248 results about "Topographic map" patented technology

The invention discloses a power construction unmanned aerial vehicle path planning method and system, and relates to the technical field of space calculation, and the method comprises the following steps: determining a target region needing power construction and a preset construction point coordinate; obtaining a topographic map of the target area based on the geographic information database, constructing a three-dimensional map model, and marking the preset construction point coordinates; generating an initial construction path of the unmanned aerial vehicle; the method comprises the following steps: acquiring meteorological data in real time through meteorological data of a meteorological station in a target area, establishing a meteorological obstacle three-dimensional model, and dividing a preset radius threshold with a meteorological obstacle as a circle center into non-flying areas according to the severity level of the meteorological obstacle; adjusting the initial construction path based on the non-flying area; the cruise height is adjusted according to the meteorological data and topographic relief, a relief tracking path is generated, and the constant relative height is kept; and combining the battery capacity, the flight speed and the task priority, dynamically distributing inspection road sections, and generating a corresponding power construction unmanned aerial vehicle flight path.

The invention provides a GNSS-RTK-based topographic mapping method and system, and the method comprises the steps: obtaining multi-source positioning signal data in a target region, the multi-source positioning signal data comprising a satellite original observation value, a receiver antenna phase center deviation parameter, and real-time dynamic differential correction information; performing multi-path interference suppression processing on the multi-source positioning signal data to generate a phase observation sequence after interference suppression; inputting the phase observation sequence after interference suppression into a topographic feature calculation model, and extracting topographic elevation change feature parameters of the target area; performing spatial fusion processing based on the terrain elevation change characteristic parameters and reference elevation parameters in a preset terrain database to generate three-dimensional terrain curved surface data of the target area; and dynamically adjusting the topographic map updating frequency according to the difference degree between the three-dimensional topographic surface data and the historical topographic surveying and mapping result, and outputting a real-time topographic surveying and mapping result. According to the invention, precision, real-time performance and resource efficiency can be considered in complex terrain environment application.

The invention relates to the technical field of earthquake prediction, in particular to a submarine seismic oscillation prediction method and device based on earthquake exploration, and the method comprises the following steps: selecting a monitoring region, collecting the submarine topographic data of the monitoring region, and drawing a topographic map; selecting a plurality of monitoring points according to the topographic map; geomagnetic field information, electric wave information, micro-seismic activity information and seabed deformation information of each monitoring point are collected and recorded; converting the collected information into acoustic signals and transmitting the acoustic signals to a sea surface buoy, and converting the acoustic signals into electric signals by the sea surface buoy and transmitting the electric signals to a ground data center; by optimizing site selection of monitoring points, integrating geomagnetic-electric wave-microseismic-deformation multi-source data, realizing high-efficiency data transmission by using an acoustic-electric staged communication chain, and finally realizing early recognition of earthquake precursor in combination with threshold analysis, the method can significantly improve the coverage range, data precision and early warning timeliness of seafloor earthquake monitoring, and has good application prospects. And a technical support is provided for marine geological disaster prevention and control.

The invention discloses a marine surveying and mapping method based on multi-beam sounding correction, and belongs to the technical field of marine surveying and mapping. The method comprises the following steps: acquiring sounding echo signals, sound wave propagation time delay data and temperature data through a multi-beam sonar array, an acoustic chromatography transceiving array and a laser Raman probe; and fusing the data to construct a dynamic refractive index field model, correcting sound ray refraction distortion by adopting an adaptive variable step size algorithm, carrying out weight allocation and data fusion on space-time adjacent beams to obtain high-confidence water depth, and generating an isobath topographic map. The problem of refraction distortion is solved through multi-source data fusion, the sound ray tracking step length is dynamically optimized, noise interference is suppressed through weighted fusion, and the precision and reliability of topographic surveying and mapping in complex environments such as a deep sea hydrothermal region are remarkably improved.

The invention discloses a quadruped robot motion control method based on topographic map reinforcement learning. The quadruped robot motion control method comprises the following steps: S1, building a quadruped robot model; s2, constructing a topographic map confidence estimation model; s3, constructing a state estimation model; s4, constructing an actor network and a commentator network to train the quadruped robot model; and S5, acquiring data of the laser radar and the inertial measurement unit by using a sensor fusion technology, generating a height map around the quadruped robot in real time, and updating environmental terrain information. By introducing the topographic map confidence estimation model and combining topographic map generation and topographic uncertainty estimation, the motion strategy of the quadruped robot in a complex terrain can be adjusted in real time, the adaptability of the robot to irregular terrains, obstacles and topographic changes is remarkably improved, and the reliability of the quadruped robot is improved. And control errors and falling risks caused by topographic changes or sensor noise are reduced.

The invention relates to a southern grassland soil carbon reserve dynamic evaluation method and system fused with remote sensing monitoring, and relates to the technical field of soil carbon reserve evaluation, and the method comprises the steps: drawing a target region topographic map based on multi-source satellite remote sensing data, inputting an initial soil carbon reserve inversion model, and outputting an initial soil carbon reserve distribution diagram and a deterministic thermodynamic diagram; extracting an uncertain area according to a certainty degree threshold value, and configuring and labeling supplementary sampling points according to a division rule; acquiring parameter information of the detection robot, generating a digital twinborn model in combination with the topographic map, configuring a supplementary sampling scheme, and sampling supplementary sampling points to obtain supplementary soil carbon reserve data; and returning the supplemented soil carbon reserve data to the initial soil carbon reserve inversion model, generating a corrected soil carbon reserve distribution diagram and a corrected determinacy thermodynamic diagram, judging that the task is completed when determinacy reaches the upper limit of resource consumption, otherwise, continuing to supplement sampling correction. The problems that traditional soil carbon reserve assessment is inaccurate and low in efficiency are solved.

The invention discloses a grinding wheel wear degree identification method and device based on adaptive neural fuzzy reasoning. The method comprises the steps that a grinding temperature signal, grinding force and the surface quality of a workpiece are obtained; determining the abrasion stage of the grinding wheel according to the surface quality, the grinding force and the grinding temperature; extracting the total number of thermal pulses in the grinding temperature signal as the number of dynamic effective abrasive particles; a grinding wheel surface topography graph is obtained, abrasive dust and abrasive particle abrasion in the grinding wheel surface topography graph are recognized and distinguished through an HSV segmentation method, the area rate is calculated, and the abrasive dust proportion and the abrasive particle abrasion proportion are obtained; and the abrasive dust proportion, the abrasive particle abrasion proportion and the dynamic effective abrasive particle number serve as input, the abrasion stage serves as output, the self-adaptive neural fuzzy inference system is trained, and the trained self-adaptive neural fuzzy inference system is obtained for abrasion degree recognition. According to the method, the abrasion condition of the grinding wheel can be accurately and conveniently judged by utilizing the self-adaptive neural fuzzy reasoning technology and synthesizing the multi-dimensional characteristic signals in the grinding process.

The invention provides a base station electromagnetic radiation visual monitoring method and device, and the method comprises the steps: determining a three-dimensional topographic map of a monitoring region, carrying out the electromagnetic radiation measurement of an actual geographic position corresponding to a preset collection point on the three-dimensional topographic map, and obtaining the actual measurement data; obtaining beam characteristic parameters of each base station and space coordinate data of the actual geographic position, and calculating predicted electromagnetic radiation data of the actual geographic position according to the electromagnetic radiation prediction model; correcting the model, and calculating electromagnetic radiation data of a target area on the three-dimensional topographic map based on actually measured electromagnetic radiation data and the corrected electromagnetic radiation prediction model; and visually displaying the actually measured electromagnetic radiation data of the preset acquisition point and the electromagnetic radiation data of the target area. Therefore, accurate monitoring and visual display of the electromagnetic radiation of the base station are realized, so that the accuracy and reliability of electromagnetic radiation evaluation are improved, and the overall change rule of the electromagnetic radiation value of each position in the whole monitoring area can be visually observed.

The application discloses a room semantic segmentation method, which comprises the following steps: S1, acquiring a topographic map of a house, detecting door features on the topographic map, and generating a setting area based on the detection positions corresponding to the detected door features; S2, segmenting the setting area to segment out doors from the setting area, and then verifying the segmented doors to determine the shapes and positions of the doors; and S3, based on the shapes and positions of the doors, performing semantic classification on the topographic map, and then generating a topographic map after the semantic classification. The room semantic information of a grid image is recognized and segmented in a deep learning manner, the understanding of a scene semantic by a robot is improved, and different cleaning strategies or other work can be used for different rooms.

The embodiment of the invention discloses a low-altitude wind shear early warning method and device based on multi-source meteorological data. A specific embodiment of the method comprises the steps of generating a first region of interest for a target region according to a contour topographic map; determining a second region of interest according to the real-time rainfall distribution diagram and the real-time air temperature distribution diagram; performing region optimization on the first region of interest according to the real-time wind field graph to obtain a third region of interest; generating a fourth region of interest according to the second region of interest and the third region of interest; and according to the fourth region of interest and a pre-trained low-altitude wind shear prediction model, generating wind shear region early warning information. According to the embodiment, accurate prediction of the wind shear is realized, so that early warning is performed on the low-altitude aviation equipment, and the navigation safety of the low-altitude aviation equipment is ensured.

The invention discloses a dispenser height measurement method, a warping correction method, a dispenser and a storage medium, and relates to the field of dispensers. Controlling the carrying platform to drive the substrate to move, starting the laser transmitter to roughly measure the substrate, and obtaining initial point cloud data of the surface of the substrate; performing accuracy judgment on the initial point cloud data, determining material characteristics of the substrate according to a judgment result, and selecting a target height measurement mode; when a mixed height measurement mode is selected, identifying an abnormal key point and a target area of the initial point cloud data, and switching to a probe height measurement mode to perform fine measurement on the target area to obtain secondary point cloud data; the abnormal key points comprise intensity abrupt change points and boundary positions of the substrate; and carrying out point cloud processing fusion based on the initial point cloud data and the secondary point cloud data to generate a high-precision 3D morphology graph. According to the scheme, high-precision height measurement of substrates made of different materials is realized. The mixed height measurement mode overcomes the limitation of a single measurement mode, and improves the adaptability of the dispenser to various substrates.

The invention provides an underground building attribute information determination method, electronic equipment and a storage medium, and the method comprises the steps: obtaining an underground building image of a target underground building and carrying out the image correction, and obtaining a target underground building image; vectorizing the target underground building image to obtain underground building element images corresponding to the basement plane graph and the pile foundation plane graph; positioning the underground building element image based on the general plan and the topographic map, and determining the position of each building element; and determining attribute information of the target underground building structure based on the position and the element level of each building element. According to the invention, the indoor digital investigation method is adopted, the image and element information of the underground building is digitally acquired, and the digital technology of image correction, vectorization processing and space element positioning is combined for processing, so that the manpower and material resource cost is saved, and the progress and efficiency of underground building investigation are guaranteed.

The invention relates to the technical field of Beidou inspection data processing, and discloses an automatic inspection data acquisition and space-time association method under Beidou space-time reference. The method comprises the following steps: acquiring historical working condition data of inspection equipment based on nanosecond-level time synchronization and centimeter-level space positioning information of a Beidou system, and constructing a space-time dynamic prediction model; acquiring an equipment sensor measurement value, a moving track point set and a timestamp sequence in real time, and outputting a theoretical inspection value through a model; performing space-time multi-dimensional comparison on the theoretical value and the actual value, analyzing a time accumulation error, a space deviation degree and data flow form consistency, and generating a difference feature tensor; inputting the tensor into a geocoding topological reasoning network, simulating anomaly diffusion and generating an anomaly probability cloud picture in combination with topographic map node attributes and equipment distribution, and delineating an anomaly range; polling parameters are dynamically configured according to the cloud atlas, enhanced collection is started for a high-probability abnormal area, and data credibility inspection is executed on peripheral equipment.

The invention, which relates to the technical field of small watershed data management, discloses a multi-source data small watershed air-ground integrated intelligent monitoring and management system comprising a satellite remote sensing data acquisition subsystem, an unmanned aerial vehicle monitoring subsystem, a ground monitoring subsystem, a multi-source heterogeneous data fusion subsystem and a data intelligent supervision platform. The satellite remote sensing data acquisition subsystem is used for carrying out large-scale hydrological and ecological monitoring by utilizing a satellite remote sensing technology, and carrying out accurate retrieval according to a geographic position, a time range and a sensor type so as to find a specific data set meeting requirements; a user is allowed to browse a remote sensing image online, zoom-in and zoom-out operation is carried out on a specific area, meanwhile, multiple kinds of layer information are overlaid, the layer information comprises a topographic map, an administrative map and a road traffic map, and data export options are arranged in a subsystem of the system and comprise an original data file, a preprocessed product and a customized data packet.

The present invention discloses a topographic survey system for territorial spatial planning, which relates to the technical field of topographic survey. It includes an acquisition area division module for collecting historical topographic maps of the area to be measured, calculating the topographic complexity of each topographic survey sub-area, and determining the measurement method for each topographic survey sub-area; a measurement environment analysis module for collecting environmental data of the topographic survey sub-area during the time when lidar collects data, calculating the environmental error coefficient, and issuing an environmental error warning; a data acquisition module using a drone equipped with lidar to measure the topographic data of the topographic survey sub-area, marking the fine measurement area, and performing two measurements of the topographic data to form complete point cloud data; a topographic data analysis module for generating a measurement topographic map, comparing the initial topographic map with the measurement topographic map, identifying the different parts, and outputting them as the changed areas of the territorial spatial planning. It can accurately identify the changes in the terrain and can more reasonably adjust and optimize the planning layout.

The invention discloses a riverway section optimization processing method in a one-dimensional hydrodynamic model modeling process, which comprises the following steps: extracting section topographic data from a riverway topographic map, drawing an image of each section based on the section topographic data, and determining a riverway slope through the lowest point elevation of each section diagram; an L-shaped and / or linear cross section is presented for the overtopping, and the cross section of the river channel is linearly extended; inserting a certain number of new river channel sections into two adjacent river channel sections of which the elevation difference is greater than a preset elevation difference; and simulating the corresponding water level of the river channel section at the end moment specified by the model through the original river channel section data, extracting the extended and interpolated river channel section data based on the corresponding water level of the river channel section, and retaining effective river channel section data. The method has the advantages that the river section optimization efficiency is effectively improved, the operation is simple, the labor cost and the time cost of data optimization are greatly saved, and the requirement of efficiently and accurately constructing a model can be well met.

The invention discloses a multi-sensor information monitoring and self-adaptive radius-controllable turning method for a cotton field plant protection machine, and the method comprises the following steps: 1, recognizing a cotton plant through the fusion of a YOLO v5 visual model and multispectral imaging, and achieving the 3D space positioning of the plant through the combination of LiDAR point cloud data and an ICP registration algorithm; 2, constructing a high-precision farmland topographic map to realize soil topographic change detection by adopting a point cloud denoising technology assisted by time sequence Kalman filtering and semantic segmentation; 3, dynamically changing the turning radius and the rotating speed according to different cotton field plant space positions and soil topographic changes; according to the collaborative innovation scheme, the steering precision and crop protectiveness of the agricultural machine in the complex environment of the cotton field can be remarkably improved, and the method is suitable for large-scale cotton field harvesting scenes and has the industrialization potential of low cost and high reliability.

Method, system, and non-transitory computer readable storage medium are provided for creating a shelf bathymetric map. In some embodiments, a satellite image with a shelf area and related altimeter data for at least a number of points of the shelf area are obtained. The shelf area in the satellite image and depth values for the shelf area from said altimeter data are selected. The selected depth values are associated with points of the shelf area based on geo-coordinates. A training dataset and a testing dataset are created from the associated points. A neural network is trained on the training dataset. The neural network is tested on the testing dataset. Inference of the neural network is adjusted based on testing results. A depth value for each satellite image pixel of the shelf area is predicted by the neural network.

The present invention discloses an optimized energy allocation method and system for an electric vehicle and an electric vehicle. The method includes step (1) detecting remaining charge levels of a first super-capacitor and a second super-capacitor, determining whether the remaining charge levels of the first super-capacitor and the second super-capacitor are greater than a preset threshold value, and if so, proceeding to step (2); step (2) acquiring a topographic map of a road ahead by means of an electric horizon system, predicting whether there is a continuous slope ahead, and if so, proceeding to step (3); and step (3) according to a continuous slope value ahead, predicting a braking force allocation proportion when carrying out braking ahead, allocating current power outputs of the first super-capacitor and the second super-capacitor in advance according to the braking force allocation proportion, and returning to step (1).

The invention relates to the technical field of environment monitoring, in particular to a deep sea polymetallic nodule mining area plume boundary expansion rate estimation method combined with vortex structure evolution, which comprises the following steps: S1, collecting disturbed flow field data and a submarine topography map, and calculating the expansion rate of the plume boundary of a deep sea polymetallic nodule mining area on the basis of a disturbed intensity change rate and a spatial adjacency relation between the disturbed intensity change rate and topographic protrusions; constructing a structure intermittent mark area and identifying a terrain trigger point; s2, tracking a vortex evolution stage and interference characteristics in the marked area, extracting boundary jump key factors and generating a jump event set; and S3, mapping the jump event to a boundary trajectory, generating a discontinuous expansion rate diagram in combination with a terrain trigger weight, and outputting a nonlinear propulsion trend. According to the method, accurate modeling and dynamic estimation of the nonlinear propulsion trend of the plume boundary are realized by constructing a disturbance-terrain coupling mark area, extracting vortex structure evolution information and a boundary jump event and combining the terrain triggering weight to generate a discontinuous expansion rate distribution diagram.

The invention relates to the technical field of intelligent calculation of earth-rock work amount, and discloses an earth-rock calculation method and device for wind power plant road construction and a storage medium. Comprising the following steps: S1, acquiring topographic point cloud, engineering geology and meteorological time series data of a wind power plant construction area through sensing equipment; s2, constructing a topographic map structure, generating an adjacent matrix and extracting space-time diagram convolution features; s3, constructing and solving a dynamic differential model based on the features, and predicting the volume change of earthwork; s4, improving the solving efficiency by adopting a mixed precision heterogeneous calculation strategy; and S5, introducing a geomechanical constraint optimization prediction result, and outputting a construction area earth-rock distribution diagram. According to the method, the spatial structure characteristics of the complex terrain of the wind power plant are extracted by adopting the graph convolutional neural network, a high-fidelity modeling effect on the terrain form of the road construction area is realized, and the defect that terrain detail information is difficult to express is overcome.

The invention relates to computer aided design, and discloses a Braille printing method and system combined with 3D relief, and the method comprises the steps: carrying out the connection and fusion of a concave-convex topographic map and a multi-level depth map corresponding to each Braille dot matrix, and generating a dual-channel depth map as a printing pattern; controlling the 3D printing system to spray resin on the printing substrate based on the printing pattern read by the light field modulator, and scanning the surface of the resin by laser aiming at the braille dot matrix area to form a concave-convex structure corresponding to the concave-convex topographic map; on the adjacent side of the braille dot matrix area, a multi-wavelength DLP projection system is used for executing layered exposure, the embossment structure represented by the multi-level depth map is projected to the resin layer, and an embossment model is formed; and performing global curing on the whole printed piece based on ultraviolet light to form an integrated finished product of braille alphabets and 3D embossments. The invention further discloses a computer readable storage medium. The method aims at efficiently manufacturing seamless and high-precision multi-layer 3D embossment integrated finished products of braille alphabets and related semantics.

The invention belongs to the technical field of landslide identification and prediction, and particularly relates to a landslide distribution probability prediction method and system based on remote sensing data, and the prediction method comprises the following steps: step 1 to step 6, selecting a research area, capturing remote sensing data, describing a curved surface form of the research area, and constructing a digital elevation model; after screening, introducing elevation data into MATLAB software, and drawing a three-dimensional topographic map in a three-dimensional coordinate system; constructing a landslide probability model, simulating variables in the landslide, deducing seismic data, and deducing slope data; constructing a WGEN model, and deducing a precipitation density function of the research area based on GAMMA distribution to realize precipitation simulation; the prediction system comprises a web crawler module, a local database, a processor and a touch screen. According to the method, the elevation and rainfall of the plateau area are associated, multiple models are constructed, the landslide distribution probability accuracy is high, and risk early warning can be carried out within 3 hours after an earthquake.

The present invention relates to the technical field of unmanned aerial vehicles, and discloses a low-error mapping method and system based on unmanned aerial vehicle mapping. The method includes: using an unmanned aerial vehicle to collect ground point cloud images, and obtaining all overlapping regions of consecutive frame point cloud images; obtaining a set of three-dimensional coordinates of each position point in the overlapping region in all relevant frames, calculating the degree of dispersion of each set of three-dimensional coordinates, and optimizing each set of three-dimensional coordinates of the overlapping region based on a preset dispersion threshold to obtain an optimal set of three-dimensional coordinates for each position point; the relevant frames are all frame images containing a position point for any position point; calculating the mean value of each dimension in the optimal set of three-dimensional coordinates to obtain the optimal three-dimensional coordinates of the corresponding position point, and then using the optimal three-dimensional coordinates of all position points to draw a topographic map. The present invention can improve the accuracy of mapping and make the drawn topographic map more accurately reflect the actual terrain and landform.

The application provides a method and device for planning an inspection route, electronic equipment and a storage medium. The method comprises the following steps: obtaining a digital orthographic image and a digital elevation model of a target photovoltaic power station area; generating a three-dimensional topographic map of the target photovoltaic power station area according to the digital orthographic image and the digital elevation model; determining a string center position and a string orientation of the photovoltaic string in the three-dimensional topographic map; and planning an inspection route of a camera of a flying machine for the photovoltaic string according to camera parameters of the flying machine and the string center position and the string orientation of the photovoltaic string. The three-dimensional topographic map can be used to more accurately determine the string center position and the string orientation, and then, according to the camera parameters of the flying machine and the string center position and the string orientation of the photovoltaic string, a more accurate inspection route planning result can be obtained, thereby improving the accuracy of the inspection route planning.

The application discloses a PLA composite material and a preparation method and application thereof, and belongs to the field of high polymer materials. The application adds a specific amount of a specific aromatic polycarbodiimide into polylactic acid, and controls the weight average molecular weight, the polydispersity coefficient and the D-lactic acid structural unit content of the obtained PLA resin within a specific range, so that the PLA resin has good wire drawing performance and low yellowness, is suitable for the high-speed 3D printing wire market, and the obtained wire can be used for 3D printing toys, ornaments, medical human simulation organs, artworks, topographic maps, house models and the like.

The invention provides a new energy station accessory building layout planning method based on multi-source data collaboration, and the method comprises the steps: obtaining and fusing a topographic map, unmanned plane laser point cloud and GIS data, and generating corrected topographic data; drawing a station general plane graph containing a building contour, an elevation and a road network; coupling the point cloud with the general drawing, and performing three-dimensional adjustment on the site elevation to obtain a preliminary scheme; analyzing the foundation bearing capacity according to the elevation and determining the building height; building primary arrangement is conducted according to the height; and finally, calculating spacing and sunshine and wind pressure influence factors, and iteratively optimizing the layout. The layout rationality, the construction feasibility and the structure safety can be improved, and the construction cost and risks are reduced.

The present invention discloses a complex terrain analysis method based on the fusion of airborne LiDAR and spaceborne multispectral images, comprising: acquiring multispectral images and point cloud data; generating a depth map based on the point cloud data; performing rough registration on the depth map and the multispectral images to obtain rough registration point pairs; establishing a two-dimensional to three-dimensional conversion model by using the rough registration point pairs and the elevation values of the point cloud data; determining the fine registration coefficient through a search algorithm with the maximum mutual information value between the point cloud depth map and the multispectral images as the measure; converting the multispectral images according to the fine registration coefficient and the conversion model to obtain converted images; performing dynamic feature fusion on the converted images and the point cloud data to generate fusion data; generating a contour topographic map by using elevation information and displaying it in the multispectral images; and analyzing the complex scene in cooperation with the contour topographic map and the fusion data. The present invention reduces the time cost, improves the registration and fusion efficiency of heterogeneous data, and provides support for the analysis of complex scene conditions.

The invention discloses a debris flow early warning judgment method and system, and belongs to the technical field of hydraulic engineering, and the method comprises the following steps: a, determining the gully bed longitudinal gradient and the area of a drainage basin formation region of potential gully-type debris flow through a topographic map; b, obtaining lithology types of gully-type debris flow, and classifying the lithology types of the gully-type debris flow; c, calculating topographic indexes of gully-type debris flow; d, calculating a rainfall index for inducing gully-type debris flow; e, calculating an early warning discrimination index of the gully-type debris flow; and f, according to the early warning discrimination indexes of the gully-type debris flow, dividing early warning levels of the gully-type debris flow with different lithology. According to the method, a quantitative comprehensive early warning judgment index is constructed, the scientificity and accuracy of judgment of the debris flow starting critical condition are remarkably improved, multi-stage dynamic early warning from extremely low risk to high risk is achieved, and a direct operable technical basis is provided for accurate implementation of graded emergency response and disaster prevention resource allocation.

The invention provides a risk identification method and device for a fan impeller to sweep obstacles, electronic equipment and a storage medium. The risk identification method comprises the following steps: constructing a simulated topographic map for simulating the topographic condition after the construction of the wind power plant is completed based on an actually measured topographic map of the wind power plant and the construction information of each machine site; inputting the wind parameter information of each machine position point and the set information of the fan to be installed at each machine position point into a fan load simulation model to obtain the tower top displacement information after each fan is installed and operated; taking the terrain point with the risk to be identified around each machine location point as a target terrain point, and determining the minimum distance from the hub center of the target fan to the obstacle at the target terrain point based on the tower top displacement information of the target fan to be installed at the machine location point, the height of the obstacle at the target terrain point and the simulated topographic map; and if the difference value between the minimum distance and the radius of the impeller is smaller than a preset threshold value, it is determined that the target fan has the risk that the impeller sweeps the obstacle at the target terrain point.