137 results about "Regular grid" patented technology

The invention relates to the technical field of marine surveying and mapping and submarine topography modeling, and discloses a submarine topography and landform construction method based on multi-source water depth data fusion, which comprises a multi-source data acquisition module, a data preprocessing module, a feature extraction module, a fusion algorithm matching module, a three-dimensional modeling module and an uncertainty evaluation module. A historical submarine topographic map is converted into grid data, namely, submarine topography is discretized into digital representation of regular grid units, water depths of other sources are converted into the grid data, the precision of the water depths of different sources is evaluated by adopting a superposition comparison method, and an error distribution model is established to reasonably correct and fuse the water depth data of various sources. The innovation of the method lies in that topographic feature parameters including the gradient, the curvature matrix and the bionic optimization algorithm are introduced, the defect that a single algorithm is preset in a traditional method is overcome, and the precision of coral reef and fault zone complex areas is improved.

The invention discloses an infrared bidirectional thermal effect simulation method based on radiation and GPU acceleration, and belongs to the field of thermal radiation simulation and parallel computing. Dispersing the complex geometry into patch units, constructing an inter-patch radiation energy balance equation based on a radiance theory, and iteratively solving the final temperature of the patches through a radiance method; a three-level parallel strategy of a task level, a data level and an instruction level is designed, data intensive tasks such as shape factor calculation and radiance iteration are migrated to a GPU to be executed, data storage is optimized in combination with a structure array (SoA) layout and a sparse matrix compression technology, and efficient data sharing of a CPU end and a GPU end is achieved through a CUDA zero copy technology. According to the method, the dependence of a traditional method on regular grids is broken through, the calculation efficiency and precision of million-level surface patch heat radiation transmission in a complex scene are remarkably improved, and an efficient tool is provided for heat radiation indirect transmission calculation and a global illumination model in the field of three-dimensional scene infrared simulation.

The invention relates to the technical field of wafer testing, in particular to a wafer testing result visualization method and system. Through spatial discretization processing, continuous physical coordinates of test points are mapped to a fixed N * N regular grid, and mass and disordered coordinate points are classified into limited and ordered grid units through the conversion, so that the complexity of data positioning is reduced from O (n) to O (1). When rendering is carried out, a system can directly access grid data at any position through simple coordinate transformation without traversing all test points based on a data structure established on the basis of the regular grid. More importantly, the rendering mode is dynamically selected and drawn, so that the rendering calculation amount of the system does not depend on the total amount of test points any more, but depends on the number of grids in the current viewport. And the processing object is fundamentally optimized from a'test point 'to a'viewport inner grid', so that the data processing and rendering efficiency is greatly improved.

The embodiment of the invention provides a rail transit 3D data defect detection method and system based on spatial indexing, and the method comprises the steps: collecting rail 3D original data, carrying out the preprocessing, and unifying the data into a unified rail coordinate system; dividing the preprocessed track 3D data into a plurality of regular grid units as space units according to spatial positions, extracting multi-dimensional features of data in each space unit, establishing a composite index for each space unit, and storing the composite index in a space-time database; after the acquired 3D data of the current track are subjected to identical processing, spatial position areas corresponding to the 3D data of the current track and historical data are quickly matched through a composite index, and a difference value of multi-dimensional features is calculated; dynamically adjusting the defect judgment threshold of each dimension according to the statistical distribution of the difference values, judging the defect type and severity of the region meeting the threshold, and generating a detection report. The problems that traditional 3D data processing is low in efficiency and long in comparison time consumption are solved.

The invention provides a geological disaster risk assessment data processing method and system, and relates to the technical field of geological disasters, and the method comprises the steps: obtaining original observation data of an assessment region, and generating a plurality of error measurement indexes according to the original observation data; mapping the original observation data and the error measurement index to a regular grid to obtain a grid field, and constructing a geographic analysis block; constructing disaster-causing state variables based on the geographic analysis blocks, executing spatial adjacency consistency check, and if adjacent geographic analysis blocks are located in the same influence area and the KL divergence of the corresponding disaster-causing state variables is smaller than a probability target value, merging the adjacent geographic analysis blocks into a comprehensive risk block; elevation deviation caused by terrain shielding of a digital elevation model, spatial interpolation uncertainty caused by sparse rainfall stations and distortion caused by atmosphere and decoherence interference on InSAR deformation are converted into quantifiable error measurement indexes, and the accuracy of risk assessment is improved.

A rock burst risk dynamic assessment method based on a Bayesian method comprises the steps that a stope working face is divided into M * M regular grids, and each grid serves as an independent assessment unit; collecting geological and mining data, selecting a plurality of influence factors based on historical data and expert knowledge, and quantifying the plurality of influence factors by adopting a static evaluation model; determining weights of a plurality of influence factors by using an analytic hierarchy process, and calculating an initial risk score of each evaluation unit by using a comprehensive index method; normalizing the initial dangerousness score into prior distribution by adopting an S-type function, and constructing an initial dangerousness prior probability field; a power law attenuation model is introduced to calculate influence weights among the evaluation units, and an influence weight matrix is constructed; real-time monitoring data are obtained through a micro-seismic monitoring system, the risk probability of each evaluation unit is updated in real time based on the Bayesian theorem, and dynamic evaluation and evaluation result output are achieved. According to the method, the accuracy and the real-time performance of rock burst risk assessment can be effectively improved.

The application discloses a cliff three-dimensional modeling method and system based on structure surface constraint, relates to the technical field of three-dimensional geographic information systems, collects cliff regional geological data including cliff multi-view images and cliff surface dense point cloud data, and constructs a geological prior knowledge base; image recognition technology is used to process the cliff multi-view images, combined with point cloud geometry analysis, to identify the spatial orientation of structure surfaces including rock layer interfaces and joint surfaces. The application effectively solves the geometric distortion problem of traditional digital elevation models in cliff regions by fusing geological prior knowledge, uses image recognition technology to extract the spatial orientation of rock layer interfaces and joint surfaces, and uses the spatial orientation as a hard constraint condition to construct a control triangular net framework, thereby avoiding the forced smoothing error of a regular grid DEM and the overhanging surface problem of an irregular triangular net, and through an adaptive triangular division algorithm, the rock layer structure, crack distribution and dangerous rock body shape of the cliff can be accurately restored.

The application discloses a three-dimensional space field prediction method and device based on a large model and data compression, equipment and a medium, and relates to the field of space field prediction. The method comprises the following steps: simulating to generate a dynamic three-dimensional space field data set of each irregular grid under different boundary conditions, mapping the irregular grid to a regular grid, and compressing the dynamic three-dimensional space field data by using a down-sampling method; constructing a training set according to the three-dimensional space field compressed data and the boundary conditions and the three-dimensional space field compressed data at a next historical moment, thereby training a large model pre-training network, the network combines a 3D convolutional neural network and an auto-encoder structure, and a three-dimensional space field prediction large model is obtained; and the model is applied to predict the three-dimensional space field distribution at a future moment. The application can accurately and efficiently predict a three-dimensional space field.

The invention relates to a space laser radar forest structure data correction method and system, and belongs to the technical field of space laser remote sensing and forest resource monitoring. Aiming at four kinds of errors of geometric positioning offset, slow distortion, terrain broadening effect and canopy structure influence of GEDI data, UAV control points are arranged by adopting a hierarchical arrangement strategy, a homonymy point relation is established through waveform registration, and weights are calculated; performing overall geometric correction based on the regular grid control points; carrying out local distortion correction based on the encryption control point; establishing a physical compensation model to compensate the terrain broadening effect; based on the canopy structure parameters and GEDI signal quality indexes, establishing a statistical regression model to correct a canopy height residual error; and finally, obtaining a high-precision canopy height convergence result through spatial smoothing processing, and outputting corrected data. The method achieves step-by-step precision improvement from the whole domain to the local domain and from the geometry to the height, and is low in cost, high in precision and wide in application range.

The invention discloses a neutral atmosphere refractive index calculation method and system suitable for different heights, and belongs to the technical field of communication and navigation. During modeling, monthly average reanalysis data is used as input to calculate the three-dimensional refractive index field of the neutral atmosphere, and horizontal, vertical and time domain change characteristics of the refractive index are represented by adopting a regular grid, a third-order index and a trigonometric function; when in use, the refractive index of any target point at any time within a global near-surface space range of 85 km can be calculated through space-time interpolation and elevation normalization only by giving the longitude, latitude, geodetic height and simplified Julian day of the target point. According to the method, the empirical modeling of the global neutral atmosphere refractive index field is realized by utilizing reanalysis data for the first time, the refractive index calculation precision at different height positions is improved through third-order index elevation normalization, and the method has important application value in the communication and navigation fields such as electromagnetic wave signal propagation path simulation and neutral atmosphere delay calculation correction.

The invention discloses a wind field quality control method based on a single moment image structure, which comprises the following steps of: converting original wind direction and wind speed data into U and V wind components, and interpolating the U and V wind components and wind direction site observation data into regular grid data; adopting a curvelet decomposition method to decompose the grid-processed wind field data into two parts, namely a main term and a remainder term taking random change as a main term; for U and V wind speed and wind direction data, calculating a spatial gradient of a target grid point by using the main item data after curvelet analysis, and judging that the grid point with the gradient greater than a preset gradient threshold value is abnormal; performing progressive quality control for multiple times to identify discontinuous abnormal values in the main item; after main term curvelet analysis is completed, curvelet decomposition is carried out to obtain remainder term data, an abnormal threshold value is set, and a wind field area is divided into a weak rotating wind area and a strong rotating wind area; the quality control method is suitable for high-intensity weather system influence.

The application provides a variable-grid three-dimensional longitudinal wave equation forward numerical simulation method, and the numerical simulation method comprises the following steps: S1, establishing an irregular grid division strategy; S2, under the irregular grid division strategy, constructing a regular grid function relationship in a Cartesian coordinate system; and S3, performing forward numerical simulation according to the regular grid function relationship. The method reduces the number of grid units and ensures the forward simulation precision, and realizes an efficient and high-precision variable-grid forward simulation method.

The present application relates to the technical field of marine engineering digital twin and three-dimensional visualization technology field, provide a kind of based on right triangle grid's dredging topography twin's generation method and system, comprising: obtaining regular grid elevation or sampling height data after pre-processing that have been unified to engineering plane coordinate system, determine the space range covered read space range and density parameter, based on space range and total row number and total column number of calculated grid;In the space covered, generate regularly arranged vertex, construct the topological structure of isosceles right triangle grid;With vertex as unit, several Chunk blocks are divided into global grid with fixed size, establish the triangular index mapping relationship of global row and Chunk block, the three vertices of isosceles right triangle and elevation or height data are filled in each Chunk block in parallel, generate local VBO, IBO and AABB;Batch rendering and coloring according to height color table are executed to all Chunk blocks, and the visualization of topography is realized.

The invention discloses a multi-source-driven CO2 concentration high-temporal-spatial-resolution prediction method based on a dynamic diffusion model, and the method integrates the satellite observation of OCO-2, GOSAT and the like, ERA5 meteorological data, vegetation index NDVI, population activity and other characteristics on the basis of DCRNN, and achieves high-precision prediction through physical prior and a dynamic graph structure. The method comprises the following steps: unifying multi-source data to a regular grid; an adjacent matrix is dynamically generated based on the geographic position and the wind field to serve as the input of the improved DCRNN, and the diffusion relation of COs in the wind direction is described; multi-source node features are input into the improved DCRNN, and physical constraints such as mass conservation and convection consistency are introduced to improve the reliability of a result; a graph-to-grid decoding and super-resolution technology is adopted to reconstruct prediction to a higher resolution level by level, and pixel-level uncertainty can be output. According to the method, multi-source observation and meteorological driving information are fully utilized, the satellite observation blank is effectively supplemented, the fineness and continuity of a COconcentration product are improved, and the method is suitable for carbon emission accounting, carbon source and sink evaluation and environmental decision support.

The invention provides a channel gain map reconstruction method based on a k-nearest neighbor refined neural network, relates to the technical field of wireless communication, and has the technical key points that the invention provides a two-stage CGM reconstruction framework under a sparse regular grid sampling condition, and in the stage 2, local learning is carried out during query to refine prediction, so that explicit decoupling and robust extrapolation are realized. K nearest neighbors are selected from a total sample by adopting a global k nearest neighbor thought which is not constrained by a clustering boundary, spatial continuity is preferentially utilized, and k nearest neighbors in a cluster which can be used as a contrast are selected only in the same cluster. The whole process does not depend on LoS / NLoS labels or high-cost environment prior, the CGM can be reconstructed only by regular grid sampling measurement, and high-precision benefits are kept under different sampling interval values d and k. On the premise of not increasing expensive measurement and label cost, the MSE of CGM reconstruction is obviously reduced.

This invention relates to a method and system for optimizing coating trajectory to ensure uniformity of spacecraft coating thickness. The method includes: acquiring a model of the surface to be coated, generating a regular grid initial coating curve and setting constraint parameters; mapping the curve to a complex surface using a pseudo-projection algorithm, and generating a fully covered, non-intersecting initial trajectory after trajectory correction; based on an experimentally calibrated coating deposition model, constructing a multi-objective optimization function that minimizes coating thickness deviation while considering trajectory smoothness and operation time, using trajectory waypoint coordinates, coating gun attitude quaternions, and coating segment duration as optimization variables, and applying constraints such as coating distance, velocity, and attitude; using an interior-point solver for iterative optimization, limiting variable iteration deviations to ensure model accuracy; and outputting an directly executable optimized trajectory. This invention can automatically adapt to the coating requirements of complex surfaces, significantly improve coating thickness uniformity, control deviations within the allowable range of aerospace processes, and effectively improve operational accuracy and efficiency.

The invention discloses a scanning magnet beam calibration method and related equipment, and relates to the technical field of radiotherapy, and the method comprises the steps: selecting a plurality of feature points in a target radiation field range, and enabling the feature points to jointly form a regular grid covering the radiation field; the regular grid comprises at least one grid unit; for each feature point, obtaining a current value pair of the feature point which enables the deviation between the actual position and the theoretical position of the beam to be within a preset range; and for any target point in the radiation field, according to the current value pairs of the feature points, the control current of the target point is calculated through a bilinear interpolation algorithm, and high-precision and high-uniformity beam calibration of the whole field of the scanning magnet is rapidly achieved by combining a small amount of precise measurement with intelligent interpolation calculation.

In various examples, optimized cluster templates (e.g., template triblock data, template CLASes or some portion thereof such as template range data, etc.) are precomputed for various patterns of triangle clusters (e.g., regular grids and / or irregular meshes of various edge resolutions) and corresponding compression levels. For example, optimized range assignments may be computed by iteratively generating candidate range assignments using different strategies, evaluating each range assignment using a designated metric (e.g., a cost that estimates, models, approximates, or otherwise quantifies the anticipated time cost of traversal), and tracking the best (e.g., optimized) range assignment (or top N) for each optimized triblock layout. As such, a range assignment may be iteratively optimized for each supported pattern of triangles and corresponding compression level, and may be used to generate a corresponding cluster template.

The application relates to the technical field of games, in particular to a one-dimensional mapping positioning method for games, which comprises the following steps: collecting spatial coordinate data of game objects, constructing a regular gridded game map, and establishing a unified coordinate system; converting two-dimensional coordinates of the map into binary cross combination and decimal conversion to generate GeoHash codes suitable for the regular gridded game map; constructing a quadtree storage system, aggregating and storing the game objects in corresponding nodes according to the coding prefix association relationship, and dividing hot storage areas and cold storage areas in the nodes according to the position update frequency of the game objects; receiving a search request containing a center coordinate and a search radius, converting the center coordinate into a GeoHash code and intercepting a target prefix, optimizing the search precision by dynamically adjusting the coding prefix length, and accurately positioning the spatial position of the target game object within the search radius through multidimensional filtering and screening. The scheme can accurately position the spatial position of the game object through multidimensional screening.

This invention discloses a method and system for detecting defects in precision-diameter seamless steel pipes based on laser scanning, belonging to the field of non-destructive testing technology. The method includes: acquiring raw laser scanning data of the inner wall of the steel pipe containing distance, angle, and displacement information; constructing regular grid data through data conversion and spatial mapping; obtaining a reference cylindrical model through cylindrical fitting; performing coaxial error compensation and calculating radial residuals; expanding and correcting the residuals to generate an inner wall residual map; performing multi-scale decomposition on the inner wall residual map to obtain high- and low-frequency components; combining the two to complete defect identification and output the results. This invention solves the technical problems of coaxial error interference, difficulty in distinguishing defects from geometric deviations, and low accuracy in identifying minute defects in the inner wall defect detection of precision-diameter seamless steel pipes. It achieves accurate compensation for coaxial errors in the detection system, effectively separating the macroscopic geometric features and local defect features of the inner wall of the steel pipe, thereby meeting the technical requirements for quantitative and accurate judgment in precision testing.

The application provides a geological disaster risk assessment data processing method and system, and relates to the technical field of geological disasters, which comprises the following steps: obtaining original observation data of an evaluation area, generating a plurality of error measurement indexes according to the original observation data; mapping the original observation data and the error measurement indexes to a regular grid to obtain a grid field, and constructing a geographic analysis block; constructing a disaster-causing state variable based on the geographic analysis block, performing spatial adjacency consistency verification, and if adjacent geographic analysis blocks are in the same influence area and the KL divergence of the corresponding disaster-causing state variables is less than a probability target value, then the adjacent geographic analysis blocks are merged into a comprehensive risk block; the elevation deviation of a digital elevation model caused by terrain shielding, the spatial interpolation uncertainty caused by sparse rainfall sites, and the distortion of InSAR deformation caused by atmospheric and decorrelation interference are converted into quantifiable error measurement indexes, thereby improving the accuracy of risk assessment.

The invention discloses a mineral resource quantitative estimation method and device, computer equipment and a storage medium. According to the mineral resource quantitative estimation method, the continuous geological space is discretized into the independent analysis units through the regular grids, the feature dilution effect caused by large-area averaging is avoided, and in addition, geological analogy is converted into quantitative calculation from qualitative experience; the resource potential of each target prediction mineral product area is estimated by performing similarity matching on each target prediction mineral product area and a known mineral deposit in a high-dimensional feature space, so that the analogy process is more objective, standardized and repeatable, and the problems of strong subjectivity, high limitation and weak estimation accuracy of a traditional method are solved. Traditional resource quantity evaluation often provides a single estimated value which is difficult to reflect the internal uncertainty, but according to the method, probability distribution data of the resource quantity is finally generated through multiple sampling calculation, and the core requirement of modern mineral exploration investment decision on risk-income evaluation is met.

The invention belongs to the field of building photovoltaic technology, and particularly relates to a roof column arrangement method based on grid matrix and boundary adaptation, and the method comprises the steps: 1, building a roof geometric model which comprises a main body polygon and an obstacle set; 2, performing gridding discrete processing on the roof area to generate a regular grid array; step 3, performing intelligent obstacle detection and boundary feature recognition on each grid unit, wherein the obstacle detection supports unified processing of common polygonal obstacles S4 and composite structure obstacles; 4, generating an optimal scanning axis based on boundary constraint and an obstacle avoidance strategy, wherein the scanning axis comprises a longitudinal axis and a transverse axis; 5, generating a stand column point location, performing settable test on an axis intersection point, and performing intelligent compensation on a position which does not meet the condition; and 6, executing multi-scheme evaluation and optimization, and automatically selecting an optimal arrangement scheme based on a comprehensive evaluation index.

The invention provides a water-cooled wall temperature field reconstruction method based on a tube panel heat transfer network model, which comprises the following steps of: obtaining a geometric structure of a water-cooled wall tube panel, and mapping the water-cooled wall tube panel into a two-dimensional regular grid according to computational nodes; establishing a heat balance equation corresponding to the node according to the heat transfer data and the equivalent heat resistance; synthesizing the heat balance equations corresponding to the computational nodes of the upper actual installation measuring points of the water wall tube panel into linear equations, and representing the linear equations as a solution matrix; temperature measurement data are used as boundary conditions to be implanted into the solution matrix; solving the solving matrix according to a preprocessing conjugate gradient method; and mapping the temperature values in the vectors obtained by solving back to the geometric structure of the water-cooled wall tube panel according to node coordinates, and outputting a temperature field data set of the water-cooled wall tube panel. According to the method, the physical structure of the water wall tube panel is abstracted into the regular heat transfer network, the node-level linear equation is established based on the heat balance principle, and the whole-field temperature distribution of the water wall is reconstructed only through existing sparse measuring points.

The application discloses a method for applying seven-grade anomaly division method to medium-large scale geochemical exploration data, and comprises the following steps: step S1: the point position of the discrete data of the medium-large scale regional investigation is generally not located at the center position of the regular grid, and the average value gridding interpolation can be adopted to make the data points be distributed on the grid center; step S2: the WIG, Al2O3 / TiO2 and K2O / SiO2 three parameters of the 1:200,000 geochemical exploration data of the research area are calculated to obtain the three parameters of the 1:200,000 data; step S3: the nearest point gridding interpolation is performed on the three parameters of the 1:200,000 data according to the above-mentioned regular grid of the medium-large scale, so that the data gridding densities of the two are same; and step S4: the two kinds of grid data are matched, and then the seven-grade anomaly division method is used to determine and grade the evaluation of the medium-large scale geochemical exploration data; the problem that the medium-large scale geochemical exploration data lacking of background values can also use the seven-grade anomaly division method to determine and grade the evaluation is solved.

The application belongs to the technical field of water supply network risk analysis, and discloses a water supply network risk probability prediction model building method fusing multi-source data, which obtains water supply network data of a target area and classifies open source map data, then combines spatial buffer analysis and priority rule determination to realize extraction of external environment characteristics; then rule grid units are constructed within the spatial range of the water supply network, the maintenance spatial density of each grid unit is calculated, and the maintenance spatial density of the grid unit is mapped to each pipe section according to the maintenance spatial density, so that the extraction of the maintenance spatial density characteristics is realized; finally, the machine learning risk prediction model is constructed by integrating the pipe network itself attributes, external environment and maintenance spatial density characteristics, and the risk probability of the pipe section level is directly output. The application fuses open source map data spatial analysis, fault point density clustering and integrated learning prediction, and is suitable for risk probability prediction, high-risk pipe section identification and preventive maintenance decision support of urban water supply networks.

The application discloses a UAV multi-modal image registration method and device, medium and product, relates to the technical field of remote sensing image processing and computer vision, and comprises the following steps: calculating the normalized mutual information value of each wave band of the image to be registered and a reference image, selecting a wave band with the maximum value as a reference wave band, solving a global affine transformation matrix by using an enhanced correlation coefficient algorithm, performing global geometric coarse correction, and obtaining the image to be registered after coarse registration; calculating the local principal direction of the image to be registered after coarse registration and the reference image, constructing a Gaussian derivative filter, extracting structural features based on the turning theorem, generating respective structural feature maps and dividing the structural feature maps into regular grids, performing grid-by-grid template matching to obtain a sparse displacement field, performing outlier elimination and interpolation smoothing to generate a dense linear deformation field, performing nonlinear geometric correction and applying the dense linear deformation field to all wave bands of the image to be registered after coarse registration, and obtaining a final registration result. The application realizes high-precision registration of multi-modal images.

The invention discloses a multi-mode esophageal cancer identification method and system based on frequency characteristics, and relates to the technical field of medical image processing, and the method comprises the steps: synchronously collecting a photoacoustic echo sequence, a shear wave elastic displacement sequence and an optical coherence tomography image sequence, and packaging the sequences into a homologous frame index data set according to a frame index number; a frequency event graph with unit numbers as nodes is constructed according to the regular grid adjacency relation of the frequency unit graph, homonymous coupling judgment and axial propagation continuity judgment are carried out on the three-mode frequency event sequence of each node, and a suspected lesion unit set and a connected component identifier are obtained. According to the method, the homodromous coupling judgment and the axial propagation continuity judgment are carried out on the multi-modal frequency event sequence of the nodes on the graph, the abnormal sites with the multi-modal frequency characteristics in collaborative change are screened out from massive units, the false positive caused by random noise or isolated abnormality is eliminated, and the recognition specificity is remarkably improved.

The application discloses a cross-dimension multi-source satellite altimeter sea level anomaly joint estimation method and system, and relates to the field of ocean remote sensing.The joint estimation method comprises the following steps: obtaining multi-source observation data of a target sea area about a target period, forming a corrected joint observation data set through cross-dimension data processing and reconstruction operation and bias correction operation, and mapping the corrected joint observation data set to a corresponding regular space-time grid of the target sea area; based on a preset space-time search radius, constructing an observation operator, a background covariance matrix and an observation error covariance matrix corresponding to each grid point in the regular space-time grid, and generating a regular gridded sea level anomaly product of the target sea area about the target period through an optimal interpolation method without performing explicit system error correction.The application can consider large-scale background consistency and small and medium-scale structure resolution capability on multiple spatial scales, and improves the spatial continuity, statistical consistency and overall stability of the sea level anomaly estimation result.

The invention provides a road side perception abnormity real-time detection method and system based on a regular grid, and the method comprises the steps: carrying out the preprocessing of given map data and monitoring region data in road test perception data, and the road test perception data, and obtaining a preprocessed road test perception data sequence; performing anomaly detection on the pre-processed drive test perception data sequence by using a rule network composed of 18 types of meta rules, and obtaining a detection result sequence; according to the detection result sequence, performing quality index calculation by using a K-means algorithm, and obtaining a quality grade set; and performing anomaly tracing on the anomaly detection sequence by using the quality level set to obtain an anomaly tracing result. According to the method, the rule network formed by 18 types of meta rules is adopted to perform anomaly detection on the preprocessed perception data sequence, comprehensive identification of abnormal events in various scenes is realized, the coverage rate of anomaly detection is improved, and the real-time performance and high efficiency of the detection process are ensured based on the design of a regular grid structure.