1477 results about "Asphalt pavement" patented technology

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 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.

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 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 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 relates to the technical field of asphalt material preparation, in particular to a cold-mixing and cold-spreading waterborne acrylic hybrid epoxy environment-friendly asphalt material preparation process which comprises the following steps: physically mixing waterborne acrylic emulsion and waterborne epoxy emulsion to obtain waterborne acrylic hybrid epoxy emulsion; adding the asphalt pavement milling material and an activating agent into vibration stirring equipment, and stirring to obtain an activated milling material; after the activated milling material is obtained, continuously adding the water-based acrylic hybrid epoxy emulsion, the curing agent and the cold-mixed asphalt modifier into the vibration stirring equipment, and stirring and coating at normal temperature; pure water is added into the vibration stirring equipment, and the torque of the vibration stirring equipment and the temperature of the asphalt mixture are collected within a preset time period after the pure water is added; determining a local coating non-uniform evaluation value and a viscosity evaluation coefficient of the asphalt mixture; the curing reaction in the vibration stirring equipment is regulated and controlled, and the prepared asphalt material is obtained. The mechanical property of the prepared asphalt material is improved.

The invention relates to the field of road engineering, in particular to a multispectral imaging evaluation system and method for the aging degree of an asphalt pavement, and the method comprises the steps that a multispectral imaging module collects pavement spectral data; the topological feature extraction module is used for performing multi-scale feature decomposition on the spectral data and extracting topological structure features; the spectral line attention calculation module calculates weight coefficients of different spectral lines and generates weighted feature vectors; the time sequence feature learning module processes the time sequence change of the feature vector and captures an aging evolution rule; the life prediction module determines the current aging state based on the state vector, generates a plurality of possible aging evolution paths, and determines the pavement aging grade and the remaining life; the decision support module generates a maintenance decision suggestion according to the aging grade and the remaining life, and the multi-spectral imaging technology and the deep learning algorithm are innovatively combined, so that high-precision evaluation of the aging degree of the asphalt pavement and accurate prediction of the remaining life are realized, the scientificity of the maintenance decision is remarkably improved, and the maintenance cost is reduced.

The invention particularly relates to a bituminous pavement crack multi-scale segmentation method based on image recognition, which relates to the technical field of crossing of computer vision and road engineering, and comprises the following steps: extracting multi-scale features from shallow details to deep semantics, balancing feature expression capability and vehicle-mounted real-time processing requirements, and providing a multi-level feature source for feature fusion; a channel and space double-branch attention architecture is constructed, features of each coding stage are dynamically screened, noise is suppressed, and refining features are generated through dynamic residual fusion. In the feature fusion stage, a channel and space double-branch attention architecture is adopted, useful features are dynamically screened, details and semantics are balanced through a dynamic threshold correction mechanism, and segmentation imbalance caused by low-quality input is avoided; in the post-processing stage, background false detection, crack breakpoints and edge sawteeth are eliminated through a three-step progressive process, and multi-index comprehensive evaluation such as intersection-to-union ratio and F1-score is combined to ensure that a segmentation result meets the requirements of pavement maintenance engineering on precision and stability.

The invention relates to the technical field of pavement compactness detection, and discloses an asphalt pavement compactness multi-source sensing fusion detection and quality evaluation system, which comprises a data processing module for filtering and standardizing synchronously acquired multi-dimensional physical parameter data of an asphalt pavement to generate a standardized data stream; the data fusion module is used for carrying out fusion calculation on the standardized data flow by adopting a self-adaptive weighted fusion algorithm to obtain consistent fusion data; the quality evaluation module is used for generating a compaction degree evaluation result according to the consistency fusion data and a preset compaction degree calculation model; and the result output module is used for converting the compaction degree evaluation result into a graphical interface and a digital report and outputting the graphical interface and the digital report. The method can effectively solve the problems that a traditional coring method is high in destructiveness and low in efficiency, data of a single sensor is one-sided, and data of multiple sources are inconsistent, achieves efficient and accurate compaction degree quality evaluation, and remarkably improves the efficiency and reliability of construction quality monitoring.

The invention belongs to the technical field of pavement monitoring methods, and particularly discloses a distributed optical fiber permanent deformation monitoring method for an asphalt pavement under a moving load. The method comprises the following steps: laying a single-mode optical fiber in a test piece; laying a full-bridge strain gauge in the test piece; monitoring an optical fiber vibration signal of the test piece during the movement of a test wheel and a strain change of the test piece during the movement of the test wheel in real time through a strain acquisition instrument; processing the optical fiber vibration signal and the strain change by using matlab data analysis software; analyzing the data change trend according to the processed optical fiber vibration signal and the strain change, and establishing a mathematical relationship between the two; and according to the mathematical relationship, distributed monitoring of the permanent deformation of the asphalt pavement under the moving load by the optical fiber vibration signals is realized. By the adoption of the bituminous pavement distributed optical fiber permanent deformation monitoring method under the moving load, real-time, dynamic, large-range, long-distance and high-precision monitoring of bituminous pavement permanent deformation is achieved, and the defects in the prior art are overcome.

The invention relates to the technical field of intelligent construction of road engineering, and discloses an expressway asphalt pavement construction data analysis and processing system, the system performs digital modeling on an asphalt mixture and anchors the asphalt mixture to a pavement three-dimensional coordinate by creating a material state vector including a static attribute, a dynamic state and a process resume, and the system adopts a heat transfer model to construct an asphalt pavement construction data analysis and processing system. And the predicted temperature of the target vector at the future interception moment of the road roller is updated in real time and forwards simulated. Meanwhile, the system calculates a dynamic compactability window according to the compaction history and the material type, compares the predicted temperature with the window, generates a feedforward control instruction of a standard, priority or waiting operation, converts the feedforward control instruction into visual guidance, and issues the visual guidance to the vehicle-mounted terminal, so that prospective control is realized. According to the invention, the conversion of construction control from passive lag to active feedforward is realized, the fineness of the compaction process is improved, and a reliable digital quality tracing mechanism is established.

The invention relates to a digital twinning fused material-equipment collaborative crack repair design method and equipment, and the method comprises the following steps: building an electromagnetic-thermal field coupling model, and obtaining pavement temperature field distribution, the electromagnetic-thermal field coupling model being a system combining microwave heating equipment, an asphalt pavement, a crack and a repair material; based on the mapping relation between the pavement temperature and the dynamic modulus, a pavement compaction model under the action of a road roller is established through finite element simulation; actual pavement parameters are obtained, a key parameter combination of a crack repairing material and microwave heating equipment is inversely optimized according to the pavement compaction model, and the key parameter combination comprises an electromagnetic loss parameter E, heating power W, heating width b and heating time t; and designing a crack repairing material and microwave heating equipment based on the final optimized key parameter combination. Compared with the prior art, the method has the advantages of accurate repair, convenient construction, high repair efficiency, small environmental disturbance and the like.

The invention discloses a multi-element mixed enhanced intelligence-based cross-material pavement disease adaptive identification method, relates to the technical field of road intelligent operation and maintenance, and solves the technical problems that the identification rate is suddenly reduced and the false detection and omission ratio is high in a cross-material scene due to the fact that a model is developed for a single material or a general model is used in the prior art. The method comprises the following steps: S1, constructing a cross-material pavement disease image sample library; s2, constructing a pavement disease identification visual large model; s3, constructing a pavement disease pixel-level integrated enhanced intelligent recognition model; and S4, inputting a to-be-detected image to the trained pavement disease identification visual large model and the pavement disease pixel-level integrated enhanced intelligent identification model respectively, obtaining fusion output according to the adjusted fusion weight, and finally realizing pavement disease multivariate hybrid enhanced intelligent identification. The method can be simultaneously suitable for disease identification tasks in various material environments such as asphalt pavements, cement pavements and composite material pavements, and high-precision intelligent identification in a cross-material scene is realized.

The invention discloses a real-time monitoring and closed-loop regulation and control method and device for construction quality of an asphalt pavement, and relates to the technical field of intelligent monitoring of road construction. The method comprises the steps of collecting multi-modal data in a construction process and performing space-time alignment to generate a space-time aligned multi-modal data set; constructing graph structure data of the construction area based on the set; extracting a node embedding vector by using a graph neural network; synchronously outputting the compactness, the temperature uniformity index and the flatness index through a multi-task prediction model based on the vector; identifying a construction track abnormal area based on the road roller track data; and generating a construction quality digital twinborn model by integrating the information, and performing feedback regulation on an automatic control system of the road roller based on the model. Through multi-modal data fusion, graph structure modeling and multi-task collaborative prediction, real-time monitoring and dynamic regulation and control of the construction quality of the asphalt pavement are realized, the prediction precision can be effectively improved, and the monitoring efficiency and accuracy are remarkably improved.

The invention discloses an asphalt mixture component segmentation method, device and equipment, and relates to the technical field of asphalt pavement construction control, and the method comprises the steps: obtaining an initial two-dimensional image of an asphalt mixture section, and carrying out the preprocessing of the initial two-dimensional scanning image, and the preprocessing comprises the contrast enhancement and light field correction. Component division is carried out on the preprocessed image through a double-threshold segmentation method, morphological post-processing is carried out on the initial segmentation image, and each separated component segmentation image is obtained; and calculating the difference value between the image area ratio and the actual volume ratio of each component segmentation image, and calculating the relative error between the image screening grading and the actual screening grading of the aggregate components. When the difference value or the relative error exceeds the preset threshold range, the image processing parameters are adjusted, the segmentation operation is executed again, the target segmented image is obtained, the difference value and the relative error of the target segmented image are both within the preset threshold range, and the problem that the segmentation precision of the asphalt mixture components is insufficient is solved.

The utility model discloses an asphalt pavement indoor skid resistance and wear resistance test device which comprises a constant temperature and humidity chamber and a console for regulating and controlling parameters in a test process, the constant temperature and humidity box comprises an upper box body and a lower box body which are communicated with each other, a temperature and humidity control device is mounted in the lower box body, an acceleration loading device is mounted in the upper box body, and the console is connected with the acceleration loading device. The device disclosed by the utility model can be used for simulating the damage to the skid resistance and wear resistance of the asphalt pavement in the driving process of a vehicle under the conditions of different loads, speeds, temperatures and humidity, testing the wear resistance of the asphalt pavement, and monitoring and storing the skid resistance of the pavement in real time. The equipment is simple to operate, short in test period and convenient to transport, test conditions are easy to control, and convenient conditions are provided for asphalt pavement skid resistance and wear resistance indoor tests.

The invention discloses a porous asphalt concrete gap blockage identification method based on pavement noise signals, and belongs to the technical field of asphalt concrete blockage identification, and the method comprises the following steps: S1, collecting tire-pavement contact original noise signal audio data, and carrying out the preprocessing; s2, carrying out pavement gap blockage degree sensitive correlation analysis, and extracting multi-dimensional acoustic features; s3, dividing a single-layer drainage asphalt pavement data set and a double-layer drainage asphalt pavement data set, and giving a blockage level label to obtain a marked data set; s4, constructing a deep residual neural network model, and performing training and verification to obtain a gap blockage degree identification model; and S5, identifying porous asphalt concrete gap blockage. According to the method, the accurate classification of the gap blockage degree is realized through the blockage recognition model based on the acoustic characteristics, the optimal cleaning and maintenance opportunity can be determined, a scientific decision basis is provided for the maintenance of the porous asphalt concrete pavement, and the pertinence and economy of the maintenance are improved.

The invention discloses a method for predicting the residual life of an existing asphalt pavement structure, particularly relates to the technical field of computer simulation and data processing, and is used for solving the problem that the existing prediction method cannot efficiently represent the non-uniformity of an existing pavement material and the dynamic environment load influence on the premise of ensuring the precision. Existing damage data of a road surface are acquired to construct a simulation model reflecting a real initial state, material fatigue parameters are acquired in combination with cross-scale analysis, a dynamic environment boundary is driven by utilizing climate time sequence data, and then time-frequency coherence analysis is performed on a damage mode and a climate load to identify a high-threat working condition, so that the high-threat working condition is identified. And finally, preferentially operating high-fidelity thermal-mechanical coupling numerical simulation aiming at a high-threat working condition, and mapping damage evolution data output by simulation to a macroscopic performance degradation process so as to determine the residual fatigue life.

The invention relates to the technical field of recycling of renewable resources, in particular to an asphalt pavement milling material cold-recycled prefabricated part and a preparation method, and the asphalt pavement milling material cold-recycled prefabricated part is prepared from the following raw materials in parts by weight: 45 to 53 parts of waste pavement milling material with the particle size of less than 4.75 mm, 19 to 27 parts of waste pavement milling material with the particle size of 4.75 to 9.5 mm, 20 to 28 parts of stone chips, 1 to 1.4 parts of mineral powder, 1.6 to 2.0 parts of silica fume, 4.6 parts of water, 2.3 to 2.7 parts of cement and 2.3 to 2.7 parts of foamed asphalt. According to the invention, the waste asphalt pavement milling material is used as the raw material of the concrete prefabricated component, so that the resource is saved, the utilization rate of the asphalt milling material is increased, and the green development concept is met; the prefabricated parts are manufactured through a cold regeneration process, compared with a traditional hot mix plant regeneration process, energy is saved, environment friendliness is achieved, emission of greenhouse gas is reduced, and therefore the problems that the hot mix plant regeneration mode is high in cost and carbon emission are solved.

A glass powder surface gradient activation-asphalt interface bonding enhancement technology is created for the first time, and the industry bottleneck that the compatibility of waste glass and asphalt is poor is broken through. The core of the method comprises the following steps: 1, an original pretreatment process: carrying out three-stage crushing, wet magnetic separation (the magnetic field intensity is 1.2 T), plasma etching (the ratio of Ar to O2 is 4: 1, and the power is 800W) and controllable ball milling (zirconium oxide balls are used for ball milling) on waste glass; according to interface molecular engineering, a bifunctional silane coupling agent (KH-792: gamma-aminoethyl aminopropyl trimethoxy silane) and titanate (NDZ-201) are compounded with a modifying agent (the mass ratio is 3: 1), and a-Si-O-Ti-cross-linked network 3 is constructed on the surface of the glass powder through in-situ hydrolytic condensation. According to mixture collaborative design, mineral powder is replaced by 35-55% of activated glass powder, and the particle size ratio of the activated glass powder to the mineral powder is 1: 2, D90 is smaller than or equal to 20 [mu] m < 2 >, D90 is smaller than or equal to 20 [mu] m < 2 >, and D90 is smaller than or equal to 20 [mu] m < 2 >. The technical effect of forming a core-shell structure reinforced phase in the SBS modified asphalt is as follows: the dynamic stability reaches 5032 + / -210 times / mm (JTGE20-2011T0719), and compared with the traditional mixture, the water sensitivity (TSR) is improved by 79.7% from 81.3% to 96.5%.

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.

The invention relates to an intelligent regulation and control method and system for a pavement asphalt mixture paving temperature field, computer equipment and a computer readable storage medium. The method comprises the steps that an infrared temperature matrix, internal temperature gradient data and environment and equipment operation parameters of a paving area are collected; and based on the temperature gradient data, carrying out compensation correction on the shielding area in the infrared temperature matrix. And fusing the corrected surface temperature matrix with the internal temperature gradient data to form a three-dimensional temperature field tensor. And inputting the tensor into the prediction model, and outputting future temperature field prediction data in combination with environment and equipment parameters. And generating a hierarchical control instruction set according to the local temperature difference, the temperature change slope and the lowest temperature threshold in the prediction data, and distributing the hierarchical control instruction set to a corresponding execution system. And acquiring actual temperature data after instruction execution, calculating errors and dynamically updating prediction model parameters. The paving uniformity, compactness and long-term durability of the asphalt pavement are improved.

The invention discloses a radar and deep learning-based road surface internal disease three-dimensional morphology identification method, which integrates a novel technical path of qualitative identification and quantitative reconstruction, provides a high-precision and quantifiable reference for subsequent non-damage assessment by constructing a disease three-dimensional geometric model and reversely calibrating radar map characteristic parameters, and improves the accuracy and the accuracy of the three-dimensional morphology identification of a road surface internal disease. The problem that the three-dimensional morphology characteristics of the internal diseases of the asphalt pavement are difficult to accurately obtain at present is solved, and a calibration method is provided for obtaining the three-dimensional morphology characteristics of the internal diseases of the pavement based on a ground penetrating radar technology. And meanwhile, geometric data support is provided for mechanical response analysis and performance attenuation law research of the existing asphalt pavement structure containing internal diseases.

The invention belongs to the technical field of asphalt pavement materials, and particularly relates to a high-permeability asphalt regenerant as well as a preparation method and application thereof, and the high-permeability asphalt regenerant is prepared from the following components in parts by weight: 100 parts of base oil, 20-50 parts of oil slurry, 5-20 parts of plasticizer and 5-15 parts of anti-aging agent. The high-permeability asphalt regenerant provided by the invention can effectively optimize the composition of old asphalt components, improve the interface fusion efficiency of new asphalt and old asphalt, and enable asphaltene to be better dispersed in aromatic components and saturated components by virtue of colloid to form a stable colloid structure; the indexes such as high and low temperature performance and water stability of the recycled asphalt mixture are improved, the temperature sensitivity of asphalt is reduced, the influence of external environment temperature on asphalt properties is reduced, and the recycled asphalt has excellent low temperature performance; the pavement performance of the RAP material is recovered, so that the performance of the aged asphalt is basically recovered to a non-aged level, and the service life of the asphalt material is prolonged.

The invention discloses an AC pavement full-life cost and carbon emission prediction method based on a fatigue curve, and the method comprises the steps: modeling an asphalt pavement structure of a structure A and a structure B, and enabling the structure A and the structure B to be different in surface layer material and surface layer thickness; the structure A adopts a surface layer material with a known PQI exponential decay rule, and the structure B adopts a novel surface layer material to be calculated; respectively carrying out fatigue tests on surface layer materials of the structure A and the structure B to obtain respective fatigue curves; performing PQI-damage curve fitting on the structure A to obtain fitting parameters; modeling through fatigue index migration, predicting a PQI curve of the structure B, and determining a maintenance scheme of the structure B according to the PQI index of the structure B; and calculating the whole life cycle cost and carbon emission of the structure B. According to the method, the repair time interval during the road use period can be quantitatively predicted, so that the whole life cycle cost and carbon emission of the road structure are calculated, and the adaptability evaluation efficiency of the new material pavement structure in the early stage is improved.

The invention discloses a warm mix asphalt regenerant, a preparation method thereof and an asphalt regeneration method, and belongs to the technical field of road building materials. The warm mix asphalt regenerant comprises the following raw materials in parts by weight: 15-25 parts of a viscosity reduction component, 50-70 parts of a regeneration component, 10-20 parts of a performance regulator and 3-8 parts of a composite additive. The invention provides a composite asphalt regenerant with warm mixing and regeneration dual functions, which is particularly suitable for low-temperature regeneration construction of high-proportion asphalt pavement recycled materials, realizes high-mixing-amount (70-100%) regeneration of the asphalt pavement recycled materials under the medium-temperature condition of 100-130 DEG C, keeps excellent balance of high-temperature and low-temperature performance of the regenerated asphalt, and has the advantages of high-temperature mixing performance, high-temperature mixing performance, high-temperature mixing performance, high-temperature mixing performance, low-temperature mixing performance, low-temperature mixing performance and the like. The regenerated asphalt keeps excellent performance balance of a softening point of 60-68 DEG C and ductility of 30-50 cm; the construction energy consumption is reduced by more than 40%; the construction process is simplified, and multiple effects are achieved by single agent.

The invention relates to the technical field of image recognition, in particular to an asphalt pavement crack detection method and system. The method comprises the following steps: collecting a road surface image of a target road section, executing illumination compensation, and generating a to-be-analyzed road surface image; determining the road indication texture of the target road section according to the gray level change condition of the pixel points in the to-be-analyzed road surface image; removing non-pavement texture features in the to-be-analyzed pavement image by using the road indication texture; identifying a linear crack region according to pavement texture features in the to-be-analyzed pavement image, associating lane information, and generating a crack feature set of each lane of the target road section; and identifying crack connectivity between adjacent lanes according to the crack feature set of each lane, and dividing maintenance priorities of cracks of the target road section based on the crack connectivity between the adjacent lanes to obtain a pavement maintenance report of the target road section. According to the invention, the precision and reliability of crack identification are obviously improved, and accurate identification of cracks of a single lane and adjacent lanes can be realized.