473 results about "Surface reconstruction" patented technology

The invention relates to the technical field of rock mechanics, and discloses a rock three-dimensional reconstruction method and system based on multi-source information fusion, and the method comprises the steps: obtaining and preprocessing data, carrying out the spatial feature learning of a fusion feature vector through a 3D-CNN network, and constructing a three-dimensional voxel model of rock microscopic damage; converting the fused image data into a point cloud model of the underground cavern surrounding rock structure by adopting a three-dimensional reconstruction algorithm based on point cloud, and constructing a digital twin framework of the underground cavern surrounding rock structure based on an implicit surface reconstruction algorithm; feature parameters output by the three-dimensional voxel model and the digital twinning framework are used as input, and the optimal supporting opportunity and supporting parameters are output through an LSTM-CNN fusion model; in the underground engineering construction process, surrounding rock deformation data are collected in real time, and a supporting scheme is adjusted in real time through a depth deterministic strategy gradient algorithm; according to the method, the scientificity and timeliness of support design under complex geological conditions can be improved.

Disclosed in the present invention is a bridge scour curved surface morphological feature reconstruction method based on three-dimensional sonar point clouds, comprising the following steps: collecting point cloud data of a three-dimensional morphology of an underwater riverbed terrain near a bridge foundation, and acquiring original point cloud data of a complete morphology of an underwater riverbed; performing denoising and ball pivoting reconstruction preprocessing on the collected original point cloud data to complete preliminary reconstruction of point clouds; on the basis of the point cloud data having undergone preliminary reconstruction, performing point cloud binarization-based scour morphology recognition on the basis of a computer vision principle, calculating scour pit element classification values of all the point clouds, and recognizing scour pit point clouds; on the basis of the recognized scour pit point clouds, using a K-means clustering algorithm for clustering, and calculating the maximum depth of each pier scour pit; and on the basis of the obtained scour pit element classification values of all the point clouds, providing a curved surface reconstruction method based on scour recognition to perform high-precision curved surface reconstruction on the scour pits. The present invention can achieve high-precision scour pit morphology reconstruction.

The embodiment of the invention relates to the technical field of data modeling analysis, and discloses a tunnel rock stratum large deformation analysis method and system based on three-dimensional modeling, and the method comprises the steps: collecting initial three-dimensional point cloud data through three-dimensional laser scanning; constructing an initial three-dimensional geologic model containing spatial morphological characteristics and a rock stratum interface geometric topological relation through space coordinate matching and curved surface reconstruction; finite element unstructured mesh generation is carried out on the model, and a rock stratum mechanical analysis model is established in combination with physical and mechanical parameters; inputting construction parameters and process information, activating unit nodes in sequence, and solving a force balance equation to simulate stress distribution; identifying a potential deformation area through iterative calculation, and adjusting boundary conditions to predict a deformation trend; the three-dimensional space distribution cloud atlas, the time evolution curve and the position marks are fused to generate multi-view deformation early warning information, the accuracy and the visualization degree of tunnel rock stratum deformation analysis are improved, and support is provided for construction safety.

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 prediction method for quantifying the development degree of undermining diseases of rammed earth cultural relics, and relates to the field of cultural relic protection. The method comprises the steps of obtaining three-dimensional laser point cloud data and close photography three-dimensional model data of the rammed earth cultural relics; fusion of the three-dimensional laser point cloud model and the close photography three-dimensional model is realized, and a rammed earth cultural relic undermining disease three-dimensional model is constructed; based on the rammed earth cultural relic undermining disease stereoscopic model, quantitative indexes of undermining disease development are extracted, and an undermining disease development prediction model is constructed and optimized; and generating and outputting a quantitative report of the development degree of the undermining disease of the rammed earth cultural relics. According to the method, three-dimensional laser scanning and close photogrammetry are combined, differentiated routes are designed for areas with different heights, alignment of cross section contours of different models is realized based on Fourier description, a Poisson curved surface reconstruction technology is combined with a hole filling algorithm to complement missing parts of the models, spatial distribution and morphological characteristics of undercut diseases are intuitively presented, and the method is suitable for large-scale popularization and application. The change rule of undercut diseases along with time is quantified, and protection work is promoted to be changed from passive repair to active prevention.

The invention relates to the technical field of point cloud processing, and discloses a point cloud data processing method, system and device for industrial three-dimensional model construction. The method comprises the following steps: carrying out denoising and down-sampling processing on original point cloud data of an industrial part to obtain preprocessed point cloud data, calculating a local geometric descriptor, converting the local geometric descriptor into an industrial feature recurrent plot through a recurrent plot algorithm, inputting the recurrent plot into a convolutional neural network to extract a high-dimensional geometric feature vector, and mapping the feature vectors into B-spline curved surface control parameters through a deep belief network, and performing point cloud reconstruction quality evaluation according to the control parameters to obtain geometric accuracy error data and curved surface reconstruction integrity data. According to the method, the problems that in existing industrial three-dimensional model construction, a point cloud data processing method lacks intelligent feature recognition, the reconstruction precision is insufficient, and manufacturing constraints are not fully considered are solved, and the recognition accuracy of geometric features of complex industrial parts and the precision of three-dimensional model reconstruction are improved.

The invention discloses a multi-modal measurement system and method of a three-coordinate measuring machine, relates to the cross technical field of precision measurement, computer vision and intelligent manufacturing, and is used for solving the problems of low automation degree, strong subjective dependence and lack of assembly performance prediction capability in automobile covering part characteristic line detection. According to the method, point cloud data and positioning coordinates are synchronously collected through a multi-mode sensor, and a fusion point cloud sequence is generated through time sequence synchronization; constructing a high-precision three-dimensional point cloud model through noise filtering, registration and curved surface reconstruction; automatically extracting a feature line path based on curvature analysis and generating an analysis section; calculating a sharpness index through contour fitting, and generating a quality evaluation coefficient in combination with a CAD ideal model contour tolerance deviation; and finally, defects are identified through virtual assembly analysis, a sensor remeasurement path instruction is generated, and a quality report is output in combination with a quality coefficient, so that the detection precision, the efficiency and the assembly quality prediction capability in the measurement process of the three-coordinate measuring machine are improved.

The invention relates to the technical field of three-dimensional geological modeling and geological mapping data processing, in particular to an oblique photography three-dimensional surface model geological modeling system and method, and the system comprises a data collection module, a scene construction module, a boundary line processing module, a geologic body modeling module, a profile linkage module and a result output module. The data acquisition module fuses the oblique photography image and topographic data, and generates a three-dimensional earth surface model through a motion recovery structure algorithm; the geologic body modeling module constructs a closed geologic body through implicit curved surface reconstruction and constrained triangulation; a profile linkage module calls a graph neural network to predict a stratigraphic intersection line trend, and realizes two-dimensional and three-dimensional real-time synchronization based on event driving and sparse voxel hash mapping; and the result output module executes data verification and generates a multi-dimensional geological report. According to the scheme, dependence of a third-party tool is eliminated, geological mapping efficiency is improved, and the problem of section linkage delay is solved.

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 belongs to the technical field of image processing, and mainly relates to a teenager scoliosis detection method based on three-dimensional imaging, and the method comprises the steps: obtaining multi-modal data such as a back depth map, temperature distribution, an attitude angle and a plantar pressure matrix of a detected person through a depth camera, an infrared imaging device, an I MU sensor and a plantar pressure distribution sensor; the cloud platform generates a three-dimensional point cloud and obtains a back three-dimensional curved surface model by adopting a Poisson surface reconstruction algorithm, overall attitude correction is carried out by combining an attitude angle and pressure gravity center shift, and a thermal correction model of local deformation is constructed based on a thermodynamic diagram; automatically identifying spine segment mark points through a deep learning algorithm, fitting a spine center line, calculating a Cobb angle, judging the scoliosis degree and outputting an analysis report; according to the method, X-ray imaging is not needed, the detection safety is high, attitude, mechanical and thermal information can be fused, artificial attitude interference is reduced, and the method is suitable for early screening and dynamic reexamination of teenagers.

The invention relates to the technical field of intelligent welding, and discloses an intelligent welding method and system for a curved surface of a corrugated plate of a container, and the method comprises the following steps: carrying out full-coverage scanning on the corrugated plate of the container by utilizing three-dimensional scanning equipment to obtain point cloud data of the corrugated plate of the container, and preprocessing the point cloud data; performing curved surface reconstruction by using the preprocessed point cloud data, generating a container corrugated plate curved surface three-dimensional model, and performing curved surface smoothing processing; an intelligent welding planning algorithm is adopted to generate an optimal welding path, and the container corrugated plate is welded through the optimal welding path; and performing welding defect identification on the welding seam state data by using a welding defect identification model, and feeding back and adjusting a welding mode based on a welding defect identification result. According to the method, the optimal welding track adapting to the geometric characteristics of the corrugated plate is generated in combination with intelligent path planning, the welding seam state is sensed in real time through the multi-mode sensor in the welding process, and the welding parameters and modes are dynamically adjusted.

The invention discloses a collected image recognition method and system for a surveying and mapping unmanned aerial vehicle, surveying and mapping image data and surveying and mapping point cloud data of a target surveying and mapping area are obtained through a multi-mode sensor carried by the unmanned aerial vehicle, and meanwhile, a time camera is used for capturing a motion signal of a dynamic target to generate event stream data; histogram equalization and multi-scale enhancement are carried out on the surveying and mapping image data, and voxel filtering and curved surface reconstruction are carried out on the surveying and mapping point cloud data; wavelet packet decomposition is utilized to extract frequency domain features of an image in the preprocessed acquisition data, and the frequency domain features are fused with motion trail features in event stream data; and inputting the mixed feature vector into a lightweight adaptive model, dynamically adjusting weights of different modes through an attention mechanism, and outputting a surveying and mapping result of the target surveying and mapping area. The information of the image in different frequencies and directions can be described more comprehensively and meticulously, and the surveying and mapping efficiency is effectively improved.

The invention relates to the technical field of data processing, and provides a BIM model continuous grid bottom surface extraction method, device and equipment and a storage medium, according to the scheme of the invention, grid bottom surface extraction is carried out based on a user-defined data structure after BIM model triangularization, the influence of a professional design software production environment and a multi-source heterogeneous storage format is eliminated, and universality is achieved; according to the method, the cleaned and corrected triangularized grid model is subjected to space division and an elevation extraction algorithm, so that the grid bottom surface extraction efficiency is greatly improved; according to the method, curved surface reconstruction is carried out according to the spatial point cloud normal set and the point cloud data set, so that the construction accuracy of grid bottom surface extraction in the projection direction is ensured, a finer and more continuous geometric expression is provided, and the problem of model bottom surface image missing is solved.

The invention discloses a dragging positioning spraying track planning method for a local area of the surface of special equipment and a storage medium, and belongs to the technical field of industrial robot automation. The method comprises the steps of obtaining point set data of a to-be-sprayed area; calculating a convex hull based on the point set, and solving a minimum enclosing rectangle by using a rotary caliper method to determine an accurate rectangle spraying boundary; constructing a rectangular amplitude limiting sedimentary model through spraying testing and parameter identification; generating a grid track with a buffer area based on the model and the boundary, and optimizing the spraying speed by taking the minimization time as a target; and for the curved surface, performing B-spline curved surface reconstruction and extracting a normal vector to control the attitude of the spray gun. According to the method, the complex multi-parameter trajectory optimization problem is simplified into single-speed optimization through the rectangular amplitude limiting deposition model, the problems that in local spraying, trajectory planning is complex, edge control is not precise, a coating is not uniform and the like are effectively solved, and the spraying efficiency and quality are remarkably improved.

The present application relates to a geographic mosaicking method and apparatus for video images, and a computer device and a storage medium. The method comprises: acquiring real-time live streaming images of a real-world scene that are collected by a plurality of unmanned aerial vehicles, and GNSS information of the plurality of unmanned aerial vehicles; using a visual SLAM algorithm to perform input frame tracking on the real-time live streaming images, and performing pose estimation on successfully tracked input frames by combining visual trajectories and the GNSS information, so as to generate georeferenced camera poses; using the camera poses and a surface reconstruction algorithm to perform densification processing on the input frames, so as to generate a depth map of the real-world scene, and mapping the depth map into dense three-dimensional point clouds, so as to construct a three-dimensional surface model of the real-world scene; and using the camera pose and the three-dimensional surface model to perform orthorectification on the input frames, and integrating the orthorectified input frames into a global mosaicked map, so as to generate a global image of the real-world scene. By means of the embodiments of the present application, a real-time picture of a real-world scene can be quickly acquired, thereby providing robust support for a rapid emergency response in a real-world scene.

The invention discloses a construction site three-dimensional modeling method based on multi-sensor fusion. The method comprises the following steps: synchronously acquiring data by using a laser radar, a camera, an infrared sensor, a GPS (Global Positioning System) and an IMU (Inertial Measurement Unit); the method comprises the following steps of: performing denoising and filtering operation on collected original data, aligning a timestamp and a space of the collected data, fusing the collected multi-source data, and aligning and fusing the processed multi-source point cloud data through a point cloud registration and fusion algorithm to generate a complete three-dimensional point cloud model; generating a grid model by using a surface reconstruction algorithm based on the point cloud data, and performing texture mapping in combination with texture information collected by a camera; the model is simplified and the precision of the model is improved through a model optimization technology, and a reliable three-dimensional visualization foundation for construction management and analysis is formed; real-time detection and modeling of dynamic targets such as mobile equipment and workers on a construction site are realized, and the real-time response capability of the system in a complex construction site environment is ensured through combination of a lightweight neural network architecture and an edge computing technology.

The invention discloses a construction hidden danger automatic detection method and system based on point cloud and image multi-mode. The method comprises the following steps: step 1, acquiring point cloud data and RGB image data and respectively preprocessing the point cloud data and the RGB image data; 2, safety equipment detection is carried out by establishing an improved YOLOv5 model; establishing a 3D-CNN model to qualitatively judge the abnormal behavior of the personnel; 3, combining a semantic segmentation model and point cloud data processing to carry out quantitative judgment of height calculation and coordinate conversion of the fence; and 4, realizing three-dimensional live-action model reconstruction based on point cloud feature matching, Poisson surface reconstruction and GPU rendering, and detecting potential safety hazards of a construction site. The accuracy of qualitative detection is further improved, the precision error of quantitative detection is reduced, the recognition efficiency and precision of potential safety hazards are greatly improved, intelligent and all-around guarantee is provided for safety management of a construction site, remote decision is assisted, the management cost is reduced, and the method is suitable for various construction scenes.

The invention provides a three-dimensional reconstruction method for a traffic accident scene in combination with a ground-air view angle, and relates to the technical field of three-dimensional reconstruction, and the method comprises the steps: carrying out the image collection of the traffic accident scene through employing cameras of two platforms, namely an unmanned plane and an unmanned vehicle, carrying out the semantic segmentation of the image, and generating a pixel-level mask of a key target; extracting an ROI from the image according to the pixel-level mask of the key target, and performing image enhancement and denoising processing on the ROI to obtain a processed ROI image; and optimizing internal and external parameters of cameras of the unmanned aerial vehicle and the unmanned vehicle, performing absolute scale recovery, reconstructing a three-dimensional surface model by combining an SfM method, an MVS method and a surface reconstruction method of a combined camera optimization objective function based on a pixel-level mask of a key target and a processed ROI image, and performing digital quantitative analysis of an accident scene. The method can solve the problem that the existing three-dimensional reconstruction method is insufficient in camera calibration optimization and lacks absolute scale information.

The invention belongs to the technical field of vision measurement, and discloses a high-reflection curved surface reconstruction method and system based on multi-view point cloud fusion and optical optimization. The method comprises the following steps: acquiring multi-source heterogeneous data such as a stripe image, a polarization image and anchor point depth, and mapping the multi-source heterogeneous data to a unified workpiece coordinate system to form a standardized data set; calculating the normal direction of a sampling point based on data, establishing a slope field, and recovering the height through integration to obtain a geometric initial description of a curved surface; the method comprises the following steps: constructing a candidate light path through reverse ray tracing, generating a credibility weight in combination with a polarization degree, a reflection frequency, uncertainty and an incident angle index, and normalizing the credibility weight in a local neighborhood; fusing multi-source point clouds under the constraints of weights and anchor points, establishing a parameterized curved surface model, and constructing a joint optimization objective function containing geometric errors and optical consistency errors; and further adaptively adjusting a weight rule based on residual distribution, carrying out closed-loop iterative optimization, and outputting the initial surface shape of the high-reflection curved surface with high precision and good stability.

The invention relates to a roof complex curved surface curvature analysis and optimization method and device, equipment and a medium, and the analysis and optimization method comprises the steps: obtaining original point cloud data of a target roof, carrying out the preprocessing of the original point cloud data, and generating a corresponding roof entity point cloud model; establishing a curved surface reconstruction algorithm interface of the roof entity point cloud model, extracting a corresponding space coordinate point set, and generating a corresponding curvature parameter set; inputting the curvature parameter set into a preset elastic mechanical model, and determining a corresponding critical region; performing parameterization adjustment on the critical region to generate optimized curvature data, and converting the optimized curvature data into plate rolling process parameters to generate a corresponding optimization scheme; and pushing the optimization scheme to each application terminal based on the cloud collaboration platform. The precision and efficiency of modeling and analysis of the complex curved surface are improved, closed-loop cooperation of design, analysis and manufacturing is achieved, and the problems of modeling distortion, mechanical analysis lag and data isolation in a traditional method are solved.

The invention relates to the technical field of fault identification, in particular to a three-dimensional fault occurrence intelligent identification method and system based on multi-source remote sensing, and the method comprises the steps: obtaining a high-resolution optical image, a penetrating radar profile and gravity gradient data of a target region, and generating a three-dimensional geological response body fusing earth surface and underground information; inputting the three-dimensional geological response body into a vertical adaptive enhancement module, and constructing a unified structured fault feature tensor; and inputting the fault feature tensor into a dynamic curvature constrained curved surface reconstruction module to generate a fault space curved surface, and resolving trend, tendency and dip angle change functions of the curved surface at different depths. According to the three-dimensional fault occurrence intelligent identification method based on multi-source remote sensing, the high-resolution optical image, the penetrating radar profile and the gravity gradient data are fused, a structured three-dimensional geological response body is constructed, the cooperative expression ability of earth surface-underground fault information is remarkably improved, and the fault occurrence identification accuracy is improved. And high-fidelity modeling of complex fault bending and abrupt change areas is realized.

The invention discloses a drilling-measurement constrained three-dimensional geothermal geologic attribute modeling and quantification method, and relates to the technical field of data analysis and processing, and the method comprises the following steps: 1, constructing a drilling-measurement constrained three-dimensional geothermal geologic voxel basic model, and forming a three-dimensional geothermal geologic voxel basic model covering a modeling range; 2, constructing an implicit signed distance field on the three-dimensional geothermal geologic voxel basic model to express fracture geometry, generating a unified implicit geothermal geologic voxel field, and redividing voxel categories according to the unified implicit geothermal geologic voxel field; and step 3, executing moving cube surface reconstruction and prior sensitivity analysis on the unified implicit geothermal geologic voxel field to give a space confidence body and a volume interval, and dividing the space confidence body and calculating the volume interval according to the voxel occurrence frequency. Evaluation of the geothermal body is changed from traditional single volume estimation to interval and confidence expression, and a reliable basis is provided for well position deployment, risk management and development planning.

Approaches presented herein provide for the unconditional generation of novel three dimensional (3D) object shape representations, such as point clouds or meshes. In at least one embodiment, a first denoising diffusion model (DDM) can be trained to synthesize a 1D shape latent from Gaussian noise, and a second DDM can be trained to generate a set of latent points conditioned on this 1D shape latent. The shape latent and set of latent points can be provided to a decoder to generate a 3D point cloud representative of a random object from among the object classes on which the models were trained. A surface reconstruction process may be used to generate a surface mesh from this generated point cloud. Such an approach can scale to complex and / or multimodal distributions, and can be highly flexible as it can be adapted to various tasks such as multimodal voxel- or text-guided synthesis.

The invention relates to a three-dimensional sea temperature monitoring method, and the method comprises the steps: predicting a residual error through a sea surface temperature reconstruction model based on low-resolution sea temperature background data, meteorological data and geographic feature data of a to-be-monitored sea area, superposing the residual error with the low-resolution sea temperature background data, and obtaining a high-resolution sea temperature parameter of each region of a sea surface; and the precision and the physical consistency of the sea surface temperature parameters are improved. In deep sea temperature inversion, based on biochemical environment data and high-resolution surface sea temperature parameters, sea temperature parameters of all depth areas of a sea area to be monitored are predicted through a deep sea temperature prediction model, and a heat exchange rule is reflected more accurately. According to the method, surface reconstruction and deep inversion are combined, an association connection mechanism is established, information collaborative integration is achieved, complete and coherent three-dimensional sea temperature data are output, and reliable support is provided for applications such as ocean heat transfer calculation.

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

The invention belongs to the technical field of forge piece warpage measurement, and particularly relates to a large long beam type die forging warpage measurement method and system based on three-dimensional contour scanning, and the method comprises the steps: S100, scanning a forge piece, and obtaining original point cloud data; step S200, processing the obtained original point cloud data so as to realize de-noising and main body target segmentation; step S300, accurately matching all the point cloud data on the scanning path, and splicing the point cloud data in sequence to obtain final point cloud data of the forge piece; step S400, performing surface reconstruction on the final point cloud data to generate a continuous and complete three-dimensional surface model; step S500, measuring and calculating the warping degree of the forge piece by using the three-dimensional surface model; the warping detection process can be improved from original sampling inspection to sample inspection, so that the defective rate is reduced; the forge piece scrapping risk caused by blind correction is avoided, and equipment and electric furnace energy consumption and labor cost caused by repeated correction are reduced; and the operation is automatic and convenient.

This invention provides a method and system for monitoring surrounding rock deformation in underground coal mines based on three-dimensional point clouds, relating to the field of coal mine safety monitoring. The invention includes the following steps: installing a reference target in the monitoring area and collecting point cloud data; preprocessing the point cloud data, performing coarse registration using the reference target and fine registration using the iterative nearest point algorithm, and generating a triangular mesh model using the Poisson surface reconstruction algorithm; parameterizing the triangular mesh model of the monitoring area into a two-dimensional analysis mesh, calculating the three-dimensional displacement vector of each node, and establishing a displacement field matrix; calculating the displacement gradient tensor based on the displacement vector, deriving the Green-Lagrange strain tensor, and obtaining the full-field strain distribution; recording the strain value of each mesh node, and determining whether an instability warning is triggered based on the relationship between the strain value and the warning threshold; this method can achieve high-precision monitoring of surrounding rock deformation in underground coal mines.

The invention belongs to the technical field of three-dimensional surface reconstruction, and particularly relates to a robust three-dimensional surface reconstruction method based on multi-scale fusion. Acquiring three-dimensional point cloud data, fitting local implicit curved surfaces of neighborhood points by adopting a weighted least square method, and generating a geometric reconstruction grid model; extracting geometric features in different receptive fields through multi-scale convolution, introducing channel attention, space attention and a gating mechanism to perform weighted fusion on the geometric features in different receptive fields, enhancing a global dependency relationship by adopting a feature mixing operation, and generating a deep learning grid model; performing double-branch fusion on the geometric reconstruction grid model and the deep learning grid model, highlighting a geometric sensitive area, and obtaining a fused enhanced feature; inputting the fused enhanced features into an implicit function decoder, and predicting a signed distance function value of each vertex; and based on the predicted signed distance function field, a contour surface extraction algorithm is adopted to generate a triangular mesh model, so that three-dimensional surface reconstruction is completed.

The invention relates to the technical field of product design, in particular to a household appliance appearance defect optimization product design method based on image discrimination, which comprises the following steps: acquiring a household appliance appearance image, calculating a gradient direction, constructing a distribution matrix, analyzing consistency to generate a defect edge image, extracting high-frequency feature scores to identify defect areas, and clustering point cloud to output defect clusters. According to the method, by calculating the gradient direction numerical value of each pixel point and constructing the gradient direction distribution matrix, the processing capacity of the directivity difference of the household appliance surface texture is effectively improved, the defect point cloud is accurately divided through the density-based noise application spatial clustering algorithm, the defect point cloud is accurately divided, and the defect point cloud is accurately divided. According to the method, the space positioning accuracy of the defect area is improved, the precision of optimization design is ensured, curved surface reconstruction is performed in combination with the least square method, the appearance design of the household appliance is accurately corrected, and the production efficiency and the design quality are optimized.