2357 results about "Road engineering" patented technology

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 relates to the technical field of road engineering detection, in particular to a highway pavement crack image intelligent detection system and method, and the system comprises an image acquisition module, a deep learning module, an image enhancement module, a crack measurement and calculation module, a crack development trend prediction module and an information visualization module. The core innovation of the invention lies in that a differential geometry theory is introduced to construct a crack development trend prediction module, and the module comprises a crack characterization model based on a differential manifold, a multi-scale crack evolution tensor field analysis model and a nonlinear space-time crack development prediction model. A pavement is regarded as a two-dimensional differential manifold, cracks are represented as singular curves on the manifold, a multi-scale tensor field analysis technology and a non-linear kinetic equation are combined, accurate prediction of the future development trend of the cracks is achieved, the system supports multiple image acquisition modes, transverse, longitudinal and net cracks can be accurately detected, and the detection precision is high. The method adapts to complex illumination and background conditions, and predicts the expansion rate and severity change of the crack.

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 relates to the technical field of road engineering, in particular to a construction positioning method and system for simulation equipment in a steel bridge deck pavement twinning scene, and the method comprises the steps: obtaining the positioning information and construction data of a construction site in real time, and constructing a construction site data set; performing primary processing on the construction site data set through a positioning algorithm to obtain a positioning position and construction dynamic characteristics of equipment; based on a GIS technology and a BIM architecture, constructing a three-dimensional twinborn scene model of the steel bridge deck, and numbering the three-dimensional model according to bridge deck pile numbers and pile-by-pile coordinate information; and matching the processed equipment positioning position data with the three-dimensional twin scene, and displaying the real-time position and the movement track of the equipment through a model. According to the invention, the problem of inaccurate positioning data caused by signal interference in the steel bridge deck pavement construction process is effectively solved, the accurate monitoring of the equipment position and the construction track is realized, and the comprehensive monitoring capability of the construction progress and quality is improved.

The present invention relates to the field of road engineering technology, and specifically to a non-destructive detection method and system for internal defects and compactness of concrete, the method comprising: collecting dynamic response data of the internal structure of concrete, and preliminarily determining the stress abnormality area; according to the preliminarily determined stress abnormality area, deploying an intelligent sensor array, monitoring the physical state data of the local area, and generating depth monitoring data; synchronously emitting sound waves and vibration waves in the local area, monitoring the propagation path and phase change, and obtaining propagation characteristic data; reconstructing the distribution state of concrete density, and simulating the dynamic response under different load conditions to obtain compactness detection results. Through the present invention, the problems of destructive sampling, local detection and insufficient precision existing in traditional methods are effectively solved, and high-precision and comprehensive detection of internal defects of concrete is achieved, thereby improving the safety and reliability of concrete structures.

The invention provides a highway engineering quality detection method and system based on image recognition. The method comprises the following steps: acquiring a pavement image of a target highway; performing crack identification on the pavement image to obtain a crack boundary of each surface crack in the pavement image; determining spatio-temporal evolution characteristics of each surface crack; performing trend extrapolation on each surface crack based on all crack boundaries and the spatio-temporal evolution characteristics to obtain expansion confidence of each surface crack on each potential expansion point; and determining the risk level of each surface crack according to all the extension confidence coefficients, and outputting a crack risk assessment result of the target road. By adopting the scheme of the invention, the surface crack in the pavement image can be accurately positioned, and then the expansion speed and direction of the surface crack are dynamically tracked and the risk level is evaluated according to the characteristics of the surface crack, so that the safety of highway engineering is ensured.

The invention belongs to the crossing field of road engineering technology, artificial intelligence and engineering mechanics, and particularly relates to a road structure design method based on a large model and reinforcement learning. A technical closed loop of'natural language input-parameter automatic mapping-specification standard value acquisition-finite element verification-reinforcement learning optimization 'is constructed: by constructing a load parameter mapping table and a material semantic encoder, the system can automatically convert natural language input into engineering parameters such as load, material, layer thickness and the like, and the problem of adaptability to non-standard working conditions is solved. And a deviation characteristic space is constructed by further combining a mechanical theory solution and finite element simulation, and the reinforcement learning agent is driven to quickly optimize under the condition of meeting theoretical constraints. Compared with a traditional trial calculation method and an existing intelligent optimization scheme, the method has the advantages that the number of design iterations and the material cost are greatly reduced, the safety and compliance of an output scheme are improved, and intelligent spanning from experience driving to theory guiding is achieved.

The invention relates to the technical field of carbon emission accounting, in particular to a road engineering carbon emission analysis method based on multi-source heterogeneous data fusion. The method comprises the following steps: collecting carbon emission factor multi-source heterogeneous data; performing multi-source heterogeneous data anomaly identification and correction processing on the carbon emission factor multi-source heterogeneous data to generate carbon emission factor multi-source heterogeneous standard data; performing carbon emission factor cross-modal global connection fusion processing on the carbon emission factor multi-source heterogeneous standard data to generate carbon emission factor global fusion feature data; establishing an optimization relation model of actual working condition carbon emission accounting based on the carbon emission factor global fusion feature data, and generating an optimization carbon emission accounting relation model; and performing carbon emission intelligent accounting operation on the road construction project based on the optimized carbon emission accounting relation model. According to the method, the accurate accounting of the carbon emission of the road engineering is realized by carrying out fusion analysis on the multi-source heterogeneous data.

The invention relates to the technical field of road engineering, in particular to a silt roadbed filling quality detection method and system based on multi-source data, by collecting multi-source data such as humidity data, compaction degree data, mechanical construction dynamic data and roadbed deformation data in real time, key characteristic variables are extracted by adopting a data fusion technology and a principal component analysis method, and the filling quality of a silt roadbed is detected. And on the basis of the characteristic variables, constructing a silt roadbed quality evaluation model to realize real-time prediction and evaluation of roadbed quality in the construction process. And if the detection result does not reach the target standard, the system dynamically adjusts the construction parameters through a self-adaptive control algorithm to optimize the construction process and ensure that the roadbed quality meets the preset requirement. In addition, the system displays real-time monitoring results and prediction data through a visual means, and the intelligent level of construction management is improved. The method can be widely applied to infrastructure construction of roads, railways and the like, and has high application prospects and popularization value.

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 relates to the technical field of road engineering safety monitoring, in particular to an expressway slope crack identification method based on unmanned aerial vehicle laser point cloud visualization, which comprises the following steps: multi-source data collaborative acquisition: an unmanned aerial vehicle carrying a laser radar scanner and a high-resolution optical camera flies along a multi-angle combined route, and the unmanned aerial vehicle carries a laser radar scanner and a high-resolution optical camera; synchronously acquiring side slope three-dimensional laser point cloud data and an orthoimage sequence; data fusion preprocessing: denoising and filtering the data to generate an exposed slope triangular mesh curved surface model, and mapping textures to generate a high-precision live-action three-dimensional model; performing multi-dimensional feature fusion recognition, extracting curvature and texture features, inputting the curvature and texture features into a pre-training classification model, judging and outputting a crack pixel-level position; and carrying out visual output, superposing crack information rendering and generating a quantitative report containing the length and width of the spatial position. The method is high in coverage precision and identification accuracy, and provides a reliable basis for slope safety assessment.

The invention belongs to the field of data processing, and provides a road engineering low-carbon data credible interaction method and system, and the method comprises the steps: constructing a full life cycle stage division model, generating corresponding low-carbon data according to the business activity of each stage, and adding a stage identifier, a timestamp and a spatial position label to the low-carbon data; based on a preset engineering logic, a data causal relationship and a carbon emission factor model, constructing a data context tree comprising a plurality of low-carbon data nodes, and organizing the low-carbon data nodes in different space-time ranges and life cycle stages into a life cycle data context tree with a staged conduction relationship; before data interaction is carried out, multi-dimensional verification operation is carried out on target data based on the data context tree; and calculating a credible score of the target data based on a structural path verification result, a space-time consistency verification result and a carbon factor mapping verification result, and controlling the interactive access permission of the low-carbon data according to a score result.

The invention discloses a vehicle driving optimization method based on a road surface friction coefficient intelligent prediction model, and belongs to the technical field of urban traffic road engineering and vehicle control. Collecting real-time state parameters of a front road surface in real time through a vehicle vision system, wherein the state parameters comprise road surface types and road surface conditions; according to the real-time state parameters of the front road surface, the running state parameters of the vehicle and the environment state parameters, a real-time prediction friction coefficient value between the vehicle and the road surface is output through the intelligent friction coefficient prediction model; and transmitting the real-time predicted friction coefficient value to a vehicle control system, and adjusting the power distribution of the vehicle. The road friction coefficient value can be predicted in real time, and the power distribution of the vehicle is reasonably adjusted in combination with the current state of the vehicle. A power source of the vehicle is reasonably used, so that the trafficability, the driving economy and the running stability of the vehicle are improved, the driving mileage of the vehicle is prolonged, and the switching of the driving modes of the vehicle is guaranteed to have a basis.

The invention discloses an asphalt pavement structure performance analysis method and system, relates to the technical field of road engineering, and aims to solve the problem that an asphalt pavement structure performance analysis model is insufficient in self-adaptability, and the asphalt pavement structure performance analysis method comprises the following steps: obtaining test measurement data of a drop weight deflectometer; combining the adjacent structural layers according to the similarity of the structural layer materials; different numerical simulation models are established according to different configuration parameter combinations, and structural performance evaluation indexes are calculated respectively; different samples are established according to different numerical simulation models, weights of different samples are calculated and normalized, and a sample training structure performance index calculation model is established and input; and calculating a structural performance evaluation index of the target road section according to test measurement data of the drop weight deflectometer of the target road section by applying the structural performance index calculation model. According to the asphalt pavement structure performance analysis method and system provided by the invention, the attention of the trained model to a specific sample can be improved, and the adaptive ability and prediction precision of the trained model are improved.

The invention relates to the technical field of road engineering, in particular to a method for determining the optimal construction temperature of warm-mixing synchronous regeneration of waste SBS (styrene butadiene styrene) modified asphalt, which comprises the following steps: customizing a two-component synchronous regeneration agent for SBS modified asphalt with different aging degrees; warm-mixing synchronous regenerated SBS modified asphalt at different temperatures is prepared, and thermal insulation treatment is performed to simulate the actual construction process; testing the typical rheological property of the warm mixing synchronous regenerated SBS modified asphalt; drawing a warm mixing synchronous regeneration temperature-rheological property scatter diagram, and constructing a corresponding fitting equation; ideal temperature intervals of high-temperature rutting resistance, medium-temperature cracking resistance and low-temperature fracture resistance are divided, and the intersection of the three temperature intervals is used as the optimal warm mixing synchronous regeneration temperature. According to the method, the warm mixing synchronous regeneration temperature can be quickly and accurately determined, the synergistic interaction effect of the double-component synchronous regeneration agent-warm mixing agent is exerted, and meanwhile, the performance loss of the regenerated asphalt mixture caused by secondary aging due to too high heating temperature is avoided.

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 relates to the field of performance testing of road engineering materials, and discloses an emulsified asphalt in-situ cold-recycled mixture high-temperature creep test method which comprises the following steps: preparing a test piece: presetting an old material-emulsified asphalt standard test piece, and embedding a moisture regulation and control device to generate a controllable gradient; multi-field loading: coupling an unsteady-state temperature field, a moisture gradient field and a time-varying attenuation stress field to construct a composite loading environment; synchronously aligning data: synchronously acquiring macro strain and micropore data, and realizing cross-scale alignment through a space-time matrix; performing parameter inversion: inverting nonlinear constitutive parameters by combining macro and micro data, and constraining a solution space by using a thermodynamic equation; and intelligent termination output: triggering a termination mechanism based on a multi-dimensional criterion and outputting damage evolution data. Through multi-field coupling loading, cross-scale data fusion and intelligent criterion cooperation, the problems of traditional test environment distortion, parameter deviation and criterion lag are solved, and accurate analysis of the high-temperature creep behavior of the emulsified asphalt reclaimed material and reliable prediction of the performance degradation law are achieved.

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 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 belongs to the technical field of road engineering materials, and discloses a wide-temperature-range crack pouring adhesive based on rubber modified asphalt and a preparation method thereof.The wide-temperature-range crack pouring adhesive is prepared by taking the rubber modified asphalt as a matrix through a response surface method and adding SBS, basalt fibers and a modifier. The performance of the material is tested through a conventional test, and meanwhile, a test with more characteristics in northeast regions is provided, and the performance of the material is detected through injection depth, viscosity, low-temperature stretching after aging and freeze-thaw cycle stretching. Results show that a test designed by a response surface method has very strong reliability, and the modified heating type crack pouring adhesive added with the basalt fiber can significantly improve the high and low temperature performance of the crack pouring adhesive, and also has good anti-aging performance and freeze-thaw cycle resistance. And the filling depth and the viscosity of the sealant are not obviously lower than those of the same type of sealant.

The invention provides a road surface flatness repairing method based on a scheduling algorithm and related equipment, and relates to the field of road engineering. The method comprises the following steps: acquiring image data of a target road, dividing a road surface region and sub-road surface regions according to a preset region size, and coding the sub-road surface regions; and then obtaining point cloud data of the sub-pavement areas, dividing the point cloud data into horizontal and vertical column point clouds according to the width and length of the sub-pavement areas, and determining the pavement flatness according to the difference value of the key point coordinates of each column of point clouds. And determining the sub-pavement area with the flatness lower than the first threshold value or higher than the second threshold value as a to-be-repaired position, and determining a to-be-repaired category. And then candidate maintenance vehicles with the distances to the to-be-repaired position being within a set range and matched with the to-be-repaired position in category are determined, a target maintenance vehicle is determined from the candidate maintenance vehicles in combination with a departure time priority algorithm, and finally a maintenance task is sent to the target maintenance vehicle. Accurate detection and efficient repair of the pavement flatness are realized.

The invention discloses a novel concrete pavement hardness detection device, and belongs to the technical field of detection. The invention discloses a novel concrete pavement hardness detection device, and belongs to the technical field of road engineering detection. The device comprises a springback tester, an ultrasonic tester and an analysis system, and equipment credibility parameters are generated through a springback confidence model (quantitative impact energy / angular deviation) and an ultrasonic confidence model (quantitative frequency / probe centering error); combining a pavement characteristic model (analyzing water content / temperature / steel bar density) to output an environment adaptation coefficient; further dynamically calculating a springback risk coefficient and an ultrasonic risk coefficient based on a risk model (fused vibration / carbonization depth); and finally, outputting a calibration intensity value through the intensity correction model. The method solves the defects of weak anti-interference capability and insufficient precision of a traditional method, effectively improves the detection efficiency, and is suitable for high-precision scenes such as expressways and airport runways.

The invention discloses an automatic auditing system and method for road engineering completion settlement. The system comprises a data acquisition and integration module; a data preprocessing module; a settlement index construction module; an intelligent auditing engine; an abnormity early warning and tracing module; a settlement result management module; and a data analysis and optimization module. The auditing method comprises the following steps: S1, collecting and integrating multi-source settlement data; s2, big data preprocessing; s3, constructing a settlement auditing index system; s4, performing intelligent automatic auditing; s5, performing abnormal early warning and tracing; s6, managing settlement results; and S7, performing big data driving optimization. According to the invention, multi-source data intelligent integration, full-process automatic auditing, abnormal accurate tracing and dynamically optimized big data driven settlement auditing can be realized; the method is applied to whole-process management of road engineering completion settlement, and data-driven intelligent auditing and continuous optimization control are realized in the process.

The invention relates to the technical field of road engineering, in particular to a large language model-driven road change design method, which comprises the following steps of: 1) performing rough selection by using a large language model and a prompt project, and selecting a corridor zone; and 2) performing optimization through an improved artificial potential field MAPE algorithm. According to the method provided by the invention, by applying a natural language processing technology, automatic generation of a preliminary corridor belt design scheme is realized, the manpower and time cost of a route pre-selection stage is saved, a large number of alternative schemes can be produced to assist design, and the optimization effect is also higher than that of a relatively mature genetic algorithm; the method is a successful exploration of a large language model in intelligent road line selection application.

The invention relates to the technical field of asphalt modifiers, and particularly discloses an asphalt regenerant as well as a preparation method and application thereof. The asphalt modifier comprises an oil phase, a polymer phase, a nano reinforced phase and a functional additive phase, wherein the oil phase comprises petrochemical oil and vegetable oil; the polymer phase comprises four-arm radiation star-shaped SBS and a rubber powder lysis solution; the nano reinforced phase comprises silane coupling agent modified nano montmorillonite and graphene; the functional additive phase comprises maleic anhydride grafted polyethylene and sucrose ester. The asphalt regenerant provided by the invention is suitable for various types of aged asphalt, in particular to aged polymer modified asphalt, each failure phase of the aged polymer modified asphalt is accurately repaired through a multi-phase synergistic mechanism, full-dimension regeneration of the aged polymer modified asphalt from a molecular scale to macroscopic performance is realized, and the asphalt regenerant has a wide application prospect. Excellent applicability and reliability are shown in regeneration of various types of aged asphalt, and a powerful guarantee is provided for high-quality implementation of road engineering.

The invention relates to the technical field of road engineering, in particular to a DSR-based method for rapidly predicting low-temperature performance of asphalt, which comprises the following steps: preparing an asphalt cylinder sample; performing a strain amplitude scanning test to obtain a linear viscoelasticity interval; performing frequency scanning test to obtain asphalt dynamic modulus and phase angle data at different frequencies at low temperature; according to the prediction model, converting the dynamic modulus and the phase angle into a creep stiffness modulus and a creep stiffness modulus change rate; and finally, according to a low-temperature performance grade evaluation standard, obtaining the low-temperature grade of the asphalt sample. According to the method, the low-temperature performance of the asphalt can be rapidly predicted, a tedious bending beam rheometer test is not needed, and the test efficiency is greatly improved. The method also has the characteristics of low sample demand, simple operation, accurate result and the like, can be used for rapidly predicting the low-temperature performance of the laboratory asphalt, and also can be applied to asphalt extracted from a pavement core sample, so that the purpose of rapidly obtaining the low-temperature performance of the asphalt is achieved.

The invention discloses a solid waste-based cold-mixed asphalt mixture for preventive maintenance as well as a preparation method and application thereof, and belongs to the technical field of road engineering. The solid waste-based cold-mixed asphalt mixture is prepared from the following components in percentage by mass: 4.7 to 8.6 percent of modified cold-mixed asphalt adhesive, 85.8 to 93.9 percent of aggregate and 1.4 to 5.6 percent of composite filler, the modified cold-mixed asphalt adhesive is prepared from the following components in parts by weight: 86 to 96 parts of emulsified asphalt, 1 to 5 parts of bisphenol A type waterborne epoxy resin emulsion, 0.05 to 1 part of curing agent, 0.01 to 0.05 part of defoaming agent, 1.5 to 8 parts of waterborne polyurethane emulsion and 1 to 3 parts of hydroxypropyl methyl cellulose. The solid-waste-based cold-mixed asphalt mixture prepared by the method shows excellent comprehensive performance in high-temperature rut resistance, water damage resistance, freeze-thaw resistance, skid resistance, volume stability, interlayer shear resistance and the like, promotes reasonable utilization of solid waste resources, and has good economic and environmental benefits.

The invention discloses a roadbed and pavement compactness detection and regulation method for road engineering. The method comprises the following steps: deploying an intrusive sensor array to monitor an internal physical state and water-heat-force coupling phase change data; synchronously acquiring operation data of intelligent compaction equipment and scanning data of nondestructive detection equipment, and identifying a phase change critical point of the material; a disturbance propagation coefficient is calculated through a mechanical transmission chain model after data fusion, a target point is determined, and automatic micro sampling is carried out; and fusing all data to establish a macro-medium-micro three-scale fused compaction prediction model, generating a real-time regulation and control instruction to realize closed-loop control, and finally generating a three-dimensional compaction degree distribution digital twin model. According to the method, multi-source data are integrated, material phase change and mechanical transfer rules are associated, and the stability and the intelligent level of compaction quality are improved.

The invention belongs to the technical field of road engineering, and particularly relates to a method for detecting the fatigue performance of an asphalt pavement, which comprises the following steps: firstly, manufacturing a composite small beam for detection: manufacturing a water-stable layer by using a concrete material; then a blocking agent is applied to the top face of the water-stable layer, so that bonding between the asphalt surface layer and the water-stable layer is blocked, the effect that interlayer thorough disengaging and bonding failure are achieved, and interlayer damage is simulated; paving an asphalt surface layer on the top surface of the cement-stabilized layer and compacting to form a test composite board, and cutting the test composite board to form a composite small beam; and putting the composite small beam into a fatigue testing machine, and repeating the loading times to obtain the fatigue life of the composite small beam. According to the scheme, a method for researching the influence of the interlayer state on the fatigue performance of the asphalt pavement is provided, and corresponding rationalized suggestions and theoretical bases can be provided for design and construction of the asphalt pavement based on the analysis; according to the method, the interlayer damage of the actual asphalt pavement is simulated, so that the detection accuracy is very high.

The invention discloses a high-temperature instant stable dry-process high-viscoelastic asphalt modifier and a preparation method thereof, and belongs to the technical field of road engineering materials. The high-temperature instant stable dry-process high-viscoelastic asphalt modifier comprises the following components in percentage by mass: 20%-32% of matrix asphalt, 18%-20% of SBS (Styrene Butadiene Styrene), 12%-15% of a solubilizer, 35%-40% of a compound tackifier, 1.5%-2.5% of a heat conducting agent and 1.5%-2.5% of a coupling agent. The high-temperature instant stable dry-process high-viscoelastic asphalt modifier provided by the invention can be stably stored in a normal-temperature state, and does not generate a bonding phenomenon; and under the condition of high temperature, the modified asphalt can be quickly dissolved, effectively wraps the hot aggregate, is well compatible with the matrix asphalt, and has no other technical difficulties. The high-temperature instant stable dry-process high-viscosity and high-elasticity asphalt modifier provided by the invention can be directly put into commodity SBS modified asphalt to prepare high-viscosity and high-elasticity modified asphalt.