342 results about "Topographic model" patented technology

The invention relates to a terrain real scene modeling method, device and equipment and a storage medium thereof. According to the method, multi-source heterogeneous data related to the terrain in a target area is integrated, a multi-modal data cube is generated through noise filtering and data fusion under a unified coordinate system, then a data cavity area is identified based on density clustering and elevation gradient analysis, and geophysical features are extracted. Innovatively constructing a neural implicit inference model fused with physical constraints to perform joint modeling on the earth surface and underground structures, and finally converting implicit terrain representation into an explicit three-dimensional terrain model; seamless fusion modeling of the earth surface and the underground space under the complex shielding environment is achieved, the physical rationality of the model and the hidden area reconstruction precision are remarkably improved, meanwhile, it is ensured that the generated model strictly conforms to the geological physical law, and the geological engineering safety and the planning reliability are effectively guaranteed.

The invention relates to the technical field of image data processing, in particular to a difficult mountainous area slope three-dimensional modeling method and system based on a remote sensing technology. The method comprises the following steps: obtaining an original remote sensing data set of a target hard mountain area, and carrying out data preprocessing to obtain a standardized remote sensing data set; performing target hard mountainous area surface feature extraction on the standardized remote sensing data set to obtain hard mountainous area surface feature data; constructing a three-dimensional terrain model by using the earth surface feature data of the hard mountain area to obtain preliminary three-dimensional terrain model data; and performing time sequence analysis on the standardized remote sensing data set, and performing slope dynamic change analysis on the initial three-dimensional terrain model data by using a time sequence analysis result to obtain slope displacement change data. Through three-dimensional modeling, dynamic change analysis, stability evaluation and landslide early warning, a set of complete disaster prevention and reduction system for the hard mountainous area is constructed, and the prediction and prevention capability for landslide disasters is effectively improved.

The invention discloses a wharf shoreline terrain reconstruction method based on remote sensing data, and belongs to the technical field of three-dimensional terrain reconstruction. The method comprises the following steps: acquiring a multi-temporal multispectral remote sensing image, a synthetic aperture radar image, a laser radar point cloud and synchronous tidal water level data of a target wharf area; processing the multispectral image to generate an initial land and water segmentation map; carrying out tide correction by utilizing the tide water level data, fusing the multi-polarization characteristics of the synthetic aperture radar image, and correcting the ground feature type to obtain an accurate land and water boundary diagram; processing the laser radar point cloud to generate a digital surface model, extracting a shoreline contour with sub-pixel-level precision from the digital surface model, and endowing the shoreline contour with an elevation value; and superposing the shoreline contour with the elevation with the multispectral image to generate a three-dimensional terrain model. According to the method, the problems of low terrain reconstruction precision, large tide influence and insufficient automation degree of a traditional method in a complex wharf environment are solved, and high-precision and high-efficiency wharf shoreline three-dimensional automatic reconstruction is realized.

The invention relates to the technical field of intelligent forestry management, and particularly discloses a forest farm intelligent comprehensive management and control system, which comprises a space-air-ground collaborative sensing module, a fire danger dynamic modeling module and an intelligent decision execution module. The method comprises the following steps: acquiring temperature field data through multispectral satellite remote sensing, constructing a high-precision terrain model through a laser radar, extracting vegetation features through hyperspectral imaging, extracting a thermal anomaly structure by adopting topological continuous coherence analysis and a Morse-Smal complex method, and establishing an adaptive fire danger model in combination with a quantum annealing optimizer. The system can generate a fire danger thermodynamic diagram in real time and divide risk levels, and drives the unmanned aerial vehicle to perform priority patrol and obstacle avoidance path planning. The problems of difficulty in pseudo hot area identification, low fire danger prediction precision, non-intelligent path planning and the like in a complex environment are solved, and the intelligent level of forest farm fire prevention and control is improved.

The invention discloses an intelligent method and system for multi-source heterogeneous data fusion management, and belongs to the field of data processing, and the intelligent method for multi-source heterogeneous data fusion management comprises the following steps: deploying a sensor network in a historical ponding area based on historical ponding point data and urban hydrological geographic information, acquiring real-time monitoring data, wherein the real-time monitoring data comprises rainfall intensity, road waterlogging depth, community waterlogging condition and drainage pipe network water level / flow; compared with the prior art, the method has the beneficial effects that sensors are arranged in the historical ponding area to obtain real-time monitoring data, and weather forecast, a terrain model and a pipe network model are combined to construct a waterlogging prediction model to predict whether a ponding risk exists in the historical ponding area in future set time (such as 0.5-3 hours in the future); the ponding risk is treated in advance, so that the problems of traffic interruption caused by ponding, citizen travel obstruction and the like are solved.

The invention discloses a power distribution network intelligent planning method, system and device and a storage medium, and the method comprises the steps: obtaining point cloud data, carrying out the topographic feature information extraction of the point cloud data, and obtaining a topographic data set; acquiring remote sensing data, and performing earth surface change information extraction on the remote sensing data to obtain an earth surface change data set; fusing the topographic data set and the surface change data set to obtain a topographic point cloud data set; according to the terrain point cloud data set, a debris flow scouring path of the gully edge collapse area is analyzed, and a first terrain model is constructed; acquiring unmanned aerial vehicle monitoring data, simulating a line cross-trench path in combination with the first terrain model, optimizing cross-trench points and tower footing coordinates, and obtaining a power grid planning scheme; and the stability of the power grid planning scheme is evaluated, tower footing reinforcement parameters are adjusted, a final power grid planning scheme is obtained, and technical support is provided for power grid construction in the desert area.

The invention relates to a complex terrain surveying and mapping method, device and equipment and a medium. According to the complex terrain surveying and mapping method, device and equipment and the medium, laser beams with alternating polarization states are synchronously emitted through a dual-wavelength laser radar, an original point cloud with a space-time mark is captured, and earth surface points and noise points are analyzed based on time difference and polarization degradation characteristics; constructing a noise cluster function according to the noise points to identify vegetation artifacts; performing earth surface confidence evaluation on the earth surface points, filtering noise by using an elevation layering strategy, and positioning a fracture area; and finally, based on the denoised cloud layer, the fracture area and the earth surface point confidence coefficient, reconstructing a terrain curved surface, and generating a continuous terrain model. Therefore, precise reconstruction of the terrain sudden change area under vegetation coverage is realized, and the dual technical effects of resisting complex scattering interference and keeping the integrity of the terrain structure are achieved.

The invention provides an intelligent layout method, system and device for a land survey control network and a medium, and the method comprises the steps: building a space-time dynamic terrain model based on the obtained measurement data of a construction region; generating a candidate control point set in the construction area according to a preset layout density requirement; based on the space-time dynamic terrain model, performing stability analysis on each candidate control point in the candidate control point set to obtain a stability index of each candidate control point; based on the space-time dynamic terrain model, any two candidate control points in the candidate control point set are used as candidate control point pairs for time sequence intervisibility analysis, and time sequence intervisibility indexes of the candidate control point pairs are obtained; establishing a multi-objective optimization model according to the stability index and the time sequence intervisibility index; and solving the multi-objective optimization model by adopting a multi-objective evolutionary algorithm, and outputting a control network layout scheme set. By adopting the method, the point distribution quality of the control network can be improved.

The invention discloses a coastal flood control adaptive strategy optimization system based on reinforcement learning, and the system comprises an unmanned plane multi-dimensional data collection module which carries out the cooperative work through a multi-rotor unmanned plane group, and carries out the data collection; the deep learning data processing module is used for processing the data acquired by the unmanned aerial vehicle multi-dimensional data acquisition module, updating a three-dimensional terrain model, flood routing prediction, a flooding simulation diagram and abnormal signal real-time detection in real time; the reinforcement learning strategy generation module is used for state space design, action space expansion and reward function optimization; the unmanned aerial vehicle execution and feedback module is used for strategy execution tracking, post-disaster evaluation and model iteration; and the dynamic optimization closed loop unit comprises a daily mode subunit and an emergency mode subunit. According to the invention, the flood control strategy is sensed in real time, accurate decision is made, and dynamic optimization of the coastal flood control adaptive strategy is realized.

The invention relates to the technical field of unmanned aerial vehicle navigation and control, in particular to an improved sparrow searching method for three-dimensional unmanned aerial vehicle path planning. According to the method, a three-dimensional mountain terrain model is constructed through a Gaussian function superposition method, obstacles and no-fly zones are defined by adopting a cylindrical geometric model, and obstacle avoidance constraints, take-off and landing safety constraints and flight height constraints are set; a comprehensive cost function with path length, threat penalty, flight safety height and path smoothness as sub-targets is constructed, an improved sparrow search algorithm is introduced, and a sine and cosine strategy is adopted in discoverer position updating to dynamically balance horizontal exploration and vertical obstacle avoidance. A Levy flight mechanism is introduced in follower position updating so as to enhance the capability of local development and jumping out of local optimum; the method comprises the steps of population initialization, role division, iterative optimization, collision detection and an elitist retention strategy. According to the method, a safe and smooth three-dimensional flight path with the optimal comprehensive cost is output, and the method is suitable for an actual unmanned aerial vehicle navigation task.

An ARAIM availability prediction method under a complex terrain environment is provided. The method includes: 1) selecting positioning points according to an air line; 2) calculating terrain shielding angles; 3) predicting visible satellites; 4) determining a fault mode that needs to be monitored; 5) calculating a positioning error variance, an influence coefficient of a nominal deviation, and a variance of a solution separation test statistic; and 6) calculating a threshold of a solution separation test, calculating a protection level, and determining availability. According to the method, the terrain shielding angles are calculated based on terrain model data, and the visible satellites are predicted based on ephemeris data or almanac data to further calculate a protection level, while determining the availability; and the accuracy of availability prediction can, by considering the effect of terrain barriers on the prediction of the visible satellites, be improved to ensure the safety of aircrafts.

The invention relates to the technical field of digital twinning, in particular to a flood disaster evolution method and system based on the digital twinning technology, and the method comprises the steps: collecting all point cloud data of a river basin terrain, constructing a three-dimensional terrain model, obtaining the reflection intensity and elevation data of each point cloud, clustering all point clouds corresponding to the ground, and obtaining a three-dimensional model; recording the areas where all point clouds corresponding to the ground in each cluster are located as local areas; and calculating a coplanar characterization value, an erosion evaluation value, an instability risk value, a soil fixation evaluation value and a terrain evolution factor of each local area, and constructing a digital twinborn simulation platform of the river basin terrain in combination with the three-dimensional terrain model to perform analog simulation on flood disasters. The defect that a static terrain model cannot respond to terrain evolution caused by flood disasters can be avoided, simulation errors generated by a digital twin simulation platform in the flood disaster evolution process are effectively reduced, and the accuracy of risk assessment of the flood disasters is improved.

The invention discloses an underwater leveling machine path optimization method based on foundation bed pore characteristics, and relates to the technical field of ocean engineering. The method comprises the following steps: measuring three-dimensional topographic data and pore distribution characteristic data of a to-be-leveled water area foundation bed by using a multi-source sensing and control system and a multi-beam sounding method, establishing a digital topographic model of the to-be-leveled foundation bed, and generating candidate optimized leveling paths adapted to geological characteristics by constructing an initial construction path, the engineering feasibility of the leveling operation is evaluated, and the optimal position of each path point after iterative optimization is output as an optimized leveling path in combination with an optimization algorithm, so that the leveling of the underwater leveling machine is completed; according to the method, the pore distribution characteristics and three-dimensional topographic data of a seabed foundation bed are intelligently analyzed, reliable environment data are obtained, an initial construction blueprint is formed, a basis is provided for optimization, dynamic generation and online correction of a path are achieved by fusing pore characteristic analysis and an intelligent optimization algorithm, and efficient, uniform and high-precision autonomous leveling operation is achieved.

The invention relates to a photovoltaic land slope stability partition evaluation method, which comprises the following steps that: an unmanned aerial vehicle flies in an oblique photography manner according to a path planning algorithm, and acquires an image and point cloud data of a slope region; correcting the collected images, including distortion removal, noise processing, image splicing, denoising, filtering and point cloud splicing of the point cloud data; creating a real three-dimensional terrain model by combining the texture information of the image and the height data of the point cloud, and extracting terrain height information from the point cloud data to generate a digital elevation model; performing feature extraction on the three-dimensional terrain model, and analyzing a stability index of the slope; establishing a slope stability evaluation model and performing zoning evaluation, performing stability zoning evaluation according to the feature data and the clustering result, and optimizing a zoning standard; and visualizing a slope stability partition result, generating a stability partition map and a report, establishing a dynamic monitoring system, and regularly using the unmanned aerial vehicle to repeatedly fly to obtain updated slope data.

The invention discloses a power grid unmanned aerial vehicle inspection method suitable for a complex terrain area, and the method comprises the steps: S1, obtaining the terrain point cloud data and image data of the complex terrain area, and forming a three-dimensional terrain model; s2, performing overlay analysis on the power grid layout information and the three-dimensional terrain model through a geographic information space analysis technology, and planning a flight route of the unmanned aerial vehicle; s3, performing routing inspection according to the flight route and an unmanned aerial vehicle power grid global coverage routing inspection technology to obtain original power grid image data; s4, transmitting the original power grid image data to a ground control station through a wireless communication link, and processing the original power grid image data through deep learning to obtain defect positions and types; and S5, generating an inspection report according to the position and the type of the defect, and pushing the inspection report to operation and maintenance personnel through network communication for equipment maintenance and fault processing. The problems of low efficiency, high labor cost, incomplete data acquisition and inaccurate defect identification in complex terrains are solved, and the efficiency and accuracy of power grid inspection are improved.

The invention belongs to the technical field of unmanned aerial vehicle group control, and relates to a control method of a fire extinguishing unmanned aerial vehicle group. According to the method, a dynamic fire scene thermodynamic diagram, meteorological data and a fire scene terrain model are collected, and fire scene spreading core kinetic parameters are extracted to calculate a dynamic buffer area; and then predicting meteorological data of a buffer area, generating a combustible flammability index grid map, carrying out weighted fusion on a downsampling result of the dynamic fire scene thermodynamic diagram and the two, and constructing a dynamic fire danger intensity field in a prediction period, thereby solving the problem that multi-dimensional heterogeneous data cannot be effectively integrated in the prior art, and realizing accurate prediction of the dynamic evolution trend of the fire. Meanwhile, state data of the unmanned aerial vehicle group are collected in real time, open fire areas are divided in combination with a fire danger intensity field, reachability of the unmanned aerial vehicles is evaluated, the unmanned aerial vehicle group capable of being dispatched for the second time is screened, traditional strategy defects are overcome, resource allocation is optimized, timely intervention in key areas is ensured, and the overall fire fighting effect is improved.

The embodiment of the invention provides a reservoir capacity dynamic monitoring method and system based on an unmanned aerial vehicle, and the method comprises the steps: obtaining a reservoir surface feature data set through the unmanned aerial vehicle, determining the boundary of a water area, scanning the bottom of the reservoir, obtaining the underwater terrain elevation and sediment distribution data, and constructing a three-dimensional terrain model; and determining terrain and deposit change data based on the three-dimensional terrain model dynamic change data of the continuous time sequence. Sedimentation space distribution characteristics are obtained through change rate analysis, and the sediment transportation amount and the sedimentation and deposition space rule are determined in combination with the water flow speed. Key driving factors are screened through correlation analysis, a sedimentation high-risk area is determined according to the key driving factors, and the change of sediments in the area is monitored, so that the change of the reservoir capacity is mastered. The reservoir siltation can be accurately and dynamically monitored, the high-risk area and the change mode are defined, the dynamic database is constructed to update the capacity change in real time, and important technical support is provided for reservoir management and flood control and disaster reduction.

The invention provides a hydropower station reservoir area three-dimensional terrain modeling method and device based on multi-source data fusion, and relates to the technical field of three-dimensional terrain modeling, and the method comprises the steps: obtaining a multi-source data set containing point cloud data, image data, texture data and actual measurement data of a hydropower station reservoir area; preprocessing the multi-source data set to obtain a preprocessed data set; and according to the preprocessed data set, constructing a three-dimensional terrain model by using an improved Delou inner triangulation algorithm, a non-uniform rational B-spline surface reconstruction technology and a Laplacian smoothing operator. The geometric accuracy and the natural form of the three-dimensional terrain model can be remarkably improved.

The invention discloses a rotor unmanned aerial vehicle hazardous substance identification management method and system for complex terrains, and belongs to the technical field of unmanned aerial vehicle monitoring. The system comprises a three-dimensional model generation module, a hovering point acquisition module, a data acquisition module, a hazardous substance identification module, a hazard grade sorting module and a data management module. According to the invention, a three-dimensional terrain model is generated in real time through a terrain complexity quantification algorithm, so that a hovering detection point is dynamically selected on an optimal cruise path through a preset path planning algorithm; visible light, infrared and acoustic multi-mode data are synchronously collected at a hovering point, and feature vectors of hazardous substances are extracted through YOLOv7 network fusion; according to the method, the detection coverage area is expanded under the complex terrain, the identification confidence is improved, the emergency response time is shortened, and the problems that the detection blind area is expanded, the identification confidence is reduced and the response time is prolonged under the complex terrain are solved.

The invention discloses an edge sea petroliferous basin paleotopography inversion method based on a machine learning algorithm, and belongs to the technical field of geological exploration and data processing. The method comprises the following steps: constructing a seismic profile data pool and carrying out image preprocessing; establishing an affine transformation relationship between pixel coordinates and physical coordinates by using an image digitization tool, and extracting a two-dimensional data sequence; establishing a mapping function of the measuring line distance and the longitude and latitude, and constructing a three-dimensional scatter data set; carrying out gridding interpolation by adopting a K nearest neighbor regression algorithm, and constructing a three-dimensional grid model; performing motion back-pushing and deformation-removing correction by using a plate reconstruction technology to obtain a paleotopography model; and generating a three-dimensional dynamic visualization result of paleotopography evolution through time interpolation. The method solves the problems that seismic profile images cannot be quantitatively analyzed, sparse data interpolation is difficult, and paleotopography inversion neglects structural deformation, and provides technical support for multiple fields such as oil-gas exploration.

The invention relates to the technical field of garden landscape design, in particular to a garden landscape design method based on a virtual reality technology, which comprises the following steps: step 1, multi-source data acquisition and three-dimensional modeling: adopting a laser radar to scan a design site to obtain high-precision terrain point cloud data and generate a three-dimensional terrain model, the method comprises the following steps: performing three-dimensional scanning on garden plants to construct a plant resource library containing plant morphological parameters, growth characteristics and a growth cycle algorithm, acquiring ecological data of field illumination intensity, soil pH value, annual precipitation and wind direction and wind speed through a sensor array, and establishing a field ecological parameter database; and 2, constructing an immersive virtual scene: importing the terrain model into a VR engine, and automatically generating a basic landform based on an ecological parameter database, and through growth simulation and space-time rendering, realizing full-cycle presentation from short-term landscape to long-term ecological change, improving the customer scheme recognition degree to more than 90%, and reducing the modification rate by 60%.

The invention discloses an uneven terrain adaptive vehicle path planning method and system based on multi-objective optimization, and the method comprises the steps: obtaining and preprocessing point cloud data of a predetermined operation region of a vehicle, and constructing a three-dimensional point cloud map; constructing a terrain attribute model based on the preprocessed point cloud, calculating a vehicle dynamic quantity, and generating an uneven terrain model; generating a two-dimensional rough trajectory by using an Eco-KinoA * path search algorithm; a two-dimensional track is obtained through optimization of a back-end multi-objective optimization algorithm; and finally, a three-dimensional vehicle track is generated in combination with the terrain model. According to the method, the problems of insufficient terrain accurate representation, lack of vehicle and terrain dynamic interactive modeling, insufficient multi-target collaborative optimization capability, poor real-time performance and adaptability and the like when vehicle path planning is carried out under the uneven terrain condition are solved, and the reliability, energy efficiency performance and safety of path planning are remarkably improved.

The invention discloses a photovoltaic power station wind field evaluation method and system, electronic equipment and a storage medium, and relates to the technical field of photovoltaic power station engineering. The method comprises the following steps: carrying out classification processing on original point clouds, generating DEM data by using Delaunay triangulation in combination with a natural neighborhood interpolation method, and carrying out correction through ground control points and least square adjustment; and constructing a three-dimensional terrain model according to the corrected data and image data, determining a computational domain size and a boundary condition, performing terrain optimization, executing LES solution after applying near-surface turbulence inlet disturbance synthesized by PRFG3, and comparing and evaluating the obtained transient wind field data with field actually measured wind speed data. According to the method, accurate capture of complex terrain wind field features and dynamic adaptive correction of the model are realized, so that the evaluation period is shortened, the surveying and mapping cost is reduced, the precision and reliability of wind field evaluation are remarkably improved, and the demand of wind resource evaluation of a large-scale photovoltaic power station is met.

The invention provides a road three-dimensional lane line detection method and system based on binocular vision, and relates to the technical field of automatic driving, and the method comprises the steps: carrying out the online calibration of internal and external parameters of a camera and the time sequence alignment of the binocular image and IMU attitude data through collecting the forward binocular image and IMU attitude data of a vehicle; processing the binocular image after time sequence alignment, and determining a dense disparity map; generating a road point cloud based on the dense disparity map and camera parameters, and constructing an adaptive terrain model; constructing a depth enhanced BEV feature map according to the depth feature of the road point cloud and the texture feature of the binocular image, predicting candidate parameters of a three-dimensional lane line, and screening through various constraints; and then executing extended Kalman filtering and trajectory optimization to obtain three-dimensional lane line parameters. According to the invention, rapid and accurate detection of the three-dimensional lane line can be realized, the accuracy of three-dimensional lane line detection under a complex terrain is improved, and the deployment cost is reduced.

According to the model conversion method provided by the invention, the height map of the terrain and the weight distribution maps of the plurality of material layers are acquired, the target three-dimensional grid model is generated according to the height map, the weight distribution maps of the plurality of material layers are combined to generate the weight map, and based on the position of the target three-dimensional grid model in the world coordinate system, the target three-dimensional grid model is converted into the target three-dimensional grid model. Calculating texture mapping coordinates; and generating a material instance corresponding to the target three-dimensional grid model according to a preset material template, the weight map and the texture mapping coordinate. Through effective integration and conversion processing of terrain height information and multilayer material weight information, automatic conversion from two-dimensional terrain data to a three-dimensional grid model with complete material information is realized, and it is ensured that the finally generated three-dimensional model can accurately express a complex material mixing effect. And the visual authenticity and rendering efficiency of the terrain model are obviously improved.

The invention relates to the technical field of flight simulation, provides a multispectral fusion flight simulation terrain generation method, system and device, and a storage medium, and solves the problem of low accuracy of flight simulation terrain generation. The method comprises the following steps: screening a target multispectral image of which the cloud coverage rate is lower than a set threshold value and target synthetic aperture radar data of a corresponding time window; extracting terrain edge features, dynamically adjusting a radar beam incident angle, and generating point cloud data with non-uniform resolution; a double-branch processing model is constructed, a first branch processes the target multispectral image, a second branch processes the point cloud data, and fusion features are obtained through a weighting mechanism; dynamically associating the vegetation index distribution of the terrain area to be measured with the elevation information in the fusion features to generate a space-time dynamic mapping result; and based on a space-time dynamic mapping result, generating a three-dimensional flight simulation terrain model with a semantic tag for planning a flight simulation path. The accuracy of flight simulation terrain generation is improved.

The invention discloses an ocean terrain digital display method based on three-dimensional modeling. The ocean terrain digital display method comprises the following steps of 1, constructing a multi-source ocean data set; 2, performing space fusion by adopting a self-adaptive interpolation method based on position weight to generate a three-dimensional space density field; 3, performing contour surface extraction by adopting an improved Marching Cubes algorithm to generate an initial three-dimensional terrain model; 4, performing local modeling by adopting a Delaunay triangulation network reconstruction method, and constructing a complete three-dimensional terrain model; 5, obtaining a texture terrain model; step 6, constructing an LOD tree structure and realizing dynamic loading in combination with view cone cutting and a screen space error control strategy; and step 7, based on a dynamic loading result of the LOD tree structure, driving node switching through a time controller, and performing visual display. According to the method, three-dimensional modeling and an LOD tree structure are fused, and high-precision reconstruction and evolution display of the ocean topography are achieved.

The present invention discloses a method for intelligent monitoring and support optimization of slope stability based on digital twins, comprising: extracting slope, curvature and geological stratification characteristics from a holographic terrain model, calculating the preliminary change trend of the stress distribution of the rock and soil body in combination with the finite element analysis method, and determining the spatial position distribution of the potential sliding surface of the slope; adjusting the data acquisition frequency of the sensor through a time series analysis method according to the spatial coordinate set of the real-time monitoring points, and obtaining a high-frequency monitoring data set reflecting the dynamic changes of stress and groundwater; extracting stress peaks and groundwater level fluctuation characteristics from the high-frequency monitoring data set, combining the spatial characteristics of the holographic terrain model, and using a data fusion algorithm to generate a multidimensional information matrix containing terrain, stress and water dynamics; judging according to the state parameters of the digital twin, if the stress distribution exceeds a preset threshold, recalculating the force distribution of the support structure through finite element analysis to obtain an adjusted slope support design scheme.

The invention discloses an engineering surveying and positioning method and system based on Beidou. The method comprises the following steps: S1, establishing an oil field operation environment three-dimensional model, and performing satellite visibility and multipath prediction; according to the invention, by constructing a multi-path geometric model and a dual-antenna array discrimination and weighted suppression algorithm, reflection interference caused by a metal facility dense environment in a well site and a station site is effectively weakened; by fusing a local DEM terrain model and earth surface reflection characteristics and introducing vertical Kalman filtering, the stability and precision of Beidou elevation calculation are significantly improved; under the scene of insufficient visibility such as shielding of a drilling machine and large equipment, continuous and high-reliability positioning capability is kept through a tight coupling fusion strategy of IMU and vision assistance, so that high-robustness and high-precision Beidou engineering measurement positioning can be realized in a complex environment of an oil field.

There is no system that calculates transportation project costs that reflect the ability of users to adjust the transportation vehicle's travel route to avoid interference between the transportation vehicle or large cargo and the current terrain, so it is not possible to quickly select the optimal transportation route. [Solution] The large cargo transportation simulation system 1 comprises a condition receiving unit 10a, an acquisition unit 10b that acquires 3D current terrain model data of the route the transport vehicle will travel, a simulation unit 10c that simulates whether the 3D model of the transport vehicle or the 3D model of the large cargo will interfere with the 3D current terrain model based on multiple conditions and the 3D current terrain model data, a display unit 11 for the simulation results, and an adjustment receiving unit 10d that accepts user adjustments to the transport vehicle's travel route, and the system calculates transportation project costs that reflect the results, allowing for the rapid selection of the optimal transportation route.