372 results about "Boundary data" patented technology

The invention belongs to the technical field of automatic detection, and discloses an online laser detection and grading regulation and control system for particle size distribution of crushed raw ore. The invention aims to solve the problems of halo effect interference caused by adhesion of fine dust in a complex industrial environment and insufficient detection precision of a traditional method. The system obtains dynamic scattering light field data through the laser scanning module, identifies a halo effect region and generates a compensation coefficient by using the light field preprocessing module, and realizes accurate reconstruction of particle boundaries in combination with the edge reconstruction module. The particle size distribution analysis module extracts multi-dimensional geometric features based on the accurate boundary data, and generates a real-time particle size distribution curve. The grading strategy generation module formulates a regulation and control strategy according to deviation characteristics of the curve and a preset standard, and the dynamic regulation and control module adjusts parameters of crushing equipment in real time and optimizes particle size distribution. The method effectively overcomes the halo effect interference, improves the detection precision and the system stability, breaks through the single limitation of a traditional method, and provides comprehensive data support for a downstream process.

The invention discloses a three-dimensional geologic model modeling method and device. The three-dimensional geological model modeling method comprises the following steps: acquiring to-be-established geological region data and actual geological boundary data; generating an initial stratum interface grid according to the to-be-established geological region data; correcting the initial stratigraphic interface grid to obtain a corrected stratigraphic interface grid; carrying out geological rule constraint on the corrected stratigraphic interface grid so as to form simple three-dimensional stratigraphic interface model data; correcting the simple three-dimensional stratigraphic interface model data according to the seismic profile information so as to obtain a composite geologic structure model; generating a three-dimensional fault plane model according to the composite geologic structure model; and generating a composite geological structure model including a fault network according to the three-dimensional fault plane model and the composite geological structure model. Through the three-dimensional geological model modeling method, the deviation between the model and an actual geological boundary can be remarkably reduced.

The invention discloses a submarine pipeline scour-vibration response analysis method based on a cross-scale coupling framework. The method comprises the following steps: establishing a multi-physics field coupling model according to geographical and structural information of a pipeline layout area and initializing the multi-physics field coupling model; marine environment data are obtained through real-time monitoring, the model is imported for scouring dynamic deduction, and a scouring boundary data set is generated. And reconstructing a multi-physics field solving environment, and forming a real-time physics solving environment package. After the model is updated, pipeline vibration response is analyzed, and a vibration data set is obtained. And performing fatigue damage analysis, deducing a flow guide field disturbance coefficient, updating the model again, performing next time step coupling calculation, and finally obtaining a full-period coupling analysis data set. And evaluating the pipeline operation safety situation based on the data set, and generating and pushing a safety report. Various physical field effects on the submarine pipeline in the marine environment are comprehensively considered, the safety of the submarine pipeline is evaluated more comprehensively, and cross-scale coupling analysis between the scouring effect and the vibration effect is achieved.

The invention relates to a multi-physics field coupling simulation method and equipment for industrial digital twinning. The method comprises the following steps: automatically dividing a plurality of heterogeneous physical sub-domains based on actual physical field data of industrial equipment, and defining a solving region and a boundary condition for each sub-domain; and then, a variable-driven region division mechanism is utilized to construct a parallel computing map of multiple physical domains, and efficient synchronization of inter-region coupling state variables and real-time interaction of boundary data are realized. In the parallel simulation process, calculation tasks and resources are dynamically and optimally distributed through a self-adaptive scheduling algorithm, bottleneck areas are effectively recognized and eliminated, and the overall simulation efficiency and stability are improved. According to the invention, co-evolution of a plurality of physical processes such as structure, heat, flow, magnetism, electricity and the like can be realized, and unified, flexible and extensible simulation support is provided for digital twinning, state monitoring, performance prediction, control optimization and other applications of a complex industrial system.

The invention discloses an elbow connector forward and reverse intelligent deviation rectification virtual assembly blanking method, which comprises the following steps: carrying out 3d scanning on a new elbow and two old pipes, carrying out space matching on two axes of the new elbow and the axes of the two old pipes, searching an optimal assembly position, calculating boundary data of an annular track and extracting track deviation rectification characteristics; the track deviation correction characteristics are added into the preliminary cutting control data so as to compensate the track installation deviation when the cutting robot cuts; and generating final cutting control data. The device has the beneficial effects that a new bent pipe and an old pipe are scanned in a handheld 3d mode, point cloud data are recognized, a cutting route is simulated, final cutting control data, the walking route for controlling the cutting robot and control data for controlling the cutting torch to move on the sliding rail are obtained, automatic cutting is achieved in cooperation with the cutting robot, and the cutting efficiency is improved. Therefore, data support is provided for efficiently completing pipeline first-aid repair.

The invention provides an efficient transfer robot scheduling system for components in intelligent warehousing, and relates to the technical field of intelligent warehousing logistics, and the method comprises the steps: analyzing a transfer task instruction, extracting a task starting point coordinate, an end point coordinate and a path constraint condition, and collecting warehousing environment data in real time; the storage environment data comprises position offset state data, track boundary data and dynamic obstacle distance data; constructing a grid map model based on the position offset state data, the track boundary data and the dynamic obstacle distance data; and iteratively calculating a global final path node sequence on a magnetic stripe track by adopting a colistification algorithm fusing an oscillation factor disturbance mechanism and a self-adaptive weight strategy based on the grid map model. According to the invention, the problems of poor path flexibility and insufficient control precision in an intelligent warehousing component carrying system are solved.

The invention provides a building interior design layout optimization method, and relates to the technical field of indoor modeling and layout optimization, and the method comprises the steps: obtaining building structure boundary data and current situation layout information, constructing an indoor three-dimensional space model, and completing the marking of node passing attributes and a spatial topological structure. On the basis, crowd behavior data of a daily scene and an emergency scene are collected, behavior characteristics such as walking speed, obstacle avoidance response and congestion sensitivity are extracted, and a walking characteristic model used for simulating the individual motion trend is established. And performing multi-scene simulation under a daily event and an emergency evacuation event by using the walking feature model, calculating performance indexes such as passing time, local congestion degree, key node congestion probability and total evacuation time, and identifying a congestion sensitive area. And further constructing a multi-target evaluation model including traffic efficiency, congestion degree and evacuation performance, and performing global optimization on layout adjustable parameters by adopting an algorithm to obtain a candidate layout scheme set.

The invention discloses a regional carbon emission prediction method and system based on deep learning, and belongs to carbon emission prediction. The method comprises the following steps: acquiring historical carbon emission time sequence data and multi-dimensional constraint boundary data of a target area, and mapping the historical carbon emission time sequence data into an input feature vector; outputting an initial future carbon emission evolution trajectory vector; identifying and extracting a constraint violation dimension; constructing an input feature compensation tensor; generating an updated input feature vector; inputting the updated input feature vector into the depth space-time prediction model again for recursive prediction; and outputting a target carbon emission trajectory vector meeting the multi-dimensional constraint boundary data and a corresponding feature adjustment parameter set. According to the method, by automatically analyzing the multi-dimensional management constraint and fusing the multi-dimensional management constraint into the iterative optimization closed loop of the prediction model, the problem that the prediction model in the prior art only optimizes mathematical statistical errors and is seriously disjointed with multi-dimensional targets such as cost control and path feasibility in real management is solved.

The invention provides a method for simulating runoff in a cold and cold mountainous area by combining LSTM (Long Short Term Memory) to improve a VI-glacier model. The method is used for solving the technical problems that runoff components in the cold and cold mountainous area are diverse and each runoff source cannot be directly distinguished. The method comprises the following steps: firstly, determining model input data including DEM data, vegetation data, soil data, meteorological data, hydrological data and glacier boundary data; a GPM rainfall product is adopted to drive meteorological data; secondly, introducing a degree-day factor model to quantify the glacier ablation process, coupling the degree-day factor model with the VIC model, and constructing a VI-glacier model; then, an SCE-UA automatic optimization algorithm and an artificial trial and error method are combined to calibrate the VICs-glacier model, and an optimal parameter value is obtained; and meanwhile, error correction is carried out on a simulation result of the VI-glacier model through the LSTM model, so that runoff correction is realized. The model provided by the invention can relieve the uncertainty of water resources caused by glacier changes, and the future runoff can be predicted more accurately.

The invention relates to the technical field of city cadastral data analysis, and discloses a city update district boundary division method and system based on cadastral data, and the method comprises the steps: collecting the division associated cadastral data of a target city update district, and employing an improved DTW algorithm to obtain a city update district boundary; the method comprises the following steps: screening current situation boundary effective points and newly-added candidate points with history continuity from current situation measured data, extracting spatial features and ownership features for fusion, constructing a feature matrix by using a fusion feature vector, constructing a spatial ownership double-constraint graph neural network, predicting a final boundary point set of a target city update area, and obtaining a target city update area. And generating a final land parcel boundary. Therefore, by introducing the improved DTW algorithm and the spatial ownership double-constraint graph neural network, while accurate association of historical and current boundary data is established, joint optimization of spatial rationality and ownership rationality is realized by utilizing double-constraint feature fusion, and the division precision and division efficiency of the urban update district boundary boundary are improved.

The invention relates to a crop plot identification method and system based on time sequence vegetation characteristics, and the method comprises the steps: constructing a normalized difference vegetation index time sequence according to a multi-temporal satellite remote sensing image, and generating a crop probability distribution diagram through a crop classification model; performing connected domain analysis on the crop probability distribution map, extracting the center of gravity of an effective connected domain as a forward attention point, scanning the crop probability distribution map by using a sliding window, and generating a reverse attention point; based on the forward attention point and the reverse attention point, segmenting the high-resolution remote sensing base map through a visual segmentation model, generating a candidate mask set, and screening to reserve a mask with the maximum area as a land parcel segmentation mask of the forward attention point; and combining all the plot segmentation masks to generate a crop plot identification graph, and converting the boundary of each plot segmentation mask into a geodetic coordinate sequence to obtain plot vector boundary data. The method improves the recognition accuracy, and achieves the automatic and precise segmentation of the boundary of the land parcel.

The invention relates to the technical field of electric power simulation, and discloses an electric power system data parallel simulation processing method based on distributed modeling. The method comprises the following steps: acquiring voltage, frequency and power parameters of a new energy inverter and an energy storage converter, and generating a state switching feature vector through a fuzzy C-means algorithm; determining and calculating a load abrupt change subsystem according to the load index overrun, and calculating the electrical coupling strength with an adjacent subsystem; allocating reserved computing resources for the mutation subsystem through a particle swarm optimization algorithm to form a dynamic resource allocation table; and adjusting the data synchronization period of the mutation subsystem to an extended time window, and continuing parallel simulation after the adjacent subsystems wait for boundary data. According to the method, the problems that in an existing power system data parallel simulation processing method based on distributed modeling, the calculation load abrupt change and the data synchronization failure caused by strong nonlinear component state switching cannot be processed are solved.

The invention provides a high-cold and high-altitude environment-oriented energy storage battery state monitoring method and system, and the method comprises the steps: innovatively constructing a multi-scale physical constraint framework: extracting multi-dimensional features through a cavity convolution network with a time sequence perception capability, and fusing the initial state physical information of a battery; embedding inherent physical law constraints of the battery into the characteristic space, wherein the inherent physical law constraints comprise forced charge conservation, health state one-way attenuation and temperature and pressure self-adaptive stability control; a special compensation mechanism is designed for an extreme environment, accurate state estimation is realized by dynamically correcting a low-temperature diffusion behavior, and lithium precipitation safety early warning triggered by multi-condition collaboration is established. A calibration-free training strategy is adopted, model optimization is completed only through a small amount of boundary data, and adaptability is enhanced and improved in combination with plateau environment data. And the method can be operated in a resource-limited embedded platform through lightweight processing. And under the working conditions of high and cold and low air pressure, the core industry problems of insufficient adaptability to extreme environments, misalignment of physical rules, limited hardware deployment and the like are effectively solved.

The invention relates to the technical field of intelligent water conservancy and automatic control, in particular to a polder area multi-station water conservancy data real-time collection and intelligent fusion processing method and system, and the method comprises the steps: a multi-dimensional collection system construction step: collecting time sequence state, fluid field and environment boundary data, and executing time base unified cleaning; an ideal model construction step: constructing an ideal water tank model based on the law of conservation of mass and generating an ideal water level change curve; a parameter injection simulation step: generating a simulation fault water level curve according to injection efficiency attenuation and medium leakage parameters; a double-track difference calculation step: respectively carrying out difference on actual measurement and simulation data and an ideal curve to generate real and theoretical residual vectors; a similarity judgment and control step: calculating sequence similarity to judge a real physical fault or sensor data noise, and generating a fusion control instruction; according to the invention, the technical problem of distinguishing the noise of the sensor from the real physical fault is effectively solved, and false alarm or missing alarm is avoided.

The invention discloses a defect detection method and device based on a dynamic dual-threshold template, and a storage medium, and aims to improve the defect detection precision of an image shot by a display screen. Collecting a plurality of batches of defect-free sample images of the target model display screen; counting gray extreme value boundary data of each pixel point on the plurality of batches of defect-free sample images; and generating a lower limit standard template and an upper limit standard template according to the gray extreme value boundary data. And obtaining a regional difference amplification coefficient and a compensation offset. And generating a dynamic detection threshold template for the lower limit standard template and the upper limit standard template through the regional difference amplification coefficient and the compensation offset. And obtaining a to-be-tested screen body image of the target model display screen. And carrying out pixel-level difference on the to-be-detected screen body image and the dynamic detection threshold template to generate a defect mask image. And performing defect detection on the display screen through the defect mask image to generate a first defect detection result.

To provide a three-dimensional geological model correction device, method, and program that can quickly and effectively correct a three-dimensional geological model using strata information obtained from face observation.SOLUTION: A three-dimensional geological model correction device comprises: three-dimensional geological model generation means 30 for generating a three-dimensional geological model of a construction target including three-dimensional coordinates and three-dimensional stratum boundary data based on previously acquired stratum information of the construction target; face image acquisition means 21 for acquiring a face image of an already excavated area; face coordinate acquisition means 22 for acquiring three-dimensional coordinates of the face image; two-dimensional stratum boundary data extraction means 23 for extracting two-dimensional stratum boundary data from the face image; identical boundary extraction means 40 for extracting identical boundaries based on proximity of three-dimensional coordinates of boundary lines constituting the three-dimensional stratum boundary data and the boundary lines constituting the two-dimensional stratum boundary data; and three-dimensional stratum boundary data correction means 50 for correcting the three-dimensional stratum boundary data based on the two-dimensional stratum boundary data related to the extracted identical boundaries.SELECTED DRAWING: Figure 1

Disclosed in the embodiments of the present disclosure are a vehicle control method and apparatus. The method relates to the fields of autonomous driving technology and autonomous vehicles, and comprises: in response to receiving first spatial information of a first workstation, acquiring first sensing information of a first vehicle, wherein the first spatial information is generated on the basis of initial map boundary data, and both the first sensing information and the initial map boundary data are used for determining the boundary of a working area; adjusting the first spatial information on the basis of the first sensing information, so as to obtain second spatial information of the first workstation, wherein the degree of matching between the second spatial information and the boundary of the working area is greater than the degree of matching between the first spatial information and the boundary of the working area; and generating a first control instruction on the basis of the second spatial information, wherein the first control instruction is used for controlling the first vehicle to travel to the first workstation. The present disclosure solves the technical problem in the prior art of the control precision of an autonomous mining truck being reduced and thus affecting the working efficiency due to map updates being affected by network conditions.

The invention relates to a two-dimensional and three-dimensional boundary point association method based on improved boundary point coding and a medium, and the method comprises the steps: carrying out the preprocessing of original land parcel red line data, sequentially numbering land parcels, converting all the land parcels into plane boundary point elements, determining a first boundary point in each plane boundary point element, processing each land parcel into a clockwise land parcel, and carrying out the coding of the clockwise land parcels. Performing two-dimensional boundary point continuous numbering on all vertexes of the land parcel, taking the land parcel after encoding the two-dimensional boundary points as a two-dimensional surface element, and converting the land parcel into a land parcel three-dimensional stereoscopic model comprising three-dimensional boundary points, boundary lines and boundary surfaces; and continuously numbering all the three-dimensional boundary points in sequence by using a cross section analysis method to obtain a land block after coding the three-dimensional boundary points, and establishing an association relationship between the three-dimensional boundary points with successfully matched coordinates and the corresponding two-dimensional boundary points. Therefore, automatic coding of the three-dimensional boundary points of the land parcel red line data and automatic association between the two-dimensional boundary points and the three-dimensional boundary points are realized, and the three-dimensional boundary point management efficiency in land parcel management is improved.

The invention relates to the technical field of power grid data management, and provides a power grid boundary data processing method and device, a power grid boundary data processing system, a readable storage medium and a program product. The method comprises the following steps: mapping each piece of power grid boundary data into standard boundary data; determining a multi-dimensional identifier of each standard boundary data according to a regulation and control object and a scheduling version of the power grid boundary data to obtain compressed boundary data corresponding to the same multi-dimensional identifier; determining the compressed boundary data of the same scheduling version according to the multi-dimensional identifier of the compressed boundary data to obtain a boundary data snapshot of the corresponding scheduling version, and storing the boundary data snapshot in a snapshot database; when a query request is received, a first boundary data snapshot set is determined in the snapshot database, and then a second boundary data snapshot set is obtained to form a query result. By adopting the method, complex multi-condition screening and multi-granularity time window analysis are supported.

The invention relates to the technical field of terrain information processing, in particular to an intelligent decision-making system and method for excavation and filling parameters of a reservoir area of a pumped storage power station. The method comprises the following steps: acquiring topographic data of a reservoir area; determining elevation distribution characteristics according to the topographic data of the reservoir area; performing excavation and filling boundary analysis based on the elevation distribution characteristics to obtain excavation and filling boundary data; performing earth-rock volume calculation according to the excavation and filling boundary data to obtain earth-rock balance data; identifying the section excavation and filling unbalance degree based on the earth-rock balance data to obtain excavation and filling deviation data; performing slope stability analysis according to the excavation and filling deviation data to obtain slope stability data; performing leakage risk prediction according to the slope stability data to obtain leakage risk data; and identifying a seepage path according to the seepage risk data. According to the method, excavation and filling parameter optimization is realized based on a topographic information processing technology, and the reservoir area construction decision efficiency is improved.

The invention provides an automatic driving operation method and system of a crawler harvester and a storage medium, and relates to the technical field of agricultural machinery automation, and the method comprises the following steps: obtaining boundary data of a harvesting area in a target land parcel; generating a spiral global operation path of the harvesting area from outside to inside based on the boundary data, wherein the path comprises a plurality of operation line segments which are connected in sequence; controlling the crawler harvester to perform straight running operation along the current operation line segment of the spiral global operation path through a preview tracking control strategy; monitoring pose data of the crawler harvester; when it is recognized that the crawler harvester arrives at a field end point of the current operation line segment based on the pose data and harvesting operation of the field end point is completed, the crawler harvester is controlled to turn and feed lines, and the crawler harvester is made to turn to the next operation line segment; and repeating the straight driving operation and the turning line feed until the harvesting operation of the target plot is completed. According to the method, the operation continuity and the operation efficiency are improved on the premise that full coverage and field edge boundary constraints are met.

The invention provides a nuclear power plant thermal discharge dynamic change prediction analysis method, and relates to the technical field of data processing, and the method comprises the steps: collecting a temperature observation data set, extracting a temperature maximum value sequence and a temperature minimum value sequence in an equal-tide period, calculating a wave amplitude stable factor, extracting a plurality of trend inflection points of a temperature change first-order derivative curve, and calculating the temperature change first-order derivative curve. The method comprises the following steps: determining thermal expansion boundary candidate areas caused by thermal drainage, evaluating a time interval and amplitude difference between a lag response inflection point in each thermal expansion boundary candidate area and a previous dominant temperature rise point to obtain a thermal lag offset value, extracting a boundary sensitive area, performing multipoint communication fitting, determining a maximum space extrapolation boundary influenced by the thermal drainage effect, and performing thermal expansion on the maximum space extrapolation boundary. And carrying out trajectory tracking and change direction regression on the extrapolation boundaries at multiple different time points, and identifying a heat disturbance movement trend to obtain dynamic evolution data. The method can identify the diffusion trend of the warm discharged water and predict the temperature change.

The invention discloses a historical block courtyard boundary intelligent extraction and semantic analysis method based on space-air-ground multi-dimensional sensing fusion, and the method comprises the steps: data fusion, the analysis of existing data, and the fusion of multivariate heterogeneous data, and the multivariate heterogeneous data comprises satellite remote sensing, unmanned plane oblique photography and ground mobile laser point cloud. Constructing a cross-scale courtyard enclosure data cube through the fused data, cutting the data cubes of different scales into a plurality of regions, constructing a three-dimensional space cube through the cut regions, and collecting cultural feature information related to historical courtyards through the three-dimensional space cube; according to the method, satellite remote sensing, unmanned aerial vehicle oblique photography and ground mobile laser point cloud are fused through a multi-source heterogeneous data adaptive fusion mechanism, a cross-scale courtyard enclosure data cube is constructed, and a data weighted registration algorithm based on feature significance is proposed. The problems of data missing and registration deviation caused by high building density and serious shielding in historical blocks are solved.

The invention provides a vehicle turning path planning method and device for irregular land parcels, and is applied to the technical field of path planning, and the method comprises the steps: carrying out the initialization of a pheromone field based on the boundary data of a geographic information system and internal obstacle data, and constructing a rasterized map for representing a passable region; based on the current state of the vehicle, determining the minimum distance of obstacles in the surrounding environment of the target vehicle; based on the real-time movement speed, the minimum turning radius of the target vehicle is determined; determining a dynamic corridor parameter of the target vehicle based on the minimum distance and the minimum turning radius of the surrounding obstacle; based on the dynamic corridor parameters and the pheromone field of the rasterized map, generating a turning point probability density field of the target vehicle, and sampling the turning point probability density field to obtain a turning point set; and constructing a turning path of the target vehicle based on the turning point set, and determining the turning cost of the turning path. According to the invention, Pareto optimization of energy consumption and efficiency in a complex scene can be realized.

The invention discloses an LED spliced screen cloud correction method, device and equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining spliced screen data, and carrying out the single-screen basic correction of a screen module based on the spliced screen data; after the single-screen basic correction is completed, monitoring whether boundary mismatch exists or not through an edge computing node; the boundary mismatch comprises deviation of brightness and / or chromaticity of edge pixels of adjacent screen modules; if the boundary mismatch exists, uploading boundary data to the cloud through the edge computing node; and obtaining a boundary correction parameter based on a pre-trained boundary correction model in the cloud, and receiving the boundary correction parameter to carry out cross-screen compensation. Through cloud intelligent compensation, macroscopic splicing seams of the spliced screen are eliminated, the display quality is improved, the environmental factor influence is dynamically compensated, the adaptive capacity of the spliced screen is improved, the resource utilization efficiency is improved through combined utilization of edge calculation and a cloud model, and the operation and maintenance cost is reduced.

Methods and systems are configured for accessing a three-dimensional (3D) facies model including a set of layers, each layer including boundaries data representing initial facies boundaries for a set of facies represented in that layer; accessing geological constraints data representing facies trends for the set of facies represented in the facies model; for each layer: for each facies type in the layer, determining, for a portion of the layer, a distance from the portion of the layer to a facies boundary for that facies type in the layer; and based on the distance for each facies type and the facies trends represented in the geological constraints data, determining a facies probability value; stacking the layers each including facies probability values for each facies type represented in that layer; simulating facies trends for each facies type; and generating a 3D facies trend model including the simulated facies trends.

The invention discloses an urban village identification method based on a graph neural network and multi-source geographic big data, and relates to the technical field of geographic images, and the method comprises the steps: obtaining remote sensing data, social perception data and building footprint data of an urban village; based on road network trajectory data, cutting built-up area boundary data through a hierarchical buffer area strategy to obtain a basic evaluation unit; the streetscape image data, the satellite image data, the interest point data, the building attribute data and the building form data are preprocessed respectively, and visual features, social economic features and building form features are constructed; constructing a graph network structure of the graph neural network model; and according to the instance sample group, in combination with a graph network structure of the graph neural network model, constructing and training a GraphSAGE model so as to improve the recognition probability of the villages in the city. According to the method, the spatial interaction and regional relation between the network spatial structure and the multi-dimensional attributes are effectively understood through the GNN.

The invention relates to the field of building engineering planning, and provides a CIM-based building concession distance examination method, which aims at a building concession road red line single examination task in city information model CIM examination, calculates the shortest distance between a building and a road, compares the shortest distance with a theoretical minimum concession distance, and constructs a two-dimensional and three-dimensional collaborative examination mechanism to obtain a building concession distance. And automatic verification of the spatial relationship between the building contour and the road red line is realized. According to the method, the problems of accurate calculation and three-dimensional violation judgment of the building concession distance are mainly solved by taking a model passing the BIM examination as basic input and combining road red line data in a city information model CIM environment.

The invention belongs to the technical field of space geodetic survey observation data inversion regional land water reserve change, and provides a method and related equipment for inversion of land water reserves based on a Slepian basis function combined with GNSS three-dimensional deformation, and the method comprises the steps: obtaining vertical and horizontal deformation observation values of GNSS through simulation; determining a Slepian primary function of the target area according to the boundary data and a preset maximum expansion order, and further determining a function relationship between a Slepian coefficient of GNSS three-dimensional deformation and a Slepian coefficient driven by mass load change; determining an observation equation according to the function relationship, and resolving the observation equation by adopting least square joint adjustment; and according to the Slepian coefficient driven by the mass load change, carrying out inversion on the regional land water reserves of the target region to obtain a regional land water reserve change result. The method has the beneficial effect that the precision and efficiency of regional land water reserve inversion are improved.

The invention discloses an early warning control method for a performance stage, and the method comprises the steps: collecting performance stage data, building a stage model according to the collected stage data, and enabling the performance stage data to comprise stage boundary data and data of dynamic parts on the stage; acquiring foot coordinates of the actor and height coordinates from the ground by using a camera, detecting postures of the actor by using an image detection algorithm, and adjusting a risk area range of the stage according to the height from the actor to the ground; according to the foot position coordinates and speed of the actor obtained in real time, using an algorithm to predict the motion trail of the actor, and according to the real-time foot position coordinates and speed, calculating a falling risk factor; a height level matching module is embedded in the worker terminal, the position and height of the actor are detected in real time, the real-time state of the actor is recognized, and if it is judged that the actor is in a safe state, the bound worker terminal is unbound, and early warning prompt is stopped.