159 results about "Delaunay triangulation" patented technology

The invention relates to the technical field of geological disaster monitoring and early warning, in particular to a side slope slippage monitoring and early warning method based on an image recognition technology, which comprises the following steps: arranging a monitoring target and a reference target in a to-be-monitored area of a side slope, arranging two image displacement monitoring devices at opposite stable positions at equal height to acquire two-dimensional displacement data of the targets; after error correction, an equipment monitoring coordinate system included angle is calculated based on parameters such as equipment spacing, slope inclination displacement is calculated through vector synthesis, and three-dimensional slippage deformation is calculated in combination with vertical displacement; meanwhile, a multi-level early warning mechanism based on the slip rate and the accumulated slip amount is established, a Delaunay triangulation network is constructed, and an improved adaptive Kriging interpolation algorithm is adopted to realize deformation trend prediction. According to the method, binocular vision and multi-algorithm fusion are utilized to realize high-precision three-dimensional monitoring, the evaluation accuracy is improved through the dynamic weighting model and intelligent early warning, the method has the advantages of high monitoring precision, timely early warning, high adaptability and the like, and the safety of slope engineering can be effectively guaranteed.

The present invention relates to the technical field of natural ventilation in buildings, and in particular to a computationally assisted decision-making method and system for climate-adaptive building cavity design. The method comprises: using a Delaunay triangulation method to generate an initial mesh, using a Laplace operator-based mesh refinement method to adaptively refine the initial mesh, so as to obtain an adaptive mesh system, wherein the adaptive mesh system is used for dynamically adjusting the mesh density of conditional PINNs; constructing a multi-task learning framework within the conditional PINNs, wherein the multi-task learning framework is used for jointly predicting a plurality of physical field variables within the conditional PINNs; and iteratively training the conditional PINNs, and using a gradient descent algorithm to minimize a loss function until a predetermined number of training iterations or loss convergence is reached, thereby generating a key physical field variable prediction model in building cavity design. The present invention can implement efficient and accurate prediction of key physical quantities in building cavity design, and can be adapted to different building layouts and functional space characteristics.

The invention is suitable for the technical field of road detection, and relates to a semi-rigid base layer loose disease GPR image recognition and three-dimensional reconstruction method, which comprises the following steps: constructing a semi-rigid base layer loose disease random medium model, carrying out forward modeling on a road structure, generating simulation data, and expanding a data set in combination with a data enhancement technology; a DN module fusing a dynamic deformation convolution module and a RepNCSPELAN4 module is designed, meanwhile, a WIoU loss function is introduced, training is conducted through an obtained data set, and identification of the semi-rigid base layer loose disease is achieved; calculating the area of a disease region through pixel and physical size conversion based on an instance segmentation result obtained through identification; a three-dimensional point cloud is generated by adopting inverse distance weighted interpolation, and the disease volume is calculated in combination with a Delaunay triangulation method. According to the method, accurate disease recognition is achieved, meanwhile, two-dimensional recognition is converted into three-dimensional reconstruction, and a quantitative basis is provided for maintenance priority division and repair scheme formulation.

The invention provides an airborne point cloud building contour point extraction method based on a constraint triangulation network and semantic ring analysis, and belongs to the field of airborne laser radar data processing, and the method comprises the steps: obtaining an airborne laser radar point cloud data set of a to-be-processed region; performing classification processing by using a filtering algorithm to obtain a surface point set and a non-surface point set; building candidate seed points are extracted, and building point clouds are extracted; a Delaunay triangulation network is constructed based on the building point clouds, and constraint is carried out based on the distance between the point clouds; constructing a concurrent triangle set, and extracting contour points and contour connecting edges; and constructing a topological graph, performing traversal search on the topological graph, determining the minimum inclusion rectangle of the closed loop, and judging the contour point type corresponding to the closed loop according to the geometrical shape parameter and the spatial distance parameter of the minimum inclusion rectangle. According to the method, the triangulation network is constructed by using the disordered contour points, and the sequence relationship and semantic information between the points are considered, so that accurate extraction of the semantic contour points is realized.

The invention discloses a rock mass falling identification algorithm based on point cloud distance tolerance, and belongs to the technical field of rock mass monitoring, and the algorithm comprises the steps: obtaining image data of a collection region, and generating a live-action three-dimensional model and original point cloud data of the collection region; removing the water surface feature points in the point cloud data; performing density adaptive voxel downsampling on the point cloud without the water surface feature points; iCP registration is executed layer by layer by adopting a voxel size progressive decrease strategy, when ICP registration is executed on each layer, iteration convergence is controlled through a dynamic threshold value, and transformation matrixes of all layers are accumulated to obtain a final registration result; and calculating the Hausdorff distance tolerance of the point clouds after the two stages of registration, when the distance tolerance is greater than a preset threshold value, determining the rock mass falling area, and calculating the rock mass falling volume by using an Alpha-Shape algorithm in combination with Delaunay triangulation. The algorithm based on the point cloud distance tolerance is high in recognition precision in the rock mass falling area; the method can be effectively applied to rock mass monitoring and loosening and peeling detection.

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 discloses a photovoltaic power station wind field evaluation method and system, electronic equipment and a storage medium, and relates to the technical field of photovoltaic power station engineering. The method comprises the following steps: carrying out classification processing on original point clouds, generating DEM data by using Delaunay triangulation in combination with a natural neighborhood interpolation method, and carrying out correction through ground control points and least square adjustment; and constructing a three-dimensional terrain model according to the corrected data and image data, determining a computational domain size and a boundary condition, performing terrain optimization, executing LES solution after applying near-surface turbulence inlet disturbance synthesized by PRFG3, and comparing and evaluating the obtained transient wind field data with field actually measured wind speed data. According to the method, accurate capture of complex terrain wind field features and dynamic adaptive correction of the model are realized, so that the evaluation period is shortened, the surveying and mapping cost is reduced, the precision and reliability of wind field evaluation are remarkably improved, and the demand of wind resource evaluation of a large-scale photovoltaic power station is met.

The invention provides a power collection system topology optimization method and device based on a variable weight minimum spanning tree, and relates to the technical field of offshore wind power topology optimization. The method comprises the following steps: grouping a plurality of fans based on the angle difference among the plurality of fans according to the position information of the offshore booster station to obtain a plurality of fan sets; a Delaunay triangulation method is adopted to construct a reference grid connecting line of each fan set; and based on the reference grid connection line of each fan set, generating the optimal topology of the to-be-processed offshore current collection system based on a variable weight minimum spanning tree algorithm. According to the method, the grouping clustering method, the Delaunay triangulation method and the variable weight minimum spanning tree algorithm are combined, and the topology design of the offshore wind plant current collection system is efficiently, economically and rapidly achieved. According to the invention, topological connection and cable specification type selection can be optimized synchronously, and a global optimal solution is sought between the cable path length and the type cost difference caused by the change of the current-carrying capacity, so that the fine control of the overall cost of the current collection system is realized.

The invention, which relates to the technical field of mine geology and urban safety, discloses a refined collaborative prediction method and system for subsidence of a global goaf, comprising the steps of establishing a hierarchical storage system, and correcting a working face calculation boundary; extracting the maximum influence radius of all the working faces and four-dimensional coordinates of the mining boundary of each working face, and calculating to obtain a global prediction range to generate a global surface prediction grid; point set insertion and Delaunay triangulation are adopted to obtain an effective triangular unit, a local influence domain range of the effective triangular unit is calculated, and an influenced sub-grid is screened from the global surface prediction grid; and calculating a predicted point movement deformation value based on a parallel computing architecture, accumulating the predicted point movement deformation value to a global result array through a coordinate index mechanism, synthesizing a deformation component in a specific direction, generating a visual result, and performing statistical analysis. According to the method, the problems of poor adaptability and low efficiency of a traditional scheme are effectively solved, and the prediction precision and efficiency are remarkably improved.

The invention discloses a water quality monitoring intelligent early warning method and system based on multi-dimensional data analysis, and belongs to the technical field of water quality monitoring. The method comprises the following steps: processing missing values and noise through a dynamic weighted data filling algorithm to obtain complete water quality data; carrying out multi-parameter collaborative dimensionality reduction by adopting an improved t-SNE algorithm, and mapping high-dimensional water quality parameters to a three-dimensional feature space; constructing a dynamic watershed partition model based on a Delaunay triangulation network and DEM data; calculating a spatial anomaly score through a weighted local outlier factor; performing time anomaly detection in combination with STL (Standard Template Library) decomposition and a Transform model; multi-scale fluctuation detection is realized by using wavelet packet decomposition; fusing space, time and parameter dimensions to construct a three-dimensional judgment matrix, and generating a comprehensive anomaly score; and triggering a multi-level early warning mechanism according to a scoring result. The system can monitor the water quality change in real time, and gives out early warning in time when abnormity occurs, so that the water quality safety is guaranteed.

The invention discloses an ocean terrain digital display method based on three-dimensional modeling. The ocean terrain digital display method comprises the following steps of 1, constructing a multi-source ocean data set; 2, performing space fusion by adopting a self-adaptive interpolation method based on position weight to generate a three-dimensional space density field; 3, performing contour surface extraction by adopting an improved Marching Cubes algorithm to generate an initial three-dimensional terrain model; 4, performing local modeling by adopting a Delaunay triangulation network reconstruction method, and constructing a complete three-dimensional terrain model; 5, obtaining a texture terrain model; step 6, constructing an LOD tree structure and realizing dynamic loading in combination with view cone cutting and a screen space error control strategy; and step 7, based on a dynamic loading result of the LOD tree structure, driving node switching through a time controller, and performing visual display. According to the method, three-dimensional modeling and an LOD tree structure are fused, and high-precision reconstruction and evolution display of the ocean topography are achieved.

The invention discloses a miniature intelligent terminal intestinal image processing method and device, a storage medium and computer equipment. The method comprises the following steps: preprocessing an original intestinal tract image set acquired by a monocular endoscope, calculating according to the preprocessed intestinal tract image set to obtain a motion calibration scale factor and a texture calibration scale factor, and adaptively fusing to obtain a conversion coefficient from a pixel to an actual size; extracting polyp region key feature points of each image of the preprocessed intestinal image set, constructing a Delaunay triangulation graph according to each polyp region key feature point, and performing non-rigid deformation matching based on a cross-graph convolutional network and an optimal transmission algorithm to obtain a matched feature point set; and sparse 3D reconstruction is carried out according to the matched feature point set to obtain a polyp point cloud, and the polyp size is calculated according to the Euclidean distance between two farthest points in the polyp point cloud and the conversion coefficient. According to the method, the problems of monocular image scale ambiguity and non-rigid deformation can be solved, and the more accurate polyp size can be obtained.

The invention provides a slope excavation engineering quantity calculation system and method based on point cloud, and the method comprises the steps: reading the slope geological data of hydropower engineering to construct an initial three-dimensional model, and collecting the multi-stage point cloud data through a three-dimensional laser scanner; performing equidistant gridding on the point clouds of the model region according to an X / Y axis, calculating the spatial similarity and color similarity of the point clouds in grids, and dividing sub-data sets according to threshold values; fitting an excavation surface through a Delaunay triangulation network, calculating an XY plane projection area, and calculating an average Z-direction distance from a subset to the surface of the initial model; the node weight of the triangulation network is corrected by fusing rock stratum interface parameters, finally, the excavation engineering amount is dynamically output through summation of the product of the projection area of each subset and the average distance, and when the deviation of adjacent stages exceeds 10%, cross validation is conducted in combination with a profile method. According to the method, the precision and the real-time performance of slope excavation engineering quantity calculation can be improved, and automatic integration of lithologic characteristics and mechanical attributes is realized.

The invention relates to the technical field of laser welding, and particularly discloses a laser welding system and a laser welding spot position determining method.The laser welding system comprises a welding execution module, a motion execution module, a data acquisition module and an industrial personal computer; the welding execution module is used for carrying out laser welding operation on a welding seam position according to a welding instruction issued by the industrial personal computer; the motion execution module is used for driving the mechanical arm to complete mechanical actions according to the welding seam position issued by the industrial personal computer; the data acquisition module is used for acquiring contour information of a weld joint position of a to-be-welded workpiece and transmitting the contour information to the industrial personal computer; point cloud information of a to-be-welded workpiece is obtained through a laser sensor and a CCD camera, three-dimensional model reconstruction and point cloud segmentation are carried out in combination with an advanced Delaunay triangulation technology and an RANSAC algorithm, so that feature points of a welding seam are accurately extracted, then noise reduction processing is carried out on the extracted feature points by adopting a mean value replacement algorithm, and the feature points of the welding seam are accurately extracted. And the final welding spot position is more accurate.

The invention discloses a substation danger area judgment method and system based on electric field gradient perception, and relates to the field of safety monitoring, and the method comprises the steps: arranging an electric field sensor array in a key equipment area of a substation; performing noise reduction processing on the data of each sensor node to obtain an electric field vector set; obtaining the electric field intensity change rate of each monitoring point through a space vector differential algorithm, and generating an electric field gradient tensor; dividing the electric field gradient value, and constructing a dynamic danger level mapping rule; performing spatial interpolation through a Delaunay triangulation algorithm to generate an electric field gradient equipotential surface; constructing an electric field gradient space distribution model, and generating a dynamic danger boundary envelope body in real time; and correcting the boundary of the dangerous area through the pre-trained gradient compensation coefficient matrix and triggering a graded early warning signal. The method has the advantages that the electric field gradient change of the transformer substation is monitored in real time through the electric field sensor array and the wavelet denoising technology, the dangerous area is dynamically evaluated, and the accuracy and real-time performance of dangerous area judgment are effectively improved.

The invention relates to the technical field of three-dimensional modeling, in particular to a terrain modeling method and device based on a domestic three-dimensional graphic platform Railworks, and the method comprises the steps: collecting terrain data along a rail transit engineering project, and generating a structured original data pool; the method comprises the following steps: extracting and processing a discrete three-dimensional point set through a Railworks platform, and generating a triangular mesh by adopting a Gift Wrapping algorithm and a Delaunay triangulation algorithm; reconstructing a three-dimensional terrain surface model, adding an attribute database, and integrating elevation and gradient attributes according to industrial standards; and a downstream bridge and roadbed design module is connected through a data synchronization mechanism, so that design parameters are automatically updated. The device correspondingly realizes functions of each step. According to the method, the problems of high data security risk and low collaboration efficiency caused by dependence on foreign software are solved, an autonomous solution is provided, and the data processing security and the cross-professional design collaboration efficiency are improved.

The invention discloses a fault bending quantification method based on high-resolution surface fracture, and belongs to the technical field of earthquake monitoring and early warning, and the method comprises the steps: precisely extracting a surface fracture track through fusing InSAR, POT and field survey data; constructing a three-dimensional dislocation model in combination with Delaunay triangulation and slip inversion; and calculating the roughness by using the included angle between the adjacent triangular units, identifying the bending center and the bending interval of the fault, and projecting the bending center and the bending interval to the earth surface to realize the spatial representation and quantitative characterization of the bending characteristics of the fault. According to the method, the problems of insufficient deformation information and inaccurate fault geometric parameter extraction in a traditional method are solved, the fault discontinuity identification precision can be effectively improved, key constraints are provided for research of an earthquake fracture mechanism, and the method has relatively high innovativeness and engineering application value.

The invention relates to the field of precision manufacturing of aero-engine blades, and particularly discloses an aero-engine blade grinding and polishing removal amount control method which comprises the steps that an industrial robot carries 3D visual equipment to conduct multi-angle scanning on a blade pasted with mark points, the number of public mark points between adjacent scanning poses is forcibly restrained to be larger than or equal to 3, and the number of the mark points is smaller than or equal to 3; a rigid body transformation matrix is solved based on space coordinate transformation, and high-precision point cloud automatic splicing is achieved; blade point clouds before and after grinding and polishing are reconstructed through Delaunay triangulation with consistent parameters, and a triangular mesh continuous curved surface is generated; calculating the minimum space distance from each vertex of the target curved surface to the source curved surface as a removal amount error epsilon, and positioning an out-of-tolerance region based on epsilon distribution; and generating a compensatory processing track by adopting an equal residual height method. The problem of point cloud registration caused by rare geometric features of the blade is solved, machining decision is driven through curved surface space errors, closed-loop accurate control over the removal amount is achieved, and the consistency of the grinding and polishing quality of the blade is improved.

The invention discloses a centralized heat supply network pipe pressure monitoring method and system based on artificial intelligence, and relates to the technical field of heat supply system monitoring, and the method comprises the steps: firstly laying optical fibers and point pressure sensors on a network pipe, and collecting acoustic strain and pressure data; constructing a digital twin grid through same-frequency alignment and Delaunay triangulation, and reconstructing a continuous pressure field; calculating the residual error between the reconstruction pressure and the measured value at the monitoring node; extracting multi-scale residual features to form a feature matrix based on a wavelet operator of a pipe network topological structure map; inputting the features into a pre-trained spectrogram wavelet neural network, and outputting a normalized abnormal score; and finally positioning a fault pipe section according to the score and performing graded warning. Physical modeling and deep learning are fused in the whole process, closed-loop monitoring from data collection to fault diagnosis is achieved, and the precision and timeliness of pipe network anomaly detection are remarkably improved. Manual detection is not needed, and the monitoring process is more flexible.

The invention discloses an industrial complex curved surface point cloud reconstruction method based on adaptive projection, and aims to solve the problem of surface reconstruction of high-noise, non-uniformly-distributed and complex geometric point clouds. The method comprises the following steps of firstly performing down-sampling based on spatial distribution on an original three-dimensional point cloud, and then denoising and homogenizing the point cloud through an adaptive weighted local optimal projection algorithm; fitting a local plane by adopting a local least square method, projecting the point cloud to two dimensions, and then carrying out Delaunay triangularization; mapping the two-dimensional triangulation network topological relation to three dimensions to generate a three-dimensional triangulation network; and finally, abnormal triangles are eliminated through side length constraint, and the grid quality is optimized. According to the method, through whole-process cooperative processing, the point cloud data quality and complex curved surface adaptability are remarkably improved, it is ensured that reconstructed grids are smooth, regular and consistent in precision, and the high-precision requirement of complex curved surface reverse engineering in the fields of aviation, molds and the like can be met.

The invention relates to the technical field of digital twinning and simulation, and discloses a full-stack digital twinning simulation method and system for a power grid dispatching master station, and the method comprises the steps: obtaining a voltage power flow result data set and a temperature field distribution data set, building a unified virtual coordinate system, building an initial two-dimensional thermal distribution diagram according to an initial mapping matrix, and carrying out the simulation of the voltage power flow result data set and the temperature field distribution data set; carrying out Delaunay triangulation on the image to generate a mapping error distribution diagram; constructing a Markov chain state sequence, calculating a state transition probability matrix, and predicting and generating a corrected mapping matrix; the edge node loads the correction matrix to generate a lightweight state vector, the lightweight state vector is uploaded to the cloud through multi-level cache to form a set, and the cloud updates the matrix and issues a new version; according to the method, the voltage-temperature rise mapping relation is captured, predicted and corrected in real time along with working condition drifting, hidden coupling deviation caused by inconsistent data calibers is restrained, and it is guaranteed that the high-precision and high-consistency electrical-thermodynamic combined situation is always maintained in the operation process of full-stack digital twin simulation.

The invention provides a network RTK base station coordinate precision detection method and system, and the method comprises the steps: carrying out the base station networking based on a Delaunay triangulation algorithm, and determining a baseline list; obtaining satellite precision orbit information, selecting a to-be-solved baseline vector from the baseline list, and resolving the to-be-solved baseline vector by adopting a fast static positioning algorithm to obtain a preset high-precision relative coordinate result; the preset high-precision relative coordinate result is converted into coordinate values of all reference stations, the coordinate values of all the reference stations are compared with preset known coordinate values in a system, coordinate difference values of all the reference stations on all the base lines are obtained through calculation, gross error elimination is conducted based on the coordinate difference values, and processed coordinate difference values are obtained; and integrating the processed coordinate difference values of each reference station on the plurality of base lines, performing consistency analysis and statistical judgment, determining the reference station with abnormal coordinates in combination with a preset threshold value, and outputting a diagnosis alarm result. According to the invention, the reliability and precision of the network RTK service are effectively guaranteed.

The invention discloses a power transmission and transformation project pond underwater terrain intelligent measurement and backfill amount accurate calculation method and system. According to the method, high-precision three-dimensional data acquisition is realized through a multi-beam sounding system carried by an unmanned ship; an improved ant colony algorithm is combined with B-spline interpolation to optimize path planning, a safe steering angle and a minimum turning path are set, and dynamic obstacle avoidance is achieved; processing data based on a layered sound ray tracking algorithm, CUBE filtering and an attitude correction technology, and eliminating sound velocity errors and environmental interference; performing triangulation network topological structure optimization on the point cloud data by adopting a Delaunay triangulation algorithm, and generating a DEM (Digital Elevation Model) through a contour extraction technology based on region growth; the calculation units are divided through a square grid method, and the backfill amount is accurately calculated through a triangular pyramid volume formula. According to the method, the problems of low precision and poor efficiency of a traditional measurement method are solved, the measurement error is reduced, and the automation degree of underwater topographic measurement and the engineering quantity calculation accuracy are remarkably improved.

The invention discloses a bay hydrodynamic prediction method based on a hybrid Fourier neural architecture, and belongs to the technical field of hydrodynamic prediction, the method comprises the steps of data conversion, data preprocessing, topological relation construction, feature extraction and fusion, model construction, training and prediction, and the like, the data format is converted through a modified trim2nc data packet, and the data format of the trim2nc data packet is converted into the data format of the trim2nc data packet; performing preprocessing to obtain static and dynamic feature data sets; constructing a grid topological relation by using a Delaunay triangulation algorithm; space and time features are extracted through a graph neural network and a time convolutional network respectively and fused; frequency domain calculation is carried out in combination with a Fourier neural operator network with the irregular geometric boundary processing capability, physical knowledge is coupled to define a loss function training model, and finally rapid and accurate prediction of the gulf hydrodynamic force is achieved. According to the method, the problems of high calculation cost and low efficiency of a traditional hydrodynamic model are solved, the prediction precision and efficiency are considered, and a reliable basis can be provided for bay water environment management and planning.

A robot time-energy optimal smooth trajectory planning method is provided, an energy function is constructed by the square sum of path curvature rate, a cost function is constructed by the weighted sum of path energy and length, an optimization model is constructed by introducing path curvature peak and safety distance constraints, and the optimal path is searched under the environment of Delaunay triangulation. The initial path is re-optimized through deleting acute angle vertex, path replacement, removing redundant points, etc., is fitted by cubic NURBS, and is controlled by five-section S-shaped acceleration and deceleration motion under the Bang-Bang-Singular trajectory tangential jerk strategy, so that the path is smooth and collision-free, the trajectory satisfies the curvature peak and curvature rate constraints, and the time-energy is optimal. The robot is not simplified as a point, and the working environment and whether the obstacle is regular are not limited, the search of the path of any two-dimensional space containing obstacles can be processed, the smooth trajectory and fast motion are ensured, and the unified planning of geometry and motion is realized.

The application discloses a face privacy protection method and system, and relates to the technical field of face detection, comprising: acquiring a patient's medication video and extracting video frames; selecting a mask and marking mask key points; performing face key point detection and selection on each video frame, and performing detailed enhancement on the key point detection and selection through a human body posture detection algorithm to obtain face key points; and performing triangular affine transformation on the face key points and the mask key points to add a mask to the face of the video frame. The application can provide effective privacy protection for patients while not affecting the auditing and management efficiency of the medication video. By combining the FaceMesh and DWPose algorithms, as well as the Delaunay triangulation and triangular affine transformation technologies, it is ensured that the mask can be accurately overlaid on the face, and good privacy protection effect can be maintained even in complex video scenes, ensuring the reliability of privacy protection.

The invention discloses a face gear on-machine measurement comprehensive error compensation method based on sequential decoupling. Specifically, a sequential decoupling compensation strategy is provided for solving the problem that the measurement precision is limited due to mutual coupling of a measuring head pre-stroke error and a workpiece installation coordinate system error in the prior art. The method comprises the following steps: firstly, establishing a measuring head pre-stroke error model through standard ball calibration, and performing anisotropic compensation on a tooth surface measuring point by utilizing Delou inner triangulation and a weighted interpolation method; secondly, based on the compensated data, the outer cylindrical surface and the tooth top plane of the face gear are accurately fitted through an iterative optimization algorithm, an accurate measurement coordinate system is established, and the initial phase of the C axis is optimized; and finally, reconstructing an actual tooth surface by adopting a two-stage NURBS curved surface fitting method, and calculating a normal deviation. According to the method, an error propagation chain is effectively cut off through a strict execution sequence, the overall precision and reliability of on-machine measurement are remarkably improved, and a key technical support is provided for face gear closed-loop manufacturing.

The invention discloses a method for converting an elevation system contour line of a stock place to a 85 elevation datum, which comprises the following basic steps of: discretizing the contour line based on an adaptive sampling method of contour line curvature, and extracting node data on the contour line; elevation points are properly encrypted in a place with sparse contour lines by using a method for improving Kriging interpolation by using a gradient boosting tree, and elevation point data obtained by arrangement is converted into 85 elevation; according to a weighted soft constraint Delaunay triangulation algorithm, a triangulated irregular network is constructed by using 85-elevation point data, and contour lines are generated. The method provided by the invention has the advantages of being scientific, reasonable, easy to implement, high in production efficiency, wide in application range and the like, the curvature and characteristics of the contour lines are analyzed one by one by fully utilizing the contour lines of the elevation system of the stock place, and the variation characteristics of the complex space are captured more accurately; and the accuracy of conversion from the elevation line contour line of the stock place to the 85 elevation datum can be further improved.