1912 results about "Mesh model" patented technology

The invention provides a news scene three-dimensional reconstruction and visualization method based on multi-source remote sensing data, and relates to the technical field of three-dimensional reconstruction, and the method comprises the steps: extracting multi-modal data feature points through employing a spatial position weighted iterative nearest point algorithm and a tensor projection algorithm; after bidirectional attention deep neural network processing and local geometric consistency constraint screening, registration multi-source remote sensing data is generated, data enhancement is carried out through a variational auto-encoder network and a generative adversarial network, the enhanced data is used for depth information generation and texture feature migration, an initial three-dimensional grid model is generated based on a Poisson reconstruction algorithm, and the initial three-dimensional grid model is constructed; and carrying out topological optimization by combining multi-view projection consistency constraint and a grid optimization algorithm to obtain an optimized three-dimensional scene model, setting a space division function, carrying out space division, constructing a grade model and a depth region, generating a scene semantic segmentation map, and updating a visual scene.

The invention relates to the technical field of crustal stress field data processing, in particular to a crustal stress field three-dimensional dynamic inversion method based on a multi-scale adaptive algorithm. The method comprises the following steps: acquiring a geological data set of a target area; constructing a crustal stress field three-dimensional initial model based on the geological data set, and performing geologic body space division and mesh generation to obtain crustal stress field three-dimensional mesh model data; performing multi-scale region division on the crustal stress field three-dimensional grid model data, and establishing a multi-scale weighting function to obtain multi-scale partition mapping information; and constructing a cross-scale boundary adaptive transmission mechanism, and establishing a stress tensor continuity constraint model at a multi-scale partition boundary to obtain cross-scale stress boundary coupling data. Through a multi-scale adaptive algorithm and dynamic closed-loop optimization, high-precision, dynamic and continuous inversion of a crustal stress field in a complex geologic structure is realized.

The invention relates to the technical field of three-dimensional reconstruction, in particular to a multi-mode remote sensing data driven refined city three-dimensional reconstruction method and system, and the method comprises the steps: obtaining an original satellite optical image for providing city surface information; synthetic aperture radar (SAR) data is obtained and used for assisting reconstruction of a point cloud data missing region; the method comprises the following steps: acquiring laser radar data carried by a flight aerial carrier for acquiring high-precision three-dimensional point cloud; performing data preprocessing; carrying out fusion on the preprocessed multi-modal data; on the basis of the fused features, complementing space detail information; on the basis of the refined features, progressive reconstruction is carried out, vertexes and edges are gradually added from the initial vertexes, and a grid model is constructed; in the reconstruction process, performing semantic segmentation on the grid model by using a multi-category segmentation network, and judging the category of each triangular patch; time sequence reconstruction is completed through fusion of multi-temporal data, and a dynamic city change model is generated; and complementation of advantages of different modal data is realized.

The invention provides a posture recognition algorithm for any object under a monocular camera and an application system, and the algorithm comprises the steps: S1, constructing a target three-dimensional model, carrying out the multi-view annular shooting image collection of a target, and generating a dense grid model through feature extraction, matching, posture calculation and a multi-view geometric method; s2, generating an image depth map, and predicting depth information of a target in a motion process based on a monocular image sequence; s3, extracting a target image mask, and generating a target area mask graph through an image encoder, a prompt encoder and a mask decoder; and S4, executing attitude estimation, performing attitude initialization, correction and screening by combining the three-dimensional model, the depth map and the mask map, and outputting a six-degree-of-freedom attitude result of the target. According to the method, the target is subjected to annular shooting modeling through the method based on multi-view geometry, the three-dimensional model of the target is generated, attitude estimation is achieved in combination with the image mask and the depth map, the generalization ability of an attitude estimation algorithm in an actual scene is improved, and the application range of the attitude estimation algorithm in the actual scene is widened.

The invention relates to the technical field of quality monitoring, and discloses a diamond high-strength micro-powder quality detection method and system based on artificial intelligence. The method comprises the steps of obtaining a two-dimensional projection image sequence of diamond micro-powder particles, calculating a projection matrix based on camera calibration parameters and geometric constraints, obtaining a multi-view image data set of the particles, establishing a pixel-level corresponding relation, extracting three-dimensional space coordinates of the surfaces of the particles, and reconstructing dense point cloud data of the particles. Establishing a local coordinate system based on the dense point cloud data, determining attitude parameters of particles in a three-dimensional space, if the attitude parameters deviate from a normal range, performing attitude compensation processing to obtain standardized point cloud data, and performing three-dimensional grid model construction on the standardized point cloud data; and calculating geometrical characteristic parameters of the particles based on the three-dimensional grid model, performing defect detection on the surfaces of the particles, and generating a crystal integrity evaluation report of the particles. The quality detection accuracy of the diamond high-strength micro-powder particles is improved.

The invention provides a three-dimensional modeling processing method based on unmanned aerial vehicle oblique photography. The method is applied to the technical field of three-dimensional modeling, and comprises the following steps: obtaining a serialized image set containing geographical coordinate information according to original image data collected by an oblique photography camera carried by a multi-rotor unmanned aerial vehicle; according to time-space synchronization parameters of the serialized image set, determining a multi-view image matching relation matrix with an overlapping degree quantitative index; determining mixed three-dimensional point cloud data fusing sparse point cloud and dense point cloud according to geometric constraint conditions of the multi-view image matching relation matrix; determining an initial three-dimensional grid model with multi-level details according to the topological connection relationship of the mixed three-dimensional point cloud data; and determining an optimized three-dimensional model based on adaptive texture mapping according to the surface curvature distribution characteristics of the initial three-dimensional mesh model. In this way, the efficiency of three-dimensional modeling can be improved.

The invention discloses a three-dimensional automatic modeling method for a high-precision transformer substation. The method comprises the following steps: collecting laser point cloud data and multi-view pictures of the transformer substation; dense point cloud data registration, multi-view image camera parameter reconstruction, multi-view image projection and adaptive point cloud density control are carried out; approximating the point cloud data by using three-dimensional Gaussian distribution functions, summing all the three-dimensional Gaussian distribution functions to obtain a Gaussian distribution geometric field represented by the three-dimensional Gaussian distribution point cloud, and reconstructing and rendering a three-dimensional grid to obtain a three-dimensional grid model; setting constraint conditions of equipment on the basis of the three-dimensional grid model, and generating a three-dimensional equipment model, equipment coordinates and equipment classification names by using a volume segmentation algorithm and a three-dimensional marking algorithm; and converting the equipment model into a GIM model file, generating a PMS file from the equipment coordinate and the equipment classification name, and synchronizing the PMS file to a GIM and PMS 3.0 system. According to the method, the problems of low efficiency and inconsistent quality in the traditional manual modeling process can be effectively solved.

The invention provides a CAD model reconstruction method and device for a topological optimization result, and relates to the technical field of computer modeling, and the method comprises the steps: carrying out grid preprocessing, carrying out component type grid segmentation, carrying out patch type grid segmentation, obtaining at least two sub-grid patches, carrying out parameterization on each sub-grid patch, and obtaining a final parameterization result. And performing uniform interpolation sampling based on the final parameterization result to obtain sampling points, generating a spline surface by using the sampling points, assembling the spline surface, and generating a reconstructed CAD model corresponding to the three-dimensional topological optimization fruit. The grid model reconstruction method has the advantages of being high in automation degree, high in realizability, easy to operate and the like, is not limited to a tubular topological optimization structure, has no obvious difference in effect when processing tubular and non-tubular model characteristics, has higher universality, can adapt to the diversity requirements of industrial structure optimization, and is suitable for large-scale popularization and application. And meanwhile, the reconstruction efficiency and the reconstruction effect from the triangular mesh model to the CAD model can be improved.

The invention provides a method and a system for drawing a regional energy consumption map of an electric vehicle. Wherein the acquired driving data and external meteorological information comprise multiple parameters and temperature gradients in the GB32960 standard. A dynamic grid model is constructed based on administrative division and a road network, track points are mapped into space grid units by using an adaptive algorithm, and the units combine information such as gradient, temperature and traffic flow. A trajectory analysis technology is adopted to segment a driving segment crossing a grid boundary, and feature vectors are generated; by establishing a mapping relationship between the feature vector and the energy consumption contribution degree, the original energy consumption is calculated, and multi-factor correction is performed to generate a dynamic energy consumption reference value. And associating the distribution density of the charging piles with the traffic flow weight by using a space-time coupling diffusion model, and generating a three-dimensional dynamic map through a rendering engine. According to the technical scheme provided by the embodiment of the invention, the accuracy of electric vehicle energy consumption estimation and the scientificity of charging facility layout are improved.

The invention relates to the technical field of image processing, and discloses a machine vision-based rare metal processing quality detection method, which comprises the following steps of: acquiring a multispectral polarization image and a surface normal graph of a to-be-detected workpiece; reconstructing a three-dimensional mesh model on the surface of the workpiece, and mapping pixel information of the multispectral polarization image into multidimensional physical attributes of vertexes on the three-dimensional mesh model; extracting depth features of the surface of the machined part by adopting a graph convolutional neural network; the depth features are input into a segmentation decoder and a normalized stream model in parallel, and a defect probability graph and a likelihood graph are generated; performing joint judgment on the defect probability graph and the likelihood graph; and extracting geometric information and multi-dimensional physical attributes corresponding to the judged defect area, and inputting the geometric information and the multi-dimensional physical attributes into a defect classifier to determine the type of the defect. According to the method, known defect types can be accurately identified, novel defects which are not learned can be effectively detected, and the generalization ability and robustness of detection are greatly enhanced.

The invention relates to the technical field of geological exploration and three-dimensional modeling, in particular to a mining unmanned aerial vehicle high-precision three-dimensional geological modeling system which comprises a multispectral imaging acquisition module, a point cloud-image high-precision registration module, a geological feature fusion extraction module, a three-dimensional geological model construction module and a geological attribute visualization output module. Wherein the multispectral imaging acquisition module is used for acquiring registration image data and original point cloud data; the point cloud-image high-precision registration module is used for carrying out consistency matching and outputting a registration point cloud-image data set; the geological feature fusion extraction module is used for identifying geological boundaries and outputting geological feature vector data; and the three-dimensional geologic model construction module is used for generating a three-dimensional grid model with attribute topology. According to the method, through accurate three-dimensional modeling and lithology visualization, geological features and lithology information are efficiently combined, and reliable data support is provided for rock mass stability analysis.

The invention discloses an automatic three-dimensional reconstruction method and system based on power transmission corridor point cloud. The method comprises the following steps: acquiring data and exporting point cloud data; noise points, outliers and ground points are removed from the acquired point cloud data of the power transmission corridor, and down-sampling is performed on the point cloud with a large data volume; performing clustering segmentation on the preprocessed point cloud of the power transmission corridor, positioning the position of a tower, determining a point cloud range of a power line, and removing point clouds of other objects on the ground; aiming at the structural characteristics of a power line and an insulator in the power transmission line, extracting point clouds of the power line, the insulator and a tower by adopting a geometric constraint principal component analysis (PCA) algorithm; performing automatic geometric model reconstruction on the tower, insulator and power line point clouds according to different reconstruction rules to generate each module grid model; and transforming the grid model of each module, restoring the grid model to the original position of the point cloud, and generating a power transmission line digital twin model conforming to the real size. According to the method, automatic segmentation, classification and real-time reconstruction can be accurately carried out on the point cloud of the power transmission corridor.

The invention provides a chip bonding wire three-dimensional measurement method and system based on an inner cavity reflection camera system, and relates to the technical field of three-dimensional measurement. The method comprises the following steps: performing one-time exposure imaging on a chip bonding wire to be detected through an inner cavity reflection camera system to obtain at least three mutually independent visual angle images in the same frame; performing brightness normalization compensation and geometric calibration on the visual angle image to obtain a visual angle data set with uniform brightness and correlation; pairing the view angle data sets in pairs, extracting parallax information by using a feature matching algorithm based on optical flow, and fusing multiple pairs of parallax to generate a lead three-dimensional point cloud; performing noise filtering and curved surface reconstruction on the three-dimensional point cloud to obtain a continuous three-dimensional grid model of a lead; and performing texture mapping on the three-dimensional grid model by adopting any visual angle in the visual angle image or the combination of the visual angles, and outputting a lead three-dimensional reconstruction result with textures. According to the invention, high-precision, large-depth-of-field and rapid three-dimensional measurement of the chip bonding wire is realized.

The invention discloses a computer numerical simulation method, system and equipment for a composite material, particularly relates to the technical field of analog simulation, and is used for solving the problem of simulation distortion caused by neglecting the randomness of a microstructure in the prior art. The method comprises the following steps: acquiring microstructure image data of a composite material, extracting fiber arrangement direction and pore distribution parameters, and generating a fiber direction probability density function and a pore topological relation; constructing a non-uniform grid model constrained by a local coordinate system according to the fiber direction probability density function; identifying a weak connection area based on a pore topological relation and marking nodes; applying dynamic decoupling constraint to the weak connection area, wherein the dynamic decoupling constraint comprises initial rigidity and rigidity attenuation rate; applying an external load to the model and calculating a real-time stress coefficient of the weak connection area; dynamically adjusting the constraint parameter through threshold judgment and iterative correction until the stress coefficient is converged; and finally, outputting a corrected macroscopic mechanical property result.

The invention discloses an intelligent water conservancy three-dimensional twinborn scene construction method and system, and relates to the technical field of intelligent water conservancy, and the method comprises the steps: collecting scene data in real time through a multi-source sensor disposed at a water conservancy facility site, including hydrological parameters, facility structure data, environment image data and ecological monitoring data; performing space-time alignment and deviation correction on the scene data by using a deep learning driven multi-modal feature fusion algorithm to generate a three-dimensional water conservancy grid model of a unified coordinate system; according to the real-time data updating frequency and the environment change trend, a local or global updating strategy of the three-dimensional water conservancy grid model is adaptively adjusted, the optimized three-dimensional water conservancy grid model and a virtual reality engine are integrated, and a twin scene supporting gesture interaction is constructed; an ecological simulation module is embedded in the twinborn scene to dynamically evaluate the influence of water conservancy activities on water quality and biological habitats.

The invention provides a three-dimensional data synthesis method, electronic equipment, a storage medium and a program product, and the method comprises the steps: obtaining a plurality of texture-free three-dimensional grid models, carrying out the rendering of each three-dimensional grid model, obtaining a plurality of view images, and constructing a training sample pair in combination with a semantic description text; based on the training sample pair, utilizing a low-rank adaptation technology to carry out fine tuning on the first text graph model to obtain a second text graph model with multi-view consistency understanding ability; modeling a latent space semantic difference between the rendered image of the to-be-deformed three-dimensional grid model and the target semantic text based on the second text graph model, constructing an optimization constraint and updating parameters, and obtaining a deformed three-dimensional grid model conforming to target semantics; and generating a texture image by using the texture generation model, and attaching the texture image to the surface of the deformed three-dimensional grid model to obtain synthetic three-dimensional data with textures. The reconstruction precision, the diversity expression ability and the cross-category generalization ability of the synthesized three-dimensional data are obviously enhanced.

The invention provides an urban groundwater inrush risk assessment method based on a three-dimensional grid model and an XGBoost algorithm, and belongs to the technical field of geological disaster early warning. The method comprises the following steps: acquiring geological, environmental and historical disaster data in real time through a multi-source heterogeneous data interface; constructing a heterogeneous grid unit based on three-dimensional geological modeling, and dynamically binding parameters such as underground water level, fault activity and lithologic permeability coefficient; an XGBoost algorithm is combined with second-order Taylor expansion to optimize gradient calculation, and a nonlinear risk assessment model is constructed through Bayesian hyper-parameter tuning and SHAP value feature interpretive analysis; identifying contiguous dangerous areas based on spatial autocorrelation analysis and an adaptive threshold segmentation algorithm; and a risk thermodynamic diagram, geological section superposition and real-time early warning are realized through a 3D GIS platform. According to the method, the problems that a traditional method depends on a linear model, data is single and local risk description is insufficient are solved, and the accuracy, efficiency and engineering practicability of risk assessment are remarkably improved.

The invention discloses an automatic planning method and system for a curved surface path of a grinding robot, and the method comprises the following steps: S1, constructing a to-be-machined three-dimensional curved surface model and a triangular mesh model, and relates to the technical field of automatic control of robots for surface machining in the manufacturing industry. According to the method, a complex three-dimensional surface coverage path planning problem of a workpiece is converted into two low-complexity sub-problems of key point sampling of a two-dimensional path planning domain and three-dimensional shortest path searching on a triangular mesh model, a small number of sampling points are sampled only on the two-dimensional path planning domain, and the sampling process depends on a spatial index framework; according to the method, global traversal of disordered point clouds is avoided, three-dimensional coordinates are positioned through nearest neighbor search of a KD tree algorithm, adjacent three-dimensional ordered key points are sequentially connected through a graph search algorithm, and a continuous machining path is formed, so that the operand is greatly reduced, real-time response of path planning is facilitated, and the problems that traditional online planning is long in time consumption and difficult in real-time response are solved.

The invention provides a high-quality 3D Mesh reconstruction method based on brain EEG (electroencephalogram) signals. The electroencephalogram signals can be quickly and efficiently converted into a high-fidelity three-dimensional mesh model. Firstly, an EEG encoder extracts time domain and frequency domain features from an EEG signal to enhance the representation capability of the signal. The time-frequency embedding is then input to a two-stage image generation module guided by the EEG, generating a high-quality two-dimensional image. And finally, through a multi-view diffusion model and a sparse view reconstruction technology, the generated two-dimensional image is used as input, and reconstruction of the three-dimensional grid is rapidly completed. According to the scheme, the technical problem of converting the EEG signal into the three-dimensional object is effectively solved, an important breakthrough is made in the fields of electroencephalogram signal processing and three-dimensional reconstruction, and a new view angle and a new tool can be provided for research in the fields of acknowledging science, psychology and neuroscience.

The invention provides a three-dimensional visual model construction method and system for a mine slope, and relates to the technical field of data processing, and the method comprises the steps: obtaining the inclined image data of the mine slope; performing error correction on the inclined image data; performing live-action modeling according to the inclined image data after error correction to obtain a three-dimensional grid model and a point cloud data file; generating a digital terrain model according to the point cloud data file; extracting a contour line of the digital terrain model, and exporting a contour line file; generating a three-dimensional terrain curved surface by using a terrain data generator according to the contour line file; the three-dimensional terrain curved surface extends downwards by a preset depth, and a three-dimensional entity slope model is generated; physical parameters of side slope rock soil are set, and a Moire-Coulomb intensity criterion is given to the three-dimensional entity side slope model so as to simulate shear failure characteristics of the rock soil; on the basis of shear failure characteristics of rock and soil, grid division is carried out on the three-dimensional solid slope model; and generating a three-dimensional visual model of the mine slope.

The invention relates to the technical field of machine tool intelligent monitoring, and discloses a numerical control machine tool intelligent monitoring and optimizing system based on digital twinning, which comprises a data acquisition module used for carrying out discrete time working condition data acquisition and dynamic precision weight distribution on a numerical control machine tool to obtain a dynamic precision distribution matrix; the calculation module is used for calculating a geometric simulation precision grade and a physical simulation precision grade; the construction module is used for constructing a self-adaptive geometric grid model; the self-adaptive refinement module is used for carrying out self-adaptive refinement on a contact area for cutting force monitoring to obtain a cutter workpiece contact physical simulation model; the cooperative adjustment module is used for inputting the self-adaptive geometric grid model and the tool workpiece contact physical simulation model into a working condition conversion state machine for cooperative adjustment, and a self-adaptive precision simulation result is obtained. And the reliability and robustness of the system are improved.

The invention discloses a method for evaluating the bearing time of an internal fault of large oil-filled main equipment, and belongs to the technical field of relay protection of oil-filled main equipment of a power system. Obtaining a plurality of fault currents in the internal fault current range of the oil-filled main equipment; establishing a three-dimensional geometric simulation model and a grid model of the oil charge main equipment; calling a transient pressure-based solver, simulating a turbulence phenomenon and an oil pressure rise phenomenon of the oil-filled main equipment under a fault current condition, judging whether the oil-filled main equipment is broken or not, and obtaining allowable fault bearing time of the oil-filled main equipment under different fault currents; and establishing a neural network model for mapping the fault current and the allowable fault withstanding time through a convolutional layer, a pooling layer and a full connection layer in the convolutional neural network, so as to evaluate the allowable fault withstanding time of the oil-filled main equipment. And the fracture and failure phenomena of the oil-filled main equipment in a high-stress state are accurately captured, so that a quantitative method which is more accurate than a traditional empirical method is provided for evaluating the fault bearing time of the oil-filled main equipment.

The invention discloses a cultural relic digital fingerprint identification method based on geometric texture and spectral information, and the method comprises the steps: obtaining multi-source data, carrying out the texture mapping, and forming a three-dimensional grid model with texture data; curvature values and topological features of all vertexes of the three-dimensional grid model are calculated, feature fusion is carried out on the basis of local saliency adjustment feature weights, and fingerprint point location screening is completed; based on the screened fingerprint point locations, a significant plane is constructed through a bit plane, and texture features of the cultural relics are extracted based on an improved histogram and a gray-level co-occurrence matrix; extracting characteristic wave bands of the cultural relics based on the screened fingerprint point locations in combination with the hyperspectral data; and multi-modal fusion identification is carried out based on features of geometry, texture and spectral information. According to the method, the geometric structure, the texture features and the hyperspectral information are fused, multi-mode collaborative cultural relic identity high-precision identification is achieved, and the method has the advantages of being high in accuracy, high in robustness, good in interpretability and capable of adapting to complex environments.

The invention relates to an unmanned aerial vehicle flight path planning method in a complex city low-altitude environment. The method comprises the following steps: S1, acquiring geographic information data of a target city area; s2, constructing a three-dimensional grid model of a target city region according to the geographic information data; s3, extracting obstacle boundary and no-fly zone information from the three-dimensional grid model, initializing the flight path of the unmanned aerial vehicle by adopting an A * algorithm, and obtaining a preliminary flight path planning result; s4, performing global optimization on the preliminary route planning result to obtain an optimized route planning result; and S5, if the optimized flight path planning result satisfies a preset condition, outputting the optimized flight path planning result, and if the optimized flight path planning result satisfies the preset condition, returning to S4 until the preset condition is satisfied. According to the invention, safe and efficient flight of the unmanned aerial vehicle in a complex dynamic urban low-altitude environment is realized.

The invention discloses a grid model and entity model fusion method, computer equipment and a storage medium. The method comprises the steps of data preprocessing, data conversion and data fusion. Performing data cleaning, topological repair and geometric optimization on the grid model to obtain first model data, and performing closure repair, connectivity repair and redundant element cleaning on the entity model to obtain second model data; converting the first model data and the second model data into a grid-entity hybrid model Sa and a grid-entity hybrid model Sb; and performing data fusion on the grid-entity hybrid model Sa and the grid-entity hybrid model Sb through bounding box detection, model intersection, connection of intersection edges into rings, combination of the rings into surfaces and enclosing of the surfaces into a body, and rendering the fused data to obtain the grid-entity hybrid model. The method has the advantages that the grid and the entity heterogeneous model are effectively fused, and the grid structure and the entity structure can be displayed at the same time after rendering.

A system for estimating a three dimensional pose of one or more persons in a scene is disclosed herein. The system includes one or more cameras and a data processor configured to execute computer executable instructions. The computer executable instructions include: (i) receiving the one or more images of the scene from the one or more cameras; (ii) extracting features from the one or more images of the scene for providing inputs to a three dimensional pose estimation neural network; (iii) generating, by using the three dimensional pose estimation neural network, vertices of a canonical human mesh model for the one or more images of the scene; (iv) retrieving a weight matrix from an annotation server that corresponds to a desired keypoint set; and (v) generating the desired keypoint set by multiplying the retrieved weight matrix with the vertices of the canonical human mesh model.

The invention relates to a three-dimensional Mesh model hole repairing system and method considering curvature characteristics of a scene structure, and belongs to the technical field of three-dimensional modeling and graphic processing. Comprising the following steps: S1, identifying boundary holes in a three-dimensional Mesh model, and classifying the boundary holes according to form and location features; s2, constructing a hierarchical structure of the boundary holes based on a topological relation of the block grids; s3, repairing boundary holes layer by layer based on the hierarchical structure, wherein the boundary holes are converted into closed holes, and curved surfaces are fitted; and S4, smoothing the triangulation network of the repairing area and the adjacent boundary of the original model, so that the triangulation network is naturally transited. According to the method, each block grid serves as a basic repairing unit of the boundary holes, the hierarchical relation of the boundary holes is established, and the holes are repaired layer by layer from outside to inside, so that the hole repairing efficiency is improved, the applicability of the method is enhanced, and the repairing precision is ensured.

The invention is suitable for the field of image processing, and discloses a multi-source point cloud data fusion method, terminal equipment and a storage medium. The multi-source point cloud data fusion method comprises the following steps: acquiring target data synchronously acquired by a plurality of three-dimensional scanning devices, wherein the target data comprises a plurality of point cloud data and a plurality of texture images; performing multi-source point cloud fusion on the plurality of point cloud data to obtain a three-dimensional grid model, and associating the three-dimensional grid model with the plurality of texture images; and performing texture mapping on the three-dimensional grid model according to the plurality of texture images to obtain a three-dimensional texture map. According to the method, the flexibility and fusion precision of dynamic scanning are improved, and the defect that a traditional fixed array is difficult to adapt to layout changes is overcome.

The invention relates to a footwear style design method based on a digital three-dimensional model. The method comprises the following steps: acquiring three-dimensional point cloud data of the protective shoes, and extracting distribution characteristics to construct a three-dimensional grid model after noise reduction processing; dividing the model into a sole area, a vamp area and an anti-smashing head area, and obtaining a closed boundary point sequence of each area; extracting a sole thickness distribution value, an anti-smashing head curvature value and a vamp wrinkle value based on the boundary point sequence, and generating a feature vector data set; constructing a finite element mechanical simulation model by using the feature vector data set, and generating a protection performance quantitative relation data set; and a multi-objective optimization model is established in combination with the quantitative relation data set, and an optimal structure parameter combination meeting preset safety standard constraint conditions is generated. By means of the method, the efficiency and precision of protective shoe design can be improved, a data-driven standardized process is provided for protective shoe structure design, it is effectively guaranteed that products meet the safety standard, and the comprehensive performance is optimized.

The invention relates to the technical field of ball valve design and simulation, in particular to a three-dimensional simulation design method and system for a ball valve. The method comprises the following steps: performing reference geometric construction based on a ball valve design specification, and performing geometric parameterization to obtain an initial geometric configuration; importing the initial geometric configuration into a finite element analysis platform, and endowing material attributes to obtain a finite element mesh model; performing ball valve working stress analysis on the finite element mesh model to obtain a stress-strain field; performing model fluid domain grid division according to the initial geometric configuration and the stress-strain field to obtain a fluid domain grid; valve opening change setting is conducted on the fluid domain grids, and a CFD calculation model is obtained; internal flow field transient simulation of the ball valve under different opening degrees is conducted on the CFD calculation model, and fluid dynamic parameters are obtained. The dynamic characteristics of the valve under the complex working conditions are accurately captured, and the working performance of the valve under different working conditions is improved.