the disease type and distribution of the abnormal reflection points, analyzing the severity and range of a disease range according to the disease distribution diagram, and repairing the internal diseases of the pavement according to the severity and range.

The invention relates to an urban updated unmanned asphalt pavement compaction system and an intelligent control construction method. The unmanned asphalt pavement compaction system comprises an unmanned road roller, a server, infrared temperature acquisition equipment, environment temperature detection equipment, steel wheel temperature monitoring equipment, compaction degree monitoring equipment, vehicle-mounted laser radar equipment and a control and signal processing module. Multi-source sensing of a construction site is achieved, it is guaranteed that the pavement compaction quality can be monitored, and on the basis of multi-source sensing data obtained in real time, running and working parameters of an unmanned road roller are dynamically adjusted through the intelligent control construction method of the urban updating unmanned asphalt pavement compaction system, so that the pavement compaction quality is improved. The adaptability of asphalt pavement compaction of the unmanned road roller under different working conditions is improved, and the construction quality is further guaranteed.

The invention provides a design method and system for an ultra-large-particle-size long-service-life asphalt pavement, and belongs to the technical field of long-service-life asphalt pavement design. The method comprises the steps of obtaining basic parameter information of a pavement design project; according to the basic parameter information, the thickness and variation parameters of the pavement structure layers meeting the thickness requirement are initially planned, and the material Poisson's ratio, the temperature distribution of each structure layer and the material modulus are determined; randomly generating pavement structure layer thickness, temperature distribution, material modulus and traffic load parameters by adopting a Monte Carlo method, and carrying out pavement mechanical response calculation; checking the reliability and fatigue damage of the flexible base asphalt pavement according to a fatigue limit theory and a cumulative damage theory respectively; according to the flexible base asphalt pavement rut prediction model, pavement rut checking calculation is performed, the reliability of a pavement structure under the environment-load coupling effect is improved, and the long service life of the pavement structure is achieved.

The invention belongs to the field of asphalt mixture performance analysis, and particularly discloses a fatigue performance analysis method for an asphalt mixture of an asphalt pavement, which comprises the following steps of: synchronously acquiring a dynamic strain field and a temperature field in a material by fusing an embedded sensor in a paving and rolling construction process; a temperature-strain coupled fatigue damage evolution model is combined to construct an on-line fatigue performance analysis system oriented to the whole construction process, so that a complex heat-force coupling environment and a non-uniform compaction process in actual paving operation are effectively restored; scale effect deviation and boundary condition distortion caused by difference between laboratory test piece preparation and on-site working conditions are remarkably reduced, and meanwhile, in the online detection process of the fatigue performance of the asphalt mixture, instant quantitative judgment of the performance state of the pavement structure is realized by positioning a damage remarkable overrun area; and the in-situ monitoring capability on the initial fatigue damage is fully reflected, so that the abnormal strain accumulation process before microcrack initiation can be captured.

The invention discloses a heavy traffic asphalt pavement damage evolution prediction system, and relates to the technical field of road engineering, and the system comprises a data acquisition module which is used for obtaining continuous multi-frame time sequence images of pavement cracks, a vehicle-mounted axle load spectrum and environment temperature and humidity data; the image processing and space-time modeling module is used for performing multi-scale fractal processing and dynamic time warping on the time sequence image and calculating a cross-scale fractal dimension sequence; the material performance association module is used for establishing and updating a probability association model of the fractal dimension and the shear modulus in real time according to the test data of the dynamic shear rheometer; the multi-physics field data fusion module is used for performing multi-physics field feature fusion through the fractal attention network to generate a multi-physics field collaborative damage correction factor; and the damage prediction and early warning module is used for predicting a fractal dimension growth trend through a fractal domain adaptive transfer learning algorithm, and outputting damage evolution early warning based on a viscoelasticity phase consistency verification result.

The invention discloses an asphalt pavement base crack identification method and device based on a ground penetrating radar, and belongs to the technical field of road engineering pavement maintenance. The method comprises the following steps: 1) carrying out crack image identification on a radar slice map through a YOLOv8n model; 2) based on an identification result, extracting A-scan signals of a crack area, and classifying time-frequency features by using a Light GBM model; and 3) clustering classification results through a'multi-segment clustering + PCA 'analysis method, and filtering false detection cracks. The device is used for executing the method. According to the method, the map and the time-frequency characteristics are fused, the problem that the false detection rate is high due to subjective labeling or objective interference of a single identification method is solved, experiments show that the false detection rate is reduced to 2.8% from 11.2%, and the accuracy and engineering applicability of crack identification are improved.

The invention relates to the field of highway construction, in particular to an intelligent asphalt pavement rolling control method and system, and the method comprises the steps: deploying machine vision equipment to collect an image of a just-paved asphalt mixture, recognizing the segregation degree in combination with a convolutional neural network, and generating a segregation distribution thermodynamic diagram with geographic coordinates; the road roller is integrated with a positioning sensor, a temperature sensor, a vibration sensor and a speed sensor, relevant parameters are collected, and the real-time compaction degree is calculated. The thermodynamic diagram and the compaction degree are subjected to space-time matching, optimal operation parameters are calculated through a dynamic coupling model on the basis of data such as the segregation degree and the temperature of a target area, the optimal operation parameters are wirelessly sent to a road roller control system to adjust speed and vibration parameters, and a road roller feeds back the new compaction degree after execution to form closed-loop control. The problem that separation and compaction control are disjointed in the prior art is solved, separation information and the compaction process are deeply fused, and underpressure of a separation area and overpressure of a uniform area are avoided.

The invention discloses an asphalt pavement maintenance strategy intelligent generation method and system, and relates to the technical field of road engineering.The maintenance strategy generation method comprises the steps that traffic analysis data information and traffic load data information are extracted from a multi-source traffic monitoring system, and the traffic analysis data information and the traffic load data information are obtained through a laser scanning and image intelligent recognition algorithm; analyzing the pavement structural disease level in each grid unit; according to the road surface structural disease level, the road condition risk level of each grid unit under the traffic load and damage superimposed effect is analyzed, a risk response area is divided, and a service life loss analysis instruction is generated; analyzing an accelerated decline trend of pavement structure deterioration of each grid unit in the risk response area to determine a life reduction value of each grid unit in the risk response area; after comparison, generating a pavement maintenance strategy of a corresponding grade; the maintenance strategy generation method has the advantages of being high in real-time performance, fine in area recognition and dynamically adjustable in strategy response.

The invention discloses an asphalt pavement maintenance decision-making method based on a multi-objective function. The method comprises the following steps: S1, constructing a highway asphalt pavement maintenance measure library; s2, calculating the total carbon emission amount of each maintenance measure in S1; s3, the economic cost of each maintenance measure in the S1 is calculated; s4, calculating an evaluation index of the asphalt pavement maintained by each maintenance measure in the S1; s5, dividing the asphalt pavement into a plurality of road section units, and establishing a 0-1 linear programming model; s6, solving the model established in the step S5 based on an NSGA-II algorithm to obtain a group of non-dominated solutions; and S7, selecting an optimal solution from the non-dominated solutions obtained in the step S6 by adopting an ideal point method to obtain an optimal maintenance measure of each road section unit. According to the method, the problems that factors such as economic benefits, pavement performance and traffic conditions are pursued unilaterally in the project-level asphalt pavement maintenance decision-making process, the influence of a maintenance scheme on the environment is neglected, and decision-making is carried out only by relying on subjective experience of engineers are solved.

Low-carbon, carbon-neutral, and carbon-negative asphalt composites are disclosed. The composites comprise an asphalt binder and a functionalized biochar incorporated as a partial replacement for the binder and / or mineral filler. The biochar is physically, chemically, or mineralogically modified to enhance dispersion, interfacial bonding, mechanical performance, and carbon sequestration. The invention further includes methods for producing such composites, biochar-based additive compositions, and kits for practical implementation. Applications include asphalt pavements, waterproofing membranes, crack sealants, conductive deicing systems, and VOC-reducing asphalt mixtures. The resulting materials demonstrate improved durability, thermal and electrical properties, and significant reductions in greenhouse gas emissions.

The invention discloses a road roller intelligent control method based on a road surface compaction quality real-time state, an upper computer mainly judges compaction states and quality such as compaction degree, strength and modulus in a road surface compaction process in different rolling stages in situ through an in-situ detection vehicle, and a lower computer mainly aims at parameters fed back by the in-situ detection vehicle. According to the method, road surface compaction states and rolling process models in different rolling stages are learned and predicted, target function optimization considering the compaction degree, strength, modulus and the like is obtained, and the vibration frequency, amplitude, running speed, rolling times and the like of the road roller are adjusted in time, so that accurate regulation and control of the road surface compaction quality in different rolling stages are achieved. On the basis of comprehensively detecting the compaction quality of the asphalt pavement, automatic optimization of a rolling process considering target functions such as the compaction degree, the strength and the modulus can be completed, and the method has the advantages that pressing, detection and adjustment are carried out simultaneously, and the method is accurate and reliable.

The invention discloses a self-repairing high-energy-storage ice-snow-resistant double-layer composite microcapsule suitable for an asphalt surface layer and a preparation method and application thereof, and relates to a microcapsule preparation method and application thereof. The invention aims to solve the technical problems of poor core material release and self-healing effects, unstable shell wall material, low heat conductivity, easy leakage and single function of the existing self-repairing microcapsule for the asphalt pavement. The double-layer composite microcapsule is sequentially composed of an inner phase change microcapsule core, an inner phase change microcapsule shell, an outer self-repairing microcapsule core and an outer self-repairing microcapsule shell from inside to outside. Preparing an internal phase change microcapsule core from n-caprylic acid and tetradecane; preparing an internal phase change microcapsule shell by using a carbon nano tube and a double polymer; preparing an external self-repairing microcapsule core from bio-oil and a carbon nanotube; the outer self-repairing microcapsule shell is prepared from the carbon nano tube and the double polymer. Compared with a common asphalt pavement, the healing index of the surface layer of the asphalt pavement prepared from the double-layer composite microcapsule is improved by 8.1%-26.3%. The method can be used in highway fields.

The invention belongs to the technical field of asphalt pavement construction, and discloses a municipal road reconstruction engineering asphalt pavement construction quality control method, which specifically comprises the following steps: 1, carrying out three-dimensional laser scanning surveying and mapping on longitudinal and transverse joints and crack distribution of an original cement concrete pavement in the treatment research of the original pavement; the geometrical morphology and modulus characteristics of an original pavement are accurately analyzed through three-dimensional laser scanning and a dynamic modulus test, the thickness design of an asphalt layer is optimized, adaptive materials are intelligently screened according to climate characteristics and traffic load grades of a construction area, and the performance stability of an asphalt mixture is improved; meanwhile, by means of the intelligent paving technology, the flatness and thickness uniformity of a paving layer are guaranteed, the paving temperature is accurately controlled, the paving performance of the mixture is improved, rolling parameters can be automatically adjusted according to key information such as the paving thickness and the temperature, and the uniformity of the compaction quality is improved.

The invention belongs to the technical field of asphalt pavement maintenance management, and particularly relates to abnormal value identification according to characteristics of maintenance data and a quartile spacing method to obtain a normal data set and an abnormal data set after abnormal maintenance measures are removed; constructing a long short-term memory network model, and finding a group of optimal hyper-parameters by using a quintuple cross validation grid search method; and training by using the LSTM model and the collected normal data set to obtain the optimal weight and offset parameter of the model, and obtaining an asphalt pavement maintenance engineering data prediction model for predicting and filling the vacancy in the data set. The invention provides a pavement maintenance data abnormal value cleaning method considering time sequence characteristics. According to the method, reference is provided for asphalt pavement management data cleaning research, the availability of data in a pavement management system is improved, and a decision maker can be helped to formulate a scientific and reasonable pavement maintenance scheme.

An automatic generation method for three-dimensional morphology of ruts in asphalt pavements comprises: constructing a standard rut cross-section representation model, classifying ruts, acquiring detection data of a rutted section of an asphalt pavement, selecting different rut cross-sections at equal intervals in a longitudinal direction of the pavement, denoising and smoothening the rut cross-sections, selecting feature points according to geometric fluctuation features of the rut cross-sections, connecting the feature points and fitting a cross-sectional curve based on an evolution law of rut deformation, and fusing multiple reconstructed rut cross-sections to realize automatic generation and visualization of three-dimensional morphology of a rut.

The invention discloses a semi-rigid asphalt pavement crack depth estimation method, equipment and a medium, and relates to the technical field of road detection. The method comprises the steps of collecting a high-resolution image of a road surface through a mobile detection platform, segmenting a crack region in the high-resolution image by adopting an image segmentation model, and obtaining a binary image of a crack; pixel accumulation, edge detection, skeletonization, skeleton trimming and orthogonal projection are carried out on the crack binary image to extract surface parameters of the crack, and the surface parameters comprise the type, the length, the width and the area; inputting the fracture surface parameters into the fracture depth prediction model, and outputting a fracture depth prediction value; and generating a crack depth grade label according to the depth predicted value, and outputting a corresponding maintenance strategy. According to the method, the crack surface parameters and the pavement structure parameters are combined, the prediction result has good accuracy and consistency through the coupling relation with the depth index, and the method adapts to different crack types and working conditions.

The invention discloses an asphalt road void ratio detection method using a three-dimensional ground penetrating radar, and belongs to the technical field of asphalt road detection.The asphalt road void ratio detection method includes the following steps of S1, a preparation stage, S2, road surface scanning, S3, water spraying operation and S4, data processing and analys.According to the scheme, sampling or destructive testing does not need to be conducted on a road surface, and damage to the road surface is avoided. Therefore, the integrity of the pavement is protected, and interference and repair cost in the detection process are reduced. The three-dimensional ground penetrating radar is used for scanning, and the porosity data of the road surface can be rapidly obtained. Compared with a traditional method, the technology has the advantages that the detection time is greatly shortened, the working efficiency is improved, and the method is particularly suitable for large-area pavement detection. Through the innovative technical means, the precision, efficiency and reliability of asphalt pavement void ratio detection are remarkably improved, and powerful technical support is provided for pavement quality evaluation and maintenance.

The invention belongs to the field of road maintenance detection, and discloses an asphalt pavement crack detection method and system based on image analysis, electronic equipment and a storage medium, and the method comprises the following steps: collecting an image of an asphalt pavement, and preprocessing the collected image to obtain a first image; segmenting the preprocessed image by using a full convolutional neural network, and performing morphological processing on the segmented image to obtain a second image; calculating a gray level co-occurrence matrix of the second image and extracting texture features, detecting edge information of the second image by using an edge detection algorithm, and combining the texture features with the edge information to obtain a crack candidate area; constructing a convolutional neural network model, and training the convolutional neural network model through the historical crack image and the historical non-crack image to obtain a crack recognition model; and inputting the crack candidate region into a crack identification model for crack identification to obtain a crack identification result.

The invention belongs to the technical field of asphalt pavement repairing, and particularly relates to a local repairing technology of an asphalt pavement, which comprises the following specific contents: detecting a disease range by adopting ground three-dimensional laser scanning or ground penetrating radar, determining a repairing boundary, sampling and detecting the aging degree, the moisture content and the grading type of the asphalt of the original pavement, and determining the repairing quality of the asphalt pavement. According to the method, the bonding strength of the repairing material and the asphalt layer of the original pavement is enhanced by heating and activating the interface of the original pavement and emulsifying the asphalt bonding layer, and matching the repairing material with the shrinkage coefficient of the original pavement and reinforcing and compacting the edge, so that the condition that the repaired position is cracked, loosened and damaged in a short time is avoided; warm-mixed asphalt is adopted, the heating temperature is reduced by 40-60 DEG C, cold-mixed emulsified asphalt is popularized, and the asphalt does not need to be heated, so that release of a large amount of volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs) and dust is effectively avoided, and air pollution is avoided.

The invention discloses high-viscosity and high-elasticity modified asphalt and a preparation method thereof, and belongs to the technical field of highway engineering. The high-viscosity and high-elasticity modified asphalt is prepared from the following raw materials in parts by weight: 100 parts of matrix asphalt, 4 to 5 parts of styrene-butadiene-styrene block copolymer, 1 to 2 parts of polypropylene particles, 1 to 2 parts of TMC modifier, 1.5 to 3 parts of compatilizer, 0.5 to 1.5 parts of amide wax, 0.3 to 0.5 part of nano montmorillonite, 0.5 to 1 part of flexibilizer and 0.1 to 0.2 part of stabilizer, wherein the TMC modifier is a mixture formed by mixing simethicone, amino silicon oil, lauryl phosphate and castor oil polyoxyethylene ether according to the mass ratio of 5: 3: 1: 1. The high-viscosity and high-elasticity modified asphalt provided by the invention is high in softening point, good in viscosity and elasticity recovery capability at 60 DEG C, good in water resistance, aging resistance, weather resistance and high-temperature stability, and small in kinematic viscosity at 170 DEG C. The high-viscosity and high-elasticity modified asphalt provided by the invention is good in construction workability, and is beneficial to prolonging the service life of an asphalt pavement.

The invention provides a two-component permeable super-viscous anti-freezing coating and a construction process and equipment. The two-component permeable super-viscous anti-freezing coating comprises a component A, namely a high-permeability super-viscous anti-freezing coating consolidation material (anti-freezing component), and a component B, namely a high-permeability super-viscous anti-freezing coating carrier anti-skid material (carrier component). By utilizing special equipment, an anti-freezing material, emery, a penetrating agent, an adhesive, modified emulsified asphalt and the like are uniformly mixed and spread on an asphalt pavement of a road, and the double-component permeable super-viscous anti-freezing coating has the effects of melting ice and snow, pre-maintaining the pavement, filling tiny cracks and surface gaps, preventing water, inhibiting looseness and the like; the emery can increase the roughness degree of the road surface and play roles in increasing the friction coefficient of the road surface and ensuring the driving safety, so that the anti-skid performance of the road surface is improved, the damage of water, ice, snow and the like is avoided, and the purposes of protecting the structure of the road surface and prolonging the service life of the road surface are achieved; the method is an economical, effective, convenient and fast preventive maintenance measure.

The invention provides a construction device and method based on real-time monitoring of an asphalt pavement. The method comprises the following steps: collecting a visual detection image after paving an asphalt mixture in a target construction area; all asphalt aggregate particles are extracted from the collected visual detection images, the particle size characteristics of all the asphalt aggregate particles are determined, and aggregate groups in different particle size ranges are obtained according to all the particle size characteristics; obtaining the static distribution quantity of each aggregate group, determining the static boundary information of all aggregate groups in the visual detection image, and further determining the paving uniformity of the target construction area according to the static boundary information and all the static distribution quantities; and dynamically adjusting the screw pitch and the spiral rotating speed of a spiral material distributing machine in the asphalt concrete paver during asphalt pavement construction through the paving uniformity. By the adoption of the scheme, in the construction process of the asphalt pavement, the paving uniformity of asphalt paving can be monitored in real time, the paving parameters can be automatically adjusted, and therefore the overall paving uniformity in the construction process is improved.