46 results about "Grid computing" patented technology

The invention discloses a field soil heavy metal pollution health risk dynamic assessment and intelligent early warning system, and relates to the technical field of soil environment monitoring. The system comprises a multi-source data acquisition unit, a data preprocessing unit, a risk calculation engine and a visual interaction terminal. The key technical point is that a dynamic field evolution analysis module and an adaptive grid rendering control module are introduced; the dynamic field evolution analysis module constructs a pollution potential energy field matrix representing a pollutant migration trend based on soil heavy metal concentration and hydrogeological parameters, and calculates a space-time gradient change vector of the pollution potential energy field matrix; and the latter dynamically adjusts the grid local density according to the gradient vector module value, and automatically encrypts the computational nodes in the region with severe risk change. In cooperation with a time sequence prediction deduction and feedback correction mechanism, the method can simulate the dynamic evolution of the pollution plume in the porous medium in real time, solves the problems that a migration rule is difficult to capture and the calculation efficiency of a uniform grid is low in traditional static evaluation, and achieves three-dimensional dynamic risk early warning with high precision and low calculation power consumption.

The invention discloses a bare concrete appearance quality evaluation method, which belongs to the field of concrete quality evaluation, and adopts the technical scheme that process data are synchronously acquired in a bare concrete pouring process; obtaining concrete surface appearance index data after demolding; performing time synchronization and spatial inverse registration on the acquired data, and performing gridding association on the appearance indexes and the process data in the corresponding time windows; for each grid unit, extracting vibration effective energy, pumping pressure fluctuation characteristics, template deformation characteristics and environment correction factors from the process data in the corresponding time window and space range, and combining the vibration effective energy, the pumping pressure fluctuation characteristics, the template deformation characteristics and the environment correction factors into a joint characteristic vector; constructing a structural causal model, calculating the cause posterior probability of the appearance defect for each grid, and outputting cause probability distribution of under-vibration, over-vibration, unstable pumping, insufficient template rigidity and environmental sensitization; and generating an appearance quality score according to the cause probability distribution. The method has the beneficial effect that the method for evaluating the appearance quality of the fair-faced concrete is provided.

The invention discloses an ancient building group fire early warning method and system based on an internet platform, and relates to the technical field of fire early warning, and the specific implementation scheme is as follows: obtaining a visible light image, and determining a scene type based on smoke detection confidence; the method comprises the following steps: after triggering to execute registration operation on an original infrared image, extracting an infrared feature map and a visible light feature map, generating an attention weight map according to the infrared feature map and the visible light feature map, and generating a preliminary fusion feature by combining the infrared feature map and the visible light feature map; performing dimension reduction compression processing on the preliminary fusion feature to obtain a low-dimensional feature vector, and inputting the low-dimensional feature vector into a classifier to obtain a fire occurrence probability of the current monitoring grid so as to select an early warning scheme; and marking the current monitoring grid as a risk source grid, calculating a directional propagation coefficient, updating a fire occurrence probability of an adjacent target grid, and adjusting an early warning scheme. According to the technical scheme of the invention, the problem of poor effectiveness of fire early warning of the ancient building group caused by abnormal fire behavior recognition is solved.

The present invention relates generally to a system designed to provide application graphical display while using High-Performance Computing systems which are based on GRID systems, in which applications can be executed on any one out of multiple compute nodes while the user interactive session (also known as an X session) is viewed from a control session. In specific, the invention relates generally to a system which creates a separate selfsustained X Display session for each launched application, while a list of available sessions is provided to the main user graphical session allowing interacting with the remote application without directly affecting its integrity in case of disconnection.

The invention provides a two-dimensional flow field calculation method and system for a vertical axis wind turbine, and relates to the technical field of computational fluid mechanics, and the method comprises the steps: building a two-dimensional numerical model for a middle plane of the vertical axis wind turbine; based on the two-dimensional numerical model, determining a two-dimensional flow field of the vertical axis wind turbine at the current moment; according to the two-dimensional flow field, blade lift force is determined; generating a target blade tip vortex element, and calculating the strength of the target blade tip vortex element through the Rogowski lift theorem; updating the position and strength of the vortex element of the blade tip vortex; traversing all grids in the two-dimensional flow field drainage basin based on the updated blade tip vortex elements, and for each grid, calculating the blade tip vortex induced velocity of the position where the grid is located; calculating and applying a required mass source item and a required momentum source item according to the induced velocity; and after the preset updating frequency is reached, outputting a calculation result. The calculation amount is reduced, and the calculation efficiency and accuracy are improved.

The invention provides a tight gas reservoir gridding evaluation method, system and device and a storage medium, and the method comprises the steps: obtaining dynamic and static data of a target block, the dynamic and static data comprising geological data and production dynamic data; geological reserve gridding parameters are determined based on the geological data, and the geological reserves are gridded; determining the dynamic reserves of each well in the target block based on the production dynamic data, and meshing the dynamic reserves of each well; calculating the unused reserves and the ratio of the dynamic reserves to the static reserves of the target block grid by grid based on the geological reserve gridding and the dynamic reserve gridding of each well; and obtaining a gas reservoir evaluation result based on the unused reserves and the dynamic and static reserve ratio. According to the method, fine evaluation and infilled well arrangement of the tight gas reservoir are achieved, well pattern infilled evaluation refinement is high, calculation is convenient, and the method has great significance in development evaluation of the tight gas reservoir, development scheme compiling, recovery ratio improving countermeasure making and the like.

The invention provides a GNSS interference detection positioning method and system based on an ADS-B network, and relates to the technical field of satellite navigation. And based on the historical state data of the aircraft, predicting the state of the aircraft by using the time sequence prediction model to obtain a predicted value of the state of the aircraft. And if the deviation between the predicted value and the received true value is greater than a preset threshold value, judging that the aircraft is interfered, and calculating the interference confidence coefficient. A monitoring area is divided into grids, interference indexes in the grids are calculated, and a potential interference area is determined. And the ADS-B message of the aircraft with the highest interference confidence in the potential interference area is selected as an interference source to trigger a virtual signal. And finally, calculating the time when the interference source triggers the virtual signal to the ground station, and obtaining the position of the GNSS interference source based on the time. According to the interference detection positioning provided by the invention, the GNSS interference source can be efficiently and accurately detected and positioned, and the reliability of interference identification and the aviation safety monitoring capability are improved.

The invention discloses a space target three-dimensional reconstruction and intelligent identification method based on an RGB-D camera, and the method comprises the steps: obtaining a depth image and a color image of a space target through the RGB-D camera, converting an original depth image in an image coordinate system into point cloud data in a camera coordinate system through a pre-calibrated camera internal reference and a transformation matrix, and carrying out the recognition of the point cloud data in the camera coordinate system; obtaining corresponding color information from the color image through the camera parameters; a visual odometer of SLAM is adopted to transform all the point cloud data to the same global coordinate system for accumulation, and a complete point cloud model representing a space target contour is obtained; preprocessing the point cloud model, searching for a triangular mesh on the real model closest to each point in the point cloud model, calculating the Euclidean distance from each point to the corresponding triangular mesh, and endowing each point with color information according to the Euclidean distance; and performing automatic semantic annotation on the point cloud model, and realizing three-dimensional intelligent identification of the component based on an improved Pointnet + + architecture.

The invention relates to the cross technical field of geographic information science and environmental science, in particular to an urban carbon emission regression prediction method, which comprises the following steps: acquiring urban annual statistical data as original characteristics, and acquiring corresponding carbon dioxide emission; dividing a city latitude and longitude extreme value range into uniform grids, and calculating a coordinate deviation vector and an Euclidean distance from the city to a grid center point; carrying out vector projection on the deviation vector along three unit directions which form 120 degrees with one another, and combining geometric progression spatial frequency coding to generate a spatial embedded feature map; flattening the feature map, obtaining an original attention score through a full connection layer, and combining with spatial distance gating mask screening and merging to obtain a weighted feature; and splicing the weighted features and the original features to obtain an enhanced feature map, training the model, obtaining a carbon emission prediction model, inputting the enhanced feature map of the city to be predicted, and obtaining a carbon emission prediction value.

The invention discloses an induction heating optimization method and system based on numerical simulation. The method comprises the following steps: S1, establishing a three-dimensional geometric model comprising an induction coil, a workpiece and a magnetizer; s2, electromagnetic parameters and thermal field parameters are set based on the three-dimensional geometric model; s3, performing grid division on the three-dimensional geometric model; s4, operating an electromagnetic-thermal sequential coupling solver, calculating transient distribution of an electromagnetic field and a temperature field based on the parameters set in S2 and the grids generated in S3, dynamically updating material attributes according to the current temperature field in each time step, and performing iterative solution; and S5, processing the field distribution data obtained by solving in the step S4, generating a visual result and extracting key performance indexes. According to the invention, the distribution of the magnetic field and the temperature field can be accurately optimized, and meanwhile, extremely high heating efficiency, excellent temperature uniformity and excellent process controllability are realized.

The application discloses a kind of NGSO constellation to GSO earth station lumped interference determination method and system, belong to satellite communication and radio electromagnetic compatibility analysis technical field, method includes: acquisition NGSO constellation and GSO earth station core parameter;Analysis orbit parameter determines reference satellite position plane, conversion geocentric angle and divide coarse grid;Iterate coarse grid and deduce whole constellation satellite three-dimensional position;Calculate link angle and screen collinear interference satellite, mark initial CIR;Satellite position probability density function is constructed, and the total interference probability that initial CIR is integrated is obtained;Compare threshold probability and optimize CIR range;Subdivide final CIR into fine grid, calculate each point lumped interference and probability;Local cumulative distribution curve is constructed, and interference determination is completed by comparing with protection limit value.The application is combined with physical geometric constraint and probability density distribution theory, greatly reduce the amount of calculation, guarantee determination accuracy and compliance, applicable to spectrum coordination, satellite network declaration and other engineering scenarios.

Embodiments include methods for synchronizing an augmented reality (AR) object placed in a 3D mesh onto a video feed. A computing device may first receive a video feed including a sequence of frames of a scene and depth or motion data captured by a camera. The computing device may generate a three-dimensional (3D) mesh based on the depth or motion data. The computing device may texture the 3D mesh to create a 3D model. Upon performing object recognition, the computing device may identify anchor points in the 3D model and anchor points in the video feed. The anchor points are used to calculate the location of the AR object.

The invention provides a submarine cable burial depth monitoring method, a computer program product and electronic equipment. The method comprises the following steps: acquiring basic temperature data of a to-be-measured space point in a first submarine cable in each unit time of a preset time period; the basic temperature data comprises soil temperature data; obtaining a feature set of the spatial point to be measured according to the basic temperature data; and inputting the feature set into a burial depth monitoring model to obtain burial depth data of the to-be-measured spatial point. And reasoning the feature set by using the burial depth monitoring model to obtain the burial depth data of the to-be-measured spatial point without calculating the heat dissipation condition, thereby reducing the error introduced by parameter estimation in the calculation, avoiding a large amount of grid calculation, saving the calculation resource, reducing the complexity of submarine cable burial depth measurement and calculation time consumption, and improving the calculation efficiency. And the burial depth measuring and calculating efficiency is improved.

The embodiment of the application discloses a method for determining ionospheric parameters based on user crowdsourcing data, and relates to the technical field of satellite navigation and positioning. The method comprises the following steps: acquiring ionospheric data uploaded by multiple user terminals, taking each user terminal as a target station, calculating the standardized residual error corresponding to each user terminal by using the Kriging interpolation method, and eliminating the user terminal whose standardized residual error is greater than the standardized residual error threshold; determining the target grid corresponding to each user terminal on the pre-constructed Q4DIM network, calculating the slant path ionospheric delay corresponding to the target grid, and extracting the slant path ionospheric delay corresponding to the target grid and sending it to the user terminal according to the target grid corresponding to the user terminal. The ionospheric data uploaded by the user terminal in real time can improve the resolution of the ionospheric data, expand the coverage range of the ionospheric product, broadcast accurate ionospheric data to the user terminal, and improve the rapid positioning accuracy of the user terminal far away from the reference station.

A kind of underwater vehicle noise prediction correction method based on bayesian inference, calculation model (1) includes Corcos autospectrum and Corcos normalized cross power spectral density function calculation model;According to calculation model (1), construct the schematic diagram (2) of bayesian network, the key factor identification and state analysis of the key factor of the modeling of the influencing factor of turbulent fluctuation pressure in bayesian network in schematic diagram (2) of bayesian network are built-in bayesian inference;According to the schematic diagram (2) of bayesian network, model in NETICA software, construct directed acyclic bayesian network (3);Reference calculation model (1) and directed acyclic bayesian network (3) are simulated setting (4) and noise signal comparison (5).The present application has the advantages of ensuring the precision of low-frequency noise prediction in sparse grid large size, improves the problem that the grid scale of finite element model and the space related scale of turbulent boundary layer pressure do not match and the calculation amount is too large when fine grid is used.

The invention relates to a radar metal ball calibration method and device, computer equipment and a medium, and the method comprises the steps: obtaining the directional diagram data of a radar transmitting antenna and a receiving antenna, carrying out the normalization processing of the directional diagram data, and obtaining the normalized data; on the basis of the normalized data of the corresponding angles, discrete grids are constructed, and solid angle infinitesimal elements of all grids in the discrete grids are calculated; performing discrete integral operation on the normalized data of the corresponding angle based on the solid angle infinitesimal to obtain integral data of the corresponding angle; obtaining an input parameter of radar calibration, and calculating a theoretical reflectivity factor of the receiving antenna at each angle based on the input parameter and the integral data; and calculating a corresponding radar calibration parameter based on the theoretical reflectivity factor of each angle, and transmitting the radar calibration parameter to a signal processor to complete system calibration. According to the method, the calibration precision of the radar system in the wide-transmitting narrow-receiving mode can be improved.

An encoding method is provided and includes: obtaining a volumetric mesh; performing mesh segmentation of the volumetric mesh to generate multiple segments of mesh content; performing mesh decimation of a segment of mesh content to generate a base mesh; performing mesh subdivision of the base mesh to generate multiple subdivided base meshes; calculating multiple mesh displacements between the multiple subdivided base meshes and an original volumetric mesh surface to generate multiple transformed displacement coefficients; converting the multiple transformed displacement coefficients to multiple quantized transformed displacement coefficients; scanning the multiple quantized transformed displacement coefficients along a three-dimensional space scanning pattern within each level-of-detail to form three one-dimensional arrays; and re-arranging the multiple quantized transformed displacement coefficients in the three one-dimensional arrays to a two-dimensional image according to the each level-of-detail and a packing order indicated by a specific flag.

The invention relates to the technical field of distribution network monitoring and evaluation, in particular to a distribution network equipment health evaluation method, system, equipment and medium based on a point cloud model, and the method comprises the steps: collecting data of a distribution network and a surrounding environment, constructing a four-dimensional space-time model, and calculating an activity envelope according to an actual process model of a dynamic object based on the constructed four-dimensional space-time model. Generating a static safety buffer area distributed along the power line, converting a space-time range jointly defined by the static safety area and a preset time window into a discrete four-dimensional grid based on the active envelope body, calculating the occupancy probability of a dynamic object based on the discrete four-dimensional grid, and calculating the occupancy probability of the dynamic object based on the discrete four-dimensional grid. A prospective risk value generated by a dynamic object for a power line is quantified through a first-level algorithm, the prospective risk value and a four-dimensional space-time model are subjected to data association and visualized presentation, a complex risk assessment result is converted into visual decision support information, and the decision support information is displayed in a real-time manner. Therefore, the defects of the existing method in the aspects of data dimension, risk quantification capability and information presentation mode are overcome.

The invention discloses a method for predicting the running speed of a detector in a gas pipeline. The method comprises the steps that S1, the pipeline, fluid and PIG are initialized, and parameters are calculated; s2, calculating a fluid initial state, defining a PIG initial static state, and constructing a PIG state matrix for recording a PIG state and a flow field matrix for storing grid fluid parameters; s3, updating a PIG state matrix based on the PIG head and tail fluid pressure difference; s4, judging whether the PIG crosses grids or not, and dividing upstream and downstream flow fields; s5, calculating flow velocity and pressure of upstream and downstream flow fields in a grid-dividing manner, and storing the flow velocity and pressure into a flow field matrix; s6, iteratively updating the two matrixes under the condition that PIG does not reach the end point of the pipeline; and S7, after the PIG reaches an end point, drawing a full-period speed prediction curve based on a PIG state matrix, and verifying the full-period speed prediction curve by using a flow field matrix. According to the invention, the problem of inaccurate data caused by insufficient PIG speed control precision, response lag and odometer wheel slipping is solved. According to the invention, bidirectional coupling of the flow field and PIG motion is realized, the speed prediction precision and real-time performance are improved, and a quantitative basis is provided for optimization of a pipeline detection scheme.

The invention relates to the technical field of computers, and particularly provides a hybrid parallel computing method and device for power grid computing deduction generality service, and the method comprises the steps: carrying out the clustering of sample data based on the complexity and intensity of the sample data, and distributing each cluster in a clustering result to each equipment cluster as training data; splitting the artificial intelligence model according to layers, and distributing the split model layers to parallel computing equipment in each equipment cluster; calculating the task parallel complexity of each equipment cluster based on the time required for executing the calculation task by the parallel calculation equipment in each equipment cluster; and based on the task parallel complexity of each equipment cluster, adjusting the model layer allocated by the parallel computing equipment in each equipment cluster. According to the technical scheme provided by the invention, data and a training model required by power grid application are divided more finely, efficient execution of an algorithm model is realized, and the overall effect of power grid calculation deduction service is improved.

The application discloses a kind of grid platform construction and running method for large-scale ecological quality and service evaluation, constructs multilevel unified space grid system;Obtain multi-source ecological data, and standardize processing to multi-source ecological data and establish data quality control mechanism and version management mechanism, form ecological evaluation basic database;Based on ecological evaluation basic database, establish layered microservice platform architecture, and encapsulate ecological evaluation model as standard model container;Based on the evaluation task parameters configured by user, the first evaluation result is obtained by automatically executing the grid computing process through the layered microservice platform architecture, the first evaluation result is verified by calling the precision verification process, and the second evaluation result that passes verification is inputted into the early warning system through the standard interface to display the early warning information in linkage. The application improves the execution efficiency and intelligent level of ecological evaluation business, and meets the large-scale and visual ecological evaluation business demand.

This application relates to an automated method and apparatus for measuring the volume of a pile. The method includes: scanning the target pile and the container environment storing the target pile to collect scanned point cloud data and sampled point cloud data; performing point cloud registration on the scanned and sampled point cloud data to obtain registered point cloud data, and then cropping and snapping it to obtain a set of boundary points at the boundary between the target pile and the container environment; based on the boundary point set, denoising and segmenting the cropped registered point cloud data to obtain segmented point clouds; and extracting the complete surface information of the target pile based on the boundary point set and the segmented point clouds to perform surface reconstruction to generate a closed triangular mesh corresponding to the target pile, and using the closed triangular mesh to calculate the volume of the target pile. This solves the problems of insufficient accuracy, difficulty in handling boundary issues, high data acquisition requirements, and limited application scenarios in existing point cloud volume measurement technologies.

The application discloses a site soil heavy metal pollution health risk dynamic assessment and intelligent early warning system and relates to the technical field of soil environment monitoring.The system comprises a multi-source data acquisition, data preprocessing, risk calculation engine and visual interactive terminal.The key technical point of the application lies in the introduction of a dynamic field evolution analysis module and an adaptive grid rendering control module:The former constructs a pollution potential field matrix representing the migration trend of pollutants based on soil heavy metal concentration and hydrogeological parameters, and calculates the spatio-temporal gradient change vector;The latter dynamically adjusts the local density of the grid according to the gradient vector module value, and automatically encrypts the calculation nodes in the area where the risk changes dramatically.Coupled with the time series prediction deduction and feedback correction mechanism, the application can simulate the dynamic evolution of the pollution plume in the porous medium in real time, solve the problems that the traditional static assessment is difficult to capture the migration law and the uniform grid calculation efficiency is low, and realize the high-precision, low-computing-power-consumption three-dimensional dynamic risk early warning.

The invention relates to the technical field of intelligent control, and provides a method for recycling and optimizing a potential well pattern by excavating remaining oil after polymer flooding of a first-class oil reservoir, which comprises the following steps of: acquiring basic data of all unit grids in all grid units of a well pattern in a block after polymer flooding of the first-class oil reservoir; dead oil zone grids in the grid units are screened, and the remaining oil tapping potential of the dead oil zone grids is calculated; determining dead oil zone clusters formed by dead oil zone grids, calculating the comprehensive potential of the dead oil zone clusters, and screening high-potential dead oil zone clusters; the new well fitness of each dead oil area grid in the potential dead oil area cluster is calculated, new well positions determined by the potential dead oil area cluster are obtained, site selection is carried out on the new well positions again according to the relative distribution of all the new well positions, and optimization of reuse of the potential tapping well network is achieved. The invention aims to improve the well pattern reutilization optimization effect.

The invention discloses a pipeline water-gas two-phase flow high-performance calculation method based on local time step length, which comprises the following steps: setting a calculation grid according to collected pipeline design data; preliminarily estimating the time step length of each grid calculation according to the Crawler condition; adjusting the preliminarily estimated time step length to obtain a local time step length of each grid; and based on the local time step length of each grid, solving a pipeline water-gas two-phase flow mathematical model, and judging whether a Kink condition is met or not. By introducing local time step adjustment, efficient, accurate and stable numerical simulation of the water-gas two-phase flow of the pipeline is realized, and the problem of high solving cost of a mathematical model of the water-gas two-phase flow of the pipeline is solved.

The invention discloses a farmland information acquisition system for communication between an unmanned aerial vehicle and a ground Internet of Things node, and relates to the technical field of agriculture, and the system comprises an acquisition module, a task planning module, a flight control module and a man-machine interaction module. A fixed-wing unmanned aerial vehicle and a multi-rotor unmanned aerial vehicle are adopted to form an acquisition module, the fixed-wing unmanned aerial vehicle and the multi-rotor unmanned aerial vehicle cooperate with each other, a task planning module is based on a farmland GIS map, abnormal areas can be accurately screened out through grid division, normalized vegetation index calculation and other operations, tasks of the fixed-wing unmanned aerial vehicle and the multi-rotor unmanned aerial vehicle are reasonably distributed for different monitoring requirements and farmland area characteristics, and the monitoring efficiency is improved. The fixed-wing unmanned aerial vehicle is used for preliminarily macroscopically monitoring a large-area and flat-terrain area; for a local fine monitoring area formed by abnormal grid aggregation, the multi-rotor unmanned aerial vehicle is arranged to carry out targeted deep monitoring, tasks can be reasonably allocated according to different area characteristics and monitoring requirements of a farmland, and the operation efficiency is greatly improved.

The invention belongs to the technical field of image processing, and particularly relates to a geological three-dimensional exploration image reconstruction method, which comprises the steps of calculating credibility weights, adaptive adjustment parameters and geological complexity of data points, and determining contribution weights of the data points to grid nodes; screening adjacent points of the grid nodes, and constructing an initial three-dimensional grid based on the geological attribute values; calculating a gradient vector of each node of the initial three-dimensional grid, constructing a structure tensor matrix, decomposing the structure tensor matrix to obtain a feature value and a feature vector, dividing a structure region according to the feature value, calculating a relative weight and a normalized adjustment factor in each direction, and combining a preset region type factor to obtain a smooth adjustment coefficient of each grid node in each direction; and constructing a diffusion matrix through the smooth adjustment coefficients in all directions and the corresponding feature vectors, and iteratively optimizing the initial three-dimensional grid through an anisotropic diffusion technology to obtain a reconstructed geological three-dimensional exploration image. According to the invention, the accuracy of geological three-dimensional exploration image reconstruction is improved.

The application discloses a sub-resolution auxiliary pattern exposure model training method and related devices, applied to the technical field of auxiliary pattern exposure, comprising obtaining a printed image formed after sub-resolution auxiliary pattern exposure and extracting a printed contour; the printed contour retains a contour corresponding to the sub-resolution auxiliary pattern; the printed image is grid divided, and a grid is formed on the printed image; a correction scale is arranged in each grid; an area proportion covered by the auxiliary pattern printed contour in each grid is determined based on the correction scale; an initial model is trained with the area proportion as an input value to obtain an exposure model. By dividing the grid in the printed image, the area proportion of the auxiliary pattern printed contour in each grid is calculated, the area proportion is not binary data, and the printed degree of the sub-resolution auxiliary pattern can be accurately represented. The initial model is trained by the area proportion, so that the exposure model after training has higher accuracy.

The invention relates to the technical field of photogrammetry, in particular to a geologic body modeling method and system based on an unmanned aerial vehicle laser radar, and the method comprises the following steps: obtaining laser ranging and pulse counting, calling a field programmable gate array to carry out time marking, retrieving adjacent frame data, and generating an instantaneous attitude and coordinates through linear interpolation; a three-dimensional laser point cloud is generated based on installation error matrix conversion, a local gradient is calculated by mapping grids to screen ground points, and a geologic body three-dimensional digital model is constructed by utilizing Delaune triangulation. According to the method, the field programmable gate array is utilized to mark data time, the interpolation algorithm is combined to solve the instantaneous attitude, the three-dimensional point cloud is generated based on the error matrix, the grids are mapped, the gradient is calculated to screen the ground points, the geologic model is constructed through Delaune triangulation, and high-density ground surface data can be obtained without contact measurement. And the modeling reduction degree of the complex terrain is improved.