30 results about "Delaunay triangle" patented technology

The invention discloses a Delaunay triangle and curvature minimization-based point cloud integrity improvement method and system, and the method comprises the following steps: converting a point cloud under a three-dimensional rectangular coordinate system into a spherical coordinate system, and then projecting the point cloud to a two-dimensional plane coordinate system to form a two-dimensional plane point cloud; carrying out Delaunay triangularization, and then projecting back to a three-dimensional rectangular coordinate system to form a spatial two-dimensional triangular mesh; the side length, the area and the unit normal vector of each triangular mesh are calculated, and abnormal triangular meshes are removed according to the side length; searching boundary points of the point cloud according to the topological relation of the triangular mesh edges; searching the boundary points of the missing part according to the corresponding relation of the boundary points; filling a plurality of points in the missing part based on spherical projection; and calculating the curvature of the filling point, and performing iteration to enable the curvature to be minimum so as to correct the position of the filling point. According to the method, the boundary points of the point cloud can be effectively detected, the filling points are generated, and the missing parts are repaired, so that the integrity and the accuracy of the point cloud are improved.

The invention discloses a camera self-calibration method based on a Delaunay triangulation network, and relates to the technical field of camera calibration, and the method comprises the following steps: S1, collecting an image in an experiment region, carrying out the corner detection of the experiment image through employing a Harris algorithm, and eliminating false points through employing a Gaussian smoothing function; and S2, constructing a Delaunay triangle by using the feature angular points extracted in the S1, and optimizing and removing'ill-conditioned triangles'. Computer vision and point cloud data processing are combined, the Delaunay triangulation network is constructed to simulate topographic feature information, feature matching of a three-dimensional point cloud and a two-dimensional image is achieved, camera self-calibration under the complex topographic condition is achieved, calibration precision is high, robustness is good, and the method is not prone to being affected by noise and initial values; by constructing the Delaunay triangulation network of the image and the point cloud to represent the scene topographic features, the requirement of camera calibration for the geometric features of the scene ground features is reduced, camera self-calibration under the complex topographic condition is realized, the calibration steps are simplified, and the flexibility and universality of camera calibration are improved.

The invention provides a method for evaluating the uniformity of a mixed material. The method is used for solving the technical problem that an existing method for evaluating the uniformity of the mixed material cannot meet the requirement for evaluating the mixing uniformity of powder raw materials with different granularities and different densities. The method comprises the following steps: performing appropriate sampling at different positions of powder to be analyzed; photographing the surface of the sampled mixed material according to the granularity and specific characteristics of the raw material powder; selecting a proper subject matter in the photographed image, and sequentially carrying out binaryzation, subject matter marking, Delaunay triangulation, Voronoi image change and intercept point statistics on the photographed image; determining the mixing uniformity of a single sampling position according to an intercept point statistical result; counting the mixing uniformity of all sampling positions; and calculating the confidence degree of the mixing uniformity analysis result of all sampling positions by using distribution inspection, and determining the confidence degree of the judgment result. Compared with the prior art, the method has the advantages that the analysis speed is high, complicated chemical and physical pretreatment is not needed, real-time online monitoring can be realized, and the accuracy is relatively high.

The invention discloses a three-dimensional reconstruction live-action model tree model generation method, and belongs to the technical field of three-dimensional model reconstruction. The method comprises the following steps: carrying out multi-station foundation laser radar scanning on a tree to obtain point cloud data; preprocessing the point cloud; performing branch and leaf separation on the tree point cloud to obtain a leaf point cloud and a branch point cloud; performing leaf cluster scale clustering to obtain each leaf cluster; constructing a Delaunay triangulation network model for each leaf cluster to obtain each leaf model; for the branch point cloud, an Alpha-shape algorithm is adopted to construct a branch model; the leaf model and the branch model are fused, and three-dimensional modeling of the whole tree is completed; and rendering the tree model to complete generation of the tree model. According to the method, high-precision and high-reduction-degree tree model reconstruction is realized, and the method has relatively high data rendering and processing efficiency.

The present invention discloses a camera self-calibration method based on Delaunay triangulation, which relates to the field of camera calibration technology. The method comprises the following steps: S1: collecting images within an experimental area, detecting corners of the experimental images using the Harris algorithm, and eliminating pseudo points using a Gaussian smoothing function; S2: constructing Delaunay triangles using the characteristic corner points extracted in S1, and optimizing and eliminating "pathological triangles". The present invention combines computer vision with point cloud data processing, simulates terrain feature information by constructing a Delaunay triangulation, achieves feature matching between three-dimensional point clouds and two-dimensional images, and realizes camera self-calibration under complex terrain conditions. The calibration method has high calibration accuracy, good robustness, and is not easily affected by noise and initial values. By constructing a Delaunay triangulation of images and point clouds to represent scene terrain features, the requirements for camera calibration on the geometric features of scene objects are reduced, camera self-calibration under complex terrain conditions is realized, the calibration steps are simplified, and the flexibility and universality of camera calibration are improved.

The application discloses a grid mapping method for finite element method or finite volume method and phase field method dendrite growth calculation. The application relates to the technical field of welding simulation. Specifically comprises the following steps: step 1, obtaining the field variable distribution in the numerical simulation calculation of the finite element method or the finite volume method welding process; step 2, exporting the coordinates and field variable data of the nodes with the temperature greater than the metal melting point; step 3, performing triangular partitioning on the melting area according to the node coordinates; step 4, drawing the Voronoi diagram of the melting area according to the circumcenters of the Delaunay triangles; step 5, setting the phase field method nodes; step 6, sequentially processing the units in the Voronoi diagram, taking the base point of the unit and the base point directly connected with the base point as known points, and obtaining the field variable value of the phase field method nodes by the interpolation method; and step 7, using the obtained field variable value for the calculation of the phase field method grain growth.

A three-dimensional Mesh grid generation method for three-dimensional reconstruction of a stereo satellite belongs to the field of satellite image three-dimensional reconstruction production, and is characterized by comprising the following steps: performing intersection processing on a DSM image and building vector Shp data to obtain a roof DSM and a ground DEM; respectively processing the building vector Shp data, the roof DSM and the ground DEM to obtain three-dimensional vector feature points; performing grid turning point cloud processing on the ground DEM and the roof DSM; constructing a Delaunay triangulation network in a partitioning manner; and combining and outputting a final Mesh grid. By inputting a high-resolution DSM image and building vector Shp data of a corresponding region, extracting topographic features of a reference DEM and inputting the DSM by using a gradient calculation method, and by means of the satellite large-area three-dimensional grid generation method based on building geometric features and the DSM, the defects that the side face of a building is too fine in a satellite large-area three-dimensional scene in a traditional method, and the size of the building is too small can be effectively overcome. The technical problems of obvious splicing seams and unnatural texture transition in the prior art are solved, the existing topographic features are fully utilized, and the precision and attractiveness of the three-dimensional grid can be effectively improved.

The present invention relates to a method for generating a drivable area for trajectory planning of an autonomous vehicle, comprising the following steps: 1. extracting road conditions and expanding obstacles and road boundaries; 2. performing a Delaunay triangulation algorithm based on the expanded obstacles and road boundaries to output a triangle connectivity list and a Delaunay triangle mesh; 3. generating a rough triangle edge path based on the triangle connectivity list and the Delaunay triangle mesh; and 4. integrating triangle edges based on the rough triangle edge path to form a drivable area. Compared with existing technologies, the present invention has the advantages of improving the performance of trajectory planning systems, a simple algorithm structure, and strong robustness.

The invention provides a GNSS imaging method and device for detecting short-wavelength deformation, and the method comprises the steps: firstly determining the weight of each to-be-estimated point based on a space structure, then extracting an estimated value of a vertical speed, and generating a GNSS image; the step of determining the weight based on the space structure comprises the steps of firstly obtaining a known observation station connected with a to-be-estimated point based on a Delaunay triangle, then obtaining a preliminary weight by using Gaussian process regression, and obtaining a final weight of the connected known observation station after re-weighting based on velocity uncertainty; the step of extracting the estimated value of the vertical velocity comprises the step of extracting the estimated value of the vertical velocity of the to-be-estimated point by adopting generalized weighted median filtering processing based on the final weight of a known observation station connected with the to-be-estimated point. The invention provides a Gaussian process regression GPR-VU scheme considering speed uncertainty, a space structure between a known point and an unknown point is constructed by using a covariance matrix, an earth crust deformation GNSS image in a research area is generated, and detection of short wavelength deformation in an area with complex geology and strong structural activity is realized.

The invention relates to the technical field of geology, in particular to a geologic occurrence difference algorithm based on Delaunay triangulation, which comprises the following steps of: 1, establishing a normalized geologic occurrence table which comprises a number, N, E, an occurrence direction D and an occurrence angle P; 2, constructing a Delaunay triangle according to N and E in the normalized geological occurrence table, establishing a Delaunay triangle table, and storing in a manner of triangle number, vertex 1, vertex 2 and vertex 3; 3, extracting edges of a Delaunay triangle based on the Delaunay triangle table, and establishing an edge information table which comprises an edge number, a vertex 1, a vertex 2 and a subordinate triangle; 4, a plurality of points P1, P2,..., Pn are obtained through intersection with the geological boundary line DZ1, the points are stored in an intersection point information table, and the intersection point information table comprises intersection point numbers, geological boundary numbers, edge numbers, N and E; and 5, solving the direction and angle of the occurrence of the intersection point, and interpolating the occurrence of any point of the geological boundary line.

The application discloses a kind of triangle mesh model construction methods based on nearest point local optimization.The method of the application comprises the following steps: obtaining the original image of target entity, obtaining planar point set according to the original image, and then constructing initial polygon, the internal area of initial polygon is divided into several grids and is sorted;Initial polygon is disassembled into initial triangle;According to the grid order, insert data points, after inserting each data point, obtain the nearest data point, and then locate all non-Delaunay triangles, delete all internal boundaries of non-Delaunay triangles, generate several new triangles;Finally, all initial polygon related triangles are deleted from the initial triangular mesh model, and the triangular mesh model of the target entity is obtained.The application quickly locates the non-Delaunay triangle in the triangular mesh by the nearest point, optimizes the efficiency of triangular mesh construction, and improves the image processing efficiency based on Delaunay triangulation without changing the triangulation effect.

The present application relates to a method for calculating the uniformity and porosity of a mixed material based on graph features, comprising: performing a threshold segmentation on a CT image of the mixed material to obtain a solid particle region; determining the position of each solid particle in the solid particle region; determining multiple Delaunay triangles based on the position of each solid particle; determining graph features based on the side lengths of the multiple Delaunay triangles; determining the uniformity of the mixed material based on the graph features; performing a secondary threshold segmentation on the CT image of the mixed material to obtain a polymer material main region, the polymer material main region including regions where multiple pores are located; and determining the porosity of the mixed material based on the number of pixels in the regions where the multiple pores are located and the number of pixels in the polymer material main region. The method for calculating the uniformity and porosity of a mixed material based on graph features of the present application can automatically and accurately obtain the uniformity and porosity of the mixed material, and has a relatively fast calculation speed.

The invention relates to the technical field of big head sticker generation, and discloses a blind box big head sticker generation method and system based on dynamic grid layout, and the method comprises the steps: carrying out the uniform grid division of an input image based on the dynamic grid layout, and setting a seed point at the center of each grid; by enumerating a triple and executing a hollow circle test, screening units conforming to a Delaunay triangle, further calculating the Euclidean distance between the center of mass of each unit and the center of mass of the image, and normalizing the Euclidean distance into a distortion factor based on a preset maximum distance; constructing an affine distortion matrix and transforming triangular vertex coordinates; according to the method, the structural integrity of the image is ensured, multi-form dynamic distortion and multi-mode resource binding are flexibly supported, and different grid layouts (grids in different shapes), blind box random star IP display and sound resource and timestamp addition can be realized. The grid shape and content distribution are dynamically adjusted through an algorithm, star materials are randomly loaded in combination with a blind box mechanism, and finally the personalized large-head sticker is generated.

The present invention discloses a method for extracting building contours from ground laser point clouds based on an improved Alpha Shapes algorithm, which is characterized by comprising the following steps: (1) firstly performing building facade segmentation based on a RANSAC algorithm to obtain a plurality of relatively independent building facade point clouds; (2) establishing a Delaunay triangulation network according to the point set of each plane; (3) setting the radius R of the detection circle in the Alpha Shapes algorithm to 1 to 2 times the average point spacing; (4) if the length of a certain side in a triangle is greater than 2R, the triangle is deleted; (5) judging each side of the triangle: if a circle with a radius of R passing through two points of a certain side contains other points, the triangle is deleted; (6) finding the edge of the triangulation network on the obtained triangulation network; (7) merging point cloud patches to obtain a complete building contour line. The present invention has the advantages of high efficiency and good stability.

The invention relates to a method for constructing a base station coverage simulation lattice by fusing measurement data. The method comprises the following steps: 1) generating a Delaunay triangular grid by using a stationary point insertion algorithm, and 2) generating a polygonal grid by using a Thiessen polygon algorithm and fusing an MR report of a base station, namely a whole network base station coverage simulation grid. According to the method, the Thiessen polygon algorithm is combined with accurate user report information, so that the accuracy of the coverage range is ensured. Secondly, data are automatically processed through an algorithm, dependence on field measurement is reduced, cost is reduced, and efficiency is improved. And furthermore, a real-time monitoring and updating mechanism is established, so that environment change and base station parameter adjustment can be quickly responded, the coverage range of the base station can be automatically recalculated and updated, and the timeliness of a drawing result is kept, thereby meeting dynamic network planning and optimization requirements. And finally, a user and an operator can conveniently inquire the base station information, carry out parameter adjustment and check the change of the coverage area in real time, so that the user experience and the convenience of network management are improved.

The application discloses a kind of unmanned aerial vehicle maritime communication flight path planning method, device and system, belong to path planning technical field, method includes: grouping to the user scattered on sea surface, and form Delaunay triangle by grouped user;Determine the hovering point of unmanned aerial vehicle in each described Delaunay triangle;According to each described hovering point, the flight path of unmanned aerial vehicle is planned, the order that unmanned aerial vehicle visits each described hovering point is determined, and the shortest path is acquired;Based on the shortest path, the energy consumption of unmanned aerial vehicle in acceleration, deceleration and uniform speed stage is optimized, and the optimal path of unmanned aerial vehicle maritime communication is acquired.The method can acquire the shortest path and optimize the energy consumption of unmanned aerial vehicle in acceleration, deceleration and uniform speed stage, acquire the optimal path of unmanned aerial vehicle maritime communication.

The invention discloses an electric power Beidou partition networking and grid broadcasting method and system, and the method comprises the steps: carrying out the partition networking of a whole network region, forming a plurality of subnetwork partitions, and determining the boundary line of each subnetwork partition; dividing all stations in the whole network area into a Delaunay triangulation network comprising a plurality of triangular units; determining a boundary triangular unit through which the boundary line of each subnet partition passes; determining the area of each subunit obtained by dividing the boundary line in each boundary triangular unit, and enabling the corresponding boundary triangular unit to belong to the subnet partition where the subunit with the largest area is located; and uniformly dividing each sub-network partition to obtain a plurality of grid points, dividing each grid point to the sub-network partition corresponding to the triangular unit where the grid point is located, and generating a grid point virtual observation value for a subsequent grid broadcast service. According to the method, the optimal network element shape of the boundary region can be guaranteed while the power Beidou base station network is networked in a partitioned manner, and the optimal service of all-region grid differential positioning is guaranteed.

An endless belt includes a base material layer, the base material layer containing a polymer material and conductive particles, wherein in a section of the base material layer in a thickness direction, the conductive particles have an area ratio of 9.0% or more and 14.5% or less, an average value of areas of Delaunay triangles taking centers of gravity of the conductive particles as vertices is 0.10 μm2 or more and 0.90 μm2 or less, and a standard deviation of the areas is 0.010 μm2 or more and 0.080 μm2 or less.

The invention discloses a remote-sensing image splicing method based on Delaunay triangular feature constraint, and relates to the technical field of remote-sensing image processing, and the method comprises the following steps: constructing an image pyramid through employing an SIFT algorithm, carrying out Gaussian difference and extreme value detection positioning, extracting remote-sensing image feature points and descriptors, and for each extracted feature point, carrying out the segmentation of the extracted feature points; feature description is carried out by using a texture feature descriptor, and image feature points are screened by using an RANSAC (Random Sample Consensus) algorithm; according to the remote sensing image feature matching method, SIFT feature matching is constrained by using the ratio of the nearest neighbor distance to the next neighbor distance and the Delaunay triangulation network, the method accords with the landform, highly similar and repeated feature points are deleted, and the accuracy of remote sensing image feature matching is improved; on the basis of Delaunay triangulation, shape features and image texture features of triangles are combined, the triangle similarity principle, the cosine theorem and similar features are utilized, the optimal image projection transformation matrix is obtained, and the remote sensing image splicing result is further optimized.

The present invention discloses a method for classifying urban block functions by integrating POI pre-classification and graph neural network. The method comprises the following steps: S1, constructing a Delaunay triangulation network using urban block POI, S2, determining the importance ranking of POIs in the urban block according to the average side length of the Delaunay triangulation network edge connected to each POI point, S3, selecting the top three POI types in the urban block as the combined labels of the urban block functions, S4, merging the combined labels to obtain pseudo labels of urban block functions, S5, establishing a POI graph network of each urban block based on the Delaunay triangulation network, S6, training a graph neural network classification model using the pseudo labels of urban block functions, and S7, classifying urban block functions using the trained graph neural network classification model. The method of the present invention can extract the spatial structure information of POI data, enrich the semantic information of POI data, and thus improve the accuracy of urban block function classification.

The invention discloses an elevation calculation method and system based on Delaunay triangulation networks, and the method comprises the steps: obtaining a plurality of elevation point sets to be calculated, and carrying out the triangulation of the elevation point sets, and obtaining a plurality of Delaunay triangulation networks; the Delaunay triangulation network is projected into a two-dimensional plane to obtain a triangle set, triangles in the triangle set are split to obtain a triangle undirected graph, and the undirected graph comprises a vertex set and an edge set; obtaining a to-be-queried point, and searching a first point location closest to the to-be-queried point in the undirected graph by using a KD tree; and based on the to-be-queried point and the first point location, determining a triangle containing the to-be-queried point, and based on a parameter equation of a plane where the triangle is located, obtaining an elevation value corresponding to the to-be-queried point. According to the method, the elevation value in a large-scale scene can be quickly and accurately calculated.

The present invention discloses an image registration method based on improved ORB feature extraction and grid feature matching, which includes the following steps: input the image to be extracted; use the improved FAST algorithm to extract the feature points of the image to be stitched; establish a BRIEF descriptor and obtain the BRIEF descriptor with direction; according to the set of feature points of the image to be stitched, establish a Delaunay triangle grid with the feature points as vertices; judge the triangle similarity and obtain the similar triangles composed of feature points; use the Hamming distance to pair the vertices of the similar triangles to obtain the best matching feature point pairs; use the SVD method to obtain the affine matrix parameters; the image registration method proposed by the present invention can improve the feature extraction efficiency and extraction accuracy while ensuring the image quality, reduce the false matching and improve the stability. It not only improves the real-time performance of video stitching, but also reduces the waste of memory resources, lowers the equipment cost, greatly improves the work efficiency, and provides a better method for image stitching.

The present invention provides a GNSS imaging method and device for detecting short-wavelength deformation. For each point to be estimated, a weight is first determined based on the spatial structure, and then an estimated vertical velocity is extracted to generate a GNSS image. Determining the weight based on the spatial structure includes first determining known stations connected to the point to be estimated based on the Delaunay triangle, then using Gaussian process regression to obtain preliminary weights, and then re-weighting the connected known stations based on velocity uncertainty to obtain the final weights. Extracting the estimated vertical velocity includes extracting the estimated vertical velocity at the point to be estimated using a generalized weighted median filter based on the final weights of the known stations connected to the point to be estimated. The present invention proposes a Gaussian process regression (GPR-VU) scheme that accounts for velocity uncertainty. This scheme uses a covariance matrix to construct the spatial structure between known and unknown points, generating GNSS images of crustal deformation within the study area, and enabling the detection of short-wavelength deformation in areas with complex geology and intense tectonic activity.

The application relates to the technical field of finite element mesh, and particularly discloses a hexahedral mesh parallel generation method for a fast reactor core assembly based on a block structure method, wherein Delaunay triangle partitioning is performed on the region of the same side of the wire winding, a Laplace equation is solved to generate an isopleth, and an orthogonal mesh is generated according to the isopleth to obtain a triangular surface mesh template of the same side of the wire winding; the fuel rod assembly is divided into six sections, each section is divided into a plurality of layers, the first section is taken as a base section, based on the triangular surface mesh template of the same side of the wire winding, block meshes are divided in each layer, quadrilateral surface meshes are generated in the block meshes, each layer surface mesh of other sections is obtained by rotating each layer surface mesh of the first section by a set angle, and the hexahedral mesh model is formed by connecting the layer surface meshes; the hexahedral mesh model is expanded; and the loop calling function is parallel optimized. The application solves the problems of incorrect generation of the hexahedral mesh of the fast reactor core assembly and low mesh division efficiency.

The application is a Voronoi porous structure topology optimization method for advanced construction, which comprises the following steps: given an initial structure design space R and a structure stress condition, a user specifies the construction parameters of the Voronoi porous structure, including a preset volume fraction f, and sets the porous unit thin wall width t in combination with a manufacturing process; a relationship between the Delaunay triangle side length and the local volume fraction and the equivalent Young's modulus is established; the optimal equivalent Young's modulus is calculated according to the stress condition and the optimization target of the structure; the gradient Delaunay triangle is constructed according to the local volume fraction of the grid element; the vertices of all Delaunay triangles are extracted, the Voronoi polygon is generated and is given a width t, and the construction area is generated. The gradient Voronoi porous structure is generated by adopting the Delaunay triangle reconstruction, the Delaunay triangle side length is taken as a design variable, the Voronoi porous structure is constructed according to the optimal equivalent Young's modulus obtained by the maximum structure stiffness, and the optimization layout of the material is realized.

The invention relates to a Voronoi porous structure topological optimization method for advanced construction, which comprises the following steps of: giving an initial structure design space R and a structure stress condition, assigning construction parameters of a Voronoi porous structure by a user, wherein the construction parameters comprise a preset volume fraction f, and setting the width t of a porous unit thin wall by combining a manufacturing process; establishing a relationship among the side length of the Delaunay triangle, the local volume fraction and the equivalent Young modulus; the optimal equivalent Young modulus is calculated according to the stress condition of the structure and the optimization target; constructing a gradient Delaunay triangle according to the local volume fractions of the grid units; and extracting vertexes of all the Delaunay triangles, generating a Voronoi polygon, endowing the Voronoi polygon with a width t, and generating a construction area. The gradient Voronoi porous structure is generated through Delaunay triangle reconstruction, the side length of the Delaunay triangle serves as a design variable, the Voronoi porous structure is constructed according to the optimal equivalent Young modulus obtained according to the maximum structural rigidity, and optimized layout of materials is achieved.

The application discloses a kind of method and system for multiple robots to avoid obstacles based on thiesen polygon, the method comprises: initialization limited space environment, obtain selected bounded region, selected bounded region is divided using thiesen polygon, distribute pursuit target and pursuit target point, using Delaunay triangle to region segmentation corrosion, obtain safe movement area, based on pursuit target point and safe movement area obtain pursuit obstacle avoidance direction control pointing point.The system includes: initialization module, thiesen polygon module, task allocation module, safe area division module, pursuit direction point module and escape direction point module.Through using the application, a series of problems caused by using reinforcement learning, estimation prediction and other methods can be avoided, and the robot's collision avoidance and pursuit direction selection under the condition of multiple obstacles can be realized with lower algorithm complexity.The application can be widely applied to the field of robot pursuit obstacle avoidance technology.

The invention relates to a channel plane boundary separation method based on a Delaunay triangle, and belongs to the field of channel surveying and mapping and channel maintenance. The method comprises the following steps: dynamically correcting a water depth point in a channel topographic mapping to obtain an actual water depth; a water depth point with the actual water depth equal to the channel maintenance water depth serves as a boundary point, and a boundary point set is formed; adding the boundary point set to the original water depth data set, reconstructing a Delaunay triangulation network, screening out all triangles of which the actual water depth is greater than or equal to the channel maintenance water depth, and obtaining a triangular region set; counting the occurrence frequency of each edge of the triangles in the triangular region set, and adding the triangular edges representing region boundaries into a boundary set; and searching edges capable of forming a closed area in the boundary set, combining the edges into a plurality of independent closed polygons, namely channel plane boundaries, and removing holes contained in the largest closed polygon to separate to obtain a channel navigable water depth area range.

The invention discloses a CORS network reference station layout evaluation method, a master station determination method, electronic equipment and a storage medium. The method comprises the following steps: establishing a CORS network diagram based on a Delaunay triangle according to coordinates of each reference station; performing external expansion on the boundary of the CORS network diagram according to a set external expansion distance to obtain a CORS network external expansion diagram, and determining a corresponding CORS network service range; determining a Thiessen polygon corresponding to each base station according to the CORS network external expansion graph; in the service range of the CORS network, map grids included in the Thiessen polygons are determined respectively, and the service range of the corresponding reference station is obtained through calculation so as to be used for reference station layout evaluation of the CORS network. By adopting the method disclosed by the embodiment of the invention, the layout condition of the reference station of the CORS network can be effectively and accurately evaluated so as to guide layout optimization and further improve the service quality of the RTK network.

The invention provides a skeleton path generation method and system based on triangulation network bidirectional search, and relates to the technical field of additive manufacturing, and the method comprises the steps: carrying out the grouping and pairing of a plurality of inner contours and outer contours obtained through the slicing of a three-dimensional model; constructing a constraint Delaunay triangulation network for each group of contours, dividing a connected domain into a plurality of grid triangles, and defining a brother relationship between midpoints of two internal edges in a triangle at least comprising two internal edges; in each constructed triangulation network, any pair of points with a brother relationship is taken as a search starting point, and a skeleton path is adaptively generated according to contour characteristics by adopting a path point bidirectional search algorithm. According to the method, skeleton path generation is carried out on each connected domain through the path point bidirectional search algorithm based on the Delaunay triangulation network, the problems that in the prior art, skeleton extraction efficiency is low, and use conditions are limited are solved, and the additive manufacturability of complex and long and narrow features and thin-wall features is improved through the generated single skeleton path.