866 results about "Highway engineering" patented technology

The invention relates to the technical field of highway engineering informatization, in particular to a geometric registration method and system based on a BIM model and an AR real scene. The method comprises the following steps: obtaining multi-source data of a construction site, and generating an AR real scene of the construction site according to the multi-source data; fusing multi-source data to obtain accurate parameters of the construction equipment; calculating a spatial transformation matrix of a construction site through accurate parameters of construction equipment, and obtaining an initial registration result of the BIM model and the AR real scene by combining engineering characteristics and the spatial transformation matrix; a dynamic error compensation mechanism is introduced, the initial registration result is corrected through the dynamic error compensation mechanism, and a local registration result is obtained; and constructing a global and local coordinate system mapping optimization model, and mapping the local registration result to a global coordinate system by using the global and local coordinate system mapping optimization model to obtain a global registration result. According to the method, a reliable spatial data basis is provided for highway engineering quality inspection, construction guidance and defect identification.

The invention relates to the technical field of application of information technology in constructional engineering, and discloses a method for intelligently extracting engineering quantity application in highway engineering. The method comprises the following steps: standardizing an engineering scale in highway engineering design to form a standardized engineering scale; establishing a preliminary budget project reference template; establishing a connection relationship between the preliminary budget project reference template and the standardized engineering scale, wherein the connection relationship at least comprises a semantic correspondence relationship between project sections and engineering scale fields, a logic matching rule between quota subitems and engineering parameters, and a self-adaptive adjustment mechanism for table format differences; when a new engineering quantity table is imported, automatically identifying and analyzing a data field and a structure of the new engineering quantity table based on a connection relationship, mapping data in the new engineering quantity corresponding table to a corresponding project section and a quota sub-target of a preliminary budget project reference template through semantic analysis and a logic matching rule; and generating a budget file meeting the cost compilation requirement.

The invention relates to the field of highway engineering safety monitoring, in particular to a highway slope stability image monitoring and risk early warning system which comprises an image acquisition module, a slope parameterization representation module, a multi-scale curvature flow analysis module, a Riemannian manifold learning module and a risk early warning module. Differential features are extracted by calculating a measurement tensor and a curvature tensor of the curved surface; constructing multi-scale representation of the slope curved surface by applying a curvature flow theory, and identifying deformation characteristics under different scales; according to the method, riemannian manifold learning and a geodesic convolutional network are utilized to extract advanced features, geological disaster precursors such as landslide, collapse and debris flow are accurately identified, the system has a self-adaptive monitoring frequency adjustment function, monitoring modes are automatically switched according to risk levels, the slope disaster risk is greatly reduced, and a powerful guarantee is provided for safe operation of roads.

The invention discloses a highway engineering road and bridge measurement method based on BIM, and belongs to the technical field of highway engineering measurement. According to the method, the problems that the modeling efficiency and accuracy are difficult to consider, the modeling precision of a non-important area is redundant and the like in the existing road and bridge measurement method for the highway engineering are solved. The method comprises the following steps: acquiring satellite positioning data by using a satellite positioning system in a measurement area, acquiring point cloud data by using laser scanning equipment, and acquiring road and bridge images by using image acquisition equipment; converting satellite positioning data into unified coordinate system data information, carrying out spatial registration on the unified coordinate system data information and the point cloud data, and dividing an important region and a non-important region; constructing a precise three-dimensional point cloud model for the important area, constructing a path point cloud model for the non-important area, and integrating road and bridge images; and finally fusing the model to obtain road and bridge parameters. The method can improve the model efficiency and reduce the model resource overhead while effectively improving the measurement precision, and is suitable for the measurement work of roads and bridges of highway engineering in various environments.

The invention provides a safety evaluation method and system for a road area environment in a highway engineering construction period. The method comprises the steps of obtaining multi-source sensing data of the road area environment in the highway engineering construction period; inputting the multi-source sensing data into a multi-scale time sensing coding module to obtain sequence features of a macro-scale satellite and a micro-scale unmanned aerial vehicle; the sequence features are input to a multi-modal fusion Transform module, and multi-scale fourth features are obtained; inputting the multi-scale fourth feature into a change detection module to obtain a change labeling graph and a first change event log; and based on the change labeling graph and the first change event log, constructing a risk early warning module to obtain a second change event log. Through multi-source data fusion of satellite remote sensing and unmanned aerial vehicle images, accurate perception and dynamic monitoring of the road area environment in the highway engineering construction period are realized, the accuracy and real-time response capability of environmental safety assessment are improved, and the method is suitable for the field of highway engineering construction and construction safety management.

The invention provides a highway engineering quality real-time monitoring method and system based on digital twinning, and the method comprises the steps: collecting construction data, and carrying out the preprocessing of the construction data, and obtaining a behavior time sequence and a coverage rate index sequence; constructing a behavior graph, performing quality prediction on each behavior segment node through a graph neural network to obtain a predicted quality score, and performing coverage rate index sequence correction to obtain an actual quality score; mapping the actual quality score to a spatial position to obtain a spatial quality tensor, wherein the spatial position is a three-dimensional position obtained by combining equipment position data and a compaction horizon number; performing structural consistency analysis on the spatial quality tensor, identifying and marking a topology abnormal region, and outputting a structural consistency scoring tensor; and generating a visual twin layer based on the spatial quality tensor and the structural consistency scoring tensor, and performing graph level labeling and section mapping on the abnormal region.

The invention relates to the technical field of construction progress collaborative management, in particular to a multi-source data driven construction progress intelligent collaborative control method and system. The method comprises the following steps: acquiring multi-source data of a construction site; dynamically fusing the multi-source data to obtain a three-dimensional construction map; constructing a construction plan planning model, and generating an optimal construction plan by using the construction plan planning model based on the three-dimensional construction map; and performing dynamic resource scheduling and allocation according to the optimal construction plan to obtain a resource allocation scheme. According to the method, the three-dimensional construction map is constructed by fusing the multi-source data, then the construction plan planning model is constructed to obtain the optimal construction plan, and finally resource allocation is performed based on the optimal construction plan, so that the problems of data islands, progress lag and response lag in traditional highway engineering construction are solved, and the construction efficiency and safety are remarkably improved.

The invention relates to the technical field of electric digital data processing, in particular to an AI-driven highway engineering full-cycle carbon emission optimization method and system, and the method comprises the steps: constructing a highway engineering full-cycle carbon emission digital twinborn model, integrating multi-source heterogeneous data, and constructing a highway engineering full-cycle carbon emission digital twinborn model; and real-time monitoring, accurate accounting, intelligent prediction and early warning and collaborative optimization of construction carbon emission are realized by applying an artificial intelligence technology, and a multi-dimensional carbon reduction path is generated. According to the method, the accounting boundary can be comprehensively defined, real-time monitoring and accurate accounting are realized, system-level intelligent collaborative optimization is provided, the carbon emission management level of highway engineering is remarkably improved, and near-zero carbon construction is promoted.

The invention discloses a pavement maintenance decision-making method, system and equipment, a medium and a product, and relates to the field of highway engineering management. The method comprises the following steps: firstly, collecting performance data of a target road section, and identifying a to-be-optimized pavement maintenance unit through a threshold judgment method or a K-means clustering algorithm; encoding each maintenance measure type and the corresponding maintenance opportunity into a real number vector, and taking the real number vector as a maintenance scheme code; constructing a multi-target fitness function covering pavement performance, maintenance cost and carbon emission; carrying out iterative optimization on the maintenance scheme through a particle swarm optimization algorithm on the basis, and outputting a particle swarm optimization solution set; performing rapid non-dominated sorting and congestion degree distance calculation on the particle swarm optimization solution set, and extracting a Pareto optimal solution set; and fusing the Pareto optimal solution and the full-life-cycle comparison data of the target road section, and outputting a maintenance decision scheme for each pavement maintenance unit, so that the decision efficiency and the scientificity, accuracy, sustainability and refinement degree of the maintenance decision scheme are improved.

The invention provides a bridge performance evaluation and life prediction method based on big data analysis, and relates to the technical field of bridge preventive maintenance in highway engineering, and the method comprises the steps: obtaining three-dimensional scanning data of an old bridge and a new bridge under a common service condition, and combining with complex service conditions such as dynamic load, temperature difference, creep shrinkage, etc. And the dynamic response of the connection part in an actual use environment can be accurately simulated and evaluated. Especially under the condition of common service of new and old bridges, the degradation and damage of the connection part are particularly significant, and by combining with a big data technology, the progress of material aging is tracked in real time, and possible hidden damage of the connection part is helped to be predicted. By constructing the aging factor, the damage index and the corrosion index and associating the aging factor, the damage index and the corrosion index with the connection coordination index graph, a specific rigidity loss factor can be provided for each connection unit, the performance degradation degree of the bridge connection part is reflected, and a scientific basis is provided for subsequent reinforcement and maintenance strategies.

The invention discloses a highway engineering construction remote material abnormity management method, which relates to the technical field of material management, and comprises the following steps: collecting material information parameters for analysis, obtaining an analysis result and carrying out abnormity identification, outputting an abnormity identification result, triggering a response mechanism for the abnormity identification result, and carrying out automatic early warning. By constructing a full-process digital highway engineering construction remote material anomaly management system, the problems of multiple types of traditional management are solved, multi-source data are integrated to automatically correct errors and generate accurate data, and the material anomaly management system is established by means of space-time dimension cross validation and construction process compliance analysis. A preset abnormal feature combination library is combined to capture a composite risk, a hierarchical response and a mapping table are adopted to realize differential early warning, responsibility is clarified through receiving verification and block chain evidence storage, and a closed loop is formed by combining treatment with template optimization and dual verification, so that the risk is reduced, and the management intelligence and refinement level is improved.

The invention discloses a road culvert inner wall damage image detection and traffic capacity evaluation method and system, and relates to the technical field of road engineering detection and computer vision, and the method comprises the steps: collecting multi-source data through an annular camera, a laser section scanner and a mileage encoder carried by a detection robot, and carrying out the panoramic expansion and time-space registration; using a multi-scale attention panoramic segmentation network to identify damages such as lining cracks, joint slab staggering, damage and chipping, steel bar exposure and water leakage; calculating the clearance size and the deposition thickness of the culvert by adopting an ellipse fitting method; according to the method, the culvert detection speed reaches 50 m / h, and the damage detection accuracy reaches 89% or above.

The invention provides a mobile highway engineering quality detection device and method, and belongs to the technical field of highway quality detection.The mobile highway engineering quality detection device comprises a walking support, detection rollers, a cleaning assembly, a driving assembly, an elastic supporting assembly and an alarm assembly; the detection rolling wheel is arranged below the walking support, the elastic supporting assembly is installed on the bottom wall of the walking support and used for providing elastic supporting for the detection rolling wheel, so that the detection rolling wheel can move up and down when rolling to the convex and concave positions of the road surface, and the alarm assembly is installed on the side wall of the walking support. Compared with the prior art, when the detection roller rolls along the road surface to detect the flatness of the road surface, gravel sundries on the road surface on the front side of the detection roller can be cleaned, so that the detection roller is prevented from acting on the gravel sundries, and the accuracy of a detection result is improved.

The invention discloses a digitized collaborative management and control platform and method for a highway roadbed slope, and belongs to the field of highway engineering. The method comprises the steps that a three-dimensional geological information model of the highway roadbed slope is constructed; sensing and fusing multi-source heterogeneous data; intelligent analysis and early warning are realized; co-processing and closed-loop management; optimization and self-learning of a machine learning algorithm model; and visualizing the slope of the whole highway. According to the invention, through the AI algorithm, the conversion from manual interpretation to intelligent prediction is realized, the early warning time is advanced, and passive response is changed into active prevention and control. According to the invention, information sharing and business collaboration are realized through process driving, and the emergency disposal efficiency is greatly improved. Visual and scientific decision support is provided for slope state evaluation and treatment scheme making based on the digital twinborn model and the multi-source fusion data, and dependence on human experience is reduced. According to the invention, a complete slope electronic health record is established, a data basis is provided for long-term performance evaluation and maintenance planning of the slope, and full-life-cycle management of assets is realized.

The invention discloses a lightweight method and system for a highway engineering three-dimensional live-action model and a medium, and relates to the technical field of three-dimensional live-action modeling. The method comprises the following steps: firstly, carrying out engineering semantic segmentation on an input three-dimensional grid model, and extracting design parameters in a BIM / GIS (Basic Information Model / Geographic Information System); then, constructing a multi-level constraint model fusing semantic constraints, engineering precision constraints and design parameter constraints; and finally, carrying out iterative simplification under the guidance and limitation of the multi-level constraint model by adopting an improved quadratic error measurement algorithm. The method solves the problems of semantic information loss, out-of-control local precision and disjunction with design intention when a traditional pure geometric simplification method is applied to highway engineering, and can intelligently reserve key engineering characteristics, control geometric errors and fit a design form while ensuring that the data size of the model is greatly reduced. And a high-quality lightweight model suitable for professional analysis and application is generated.

The invention relates to the technical field of unmanned aerial vehicle application and highway engineering monitoring, in particular to a highway slope engineering inspection unmanned aerial vehicle which comprises a multi-rotor aircraft provided with a flight controller, the bottom of the multi-rotor aircraft is connected with a first holder, a plurality of supporting legs are arranged on the periphery of the first holder, and a second holder is arranged at the bottom of the first holder. An equipment tray is arranged at the bottom of the second holder; the laser projector is fixed at the bottom of the equipment tray and is used for projecting a reference image; the marking gun is fixed at the bottom of the equipment tray and is used for emitting marking paintballs; the high-definition camera is fixed to the bottom of the equipment tray and located between the laser projector and the marking gun. Optical axes of the high-definition camera and the laser projector are parallel to each other and are consistent with the emission direction of the marking gun; through multi-module collaborative operation, the slope inspection efficiency and precision are remarkably improved, and the system is particularly suitable for high-precision and automatic slope disease detection and safety evaluation under complex terrain conditions.

The present invention relates to the technical field of pavement materials, and particularly relates to a high-performance asphalt concrete pavement material and a preparation method thereof. The formula of the pavement material includes asphalt, high melt index SBS, fine aggregate, coarse aggregate, fly ash, water reducer, low-temperature anti-cracking agent and anti-freezing agent. Among them, the preparation method of the low-temperature anti-cracking agent includes stirring and melt spinning of homopolypropylene, nano-silicon carbide and low melt index SBS to obtain the low-temperature anti-cracking agent. By optimizing the ratio and adding specific components, the material has good low-temperature anti-cracking performance, anti-freezing performance and anti-stripping performance. The high-performance asphalt concrete pavement material provided by the present invention is expected to be applied to highway engineering and road construction fields in low-temperature regions.

The invention relates to the field of engineering management, and particularly discloses a highway engineering management method and system based on big data analysis, and the method comprises the steps: firstly obtaining the data of a temperature sensor disposed in concrete and an image frame of a pouring region in real time, and carrying out the intelligent correlation of the data and the information of a BIM component related to the current pouring, therefore, a dynamic digital twinborn body capable of reflecting the pouring state in real time is generated. On the basis, a pre-trained intelligent analysis model is introduced, abnormal mode detection is carried out on collected temperature time sequence data, and surface defect recognition is carried out on image frames. Particularly, for temperature time sequence data, key time sequence mode features are effectively extracted and strengthened through advanced feature coding and fine-grained enhancement technologies. And meanwhile, the subjectivity and hysteresis of manual inspection are made up through automatic identification of the surface defects by the image analysis model. And finally, the intelligent analysis results are visually presented on the digital twinborn body.

The invention discloses a YOLO-OCR highway engineering quantity intelligent hitching system, which relates to the technical field of highway engineering quantity and comprises a drawing engineering quantity analysis module, a structured data correction module, an engineering component intelligent hitching module and a standardized list generation module. The method comprises the steps of receiving drawing image data containing an engineering quantity table, positioning and identifying a table area to generate preliminary structured data, repairing identification errors based on context rules, associating engineering quantity information with candidate component nodes in a knowledge graph by calculating similarity, and generating a standardized contract list according to pricing specifications. And engineering quantity intelligent hooking and list generation are realized. According to the method, accurate engineering quantity recognition is achieved through the mixed visual model and semantic verification, intelligent component hooking is completed by means of the knowledge graph, data source backtracking and model self-adaptive learning capabilities are achieved, and engineering management efficiency and data accuracy are improved.

The invention relates to the technical field of highway engineering safety monitoring, in particular to a highway subgrade three-dimensional deformation monitoring system based on unmanned aerial vehicle oblique photography, and the system comprises an unmanned aerial vehicle oblique photography module which adopts a five-lens synchronous shooting strategy to realize the omni-directional coverage of a subgrade; the three-dimensional point cloud generation engine generates a high-precision three-dimensional point cloud model through feature extraction, registration and triangulation strategies; the deformation field analysis platform models a roadbed surface into a parameterized Riemannian manifold based on a differential geometry theory, captures deformation dynamic characteristics through multi-scale curvature flow analysis, and identifies potential risks by using topological evolution characteristics of deformation singular points; and the risk evaluator evaluates the risk level based on the singular point density, the change rate and the topological stability and generates early warning information. According to the invention, millimeter-level accurate monitoring of roadbed deformation is realized, various deformation modes from micro-cracks to large-scale settlement can be captured, the potential landslide risk is early warned 30-45 days in advance, and the false alarm rate is significantly reduced.

The invention relates to the technical field of highway engineering monitoring, in particular to an acoustic emission diagnosis method and system for fatigue cracks of a heavy-duty highway, and the method comprises the steps: collecting acoustic emission signals by a multi-depth piezoelectric ceramic sensor array pre-buried in a pavement structure; carrying out time-frequency domain topological feature extraction on the collected signals, wherein the time-frequency domain topological feature extraction comprises wavelet packet entropy value mapping and phase-space reconstruction, and extracting topological invariants such as correlation dimensions and Lyapunov indexes; inputting the time-frequency feature vector into a transfer learning model to realize multi-scale feature fusion, and innovatively adopting a gradual change domain to realize smooth transition from a source domain to a target domain; a fractal stress field model is constructed based on the fusion features, and stress diffusion depth estimation and crack evolution prediction are achieved; a crack propagation area is automatically marked through correlation coefficient analysis, a crack temperature diagram is generated, and a maintenance decision suggestion is output, so that early-stage microcrack detection of the heavy-load highway is realized, the detection sensitivity is improved by about 35%, and the depth positioning precision reaches + / -1.5 cm.

The invention provides a highway engineering quality management method and system based on a cloud platform, and a medium, and belongs to the technical field of engineering quality management, and the method comprises the steps: constructing a plurality of highway engineering item standard construction processes, standard construction process results, and engineering quality test standards corresponding to the construction process results; by obtaining the construction material usage amount of each highway engineering item, the construction process corresponding to the highway engineering item is identified based on the construction process judgment model; comparing the reported construction process result with a standard construction process result to obtain the project progress qualified rate of the plurality of highway project items; and obtaining an engineering quality data test result under the current construction process, and comparing the engineering quality data test result with an engineering item quality test standard to obtain the engineering quality qualified rate of the plurality of highway engineering items. According to the method, real-time tracking and comparison of project progress and project quality can be realized, each link is ensured to be within a controllable range, problems in construction can be found in advance, and measures can be taken in time.

The invention discloses a highway engineering intelligent traffic flow prediction method based on big data, and belongs to the technical field of traffic flow prediction, and the method comprises the following steps: enabling a multi-source traffic data collection sensor network to achieve the collection of traffic data; preprocessing the data; a convolution attention fusion module is inserted between Transform encoders, local enhancement processing is carried out, and key information is highlighted; performing frequency domain fusion; a dual distillation compression model combining characteristics and a similarity matrix; and outputting a traffic flow prediction value of the future time period. According to the invention, local enhancement processing can be realized, and key information is highlighted; the frequency domain fusion module is introduced to reduce the calculation amount, explicitly model different time scale features, and improve the prediction precision. A double knowledge distillation mechanism is adopted, and the calculation amount can be effectively reduced.

The invention relates to the technical field of artificial intelligence, and more specifically discloses an artificial intelligence-based earthwork real-time dynamic monitoring system and method, and the method comprises the steps: obtaining an image of a to-be-detected earthwork region through satellite remote sensing data, extracting a feature vector and a feature matrix, constructing a classification feature vector, and finally obtaining a classification result through a classifier. Therefore, real-time monitoring of earthwork settlement and slope deformation is realized, a simple, convenient and rapid quality safety control means is provided for highway engineering construction, municipal roads, constructional engineering and landscape and garden engineering, the engineering construction efficiency is improved, and the engineering cost is reduced.

The invention relates to the technical field of highway traffic, and discloses a digital management and control method and system for highway engineering test detection. The method comprises the following steps: acquiring highway engineering test detection data, preprocessing original detection data in real time by using edge computing nodes, and generating a standardized detection data stream; based on the data stream, a dynamic window segmentation algorithm is adopted to extract time domain features of detection data, and a multi-level data quality evaluation model is established. And performing exception marking on the detection data through the model, matching exception types in combination with a historical exception data pattern library, and outputting an exception detection result and confidence. And triggering a self-adaptive sampling strategy according to an abnormal detection result, adjusting the detection data acquisition frequency and the sampling precision, and generating an optimized detection task instruction. And finally, issuing an instruction to an edge computing node, synchronously updating a parameter threshold value of the multi-level data quality evaluation model, and forming a closed-loop feedback control mechanism.

The invention provides a method for generating a highway engineering feasibility research report based on local large model training, which is based on a locally deployed large model, integrates multi-source data, and realizes mapping and verification from a fuzzy policy to a structured field through regular extraction of a standard field and construction of a highway engineering knowledge graph. The method adopts TensorRT to accelerate reasoning, injects a specification term table, optimizes term consistency in combination with comparative learning, and generates a specification text through LoRA fine tuning and a reward function. After route parameters are input, geometric features are calculated, a disaster database is associated to recommend a detour scheme, and chapter content is generated. And outputting a formal report based on the template, and ensuring data consistency through cross validation. RPA is adopted to capture standard updating, Kafka and Fiss vector libraries are combined to achieve compliance verification, knowledge graph incremental updating and conflict correction are triggered, and a full-process automatic and intelligent feasibility research report generation system is formed.

The utility model relates to the technical field of crack repairing and discloses a crack repairing machine for highway engineering, which comprises a frame, rollers are mounted on two sides of the outside of the frame, a storage box is fixedly connected to the upper portion of the frame, and a transfer pump is fixedly connected to the front side of the outside of the storage box. The input end of the material pumping pump is fixedly connected to the interior of the material storage box, the output end of the material pumping pump is fixedly connected with a conveying pipe, a discharging head is installed at the bottom of the conveying pipe, moving blocks are slidably connected to the two sides of the interior of the discharging head, and moving rods are fixedly connected to the left sides of the exteriors of the moving blocks; and the outer part of the moving rod is fixedly connected with a grip. According to the utility model, the discharge head of the crack repairing machine is convenient to replace, the problem that a bolt is manually unscrewed or tightened through a wrench in a traditional replacement mode is solved, the mode is simple and convenient to operate, time-saving and labor-saving, and the working efficiency of the crack repairing machine is improved.

The utility model relates to the technical field of highway engineering material detection, and discloses a highway engineering material detection device which comprises a main control machine body, the upper surface of the main control machine body is fixedly connected with a detection mechanism, an automatic sweeping mechanism is arranged above the main control machine body, and the automatic sweeping mechanism comprises a support. An electric telescopic rod is fixedly connected to the inner wall of the support, a movable frame is fixedly connected to the telescopic end of the electric telescopic rod, a double-shaft servo motor is fixedly connected to the inner wall of the movable frame, and two sliding frames are slidably connected into the movable frame. According to the highway engineering material detection device, through mutual cooperation of the main control machine body, the detection mechanism, the support, the electric telescopic rod, the moving frame, the double-shaft servo motor, the threaded rod, the sliding frame, the driving motor, the rotating rod and the sweeping rotating disc, a material with the strength to be detected can be placed in the detection mechanism, and the detection mechanism is matched with the main control machine body to detect the material; the electric telescopic rod can control the horizontal distance of the cleaning turntable relative to the upper and lower extrusion surfaces of the detection mechanism.

The invention discloses a highway engineering parametric modeling method based on a digital-analog driven component library, which comprises the following steps of: bringing different types of component space constraint logic (namely primary and secondary hierarchy rules) into a whole model modeling process, and determining a key design baseline point set of mutual influence among components by extracting section forms of different components; and on the basis of the design points and the standard cross section, parameterizing to generate space coordinates of different components and a coupling form with the terrain so as to support rapid adaptation and accurate construction of a three-dimensional model to complex route conditions. Through the mode, the technical problems that fitting precision of a parameterized model standard section and topographic data is lost and relevance between components is weak under the condition of a complex route are solved, meanwhile, corresponding design baselines and section parameters are stored through a database, section parameters and spatial positions of different components are calculated on the basis of clear spatial constraint logic, and therefore the fitting precision of the parameterized model standard section and the topographic data is improved. And rapid positioning, parameter updating and structure collaborative adjustment of the component are realized, so that the modeling efficiency and the design flexibility are remarkably improved.

The invention discloses a soft soil area film bag sand blowing shortcut composite structure and a construction method, and relates to the technical field of highway engineering building construction shortcuts, the technical scheme is that the soft soil area film bag sand blowing shortcut composite structure comprises a film bag sand layer arranged at the bottom and a ballast layer arranged at the top of the film bag sand layer; the film bag sand layer comprises a third film bag sand layer arranged on the original ground or above the water surface, a first film bag sand layer and a second film bag sand layer, wherein the first film bag sand layer and the second film bag sand layer are arranged on the original ground or below the water surface, and the first film bag sand layer and the second film bag sand layer are filled with film bag green sand in a layered mode according to the water depth. The ballast layer is arranged on the top of the third film bag sand layer. The method has the beneficial effects that the working procedures of drainage, desilting, replacement and filling and the like are reduced, the construction period is shortened, the equipment investment and cost are reduced, and rapid forming of the shortcut is achieved. The film bag and the sand are combined to form a high-bearing-capacity compact block, sedimentation is prevented, the maintenance cost is reduced, and smoothness and progress are guaranteed. The mechanical conveying improves the efficiency, reduces the labor intensity, is free of waste, recoverable in sand, and meets the requirements of green sustainable development.