29 results about "Grid analysis" patented technology

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 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 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 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 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 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 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 embodiment of the application provides a kind of automated production line digital model hole filling method and device, accurately identify the region to be processed by multilevel grid analysis and curvature field calculation.Innovatively designed the generation mechanism of patch based on density clustering and neural network, combined with local geometric features to realize intelligent filling optimization.The system uses non-uniform rational basis spline surface reconstruction and Laplace grid smoothing algorithm to ensure the continuity and fairness of the filling area, and is closely combined with the motion control and path planning of automated production line.This method breaks through the limitations of traditional model repair and provides an efficient and reliable solution for the integrity reconstruction of industrial digital models.

The invention relates to a contour prediction method for a femtosecond laser rotary-cut small hole. The femtosecond laser rotary cutting machining method is provided for solving the problems that an existing large-depth-diameter-ratio small hole is difficult to machine, and the machining quality is difficult to control. Femtosecond laser rotary cutting machining is a machining technology for preparing high-precision small holes, a laser beam rotates around an optical axis at a high speed to form a light knife, materials are removed layer by layer by controlling the light knife to move along a spiral path, and the purposes of accurately controlling the hole diameter and the shape, improving the machining efficiency and the like are achieved. According to the method, the distribution of laser spots in the laser ring is analyzed, and the laser flux of the light knife is obtained according to a laser flux line and a grid analysis method. The motion trail of a light cutter during machining is analyzed, the evolution law of hole contour lines under different feeding depths during machining is mastered through an ablation depth calculation method based on an ablation threshold value, a contour prediction model during femtosecond laser rotary cutting machining of the small holes is established, and theoretical support is provided for machining of the large-depth-diameter-ratio small holes of materials difficult to machine.

The invention discloses a tea tree anthracnose diffusion prediction method based on a remote sensing image and lattice point analysis, and the method comprises the following steps: obtaining an unmanned plane multispectral image of a tea tree land parcel, and carrying out the recognition of a soil background region, a healthy tea tree region and an infected region; dividing the tea tree plot into uniform grid spaces, defining the state of each grid point as a healthy grid point or an infected grid point, setting a diffusivity calculation method, and calculating the diffusivity of each grid point; setting a disease diffusion rule, updating the state of each grid point according to the disease diffusion rule, and completing the prediction of anthracnose diffusion. According to the invention, by fusing multi-temporal unmanned aerial vehicle remote sensing monitoring data and continuous time sequence environment data, a space-time coupling model for describing a disease infection mechanism between adjacent grid points is constructed, and the spatial diffusion and evolution trend of diseases is dynamically simulated; the problems that a traditional disease prediction method is high in experience dependence, poor in spatial dynamic simulation capability, low in temporal-spatial resolution and the like are solved.

This invention discloses a method for predicting the spread of anthracnose in tea trees based on remote sensing imagery and grid analysis, comprising the following steps: acquiring multispectral images of tea plantations from unmanned aerial vehicles (UAVs), identifying soil background areas, healthy tea tree areas, and infected areas; dividing the tea plantation into a uniform grid space, defining the state of each grid point as either a healthy grid point or an infected grid point, setting a diffusion rate calculation method, and calculating the diffusion rate of each grid point; setting disease diffusion rules, updating the state of each grid point according to the disease diffusion rules, and completing the prediction of anthracnose spread. This invention, by fusing multi-temporal UAV remote sensing monitoring data and continuous time-series environmental data, constructs a spatiotemporal coupling model describing the disease infection mechanism between adjacent grid points, dynamically simulating the spatial spread and evolution trend of the disease, overcoming the problems of strong experience dependence, poor spatial dynamic simulation capability, and low spatiotemporal resolution of traditional disease prediction methods.

Disclosed are integrated DFOS systems and methods that advantageously integrates fiber sensing technology with advanced grid analysis to enhance the resilience of electrical distribution systems by providing accurate and efficient risk assessments. Utilizing real-time observations from Distributed Fiber Optic Sensing (DFOS), it accurately evaluates risks associated with probable events and calculates the risk of line failures. The method develops a modified risk-aware system that incorporates minimized system loss, voltage violations, power flow violations, the number of switching operations, and radiality constraints. By integrating DFOS data with existing grid data, the method enables rapid system adaptation and localized fault detection, advancing the state of the art in grid resilience and reliability.

The application discloses a kind of based on GIS's site vertical design earthwork quantity calculation method and system, it is related to earthwork quantity calculation technical field, including: according to topographic map, construct site present situation DEM;According to vertical design drawing, construct site design DEM;Site design DEM and present situation DEM are carried out grid analysis, obtain surface fill and dig earthwork grid data;Combined with control regulation data, calculate the surface fill and dig earthwork quantity of each plot of planning land;Calculate the underground engineering excavation quantity of each plot of planning land, building underground space, subway, underground comprehensive pipe gallery;The total amount of fill and dig of each plot of planning land is calculated, and fill and dig special map is generated.The system includes present situation DEM construction, design DEM construction, surface dig and fill quantity calculation, underground engineering excavation quantity calculation, total amount of dig and fill calculation 5 modules.The method is simple, efficient and accurate, low cost, wide application range, considering the underground engineering earth volume, the result is more reasonable and accurate, provide more reliable basis for site vertical design and construction.

The invention discloses a panda track visualization processing method and device, relates to the technical field of animal behavior monitoring and visualization, and has the advantages of remarkably improving data processing efficiency, eliminating artificial subjective errors and realizing real-time dynamic visualization of panda behaviors. The method comprises the following steps: acquiring track data obtained by automatic detection of a panda; performing user-defined grid division on the monitoring picture, and performing space-time analysis on panda behaviors in each grid based on the trajectory data to obtain a grid analysis result; an activity hotspot map is generated based on a grid analysis result, and the activity intensity and stay density of the panda in different areas are visually displayed through the color depth; drawing a motion trail diagram based on continuous coordinate data of the panda, and distinguishing a moving point, a static point and a motion trail by adopting different colors and symbols; and integrating the trajectory data, the activity hotspot map and the motion trajectory map, and generating a multi-dimensional visual analysis report.

The invention discloses an urban space innovation output performance simulation and prediction method. The method comprises the steps of obtaining multi-source spatio-temporal data and constructing a database; dividing a city into standard grids, screening effective sample grids, and determining a reference construction year of the effective sample grids; constructing a time, macroscopic and mesomicroscopic multi-dimensional influence factor index system, and measuring and calculating grid characteristic indexes; constructing a quantity and growth rate two-dimensional performance indicator system, and measuring and calculating grid performance indicators; associating the features with the performance indicators to form a mapping table; using the characteristic indexes as independent variables and the performance indexes as dependent variables, and utilizing machine learning to construct a prediction model; future grid characteristic indexes are measured and calculated based on a planning scheme, the model is input to obtain predicted performance, and an innovation core development area is delimited accordingly. Multi-source data and gridding analysis are fused, and a systematic'feature-performance 'mapping relation is established; historical laws and planning scenes are communicated, quantitative decisions are provided for innovative spatial layout, and precise implementation of territorial space planning is facilitated.

This invention discloses a method for generating time-series scenarios of distributed resources, belonging to the field of grid analysis technology for distributed energy access. The method includes: acquiring historical operating data, historical meteorological data, and meteorological forecast data of distributed photovoltaic (PV) and loads within the area to be analyzed; generating historical sample daily feature vectors and scenario-to-be-generated daily feature vectors based on the acquired data, and determining a set of similar days; acquiring historical operating data of distributed PV and loads on similar days within the area to be analyzed based on the set of similar days, analyzing their power fluctuation range distribution characteristics and power probability distribution characteristics, and obtaining the upper and lower bounds of fluctuation and the power probability density function of distributed PV and loads; and obtaining a set of time-series power scenarios for distributed PV and loads considering fluctuation range correction based on the upper and lower bounds of fluctuation and the power probability density function of distributed PV and loads. This invention can fully utilize historical power information and fluctuation information to generate high-precision uncertainty scenarios.

A method for reproducing tensile strain marks on the surface of a 5-series aluminum plate through pot cover samples comprises the steps that the 5-series aluminum plate is stamped according to different stamping depths within the stamping depth range of 80-130 mm to obtain different stamping pot cover samples, strain values corresponding to drawing slopes of the stamping pot cover samples with different stamping depths are measured through the digital grid analysis technology, and the stamping pot cover samples with different stamping depths are obtained. Obtaining a database in which the stamping depth corresponds to the strain condition of the stamping pot cover sample drawing inclined plane; measuring the strain value of the part with the tensile strain mark phenomenon after the 5-series aluminum plate part is stamped and formed by using a digital grid analysis technology; and the strain value corresponding to the tensile strain mark is obtained, and the tensile strain mark on the 5-series aluminum plate part is reproduced on the stamping pot cover sample according to the corresponding stamping depth in combination with the analysis of the database. The obtained stamping pot cover sample with the tensile strain marks is directly used as a standard sample to judge whether the Luders strip tensile strain marks appear after 5-series aluminum plate stamping forming, judgment is more accurate, and the situation that samples with defects flow into a use end, and losses are caused to enterprises is avoided.

The invention relates to a WebGL-based three-dimensional local terrain protrusion weakening method, which belongs to the technical field of computer graphic visualization, and comprises the following steps of: loading a terrain grid, loading terrain data into a scene in the form of a grid in a WebGL rendering engine, storing information in the form of a binary file in a. Terrain format, then analyzing the grid, and obtaining the three-dimensional local terrain protrusion weakening method based on the WebGL. The method comprises the following steps: loading block terrain data according to a terrain detail level strategy, analyzing the terrain data, loading and analyzing downloaded secondary file data according to a terrain grid level and a row and column number, compressing the data by using a zigzag-zag coding method, then dynamically adjusting the vertex height, and finally reconstructing a terrain triangulation network. According to the WebGL-based three-dimensional local terrain bulge weakening method, the terrain bulge problem is weakened by modifying the vertex elevation of a terrain-data-free area, distortion deformation of a local high-precision terrain and a model in a scene is avoided, the terrain scarp problem existing in three-dimensional local terrain bulge can be weakened, and the terrain and the model in the scene are not deformed.

This invention discloses a method and system for professional annotation and drawing generation of BIM models based on grid analysis. The method includes: Step 1: Selecting a profession and its corresponding professional rule set through a profession selection module; Step 2: Obtaining all model data in the current two-dimensional view of the BIM system and performing corresponding data preprocessing according to the annotation type of the profession selected in Step 1; Step 3: The annotation generation module automatically generates annotations for specific components according to the selected profession; Step 4: Automatically generating drawings with professional annotations. This invention relates to the field of building information model data processing and engineering drawing automation technology, and can solve the problems of existing technologies that cannot perform automatic annotation based on grid analysis and cannot perform customized annotation for different professions.

The invention provides a gridding analysis method for determining an overlying strata energy accumulation horizon, which comprises the following steps of: rotating a working surface base map and a microseismic event coordinate, so that the direction of a working surface is parallel to an X axis, and the tendency of the working surface is parallel to a Y axis; dynamically determining a grid division range based on the section coordinate extreme value of the micro-seismic event in the target area, and dividing the area into rectangular grids with equal sizes through a preset grid side length parameter; counting an energy accumulated value of a micro-seismic event in each grid by adopting a circular window, and performing energy level conversion by adopting a logarithmic function to eliminate magnitude difference; and finally, a two-dimensional energy level distribution contour map is generated through an interpolation algorithm, and energy overlying stratum position aggregation characteristics and dynamic evolution rules are visually displayed. The method provided by the invention solves the problems of insensitive energy distribution characterization and difficult spatio-temporal evolution trend identification in a traditional method. The quantitative precision and the dynamic monitoring efficiency of micro-seismic activity analysis are remarkably improved, and reliable technical support is provided for mine safety early warning.

The invention relates to an optimization method, device and equipment of a three-dimensional special-shaped curtain wall model and a storage medium. The optimization method of the three-dimensional special-shaped curtain wall model comprises the steps that physical and chemical treatment is conducted on an original curved surface of the three-dimensional special-shaped curtain wall model, a physical and chemical curved surface is obtained, and structural lines of the physical and chemical curved surface are uniform and composed of straight lines and arcs; adopting at least one preset segmentation strategy to carry out lattice analysis on the physical and chemical curved surface to obtain at least one lattice curved surface; and calculating the curved surface rate of the at least one mesh division curved surface, and selecting a target mesh division curved surface from the at least one mesh division curved surface according to the curved surface rate so as to complete optimization of the three-dimensional special-shaped curtain wall model. According to the method provided by the invention, the problem of unsmooth vision and touch caused by sudden change of the curvature of the curved surface of the special-shaped curtain wall panel is solved to a certain extent, and the manufacturing cost is also reduced.

The invention discloses a high-precision polygon cross-order solving method and coupling analysis application, and belongs to the technical field of geotechnical engineering numerical analysis methods. The method comprises the following steps: S1, taking a grid, a material, a load and an output data file as input of a calculation model; s2, acquiring node numbers contained in each unit and corresponding node position coordinates, unit types, material parameters and integral points; s3, obtaining a material constitutive matrix of each unit in the S1; s4, determining the position of an integral point of each unit, and obtaining a feature value and a feature vector; s5, calculating a strain matrix value and a shape function at each integral point of the polygon unit; s6, obtaining a mass matrix and a stiffness matrix at each integration point; and S7, based on S1 to S6, numerical solution is carried out according to the working conditions needing to be calculated. According to the method, the combination of a cross-scale grid analysis method and a cross-order analysis method can be realized, and the contradiction between the solving precision and the calculation efficiency is balanced; the method can perform refined bending analysis on the polygonal unit, solves the problem of first-order unit shearing self-locking, and has relatively high analysis performance and universality.

The invention provides a grid division method and device, a storage medium and electronic equipment, and belongs to the field of simulation, and the method comprises the steps: determining grouping information and initial grid information of each preset group; performing model region division based on the grouping information to obtain a model region of each preset group; performing grid adaptability analysis on each piece of initial grid information to obtain each grid analysis result, and determining each piece of candidate grid information according to each grid analysis result; performing grid division on each model region according to each piece of candidate grid information to obtain each pre-simulation region, and performing simulation evaluation to obtain each pre-simulation result; if the pre-simulation result meets the simulation condition, taking the corresponding candidate grid information as target grid information, and if the pre-simulation result does not meet the simulation condition, determining the target grid information through grid parameter optimization; and based on the information of each target grid, determining a grid division scheme. By applying the method provided by the invention, different grid parameters can be configured for different model areas, and the accuracy of grid division can be improved.

The invention relates to the technical field of community public security management, in particular to an intelligent management and scheduling system for community public security gridding, and aims to solve the problem of peak supply and demand imbalance of newly-built commercial housing community charging piles, an initial grid construction module, a peak dynamic grid analysis module, a peak resource scheduling module and a peak risk early warning module are designed. The initial module collects grid reference, charging pile operation and electric vehicle violation historical data, the dynamic analysis module calculates a grid elastic coefficient in combination with the industry reference of the Ministry of House and Construction, and an adjustment threshold is set according to fire hazard grouping data, resource adaptability and a hazard improvement effect. The resource scheduling module quantifies risk emergencies, resource adaptability and reachable timeliness to calculate scheduling priorities, the risk early warning module predicts violation risk values in advance and adapts resources by means of a recurrence probability formula, objective data is used for driving, subjective decisions are avoided, grid dynamic adjustment and accurate resource allocation are achieved, and community public security management efficiency and safety are improved.