433 results about "Mesh point" patented technology

The invention relates to the technical field of computer information processing, and discloses a high-fidelity terrain surface interpolation method and system for large-scale point cloud data, and the method comprises the steps: carrying out the multi-level cleaning of original point cloud data, and generating a cleaned point cloud data set; performing adaptive tile grid division based on the cleaned data to generate a tile set covering the target area; in each tile, taking the to-be-interpolated grid point as a query point, constructing and optimizing a local Gaussian process model, and obtaining a real elevation predicted value of the query point; processing all query points in the tiles in parallel to obtain a tile elevation interpolation result set; performing weighted average on each tile result to generate a global seamless terrain surface; according to the method, the problems of poor expandability and surface discontinuity caused by local interpolation in large-scale point cloud data processing are effectively solved, and high-precision and high-fidelity terrain surface construction is realized.

The invention relates to the technical field of atmospheric dust pollution prevention and environmental protection, and discloses a multi-objective optimization layout method for dust monitoring points of a bulk cargo port, which comprises the following steps: processing historical meteorological data and port geographic information, and calculating the comprehensive evaluation concentration of each candidate grid point in combination with a pollutant diffusion model; constructing a multi-target nonlinear mixed integer programming model taking maximization of environment sensitive point coverage and minimization of concentration interpolation deviation as target functions, wherein the model comprehensively considers multiple reality constraints; solving the model by adopting an improved genetic algorithm to obtain an optimal solution set capable of forming tradeoff among different targets; and carrying out quantitative evaluation on the solution set through preset monitoring area coverage rate and monitoring accuracy indexes, and determining an optimal monitoring point position layout scheme. According to the invention, a scientific and quantitative optimized layout scheme can be provided for bulk cargo port dust monitoring, and the reliability and spatial representativeness of a monitoring network are improved.

The invention discloses an electromagnetic field simulation grid adaptive generation method based on a neural network. The method comprises the following steps: performing mesh generation on a semiconductor device simulation model to obtain original generation data, and constructing node features; an undirected graph is constructed, graph nodes of the undirected graph adopt node features of grid points, and connecting edges adopt Euclidean distances between the grid points and adjacent grid points; inputting the undirected graph into a double-branch neural network, and outputting a predicted node position; and correcting each node of the original subdivision data by using the predicted node position obtained by the double-branch neural network to form new subdivision data for electromagnetic field simulation. According to the method, physical field information can be fused to efficiently adjust the node density, and the geometric boundary and topological structure characteristics of the device can be strictly kept.

The invention relates to an earthwork balance calculation method, system and device and a storage medium, and relates to the technical field of earthwork balance design. The method comprises the steps of performing fusion processing on oblique photography data and laser radar point cloud data to generate a live-action three-dimensional model; performing grid division on the live-action three-dimensional model to obtain a grid model; based on the gridding model, defining a decision variable set including the design elevation of each grid point, the overall slope of the site, the slope height of each slope unit and the earthwork allocation amount, and constructing a comprehensive objective function including an earthwork balance objective, an economical objective and a safety objective; and under the engineering constraint condition, performing multi-objective optimization solution on the comprehensive objective function to obtain a Pareto optimal solution set, and selecting a final implementation scheme from the Pareto optimal solution set. According to the method, the problem of topographic data missing of the dense vegetation region is effectively solved, the limitation of traditional single-target optimization is broken through, and the maximization of comprehensive benefits is realized.

The invention discloses a frozen soil roadbed hot melt settlement laser scanning measurement method and system, and relates to the technical field of measurement, the method comprises the following steps: obtaining gridding surface data, and obtaining an elevation data sequence of each grid point; acquiring an elevation change index of each grid point according to the elevation data sequence of each grid point; acquiring a plurality of grid points adjacent to the ith grid point and taking the plurality of grid points as a plurality of reference grid points of the ith grid point, acquiring each relative difference quantity of the ith grid point, and acquiring a correction proportion of the ith grid point according to the plurality of relative difference quantities of the ith grid point; and obtaining target elevation data of each grid point according to the correction proportion of each grid point and the measured elevation data at the current moment, and forming a measurement result including the gridding surface data according to the target elevation data of each grid point. The method has the advantages of identifying abnormal values, dynamically correcting measurement and improving data reliability.

The invention provides a high-resolution emission flux inversion system and method. The method comprises the following steps: collecting atmosphere multi-source data; determining a distance weighting function, and calculating the correlation between the grid points in the simulation area and the observation value; generating a set sample meeting physical constraints of the assimilation object; performing singular value decomposition and dimension reduction on the set samples; replacing a tangent line and an adjoint mode of a regional air quality mode with a mixed assimilation method, and obtaining a simulated regional space grid point analysis increment; obtaining corrected concentration and flux distribution data; the data is used for carrying out emission flux inversion, and the unit time emission flux of different positions is estimated. According to the method, a traditional four-dimensional variation mode is replaced with a mixed assimilation method, and the calculation and programming difficulty is reduced; generating a set sample by using a four-dimensional sliding sampling algorithm, reducing dimensions, and calculating resource consumption; a joint assimilation algorithm is introduced to optimize the concentration and flux field, and accurate inversion of the high-temporal-spatial-resolution emission flux is achieved.

The invention discloses a thin-wall structure layered body grid generation method based on surface grid alignment, which comprises the following steps of: reading an integral surface grid with a thin-wall structure characteristic and a mapping relation, and pairing a source surface grid and a target surface grid in the integral surface grid according to the mapping relation; aligning the source surface grid and the target surface grid which are paired, updating the target surface grid, and extracting triangular mapping information of an aligned region; according to the mapping information, advancing a source surface grid to a target surface grid layer by layer to obtain a layered body grid; extracting the outer surface of the stratified body mesh, combining the outer surface of the stratified body mesh with the overall surface mesh to obtain a combined surface mesh, and performing mesh point classification; normalizing the unit normal direction of the combined surface grid, calculating the normal direction at grid points needing to be propelled according to the grid point classification, and interpolating points according to distances in the normal direction to form a constraint point set; and generating a cavity area body grid by taking the constraint point set and the combined surface grid as constraints, and combining the cavity area body grid with the layered body grid to obtain the layered body grid of the overall thin-wall structure.

The present invention discloses an unified multiple access (MA) based system for uplink transmission of data by multiple users. The system comprises an user interface integrated transmitter modules for transmitting the data from multiple user transmitters over waveforms through a cooperative unified data grid structure including grid points, said unified data grid structure including each user transmitter allocation of a few non-overlapping grid points for loading respective data bearing symbols, with zeros loaded onto unallocated grid points. The user transmitter is configured to transmit a sparsely loaded grid resembling to the unified two-dimensional data grid structure involving data-bearing Quadrature Amplitude Modulation (QAM), where a part of available grid points of the grid as allocated is loaded with QAM symbols and remaining grid points are loaded with zero symbols. A waveform modulator corresponding to user transmitter is also provided in the present system for waveform modulation of said sparsely loaded grid as per the waveforms enabling transmission for multi-antenna reception of the waveforms to a base station or an access point.

The invention discloses a GNSS (Global Navigation Satellite System) nonlinear deformation correction method based on a full-spectrum three-dimensional thermoelastic model. The GNSS nonlinear deformation correction method comprises the following steps: carrying out discrete Fourier decomposition on a temperature time sequence of each grid point; carrying out space spherical harmonic expansion and coefficient projection on each decomposed frequency; based on a space spherical harmonic expansion and coefficient projection result, considering the periodicity of the temperature, and performing sine / cosine representation of a frequency-by-frequency temperature item; performing spherical harmonic representation and time expansion on the deformed displacement field corresponding to the periodic temperature based on the spatial spherical harmonic expansion and coefficient projection result; solving a deformation equation in spherical coordinates in a Love number form to obtain an expression of a complex Love number; based on the complex spherical harmonic coefficient and the complex Love number of the temperature, full-spectrum synthesis of three-component displacement at the spherical surface is carried out; and performing internal consistency and external dispersion verification based on a full-spectrum synthesis result.

The invention discloses an aircraft simulation method, device and equipment based on parallel block sparse matrix incomplete LU decomposition and a medium, and relates to the technical field of simulation, and the method comprises the steps: building a block sparse matrix comprising a plurality of zero sub-blocks and non-zero sub-blocks based on the topological relation of each grid point in an aircraft grid and simulation physical parameters, determining dependency pairs respectively corresponding to a plurality of non-zero sub-blocks from the non-zero sub-blocks, and storing the dependency pairs by adopting a preset data structure; wherein the dependent pair comprises a pair of matched non-zero sub-blocks; respectively distributing the plurality of non-zero sub-blocks to a plurality of GPU thread bundles for parallel processing so as to update the corresponding non-zero sub-blocks based on the updated dependency pairs after the GPU thread bundles complete updating on the dependency pairs corresponding to the corresponding non-zero sub-blocks; and after the plurality of non-zero sub-blocks are updated, updating the block sparse matrix based on the plurality of updated non-zero sub-blocks, and determining an incomplete LU decomposition result according to the updated block sparse matrix so as to perform aircraft simulation.

The invention provides a thermal imaging automatic calibration and key region segmentation method. The method comprises the steps of obtaining a thermal imaging image, and then performing preliminary denoising processing on the image to obtain a denoised image; constructing a high-density grid in an image pixel dot matrix by adopting a dense sampling method according to the de-noised image so as to determine an initial pixel coordinate of each grid point; obtaining neighborhood feature vectors through an abnormal point set, and grouping the vectors by adopting K-means clustering so as to determine a temperature change mode, and fusing a temperature gradient to extract a boundary extraction basis as grid optimization input; and extracting a boundary extraction basis of the key part from the temperature change mode, adjusting the high-density grid according to the boundary extraction basis to obtain an optimized grid, and starting relocation iteration adjustment through coordinate deviation calculation. According to the method, a closed-loop optimization process of high-density grid construction, abnormal point identification, clustering analysis, grid dynamic optimization and iterative relocation is constructed, so that refinement and adaptive segmentation of a thermal anomaly region are realized.

The invention discloses a super-set deterministic weather forecast method and device based on machine learning, and the method comprises the steps: obtaining multi-source meteorological data of a target region, carrying out the meshing of the multi-source meteorological data, carrying out the historical static feature analysis and dynamic feature analysis of the meshing features, obtaining the feature weight of each mode, and carrying out the recognition of the multi-source meteorological data. The method comprises the following steps: constructing a prediction sub-model according to an extreme event, obtaining enhanced numerical prediction data, obtaining posterior probability distribution of grid points through a conditional generative adversarial network and a Bayesian neural network based on the numerical prediction data, a gridding feature and a feature weight, taking a maximum probability value as a deterministic weather forecast, and calculating a confidence interval. And obtaining a joint probability product including wind speed and rainfall joint distribution and the characteristic contribution degree. According to the method, numerical forecasting set products of different mode centers are utilized to fuse probability forecasting information, deterministic weather forecasting is obtained, smoothing of extreme events is reduced, deterministic maximum value output is provided, and meanwhile good interpretability is achieved.

The invention discloses an oil and gas resource spatial distribution prediction method of a tree enhanced naive Bayes classifier, and belongs to the field of petroleum geology and artificial intelligence, and the method comprises the steps: S1, collecting exploratory well, earthquake and geological information; s2, oil and gas resource space distribution prediction master control geological factors are extracted, and an exploratory well data set and a grid data set are made; s3, establishing a tree enhanced Bayesian network model according to the exploratory well data set; s4, calculating the oil-gas probability of the grid points by using the model; and S5, drawing an oil and gas resource space distribution probability graph by using an interpolation method. The method can achieve the accurate and efficient prediction of the spatial distribution of oil and gas resources through optimizing the selection strategy of the dependency relationship of the main control geological factors and combining the geological data features, can provide quantitative decision support for oil and gas exploration and deployment, and improves the exploration efficiency and economic benefits.

The invention provides a geological envelope body automatic generation method. The method comprises the following steps: defining a target work area; performing sparse horizon picking of a top interface and a bottom interface on the geological envelope in the defined target work area to determine a top interface horizon, a bottom interface horizon and corresponding top interface and bottom interface data; based on the grid positions corresponding to all the pickup point positions of the top interface horizon and the bottom interface horizon, according to the range of the top interface data and the range of the bottom interface data, boundary lines of the geological envelope body at the top interface and the bottom interface in the target work area are determined; determining horizon depth values in all grid points of the top interface and the bottom interface; constructing a top interface boundary constraint and a bottom interface boundary constraint according to the horizon depth value and based on boundary lines of the geological envelope body at the top interface and the bottom interface to determine an intersection point between the top interface and the bottom interface of the envelope body so as to optimize the boundary lines of the geological envelope body at the top interface and the bottom interface; and generating a three-dimensional visualization model of the geological envelope based on the optimized boundary line.

The invention relates to a communication network base station deployment method and system based on a bilevel programming model. The communication network base station deployment method based on the bilevel programming model comprises the following steps: generating a plurality of alternative measurement and control stations in a discretization manner in a station distribution area according to a preset station distribution area and a satellite elevation angle threshold value; based on ephemeris data of a target satellite, calculating a visible time window between each alternative measurement and control site and the target satellite, and generating a visible arc segment set; based on a genetic algorithm, M measurement and control stations are iteratively selected from the alternative measurement and control stations to serve as a station combination, and M is a preset station distribution number; according to the communication network base station deployment method and system based on the bilevel programming model, the alternative stations are generated at the grid points by leaving the station distribution area, and the station distribution problem is converted into the permutation and combination problem for selecting the stations. And a nested genetic algorithm is applied to finish specific selection of sites.

The invention discloses a global ionosphere modeling method based on a spherical radial basis function, and the method comprises the steps: laying Reuter grid points at an interval of 10 degrees on an ionosphere thin layer, and converting the Reuter grid points into a daily fixed geomagnetic coordinate system for modeling. Cycle slip monitoring and abnormal value identification and elimination are carried out on obtained satellite observation data (O file), then a precise satellite orbit position is obtained through interpolation in combination with a precise ephemeris file (SP3), hardware deviation is corrected through differential code deviation (DCB file), an AbBPoisson spherical surface radial basis function is adopted and converted into a 15-order truncated AbBPoisson spherical surface radial basis function, and finally, a precise satellite orbit position is obtained. The bandwidth is set to be 0.25, L2 regularization optimization is used, parameters of a radial basis function are solved through a least square method, and therefore global ionosphere modeling is carried out. Different from a traditional spherical harmonic function method, the abbeposon spherical radial basis function controls the control range of a radial base point by adjusting the bandwidth, higher precision can be provided in a data-intensive area, and the adaptability is higher.

The invention discloses a Delta robot motion limit calibration method, which is characterized in that a limit theoretical value of a tail end reachable working space range in a coordinate axis direction is obtained through robot structure parameters, then a cuboid space covering the limit theoretical value is generated, and three-dimensional grid division is carried out; and performing kinematics solution verification on the generated three-dimensional grid points, filtering out unreachable points to obtain a discrete point cloud set of a reachable space, then performing dimension reduction processing in a hierarchical slicing manner, extracting boundaries in a kernel density estimation manner, performing fitting to generate a boundary curve, and obtaining the three-dimensional motion limiting boundary of the tail end of the robot. According to the method, waste of effective space can be better reduced, dependence on human subjective experience is eliminated, and calibration repeatability and efficiency are improved.

The invention provides an airplane ice accretion model training method, a prediction method, a product, equipment and a medium. The method comprises the following steps: acquiring airplane ice accretion observation data and historical weather data; based on the space information and the time information of the airplane icing observation data and the horizontal grid, the vertical layering and the time dimension of the grid points, space-time matching is carried out on the airplane icing observation data and the grid points, and the space-time matched grid points are obtained; calculating the feature data of the space-time matched grid points by using an ice accumulation scheme to obtain ice accumulation indexes of the space-time matched grid points; constructing a training data set according to the feature data corresponding to the plurality of spatio-temporal matched grid points, the icing indexes and the observation labels of the matched airplane icing observation data; and performing model training by using the training data set to obtain an airplane icing model. The training data set provides high-order features with more physical significance for machine learning, the interpretability of the model is improved, and the prediction accuracy of the airplane ice accretion is improved.

The invention belongs to the technical field related to deep learning, and discloses a training method and application of a three-dimensional flow field prediction system of an underwater vehicle, and the training method comprises the steps: calculating the mass center of a neighbor point set for each surface grid point of a vehicle model, constructing a covariance matrix between the neighbor point set and the centroid of the neighbor point set, and performing eigenvalue decomposition to obtain a normal vector of the point; calculating a normal vector included angle between the surface grid point and each point in the neighbor point set, taking the obtained maximum included angle as the geometric feature measurement of the point, and converting the geometric feature measurement into a weight through a Sigmoid function, thereby obtaining the sampling probability of each point; randomly extracting surface grid points from the original surface grid of the aircraft based on the obtained sampling probability to obtain a point cloud of a corresponding model; and training a point cloud neural network by using the sampled point cloud data to obtain the three-dimensional flow field prediction system of the underwater vehicle. Based on the method, the prediction precision and the flow field detail recovery capability can be improved while the calculation efficiency is maintained.

The invention discloses a high-precision adaptive numerical simulation method and system for solving a nonlinear integral-differential equation, and relates to the technical field of computer simulation and numerical calculation. Comprising the steps of setting simulation conditions; constructing a grid space based on the computational domain; constructing a global cubic spline interpolation function based on the solutions on the grid points; if the updated grid point location exists, calculating a right-end integral item by using an adaptive numerical simulation integral algorithm; calculating a heuristic solution and an error estimation value; dynamically adjusting the tentative step length and updating the time according to the estimated value and the ODE tolerance; checking gradient and curvature distribution of solutions, encrypting grids for areas with violent solution changes, and sparse grids for areas with smooth solution changes; using a global cubic spline interpolation function to demap the old grid space to the adjusted new grid space; and iteratively executing the steps, and outputting an integral solution in the computational domain. And finally, collaborative improvement of integral simulation calculation in precision, efficiency and stability is realized.

The invention discloses a 2.5 D statistical optimal distributed modeling method for a geologic structure of a thin coal seam group, and belongs to the technical field of geologic modeling and mineral resource development. The method comprises the steps that drilling space information and sequence constraints of all stratums are obtained based on drilling data, elevation estimation values and corresponding estimation value variances of all points in estimation value grids of all the stratums are obtained through independent Kriging interpolation operation of all the stratums, and constraint conditions are constructed according to the sequence of all the stratums; and constructing a target function of'minimizing the sum of variance with the original value 'by utilizing the elevation estimation value and the corresponding variance on each stratum estimation value grid point, and solving the elevation value of each stratum on the grid point in the estimation value range. The method fuses adjacent horizon information and spatial statistical constraints, can more accurately describe and express complex three-dimensional spatial relationships such as stratum pinching, crossing and merging in the thin coal seam group, remarkably improves the spatial fidelity of the model, realizes automatic and quantitative correction of the stratum sequence in strip mine full-stratum modeling, eliminates manual intervention errors, and improves the modeling efficiency. And the modeling efficiency and the geometric accuracy are improved.

The invention provides a Gummel curve simulation method and system and electronic equipment, and relates to the technical field of semiconductor device emulation.The method comprises the steps that according to the actual structure of a variable-component SiGe HBT device, division is conducted in combination with a preset grid division strategy, and a discretized grid is obtained; according to the material attribute of the device, carrying out physical attribute binding on each grid point in the discretized grid to obtain a material definition result of the discretized grid; respectively carrying out conventional conductive type doping and component doping on the device to obtain spatial variation doping distribution of the device; combining a preset composite model and a preset mobility model to obtain a physical model set of the device; and a Poisson equation and a carrier continuity equation are solved in combination with numerical values, and a Gummel curve of the variable-component SiGe HBT device is obtained. According to the method, the actual current-voltage characteristics of the device can be accurately reflected, and the core requirement of high-precision simulation is met.

The invention discloses a method and device for supporting multi-radar high-resolution networking and a storage medium, and relates to the technical field of radar data processing. The method comprises the following steps: determining a space range of a networking field; according to the spatial range and the target resolution, defining a grid structure of a networking field data body; allocating computing resources for high performance computing; aiming at each radar, pre-calculating a mapping area of the detection range of the radar in the grid structure; loading the original polar coordinate observation data of each radar into the computing resource in parallel; solving a networking value of each grid point in the grid structure layer by layer based on the mapping region and original polar coordinate observation data, and generating a networking result; and post-processing and storing the networking result, and releasing the computing resources. According to the method, the solution is directly solved from the original polar coordinate observation data based on the mapping region, so that the generation and conversion of massive intermediate data are avoided, and the technical bottleneck of huge memory and video memory consumption is fundamentally solved.

A wireless communication system for enhanced reliability of wireless communication and reducing peak power in wireless data transmission across different waveforms comprising transmitter modules coupled to waveform modulators including waveform two-dimensional resource or data grids representative of a signal processing domain for transmitting data bit bearing symbols across varied waveforms under controlled sparsely / partially loading of fewer modulated data symbols of the available grid points of a larger two-dimensional resource or data grid for transmission as spaced fewer data symbols with loading zero symbols at remaining empty grid points. The modulated data symbols under controlled sparsely / partially loading including said fewer modulated data symbols being allocated in the resource or data grid and distanced there between based on a factor for partial loading and full number of symbols accommodable in the resource or data grid to reduce cross interference amongst symbols and minimize error rate.

The invention belongs to the field of robot safety, and discloses a robot arm grabbing planning confrontation attack method based on solution space barrier setting, and the method comprises the steps: S1, carrying out the multiple grabbing simulation of a robot, and recording the path sequence of an end effector during the execution of each time; s2, generating a three-dimensional thermodynamic diagram capable of representing robot path preference based on the path sequence; s3, discretizing the three-dimensional thermodynamic diagram into a three-dimensional grid; s4, calculating a reachable score from each grid point to the target grid point based on the three-dimensional grid; and S5, constructing a multi-objective optimization model based on the reachable score, and optimizing the multi-objective optimization model to obtain an optimal obstacle set. The method fundamentally solves the problems of low efficiency and low success rate caused by blindness in the prior art. According to the method, a strategy for achieving an attack purpose by using a minimum, minimum and most hidden obstacle combination can be found, so that the defects of high cost and high risk in the prior art are essentially solved.

The invention relates to the technical field of electromagnetic field numerical values, and discloses a grid generation method, an electromagnetic simulation method, a device, equipment, a medium and a product, and the method comprises the steps: extracting a plurality of feature points from a metal geometric model, the plurality of feature points being used for representing key points enabling an electromagnetic field to generate singular behaviors in the metal geometric model; determining the maximum grid step length according to the shortest wavelength and the longest side of a bounding box of the metal geometric model; the minimum grid step length, the grid encryption area, the encryption step length and the grid smoothing factor are determined, the encryption step length is the grid step length of the grid encryption area, and the grid smoothing factor is used for representing the change rate between every two adjacent grid step lengths; and according to the plurality of feature points, the maximum grid step length, the minimum grid step length, the grid encryption area, the encryption step length and the grid smoothing factor, generating a plurality of grid points so as to divide the metal geometric model into a plurality of grids. According to the method, the calculation efficiency and the result precision of the FIT algorithm can be effectively improved.

The invention provides an unmanned aerial vehicle path planning method and system based on a wind field and artificial potential field coupling method, and belongs to the technical field of unmanned aerial vehicle path planning. Constructing a two-dimensional grid chart for the target area, calculating the gradient of grid point air pressure based on air pressure data to obtain a simulated wind field, and initializing a sampling space based on environmental data and establishing an artificial potential field; random sampling is carried out in the sampling space, the growth direction of next expansion of a random tree is controlled based on the coupling force of the simulated wind field and the artificial potential field, and new nodes are generated in the direction of the random tree; performing collision inspection on the generated new nodes; and backtracking from the last sampling point around the target point to the starting point to determine a path, and pruning and smoothing to complete path planning. The sampling direction is guided through coupling of a wind field and an artificial potential field, so that the consumption of flight energy is reduced.

The invention relates to a gravity background field construction method based on iterative optimization Kriging. The method comprises the following steps: S1, obtaining in-situ gravity measurement data as a known point set; s2, based on the known point set, performing preliminary interpolation on grid points of the gridding background image by adopting a Kriging method to obtain a Kriging estimated value of each grid point; s3, by introducing a local gravity anomaly covariance and a Kriging variation function, evaluating the random uncertainty of a Kriging estimated value in an interpolation process, and dividing each grid point into a reference point and a point to be corrected based on the random uncertainty; and S4, combining the reference point and the known point set to construct a continuous distribution constraint curved surface, carrying out local continuity correction on the continuous distribution constraint curved surface based on the obtained reference point, and carrying out iterative expansion on the basis of the corrected local constraint curved surface until the continuous correction of the whole continuous distribution constraint curved surface is completed. And the construction of the gravity background field is realized.

The methods may include obtaining a frequency-domain seismic wavefield associated to grid points and organized into slices. Each slice is organized into a sequence of overlapping windows. The methods may further include, for each slice, determining a value of a first intermediate function using the frequency-domain seismic wavefield for each grid point in a first overlapping window, determining a value of the first intermediate function using the frequency-domain seismic wavefield for each incremental grid point in each n-th overlapping window, where n is an integer greater than one, and determining a value of the first intermediate function by selecting the previously-determined value of the first intermediate function for each common grid point in each n-th overlapping window. The methods may still further include determining, using a second intermediate function, a Radon-transformed seismic wavefield using the value of the first intermediate function for the grid points. A non-transitory computer-readable memory and systems are also disclosed.

The application discloses an error compensation method for compensating distance work accuracy of an industrial robot, and comprises the following steps: obtaining actual grid point distance error and grid center point distance error according to nominal grid point distance, nominal grid center point distance, actual grid point distance and actual grid center point distance; optimizing grid point first weight and grid point second weight according to the introduced distance error weight adjustment factor under the corresponding grid in the unit of grid to obtain a comprehensive weight; obtaining sample point distance error by interpolation using the actual grid point distance error and the comprehensive weight; decomposing the sample point distance error in the nominal direction to obtain the position error of the sample point in the nominal direction; converting the position error into joint angle error through inverse solution; and compensating the joint angle error into a teach pendant to complete the compensation. The application overcomes the shortcoming that the calibration effect is limited by the openness of the controller, avoids the error caused by coordinate system conversion, and expands the calibration range to a certain extent.