59 results about "Grid analysis" patented technology

The invention provides an operation optimization method and system based on electric power data conjoint analysis, and the method comprises the steps: obtaining synchronous sampling data and power grid topological parameters of a wide-area electric power system; performing equipment state evaluation, broadband resonance traceability and harmonic responsibility quantification on the synchronous sampling data and the power grid topological parameters by using a conjoint analysis engine, and generating a power grid control strategy; and carrying out operation optimization on the power equipment in the wide-area power system based on the power grid control strategy. According to the method, conjoint analysis is carried out on equipment state evaluation, broadband resonance traceability and harmonic responsibility quantification of the wide-area power system, traditional static spectrum analysis is upgraded to dynamic behavior perception, the power grid analysis depth and accuracy can be improved, the high-frequency harmonic analysis requirement can be met through broadband resonance traceability, and the method is suitable for large-scale popularization and application. Intelligent analysis can be realized for different application scenes, the waveform analysis capability and the frequency response range are improved, and the analysis effect is improved.

The invention discloses an unmanned aerial vehicle swarm distributed array antenna scattering characteristic analysis method, which comprises the following steps: obtaining infinitesimal dipole model parameters through geometric parameter equivalence of a single unmanned aerial vehicle, and calculating an initial excitation coefficient of each unmanned aerial vehicle; correcting the initial excitation coefficient of each unmanned aerial vehicle to obtain an unmanned aerial vehicle feature weight coefficient; constructing an attitude relation correction mutual coupling coefficient in an ideal state through translation and rotation when the configuration of the unmanned aerial vehicle array is changed; constructing a mutual coupling matrix, and obtaining an in-matrix excitation coefficient of each unmanned aerial vehicle under the consideration of a mutual coupling effect; and constructing and solving a balance equation, calculating an actual excitation coefficient considering a mutual coupling effect, calculating a total scattering field of the unmanned aerial vehicle array, and obtaining a radar cross section of the unmanned aerial vehicle array. According to the invention, the scattering characteristic analysis during the change of the array configuration of the unmanned aerial vehicle is realized, the problem of complex model scale in grid analysis is avoided, and the analysis efficiency is improved.

The invention provides an ultra-thin coal seam collapse early warning system based on multi-field dynamic analysis and an optimization method thereof, and aims to carry out fusion and deep analysis on data by monitoring a plurality of physical data such as a temperature field, a confining pressure field and a gas field in a coal seam in real time and combining a parallel multi-grid analysis algorithm and an LSTM time sequence analysis technology so as to realize early warning of the collapse of an ultra-thin coal seam. Therefore, early warning of the ultra-thin coal seam collapse disaster is realized, and the safety of coal mine production is ensured. The system is composed of a monitoring sensor network, a data acquisition module, a data fusion and analysis module, an early warning decision module and a display and alarm module, can dynamically predict the dangerous state of a coal seam according to multi-field coupling data, and sends out an early warning signal in time when an abnormality is found. By accurately arranging the sensors and adopting an efficient multi-grid algorithm and a powerful LSTM analysis model, the system can realize intelligent monitoring and accurate early warning of the safety state of a coal mining area in a complex environment, and the safety and intelligent level of coal mine production are greatly improved.

The invention discloses a surface feature information extraction method based on a hyperspectral and high-resolution remote sensing image, and relates to the technical field of remote sensing. The method comprises the following steps: acquiring a hyperspectral and high-resolution remote sensing image, and preprocessing the hyperspectral and high-resolution remote sensing image; cutting and fusing the preprocessed image to obtain a fused image; performing spectral analysis and wave band screening on the fused image to obtain first image data; performing image enhancement processing on the first image data to obtain a plurality of grayscale images; performing wave band synthesis on the plurality of grayscale images, and performing grid analysis and wave band screening to obtain second image data; performing threshold segmentation on the second image data, and performing grid surface turning to obtain a first vector; obtaining DEM data in a preset elevation range of the research area, and performing grid surface turning to obtain a second vector; and cutting the first vector according to the second vector to obtain a distribution vector result. According to the method provided by the embodiment of the invention, the extraction precision and reliability can be effectively improved.

The invention provides an autonomous exploration method and device for an indoor mobile robot. The method comprises the following steps: performing pose estimation on the indoor mobile robot based on point cloud data and sensor data fusion; processing the point cloud data by adopting a method of combining fan-shaped projection and binary Bayesian filtering, carrying out environment modeling and constructing a lightweight grid map; according to the environment information on the lightweight grid map, utilizing a ray edge grid analysis method, a Bayesian inference edge grid intersection segmentation method, a leading edge region segmentation method and a viewpoint sampling and evaluation method to detect a leading edge region of the explored region and segmenting the leading edge region into a plurality of sub-regions; generating an optimal viewpoint of each sub-region; exploring an unknown environment by using the optimal viewpoint and adopting a hierarchical exploration strategy combining global exploration and local exploration to obtain a planned path; and according to the planned path, generating a navigation trajectory by adopting a method of combining multi-constraint trajectory optimization and nonlinear model predictive control.

The invention belongs to the technical field of gas pipelines, and particularly relates to a gas engineering construction quality evaluation system based on big data, which comprises the following steps of: firstly, constructing a defect feature tensor, introducing a space-time grid analysis technology to analyze defect disposal aging interval data and location defect reproduction frequency data, and constructing a defect feature tensor on the basis of a preset quality-efficiency reliability quantification rule; defect features are converted into quantifiable quality-effect scores, then deep fusion of multi-source heterogeneous data is achieved by establishing a space-time incidence matrix of welding defects, welding process parameters and environment monitoring parameters, and on this basis, a fuzzy correlation analysis technology and a preset process compliance quantification rule are adopted to achieve quality-effect evaluation of the welding defects. Complex process parameters and environmental conditions are converted into quantifiable process scores, the process scores and quality-effect scores are integrated to generate a gas pipeline welding quality comprehensive evaluation value of a target contractor, and a quantifiable intelligent decision support system is provided for gas pipeline construction quality management and control of the contractor.

According to the automatic production line digital model hole filling method and device provided by the embodiment of the invention, the to-be-processed area is accurately identified through multi-level grid analysis and curvature field calculation. A patch generation mechanism based on density clustering and a neural network is innovatively designed, and intelligent filling optimization is realized in combination with local geometric features. According to the system, non-uniform rational basis spline surface reconstruction and a Laplacian grid smoothing algorithm are adopted, continuity and fairness of a filling area are ensured, and the system is closely combined with motion control and path planning of an automatic production line. According to the method, the limitation of traditional model repair is broken through, and an efficient and reliable solution is provided for integrity reconstruction of the industrial digital model.

The invention discloses an electrified railway contact line icing influence analysis method, which comprises the following steps of: obtaining key parameters such as a collision coefficient and a freezing coefficient of a water drop and a contact line in an icing calculation process by analyzing a line surrounding flow field of an overhead line system and researching heat balance of the surface of the contact line; and meanwhile, carrying out grid analysis on environmental parameters and icing boundaries so as to establish a time-varying meteorological numerical model of the contact line. By means of a contact line icing numerical model, the influence of the temperature (T), the liquid water content (LWC), the median volume diameter (MVD) and the wind speed (Vp) on contact line icing evolution is analyzed through a control variable method. Therefore, an important basis is provided for contact line icing prediction, ice prevention and ice removal in the future.

The invention relates to the technical field of tourism information service, in particular to a route guiding system for scenic spots based on urban and rural cultural tourism big data, which is characterized in that gate traffic volume and connection vehicle positioning data are acquired, tourist tracks are mapped to grid units, high-traffic areas are screened, and capacity and route integrating degree is evaluated. And sorting the culture similarity, the arrival interval and the element density, dynamically adjusting a gradient value, and combining an explanation point and scheduling data to generate a scheme. According to the method, the gate traffic volume, connection vehicle positioning and tourist trajectory data are integrated, a dynamic thermodynamic diagram is generated through gridding analysis, the passenger flow gathering area is recognized, and the response speed is increased. And dynamically matching the subject weight based on the traffic volume and the residence density difference value, and generating a diversion list of linkage of the deviation area and the resources. And constructing a route cluster adaptive to azimuth angle deviation by combining the dispatching capacity of the connection vehicle with the culture attribute similarity, and optimizing the transport capacity and culture experience collaboration.

The invention provides an analysis alarm video monitoring platform for wind power generation equipment, and relates to the technical field of video monitoring, the video monitoring platform comprises a real-time picture acquisition module, a historical picture acquisition module, a gridding division module, an analysis module and an alarm generation and management module, the video monitoring platform is also provided with a three-level architecture, the three-level architecture comprises a group headquarter unit, a province unit and a basic level unit. According to the method, after the alarm is triggered through grid analysis, the current / historical picture data is automatically associated, and the alarm event with the grade is generated by means of the event playback function, so that the false alarm caused by environmental interference is greatly reduced, and the alarm accuracy is improved. And a current picture transmitted by the video acquisition module is obtained through a real-time preview mode, and is compared with a specified historical moment picture called from the hierarchical storage system through the intelligent index, and the historical picture is used as a contrast to judge whether an abnormality exists or not and whether alarm processing needs to be carried out or not.

The invention provides a ship pier head structure strength evaluation method, which aims at the problem that a ship bow structure is easy to damage or deform under a ship pier falling working condition, obtains an accurate rigidity coefficient of a docking block through actual measurement and conversion, and establishes a complete real ship finite element model in an evaluation range to reflect accurate mass distribution and rigidity. Coarse grid and fine grid grading evaluation is adopted, the efficiency is improved while the calculation precision is guaranteed, coarse grid analysis is used for obtaining docking block counter-force, fine grid analysis can consider actual counter-force distribution in contact with a docking block, and the yield strength and buckling strength evaluation safety coefficient of the ship bow structure is provided; the damage or deformation risk of the ship docking pier falling structure can be systematically and accurately evaluated, the ship pier falling optimization design is guided, and the ship construction period can be shortened.

This application discloses a method, system, and device for identifying target geological structures in coal seams. The target geological structures include folds, faults, lower local thickening zones, and upper local thickening zones. The method acquires full measured data of cross-layer boreholes in the target longwall face, along with the strike, dip, and true dip parameters of the coal seam. Preprocessing yields the three-dimensional coordinates of the borehole entry point, the three-dimensional coordinates of the exit point, and the true thickness of the coal seam. A square nine-grid analysis window is constructed with the strike and dip of the coal seam as the directional reference. Target cross-layer boreholes with stable coal seam thickness are selected based on the deviation of the true thickness of the coal seam. A spatial plane equation of the coal seam is established to calculate the theoretical entry point elevation of the target cross-layer borehole, generating regional target geological structure identification results. A sliding window traverses the entire longwall face, outputting the overall regional target geological structure identification results. This method can stably identify hidden small target geological structures and significantly improves computational efficiency compared to traditional methods. It can be widely applied to advanced geological exploration scenarios in coal mine longwall faces.

The embodiment of the invention provides a power distribution network load adjustment method, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring node data of a plurality of power grid nodes in the power distribution network; wherein the node data comprises current, voltage and position of each node and a power transmission relation between different power grid nodes; constructing a power grid static topological structure based on the node data, and determining power grid analysis parameters; the power grid analysis parameters comprise reactance, resistance and admittance among power grid nodes; determining the equivalent static load of the plurality of power grid nodes based on the dynamic response relationship between the power of the plurality of power grid nodes and the voltage fluctuation and the power grid transmission parameters; adjusting the loads of the plurality of power grid nodes based on the objective function, and determining the load of each power grid node according to an adjustment result; wherein the objective function represents that the sum of the power transmission efficiency and the dynamic load adjustment cost is minimized. The method is used for improving the load adjustment precision of the power distribution network.

The application relates to a WebGL-based three-dimensional local terrain protrusion weakening method, and belongs to the technical field of computer graphics visualization, which comprises terrain grid loading, loading terrain data in the form of a grid into a scene in a WebGL rendering engine, storing information in the form of a.terrain format binary file, then performing grid analysis, loading block terrain data according to a terrain level of detail strategy, analyzing terrain data, loading and analyzing downloaded binary file data according to terrain grid levels and row and column numbers, compressing the data by using a zig-zag coding method, then performing vertex height dynamic adjustment, and finally performing terrain triangular net reconstruction. The WebGL-based three-dimensional local terrain protrusion weakening method can weaken terrain protrusion problems by modifying the vertex elevation of a terrain data-free area, does not cause distortion of local high-precision terrain and models in a scene, can weaken terrain cliff problems existing in three-dimensional local terrain protrusions, and does not deform the terrain and models in the scene.

The invention is suitable for the technical field of Internet, and relates to a battery car battery replacement cabinet site selection optimization method, a medium and a terminal, the process is simple, the operation is convenient, province and city latitude and longitude administrative division, DEM data, population data and POI data are fused, comprehensive site selection is performed by integrating multiple factors, and site selection is more scientific and reasonable; dynamic grid division is carried out based on Mercator conversion, accurate division of the region is realized, and a good basis is provided for subsequent analysis; internal and external indexes of the grid are constructed, and characteristics and actual requirements of different regions are fully considered; a K-means clustering method is used for constructing a negative sample, so that the reliability and the accuracy of the model are improved; through the integration of grid analysis and Logistic and RF regression, the transformation of the site selection of the power conversion cabinet from experience driving to data driving is realized. According to the method, the problems of low efficiency, high cost and unreasonable coverage caused by the fact that a traditional battery car battery replacement cabinet site selection method depends on artificial experience are solved.

This invention relates to the field of energy control, specifically to a multi-energy collaborative intelligent microgrid control system. It includes a management center communicatively connected to a grid acquisition module, a grid analysis module, and a grid control module. The management center acquires historical energy data and historical electricity consumption data, and, combining these data, establishes an energy grid model. It then analyzes the energy grid to obtain energy region data. Based on the energy observation cycle and energy region data, it establishes a two-dimensional grid coordinate system and constructs a time-series prediction model to obtain predicted grid data. Using the predicted grid data, it constructs a predicted grid matrix and uses this matrix to regulate energy in the power region, obtaining pre-regulation strategies and optimal energy distribution points. Finally, it analyzes the pre-regulation strategies based on real-time electricity consumption and real-time power generation to obtain actual regulation strategies. This invention enhances the stability and flexibility of the microgrid.

The invention relates to the technical field of automobile production, in particular to a thickness reduction limit safety margin value calculation method. According to the method, the safety margin value is reflected as the direct influence of thickness reduction on material stamping, the problems that a traditional calculation method is obscure, difficult to understand and not visual are solved, and the safety margin value of grid analysis is better applied to stamping workshops of automobile factories. According to the method, the problem that the existing grid analysis cannot completely display the thickness reduction rate and has no safety margin value is solved, and more comprehensive analysis and control of the grid analysis on the automobile sheet stamping part are realized. The method can greatly improve the judgment accuracy of the stamping performance of the automobile sheet, meets the requirements of actual stamping production of the automobile sheet, and can ensure the precision of material selection, improve the stamping production efficiency of automobile parts and reduce the processing cost while accurately evaluating the stamping performance of the automobile sheet.

The application provides an analysis alarm video monitoring platform for wind power generation equipment, relates to the technical field of video monitoring, and comprises a real-time picture acquisition module, a historical picture acquisition module, a grid division module, an analysis module and an alarm generation and management module. The video monitoring platform is also built with a three-level architecture, which comprises a group headquarters unit, a provincial unit and a basic unit. After triggering the alarm through grid analysis, the current / historical picture data is automatically associated, the alarm event with levels is generated by means of the event playback function, the false alarm caused by environmental interference is greatly reduced, and the alarm accuracy is improved. The current picture transmitted by the video acquisition module is acquired through the real-time preview mode, and is compared with the specified historical time picture retrieved from the hierarchical storage system through the intelligent index. The historical picture is used as a reference to determine whether there is an abnormality and whether alarm processing is needed.

The invention discloses a dust multi-dimensional cloud monitoring and intelligent control system, which belongs to the technical field of environment monitoring and comprises scanning equipment, fixed monitoring equipment and dust suppression equipment. The system generates a quantized dust cloud picture by fusing the scanning distribution map and the real-time concentration value, and performs gridding analysis; performing reverse traceability on the standard exceeding points by using a reverse diffusion model, and determining a main pollution source grid; and automatically controlling the dust suppression equipment of the corresponding grid to start based on comparison between the real-time index and the threshold value. According to the invention, a monitoring blind area is eliminated, and global quantitative monitoring, accurate traceability and intelligent closed-loop treatment of dust are realized.

The present invention discloses a system for monitoring a palm tree and an oil palm fruitlet in a plantation in a lightweight and efficient manner and a method thereof. The system comprises a data acquisition module (100), a tree detection module (200), a fruitlet detection module (300), and an environment representation module (400). The data acquisition module (100) comprises a remote sensing device (101) and an image-capturing device (102) mountable to a mobility platform (103) for generating an occupancy grid map associated with the palm tree in the plantation and an image associated with the oil palm fruitlet scattered within a vicinity of the palm tree, respectively. The tree detection module (200) generates a submap from the occupancy grid map to detect the palm tree therein and determine a tree position of the palm tree detected thereof, which is transformed to a global tree position on a semantic or global map. The fruitlet detection module (300) detects the oil palm fruitlet from the image, a fruitlet position, and a quantity of oil palm fruitlets using a grid analysis and transforms the fruitlet position to a global fruitlet position. The environment representation module (400) compares the tree position against a tree tracking list using a chain-based tree-tracking and re-mapping algorithm and assigns a harvest-ready status to the palm tree based on the quantity of oil palm fruitlets detected thereof.

The invention relates to the technical field of site selection of recycling facilities, in particular to a new construction waste industrial park site selection method based on grid analysis. Comprising the following steps: determining a site selection evaluation area, an industrial park processing scale and grid unit parameters; converting the rigidity and flexibility evaluation indexes into a rasterized thematic map layer; building waste generation amount estimation, space distribution and building waste generation distribution map layer generation; performing Boolean overlay analysis on the hard indexes to obtain a primary selection range; the weight of the flexible index is determined by adopting a CRITIC method, and an alternative site selection scheme is obtained after weighted superposition analysis; and constructing a multi-objective optimization model of the newly-built construction waste industrial park, and obtaining a Pareto optimal solution set through an NSGA-II algorithm. According to the method, the generation space distribution of the construction waste and the objectivity of the index weight are comprehensively considered, the scientificity and systematicness of site selection of the construction waste industrial park are improved, and the method has good universality and popularization value.

The invention discloses a radar rainfall deviation correction algorithm based on combination of probability density matching and a climate state ratio method. The radar rainfall deviation correction algorithm comprises collection and preprocessing of ground station observation data, PDF deviation correction of radar rainfall and climate state deviation correction of radar rainfall. According to the invention, effective utilization of rainfall observation data of a ground meteorological station is realized, deviation correction is carried out on a radar networking estimation rainfall product by using a ground station grid analysis field and a ground-radar climate state proportion analysis field, and the deviation between a radar rainfall estimation value and real rainfall is effectively corrected. According to the method, the discontinuity and systematic deviation of space-time distribution of a fusion product are reduced, the adaptability of the fusion product to complex terrains and rapid evolution precipitation scenes is enhanced, collaborative optimization correction of multi-scale and multi-type deviation is realized, and the reliability and service applicability of a radar precipitation product are remarkably improved.

A transmission / distribution system operation coordination-based HVDC operation system is provided, based on the operation of HVDC (High Voltage Direct Current) to expand supply stability, improve power quality, and enhance the economic efficiency of system operation throughout the domestic power system. The HVDC operation system is characterized by comprising: a power system management terminal that generates power system operation information; a plurality of HVDCs that generate HVDC availability information; a power market management server that generates power market operation information; distribution network operation information; a distribution system management computer that generates distribution network generation planning information and real-time distribution network generator operation information using distribution network generator bidding information and transmission system distribution network generation capacity acceptance information among the power market operation information; and an HVDC operation computer that generates HVDC operation planning information and distribution network generation capacity acceptance information based on the distribution network generation planning information, and generates real-time control information for controlling the operation of the HVDC based on the HVDC operation planning information, power system operation information, and distribution network operation information.

The invention discloses a main grid topology gridding construction method based on OP interconnection, and relates to the technical field of power grids. Compared with a previous power grid topology construction method, the problems that an existing distribution network is large in network scale and high in complexity are solved; the complexity of network modeling and simulation related to various protocols and technologies is high; the real-time requirement cannot be met; the problem that a visual display interface cannot be provided in the prior art is solved. Interconnection and intercommunication among various devices are realized based on OP interconnection, an optimal dynamic distribution network main network frame topology model is generated in combination with an improved DQN algorithm, and the distribution network main network frame topology model is replaced by a homologous maintenance model, so that the operation efficiency and flexibility of a power distribution network can be improved, a power supply area is divided, and the power supply efficiency is improved. The operation efficiency and the management level of the power distribution network can be effectively improved; a mapping relation is established between the distribution network main grid topology model and the power supply grid, a current grid analysis model in the power supply grid is formed, and the efficiency, reliability and manageability of a power system can be improved.

The invention discloses a vertical face positioning method and system for a marine wall-climbing robot. The method comprises the steps that S1, the system is initialized, and a global grid is established; S2, the robot is initially calibrated and placed; s3, trajectory planning and loading are carried out; s4, fusing positioning and closed-loop control; s5, deviation judgment and correction; s6, the step S4 and the step S5 are executed repeatedly until all planned tracks and operation tasks are completed; according to the method, the laser grid is projected, a stable and visible global position reference is created on a feature-free vertical face, and the positioning problem that no absolute reference object exists in a large-scale space is solved; absolute position information without accumulated errors is provided through visual grid recognition calculation, long-term drifting of the IMU and the odometer is corrected, and the positioning precision of long-time operation is guaranteed; the wall-climbing robot continuously detects the pose deviation and actively corrects the pose deviation according to the visual grid analysis result in the advancing process, the accumulated error of the IMU is corrected in real time by using the visual observation value, and the robustness and reliability are improved.

The invention discloses a grid analysis-combined power grid service package configuration method and system, and relates to the technical field of intelligent power grids, and the method comprises the steps: carrying out the content analysis of a power grid service package, and obtaining a service configuration dimension; determining the grid granularity of the configuration dimension; performing grid segmentation on each service configuration dimension, and determining segmented grids; according to the segmented grids, analyzing each grid unit, and extracting electric power features; performing feature aggregation on the power features to obtain grid aggregation features; and carrying out feature projection according to a mapping relation between the service configuration dimension and the grid aggregation feature, and configuring a power grid service package. The technical problems that in the prior art, power grid service package configuration lacks precise adaptation, resource configuration is low in efficiency, spatial structure characteristics are not fully utilized and association relation mining is insufficient are solved, service package configuration precisely adapting to power grid operation requirements is achieved, pertinence and high efficiency of power grid services are improved, and the power grid service configuration efficiency is improved. And the operation reliability of the power grid is enhanced.

The invention provides an oven temperature and time intelligent cooperative control system based on food material moisture dynamic perception, and the system collects multi-dimensional data in a cooking process in real time through a data collection module, carries out the preprocessing and grid analysis of the collected data through a data analysis module, determines the real-time state of a food material, screens out the to-be-processed candidate region of the food material, and carries out the processing of the to-be-processed candidate region of the food material. Analyzing the current cooking stage according to the food material state; the control module outputs control instructions of temperature, time, heating power and hot air circulation strength based on a cooperative control algorithm according to the current cooking stage of the food materials and the candidate area to be processed; and the execution module receives and analyzes the control instruction, and controls an execution mechanism to act according to the analyzed control instruction. Dynamic matching of temperature, time and food material states can be achieved, the problem that a traditional oven is insufficient in intelligence is thoroughly solved, the baking efficiency and the cooking quality are improved, the user operation threshold is lowered, and the oven is particularly suitable for home kitchens, small catering institutions, baking studios and other scenes.

The invention discloses an aero-engine turbine moving blade resonance point alternating stress prediction method, which comprises the following steps of: 1, generating a grid required by CFD (computational fluid dynamics) calculation according to geometric files of a turbine guide blade and a moving blade; 2, the resonance rotating speed of the movable blades is determined; step 3, carrying out grid steady CFD analysis under the resonance rotating speed; 4, carrying out grid non-full-ring unsteady calculation under the resonance rotating speed to obtain the modal force of the moving blade; 5, calculating the alternating stress of the turbine moving blade; 6, adjusting the static pressure of the outlet of the movable blade, and carrying out calculation again to obtain alternating stress; 7, changing the axial distance between the moving blade and the guide blade, and carrying out calculation again to obtain alternating stress; and 8, drawing a curve according to the alternating stress in the step 6 and the alternating stress in the step 7. The method has the beneficial effects that complex and long-time-consuming unsteady simulation does not need to be carried out on the turbine part, the method is convenient to use in the preliminary design stage of engineering, and the working efficiency is high.

The invention discloses a regional adaptive OI fusion algorithm based on station network density, terrain gradient and radar quality index. The regional adaptive OI fusion algorithm is constructed by using a ground station precipitation grid analysis field, a radar satellite joint background field, a radar quality index analysis field (RQI), a station network density analysis field (SD I) and a terrain gradient analysis field (SLP). According to the method, the precipitation fusion precision of the complex underlying surface area is remarkably improved. The rainfall error space-time structure of different areas (such as mountainous regions, river valleys and coastal zones) can be accurately captured. In a radar signal area shielded by the terrain, the error ratio of an observation field to a background field is automatically improved, and low-quality radar data is prevented from being excessively trusted; in the abrupt slope mountainous area with a sparse station network, the background field error attenuation distance is shortened, and the problem of'false details' caused by false interpolation is effectively inhibited. In a plain area with dense station networks, the attenuation distance is prolonged to keep the natural continuity of the precipitation field, and excessive smoothness is avoided.

The present invention discloses a mesh quality adjustment method and system based on geometric optimization and topological optimization, and belongs to the technical field of mesh analysis and processing. The existing mesh processing scheme does not disclose how to adjust the mesh quality, which affects the stability and accuracy of numerical calculations, and has low calculation efficiency. The mesh quality adjustment method based on geometric optimization and topological optimization of the present invention creates a mesh acquisition model, a mesh preprocessing model, a mesh quality optimization model, and a mesh degree value adjustment model, and uses geometric optimization to repair the mesh geometry information and ensure the mesh geometry integrity; then, through topological optimization, fine adjustments are made to the problem nodes and polygonal units in the mesh, thereby significantly improving the overall quality of the mesh, so that the geometric details of the simulation object can be accurately captured, and the uniformity and stability of the mesh are effectively improved, making the numerical calculation more stable and accurate, and the calculation efficiency is high.