1484 results about "Mesh model" patented technology

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 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 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 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 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 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 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.

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 relates to the technical field of computer-aided manufacturing, and provides a staged processing real-time cutting simulation method and system.The method comprises the steps that S1, initialization modeling is conducted, specifically, a blank voxel grid model, a tool body voxel grid and a triangular grid are built; s2, performing a first simulation stage of low-precision real-time cutting dominated by voxel grids, judging a space overlapping relationship between the tool body voxel grids and the blank voxel grids in real time so as to determine a voxel region to be removed, and deleting blank voxels in the overlapping region through Boolean operation; s3, in the execution process of the first simulation stage, monitoring a preset multi-dimensional switching trigger condition in real time, and when any condition or a combination of multiple conditions is met, entering a second simulation stage; and S4, a second simulation stage of high-precision real-time cutting with the triangular network as the dominant is carried out, the voxel grid intermediate workpiece is converted into a transition triangular grid, and high-precision cutting calculation is carried out based on the triangular grid. And the efficiency-precision contradiction is broken through through a staged strategy.

The invention discloses a high-temperature environment multimodal transport method and system based on composite heat insulation and active temperature control. The method comprises the steps that a multimodal transport capacity grid model simulating high-temperature transport cooperation is constructed; determining model condition hypothesis, and defining decision variables, parameters and state variables of the model; high-temperature special items and safety penalty are included in the total cost, a high-temperature associated total cost model is constructed, and a multi-scene cost calculation formula is deduced; with the purpose of minimizing the total cost, a mixed integer programming model including path connection and flow conservation, temperature constraint, refrigeration / heat dissipation energy and power constraint, node refrigeration / sunshade capacity constraint, battery and key component temperature safety constraint, butt joint / node capacity constraint and time window constraint is constructed; solving the model by adopting an improved hybrid immunity-particle swarm dual-optimization algorithm, and outputting an optimal transportation path, transportation mode, transfer node and high-temperature scene exclusive scheduling parameter; and collaborative optimization of high-temperature transportation safety, energy efficiency and economy can be realized.

The invention relates to the technical field of cold chain warehouse logistics, and discloses a cold chain warehouse logistics intelligent distribution management system based on the Internet of Things technology. The system comprises a multi-source data processing module which collects storage environment and equipment operation data through a heterogeneous sensor, and preprocesses the data to generate a normalized matrix containing parameters such as temperature and humidity; the dynamic topology updating module is used for constructing an equipment association topology library, updating a relationship according to real-time data and generating a dynamic topological graph; the goods fresh-keeping reference configuration module inputs goods characteristics and equipment operation duration based on a topological graph mapping neural network model, and outputs a goods deterioration risk coefficient; an abnormal early warning decision module generates an early warning rule according to the data, and triggers delay verification in combination with real-time data; the scheduling decision optimization module generates an optimal scheduling scheme through a decision tree in combination with early warning and a resource state; the three-dimensional reservoir area mapping module constructs a three-dimensional grid model and maps environmental parameters; and the path optimization module optimizes the optimal path of the logistics equipment by using a genetic algorithm.

The invention relates to an urban live-action three-dimensional construction method based on a high-resolution satellite image. The method comprises the following steps: carrying out stereo image pair screening and stereo image pair preprocessing on a high-resolution multi-view satellite image; carrying out adjustment optimization based on a rational function model on the satellite stereo image pair; generating an epipolar ray image based on the optimized rational function model; performing dense matching on the epipolar line image by combining building edge straight line segment constraint and an MGM algorithm to generate a disparity map; generating a three-dimensional point cloud and a three-dimensional model formed by a plurality of stereo image pairs through forward intersection based on the disparity map and the optimization parameters; generating a digital elevation model, a digital surface model and a three-dimensional Mesh model based on the three-dimensional point cloud; and carrying out precision evaluation and integrity evaluation by adopting pixel proportions of plane precision, elevation precision and height difference. According to the method, the urban live-action three-dimensional model and the corresponding digital product can be constructed quickly, efficiently and accurately by using the high-resolution satellite image.

The invention provides a substation equipment multi-view point cloud data fusion three-dimensional modeling method and system. The method comprises the steps of obtaining original point cloud data under multiple views and synchronously updating an equipment surface feature topological relation; setting a registration reference surface matched with the geometric structure of the equipment according to the spatial distribution characteristics of the point cloud; carrying out rigid alignment by adopting a point cloud registration algorithm based on a feature weight; and calling a curvature constraint-based three-dimensional reconstruction algorithm through the registration error parameters to generate a high-precision grid model. Wherein the registration reference plane setting needs to judge the point cloud coverage integrity and the overlapping area condition, and when the condition is not met, the collection view angle is adjusted or the point cloud data is complemented; the registration condition is judged through a curvature consistency index; the three-dimensional reconstruction process comprises voxel down-sampling, curved surface function construction and grid optimization, and the final model needs to be subjected to electrical safety verification. According to the method, high-precision three-dimensional modeling of the substation equipment can be realized, and the geometric feature reduction degree and the electrical safety verification reliability are improved.

Disclosed in the present application are a dual-sided laser synchronous welding heat source model establishment method, a dual-sided laser synchronous welding heat source simulation method, a dual-sided laser synchronous welding system, and a medium. Firstly, combined heat sources each comprising a Gaussian cylindrical heat source attenuation model and a Gaussian surface heat source correction model are established, and a dual-sided laser synchronous welding heat source model is established by means of a rotating coordinate system; a three-dimensional geometric model and a three-dimensional mesh model of a T-joint are established; and the consistency between simulated molten metal morphology and an actual weld shape is used as a criterion for determining whether parameter settings of the dual-sided laser synchronous welding heat source model are rational, so as to obtain an optimal finite element simulation heat source model. By establishing two heat sources each obtained by combining a Gaussian cylindrical heat source attenuation model and a Gaussian surface heat source correction model, and symmetrically applying the two heat sources to two sides of a T-joint to act on the interior and surface of a weld, the present invention realizes the accurate simulation of a weld penetration zone in a T-shaped thin-plate weldment, and thus enables the prediction of residual stress and welding deformation during a design phase, thereby optimizing the welding process, improving the welding quality and efficiency, and reducing material waste and production costs.

The invention relates to the technical field of industrial internet of things operation and maintenance, and particularly provides a remote maintenance auxiliary method integrating video monitoring and three-dimensional modeling. The method comprises the following steps: acquiring engineering graphic data and point cloud scanning data of maintenance equipment, and collecting video stream data of a maintenance equipment site; the video stream data is used for describing the operation state of maintenance equipment; the video stream data comprises a plurality of video frames; matching the point cloud scanning data with the engineering graphic data, and constructing a watertight three-dimensional grid model according to a matching result; mapping texture features of the maintenance equipment in a target video frame to the surface of the watertight three-dimensional grid model to obtain a target three-dimensional model; and receiving a first maintenance instruction marked in the target three-dimensional model by a remote expert, and sending the first maintenance instruction to a video picture of a client of an on-site maintainer. According to the technical scheme provided by the invention, the time consumption for positioning the overhaul part can be reduced.

The embodiment of the invention discloses a three-dimensional landform model reconstruction method and device based on geometry and texture combination. A specific embodiment of the method comprises the following steps: carrying out self-adaptive grid division on a landform three-dimensional point cloud and then carrying out geometric super-resolution to obtain a target three-dimensional landform sub-grid; performing color texture mapping and texture correction enhancement on the target three-dimensional landform sub-grids to obtain an enhanced landform texture map; performing collaborative bidirectional optimization on the enhanced landform texture map and the target three-dimensional landform sub-grids to obtain a super-resolution landform texture map and a super-resolution three-dimensional landform sub-grid; performing model recombination and fusion on the plurality of super-resolution landform texture maps and the plurality of super-resolution three-dimensional landform sub-grids to obtain a three-dimensional texture landform grid model; and performing density control reconstruction processing on the three-dimensional texture landform grid model to obtain a three-dimensional density texture landform model, and storing the three-dimensional density texture landform model. According to the embodiment, the quality of the three-dimensional density texture landform model can be improved, and waste of storage resources is reduced.

The invention discloses a source network, plant, river and lake integrated model simulation method and device, a medium and equipment in the technical field of regional water environment pollution treatment. The method comprises the following steps: inputting a boundary condition and an initial condition of a first model into a pre-constructed surface runoff production and convergence model of a target area, and outputting a flow rate of surface runoff and a water quality index time sequence; inputting the boundary condition and the initial condition of the second model into a pre-constructed pipe network model of a target area, and outputting a flow and water quality index time sequence of key nodes in a pipe network system; and inputting the boundary condition and the initial condition of the third model into a pre-constructed riverway and lake grid model of a target area, and simulating the river and lake hydrodynamics and water quality change process of the target area. According to the invention, coupling simulation of surface runoff, pipe networks, rivers and lakes is realized, and a propagation path and an influence mechanism of pollutants are comprehensively reflected; and high precision and reliability of the model are ensured through parameter calibration.

The invention discloses a coal mine goaf fire monitoring method and system based on multi-source data fusion, and relates to the technical field of coal mine goaf fire monitoring, and the method comprises the steps: collecting the concentration, concentration and air pressure of each wireless sensing node in a coal mine goaf in real time; according to the concentration of each node, a dual-parameter dynamic coupling gradient field traceability algorithm of fusion / gas expansion and chemical reaction mechanism is adopted to calculate a fire source coordinate; performing anomaly detection according to the concentration of each node, and positioning an air leakage point by adopting a three-dimensional oxygen concentration gradient field positioning algorithm and combining air pressure compensation for an oxygen concentration anomaly point; based on goaf point cloud data, a goaf three-dimensional grid model is constructed, and a fire source spreading path, an air leakage channel and gas concentration distribution are dynamically and visually displayed in combination with multi-source monitoring data and fire source and air leakage point positioning results. The goaf fire prevention and control system can achieve all-around prevention and control of goaf fire.

The invention discloses a medicine package online detection system based on three-dimensional reconstruction, and relates to the technical field of three-dimensional reconstruction, the system is matched with a binocular industrial camera through a numerical control rotary table to collect a double-view group covering the whole surface of a medicine package and containing an overlapping surface; carrying out feature point registration by adopting a polarization fusion SIFT algorithm, and positioning a packaging area through a model fusing packaging topology priori and edge gradient constraint; generating a disparity map based on a semi-global block matching algorithm, and combining camera calibration parameters with a rotary table rotation angle for splicing to obtain a complete packaging point cloud; a three-dimensional grid model is generated through Poisson curved surface reconstruction, accurate detection of surface concave-convex defects is achieved through curvature sudden change analysis and a tolerance threshold comparison method, and finally a defect information set is output and linked with a sorting mechanism to complete qualification judgment. The system can carry out full-surface and high-precision detection on medicine packages, is suitable for multi-specification packages, and meets the quality control requirements of industrial production.

The invention discloses a smart city planning three-dimensional scene reconstruction optimization system combined with semantic segmentation, and belongs to the technical field of three-dimensional scene reconstruction optimization. The system comprises a data sensing module which collects aerial images and laser point clouds, and complements a sheltered area to obtain city modeling data; the preprocessing module performs denoising, data registration and data fusion on the city modeling data to generate texture point cloud data; the semantic understanding module realizes multi-modal semantic segmentation of the texture point cloud data through a fine-tuned SAM network and an improved RandLA-Net, and semantic tag data is obtained through restoration and optimization; the reconstruction optimization module constructs an initial three-dimensional grid model based on the texture point cloud data, and optimizes a ground feature boundary and a missing region of the model in combination with a semantic tag; and the output application module converts the optimized model into a standard format and outputs the model. Through deep coupling of semantic segmentation and reconstruction optimization, the precision of the three-dimensional scene model is improved, and reliable support is provided for smart city planning.

The embodiment of the invention provides an aircraft skin damage identification method and device, equipment, a storage medium and a product. The method comprises the following steps: acquiring an initial point cloud of an aircraft skin surface through structured light equipment, and performing data preprocessing on the initial point cloud to obtain a preliminary correction point cloud; calculating reflection intensity distribution of each area on the surface of the aircraft skin based on the preliminary correction point cloud, and determining a compensated point cloud; extracting geometric features from the compensated point cloud, and performing denoising processing on the compensated point cloud to obtain a denoised point cloud; constructing a three-dimensional grid model representing a three-dimensional structure of the aircraft skin surface based on the de-noised point cloud, and determining a damage candidate area of the aircraft skin surface; obtaining a point cloud subset associated with the damage candidate area and carrying out damage type classification on the point cloud subset to obtain a classification result of damage types; according to a classification result, generating a damage labeling graph; and based on the damage marking graph, calibrating the damage size parameter to generate a final damage report.

The invention relates to the field of biological modeling, and discloses a shoulder joint stress simulation method and system based on a three-dimensional finite element. The method comprises the following steps: acquiring three-dimensional geometric data of a shoulder joint through scanning equipment, and generating an initial grid model; dividing the preliminary calculation grid to determine an initial stress value, simulating stress transfer distribution, and generating a preliminary stress distribution field; calculating the stress gradient change rate of each grid unit and performing local subdivision to generate a stress gradient change rate distribution diagram; performing density subdivision on the grid units exceeding the change threshold to generate a refined grid model; the calculation grid is divided again, the stress value of each grid unit is calculated, and an updated stress field is generated; calculating a difference vector, judging whether the difference vector meets a convergence condition or not, and obtaining a convergence judgment result; and if not, iteratively subdividing the local grid to generate a final stress distribution field. Through adaptive grid subdivision and iterative convergence optimization, the problem of insufficient simulation precision is solved, and the accuracy is improved.

The invention belongs to the field of cultural heritage digital protection, and discloses an ancient building three-dimensional modeling method based on three-dimensional laser scanning, which comprises the steps of extracting feature points of a point cloud data set and texture image data, and performing registration in combination with a flight log of an unmanned aerial vehicle; performing image restoration and feature extraction on the texture image data and the point cloud-image registration result through a convolutional neural network-probability Markov random field (CNN-PMRF) model; performing geometric feature extraction on the point cloud data set, fusing the texture image feature vector to obtain a geometric-texture joint feature vector, and optimizing a rough mesh model generated based on the point cloud data set; mapping the repaired texture image data to the optimized grid model to obtain a preliminary three-dimensional grid model; and processing the preliminary model parameters through a gradient boosting decision tree (GBDT) model to obtain a correction value, and adjusting the preliminary three-dimensional grid model based on the correction value to obtain an optimal three-dimensional model. The precision of three-dimensional modeling of the ancient building can be improved.

The invention discloses an innovative pit body volume detection system based on a three-dimensional laser scanning technology. Acquiring the volume point cloud information of the pit body by adopting a three-dimensional laser scanning technology; the volume is calculated through double-engine cross validation, two algorithms are used for cross validation, and it is ensured that the volume calculation result relative error meets the requirement; comprising the steps that a Matlab layered integral algorithm is adopted, specifically, discrete layered volume integration is achieved through elevation layered cutting, boundary polygon generation of a polyshape function and AlphaShape geometric reconstruction; and a Geomagic curved surface reconstruction algorithm: generating a watertight grid model based on an NURBS curved surface technology, and completing continuous volume calculation. According to the method, a non-contact measurement system is established, so that the measurement efficiency is greatly improved; a three-dimensional point cloud digital processing platform is created, full-process digitalization of scanning data automatic registration, boundary recognition and volume calculation and real-time visual output of measurement results are achieved, secondary errors caused by manual intervention are reduced, the project acceptance data traceability requirement is met, and the measurement comprehensive error rate is greatly reduced.