BIM-based overhead transmission line high-precision three-dimensional modeling method and system

Abstract

The invention relates to a BIM-based overhead transmission line high-precision three-dimensional modeling method and system, and relates to the technical field of digital twinning, and the method comprises the steps: obtaining surveying and mapping data, meteorological data and satellite remote sensing image data; constructing and forming surveying and mapping modeling based on the identified and segmented parts of the power transmission line and the surveying and mapping data; a dynamic effect simulation scheme is adopted for meteorological data, and an environment updating scheme is adopted for satellite remote sensing image data; the method comprises the following steps: acquiring parameter modeling used for representing a logical relationship between internal parts of a power transmission line, and simulating model external characteristic changes brought by meteorological data dynamic effect simulation and satellite remote sensing image data surrounding environment updating; adjusting a fusion mode of a logical relationship and a structure of internal parts of the power transmission line involved in surveying and mapping modeling and parameter modeling to obtain a fusion model; and performing physical rendering on the fusion model to obtain a three-dimensional model of the power transmission line. The method has the effect of improving the model precision of the three-dimensional model of the power transmission line.

Description

Technical Field

[0001] The present application relates to the field of digital twin technology, and in particular to a high-precision three-dimensional modeling method and system for overhead transmission lines based on BIM. Background Art

[0002] Since the concept of digital twin power grid was proposed, it has played an increasingly important role in the power grid system. With the rapid development and deep integration of technologies such as the Internet of Things, big data, cloud computing, and artificial intelligence, scenario modeling based on digital twin power grid will surely achieve a qualitative breakthrough.

[0003] The related technology uses patrol robots or drones to scan the various equipment and structures of the transmission lines to obtain the three-dimensional data of the transmission lines. The three-dimensional data is then used to build a model based on the actual transmission line scene using 3Dmax or Maya three-dimensional modeling software on the Unity development platform to provide a highly simulated three-dimensional model of the transmission line.

[0004] Regarding the above-mentioned related technologies, the inventors believe that the three-dimensional models obtained by the related technologies are not accurate enough and cannot display the details of the transmission lines. Summary of the invention

[0005] In order to improve the model accuracy of the three-dimensional model of the transmission line, the present application provides a high-precision three-dimensional modeling method and system for overhead transmission lines based on BIM.

[0006] In the first aspect, the present application provides a high-precision three-dimensional modeling method for overhead transmission lines based on BIM, which adopts the following technical solutions: A high-precision three-dimensional modeling method for overhead transmission lines based on BIM, comprising: Acquire surveying and mapping data, meteorological data and satellite remote sensing image data. The surveying and mapping data is obtained by surveying the real scene of the transmission line. The surveying and mapping data includes laser point cloud data and oblique photography data. Apply the trained power transmission line deep analysis model to the surveying and mapping data, automatically identify and segment the various parts of the power transmission line, and build a surveying and mapping model based on the identified and segmented parts of the power transmission line and the surveying and mapping data; A preset dynamic effect simulation scheme is used for meteorological data to realize dynamic effect simulation of the three-dimensional model of the power transmission line, and a preset environmental update scheme is used for satellite remote sensing image data to realize the surrounding environment update of the three-dimensional model of the power transmission line; Obtain parameter modeling for representing the logical relationship between the internal components of the transmission line, and adjust the fusion method of the logical relationship and structure of the internal components of the transmission line involved in the surveying and mapping modeling and parameter modeling according to the changes in the external characteristics of the model brought about by the completed dynamic effect simulation of meteorological data and the update of the surrounding environment of satellite remote sensing image data, and obtain a fusion model; The fused model is physically rendered to obtain a three-dimensional model of the transmission line.

[0007] By adopting the above technical solution, surveying and mapping modeling is formed through surveying and mapping data, meteorological data and satellite remote sensing image data, and the fusion method of the logical relationship and structure of the internal components of the transmission line involved in surveying and mapping modeling and parameter modeling is adjusted to obtain a fusion model, which makes the surveying and mapping modeling closer to the actual transmission line and further improves the accuracy of the three-dimensional model.

[0008] Optionally, data sorting and preprocessing are performed on the acquired meteorological data; The meteorological data that have been sorted and preprocessed are used as input parameters and are respectively input into the established physical models corresponding to different meteorological conditions. The physical models after the meteorological data are input are numerically simulated using the numerical simulation method that matches the established physical model to obtain the dynamic response results of each component of the transmission line under different meteorological conditions. The dynamic response results obtained from the numerical simulation calculation are processed and converted into a format that can be displayed in the three-dimensional modeling software, and the converted dynamic response results are integrated with the three-dimensional model of the transmission line using the three-dimensional modeling software.

[0009] By adopting the above technical solution, the meteorological data is sorted and preprocessed, and the dynamic response results of each component under different meteorological conditions can be obtained, so that the three-dimensional model can reflect more details of the actual transmission line.

[0010] Optionally, extract and analyze meteorological parameter combinations from the organized and pre-processed meteorological data, and use a preset trained decision tree model to analyze and determine whether an extreme weather scenario occurs; If no, continue with the next steps; If yes, a pre-established scenario category judgment model is used to further analyze and determine the extreme scenario category, and a corresponding specific physical model is selected from a pre-established physical model library. A numerical simulation method matching the specific physical model is used to perform calculations to obtain the dynamic response results of each component of the transmission line under the corresponding extreme weather scenario.

[0011] By adopting the above technical solution, the model is endowed with dynamic response capabilities under extreme scenario categories, so that the three-dimensional model can also simulate details in extreme weather scenarios.

[0012] Optionally, data collation and preprocessing are performed on the acquired satellite remote sensing image data; Extract the features of ground objects from the pre-processed satellite remote sensing image data, and classify the ground objects using a preset classification algorithm; Compare and analyze satellite remote sensing image data acquired at different times, calculate the degree of change of the objects, and extract the areas that have changed based on the comparative analysis results of satellite remote sensing image data acquired at different times, mark and record the changed areas, and clarify the type and scope of the change. The types of change include new objects, disappeared objects, and changes in object attributes; The surrounding environment of the three-dimensional model of the transmission line is updated according to the calculated degree of change of the ground object and the type and scope of the change.

[0013] By adopting the above technical solution, the surrounding environment of the three-dimensional model of the transmission line can be updated by utilizing the degree of change of the ground objects and the type and scope of the change, so as to realize real-time update of the three-dimensional model and ensure the availability of the three-dimensional model.

[0014] Optionally, analyze whether the meteorological data determines the extreme scenario category; If not, maintain the original setting; If yes, then according to the correspondence between the extreme scene category and the monitoring and classification scheme of ground objects changes around the transmission line under remote sensing images, the matching monitoring and classification scheme of ground objects changes around the transmission line under remote sensing images is analyzed and determined, and the monitoring and classification scheme of ground objects changes around the transmission line under remote sensing images is executed.

[0015] By adopting the above technical solution, the monitoring and classification scheme of ground objects changes around transmission lines under remote sensing images is executed according to the correspondence between extreme scene categories and the monitoring and classification scheme of ground objects changes around transmission lines under remote sensing images.

[0016] Optionally, the potential landslide area and potential vegetation destruction area are analyzed and determined based on the comparative analysis results of satellite remote sensing image data obtained at different times in the mountain area and vegetation-related areas; The potential landslide areas and potential vegetation destruction areas determined through analysis are specifically marked, and relevant information of the changed areas is recorded.

[0017] By adopting the above technical solution, potential landslide areas and potential vegetation damage areas are specifically marked respectively, and relevant information of the changed areas is recorded, so that the accuracy of the three-dimensional model can be guaranteed.

[0018] In a second aspect, the present application provides a scene modeling system for a power transmission line, which adopts the following technical solution: A scene modeling system for a power transmission line, comprising: The acquisition module is used to obtain surveying and mapping data, meteorological data, satellite remote sensing image data, scene category judgment models, extreme scene categories, mountain areas and vegetation-related areas; A memory for storing a program of any one of the above-mentioned scenarios modeling methods for power transmission lines; The program in the processor memory can be loaded and executed by the processor to implement any of the above-mentioned scene modeling methods for power transmission lines.

[0019] By adopting the above technical solution, surveying and mapping modeling is formed through surveying and mapping data, meteorological data and satellite remote sensing image data, and the fusion method of the logical relationship and structure of the internal components of the transmission line involved in surveying and mapping modeling and parameter modeling is adjusted to obtain a fusion model, which makes the surveying and mapping modeling closer to the actual transmission line and further improves the accuracy of the three-dimensional model.

[0020] In a third aspect, the present application provides a smart terminal, which adopts the following technical solution: An intelligent terminal includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute any of the above-mentioned BIM-based overhead transmission line high-precision three-dimensional modeling methods.

[0021] By adopting the above technical solution, surveying and mapping modeling is formed through surveying and mapping data, meteorological data and satellite remote sensing image data, and the fusion method of the logical relationship and structure of the internal components of the transmission line involved in surveying and mapping modeling and parameter modeling is adjusted to obtain a fusion model, which makes the surveying and mapping modeling closer to the actual transmission line and further improves the accuracy of the three-dimensional model.

[0022] In a fourth aspect, the present application provides a computer storage medium capable of storing a corresponding program, which has the characteristic of facilitating the improvement of the model accuracy of the three-dimensional model of the transmission line, and adopts the following technical solution: A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any one of the above-mentioned BIM-based high-precision three-dimensional modeling methods for overhead transmission lines.

[0023] By adopting the above technical solution, surveying and mapping modeling is formed through surveying and mapping data, meteorological data and satellite remote sensing image data, and the fusion method of the logical relationship and structure of the internal components of the transmission line involved in surveying and mapping modeling and parameter modeling is adjusted to obtain a fusion model, which makes the surveying and mapping modeling closer to the actual transmission line and further improves the accuracy of the three-dimensional model.

[0024] In summary, the present application includes at least one of the following beneficial technical effects: The surveying and mapping modeling is formed by using surveying and mapping data, meteorological data and satellite remote sensing image data, and the fusion method of the logical relationship and structure of the internal components of the transmission line involved in the surveying and mapping modeling and parameter modeling is adjusted to obtain a fusion model, so that the surveying and mapping modeling is closer to the actual transmission line and the accuracy of the three-dimensional model is further improved; After data sorting and preprocessing of meteorological data, the dynamic response results of each component under different meteorological conditions can be obtained, so that the three-dimensional model can reflect more details of the actual transmission line; The model is given dynamic response capabilities in extreme scenario categories, so that the three-dimensional model can simulate details even in extreme weather scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 The present application discloses a flow chart of a method for high-precision three-dimensional modeling of overhead transmission lines based on BIM.

[0026] Figure 2 It is a flow chart of a method for generating a three-dimensional model disclosed in an embodiment of the present application.

[0027] Figure 3 It is a flow chart of a method for generating dynamic response results of extreme weather scenarios disclosed in an embodiment of the present application.

[0028] Figure 4 It is a flowchart of a method for updating features disclosed in an embodiment of the present application.

[0029] Figure 5 The present application discloses a flow chart of a method for monitoring changes in terrain around a power transmission line.

[0030] Figure 6 It is a flowchart of a path-finding method based on a three-dimensional model disclosed in an embodiment of the present application.

[0031] Figure 7 It is a flowchart of a path-finding method based on a three-dimensional model disclosed in an embodiment of the present application.

[0032] Figure 8 It is a flowchart of a method for setting a virtual fence disclosed in an embodiment of the present application.

[0033] Fig. 9 It is a flowchart diagram of a homework process teaching method disclosed in an embodiment of the present application.

[0034] Fig.10 It is a flow chart of a method for determining a fault point disclosed in an embodiment of the present application.

[0035] Fig.11It is a flow chart of a method for determining a potential fault point disclosed in an embodiment of the present application.

[0036] Fig.12 It is a structural schematic diagram of a scene modeling system for a power transmission line disclosed in an embodiment of the present application. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-12 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0038] The present application embodiment discloses a flow chart of a high-precision three-dimensional modeling method for overhead power transmission lines based on BIM. Figure 1 , the scenario modeling method of the transmission line includes: Step S101: Acquire surveying and mapping data, meteorological data, and satellite remote sensing image data. The surveying and mapping data is obtained by surveying the real scene of the power transmission line. The surveying and mapping data includes laser point cloud data and oblique photography data.

[0039] Transmission lines include power grids, stations and various types of transmission equipment.

[0040] Laser point cloud data is a three-dimensional data set obtained through laser scanning technology, which is used to represent the spatial structure of the real scene of the power transmission line. For example, by scanning the real scene of the power transmission line through laser radar and combining it with computer vision marking technology, centimeter-level laser point cloud data can be obtained.

[0041] The oblique photography data is aerial image data obtained by oblique photography technology. Optionally, the oblique photography data is obtained by a drone capturing ground images through a camera at an oblique angle.

[0042] Furthermore, laser point cloud data provides high-precision spatial location data, which can accurately capture the geometric shape of the real scene of the transmission line. Oblique photography data provides texture information and color information, which can show the appearance details of the real scene of the transmission line.

[0043] Furthermore, the oblique photography data is composed of multiple oblique photography images. It is necessary to perform image registration on the aforementioned images to ensure that all images are in the same coordinate system, and to perform geometric correction on the images to eliminate image distortion. After that, the texture information in all images is extracted, and the texture information includes texture coordinates, color information, and texture material. The spatial coordinates of each point in all images are determined, and the correspondence between the spatial coordinates of the points and the texture information is constructed. The oblique photography data includes texture information, the spatial coordinates of the points, and the correspondence between the spatial coordinates of the points and the texture information.

[0044] Step S102: Apply the trained power transmission line deep analysis model to the surveying and mapping data, automatically identify and segment the various parts of the power transmission line, and construct a surveying and mapping model based on the identified and segmented various parts of the power transmission line and the surveying and mapping data.

[0045] The transmission line deep parsing model is used to automatically identify and segment the various sections of the transmission line.

[0046] The transmission line deep analysis model is also used to construct surveying and mapping modeling based on various parts of the transmission line and surveying and mapping data.

[0047] Step S103: adopting a preset dynamic effect simulation scheme for meteorological data to realize dynamic effect simulation of the three-dimensional model of the power transmission line, and adopting a preset environment update scheme for satellite remote sensing image data to realize surrounding environment update of the three-dimensional model of the power transmission line.

[0048] The dynamic effect simulation scheme is used to simulate the dynamic effects of three-dimensional models under different meteorological conditions.

[0049] The environmental update scheme is used to update the 3D model according to the changes in the environment around the transmission line.

[0050] Step S104: Obtain parameter modeling for representing the logical relationship between the internal components of the transmission line, and adjust the fusion method of the logical relationship and structure of the internal components of the transmission line involved in the surveying and mapping modeling and the parameter modeling according to the changes in the external characteristics of the model brought about by the completed dynamic effect simulation of meteorological data and the surrounding environment update of satellite remote sensing image data to obtain a fusion model.

[0051] Optionally, parameter modeling is recorded using BIM files and GIM files, where BIM files are used for building information modeling and GIM files are used for geographic information modeling. On the basis of surveying and mapping modeling, BIM files and GIM files are used to perform structured annotation and component decomposition on surveying and mapping modeling, so that surveying and mapping modeling is structured and hierarchical with a high realistic effect.

[0052] Optional steps based on survey data are as follows: 1. Data preprocessing: remove noise data from laser point cloud data and oblique photography data.

[0053] Noise data refers to data that contains errors or anomalies. For example, noisy data is data on a non-transmission line, or noisy data is data that exceeds the maximum value.

[0054] 2. Coordinate transformation: align the laser point cloud data and oblique photography data to the same coordinate system.

[0055] Acquire the feature points in the laser point cloud data and the oblique photography data; align the laser point cloud data and the oblique photography data to the same coordinate system by matching the feature points.

[0056] For example, significant points of the real scene of the power transmission line are set, and feature points corresponding to the significant points in the laser point cloud data and the oblique photography data are obtained. For example, the end point of the tower is used as a significant point, and data corresponding to the significant point is searched in the laser point cloud data and the oblique photography data as a feature point.

[0057] Exemplarily, the laser point cloud data and the oblique photography data are aligned to the same coordinate system through an ICP (Iterative Closest Point) algorithm, and the initial transformation matrix of the ICP algorithm is set according to the above-mentioned feature points.

[0058] 3. Texture mapping: Map the texture information of oblique photography data to the laser point cloud data.

[0059] Optionally, the corresponding oblique photography data is determined according to the spatial coordinates of each point in the laser point cloud data, and the oblique photography data is mapped to the corresponding point. That is, texture mapping determines the correspondence between each point in the laser point cloud data and the texture information.

[0060] 4. Modeling generation: obtain surveying and mapping modeling through laser point cloud data.

[0061] Step S105: Perform physical rendering on the fusion model to obtain a three-dimensional model of the transmission line.

[0062] Physical rendering can improve the surface properties of the fused model, ambient lighting, lighting models, BRDF (Bidirectional Reflectance Distribution Function) and texture maps.

[0063] Exemplarily, ambient light and reflected ambient light are simulated by physical rendering.

[0064] Exemplarily, the lighting models include Lambertian lighting and Fresnel Effect, wherein Lambertian lighting is used to simulate diffuse lighting and is suitable for rough or non-smooth surfaces; Fresnel effect is used to describe the change in reflection intensity of light at different incident angles and is suitable for simulating reflection of smooth surfaces (such as water or glass).

[0065] BRDF is used to describe the angular distribution of light reflected from a surface.

[0066] Exemplarily, the texture map of the fusion model is updated according to the texture information of the oblique photography data, wherein the texture map includes a color map, a normal map, a highlight map, a roughness map and a metalness map.

[0067] In other aspects of the present application, due to various influences of reality, various accidents may occur in the transmission line, such as: Impact of bad weather: In severe weather such as heavy rain, landslides and mud-rock flows may occur in the mountains near the transmission lines, destroying the tower foundations and breaking the conductors. Impact of flying birds: Due to strong winds and the natural migration of birds, birds may be blown into transmission lines or build nests on towers, causing line short circuits, grounding and other faults; Impact of floating objects: In windy weather, floating objects such as plastic films and kites may be blown onto transmission lines, causing line short circuits, tripping and other faults. Therefore, when modeling fusion, geological and hydrological risk factors such as landslides, mudslides, and floods will also be incorporated into the fusion model, and the impact of bird activities and floating objects on transmission lines will also be considered, and corresponding identification and early warning mechanisms will be added to the fusion model.

[0068] In response to the impact of severe weather: Based on meteorological data and feedback from monitoring equipment, scenarios such as tower destruction and wire breaking are simulated, allowing the three-dimensional model to more realistically reflect the situation when the disaster occurs.

[0069] Regarding the impact on flying birds: Bird habitats can be marked in surveying and modeling, and potential risk areas and warning status can be displayed in real time based on meteorological data and feedback from monitoring equipment.

[0070] Optionally, dynamic effects, such as bird flight trajectories, can be added to the fusion model to improve the visualization of potential risks. At the same time, the bird repellent effect and bird activity can be added and displayed in real time in the fusion model in combination with the working status of the bird repellent device. Furthermore, regarding the simulation of birds in the three-dimensional model, bird particles are generated based on the bird monitoring data, and their positions and behaviors are updated using particle systems and behavioral model algorithms. When birds approach the line, visualization effects of the electric or magnetic field can be displayed in the model to indicate the potential impact of the presence of birds on the line. If a bird collides with the line, the location can be marked in the model and the operation and maintenance personnel can be notified to handle it.

[0071] Regarding the impact of floating objects: areas prone to floating objects can be marked in surveying and modeling, and potential risk areas and warning status can be displayed in real time based on meteorological data and feedback from monitoring equipment.

[0072] Optionally, when the video surveillance equipment detects that there are floating objects approaching the line, the location is automatically marked in the three-dimensional model and the operation and maintenance personnel are notified to handle it.

[0073] Optionally, generate corresponding particles in the 3D model according to the type and size of floating objects. Use fluid dynamics algorithms to calculate the effect of wind and update the position and speed of floating object particles. If floating objects collide with the line, mark the location in the 3D model and notify the operation and maintenance personnel to handle it. The specific implementation steps can be referred to as follows: The first step is to collect historical and current wind data, including wind speed, wind direction, air pressure and other meteorological information. At the same time, the location, quantity, type and other data of floating objects can also be obtained by means of video monitoring equipment and sensor networks.

[0074] Step 2: Use the particle filter algorithm to predict the future trajectory of floating particles. Based on the historical data and current state of the wind, a large number of particles are generated to represent the possible future positions of floating objects. Each particle has an initial position and velocity, and the position and velocity of the particle are updated over time according to the force of the wind and other physical laws.

[0075] Step 3: Combine the geographic information system (GIS) data and the location information of floating objects, and use the path planning algorithm to plan the best cleaning path for the cleaning personnel or equipment. First, load the terrain, obstacles and other information into the GIS system to build a map model of the cleaning area. Use the A* algorithm or Dijkstra algorithm to determine the best path from the current location to the location of the floating object with the goal of shortest cleaning time or lowest cost.

[0076] Step 4: Use a clustering algorithm to perform cluster analysis on the locations of multiple floating objects. The K-Means clustering algorithm can be used to cluster the floating objects according to their location coordinates. For example, randomly select K initial cluster centers, and then assign each floating object to the cluster with the closest cluster center. Calculate the center position of each cluster and re-determine the cluster center. Repeat the above steps until the cluster center no longer changes or the preset number of iterations is reached. Group floating objects that are close together so that cleaning resources can be concentrated for processing. Based on the clustering results, analyze the number and importance of floating objects in each cluster and determine the key areas that need to be cleaned up. For example, clusters close to power lines or important facilities can be cleaned up first. At the same time, determine the priority of cleaning up based on the type of floating objects and the potential degree of harm. This can improve cleaning efficiency and reduce cleaning costs.

[0077] In summary, surveying and mapping modeling is formed by using surveying and mapping data, meteorological data and satellite remote sensing image data, and the fusion method of the logical relationship and structure of the internal components of the transmission line involved in surveying and mapping modeling and parameter modeling is adjusted to obtain a fusion model, which makes the surveying and mapping modeling closer to the actual transmission line and further improves the accuracy of the three-dimensional model.

[0078] The present application embodiment discloses a flow chart of a method for generating a three-dimensional model. Figure 2 , the scenario modeling method of the transmission line includes: Step S201: sorting and preprocessing the acquired meteorological data.

[0079] The data sorting in this step is used to process or transform the meteorological data, for example, normalize the meteorological data, classify the meteorological data, or increase or decrease the dimension of the meteorological data.

[0080] The preprocessing in this step is used to process abnormal values ​​in meteorological data. The preprocessing method includes at least one of deleting abnormal values, modifying abnormal values, or replacing them with reasonable values.

[0081] Optionally, the type of weather scene is determined by meteorological data.

[0082] Step S202: The meteorological data that has been sorted and preprocessed is used as input parameters and respectively input into the established physical models corresponding to different meteorological conditions, and a numerical simulation method that matches the established physical model is used to perform numerical simulation calculations on the physical model after the meteorological data is input, so as to obtain the dynamic response results of each component of the transmission line under different meteorological conditions.

[0083] Optionally, the meteorological conditions include at least one of strong wind, rain, snow, sunny days, and freezing.

[0084] The meteorological data includes at least one of temperature, humidity, wind speed, wind direction, precipitation, and snowfall.

[0085] Optionally, corresponding boundary conditions and initial conditions are set according to the input parameters. The dynamic equations of the system are solved by numerical methods to obtain the dynamic response results of each component under different meteorological conditions, and the dynamic response results include corresponding parameters such as displacement, stress, vibration, shape, etc. of each component.

[0086] Step S203: Process the dynamic response results obtained by the numerical simulation calculation, convert them into a format that can be displayed in the three-dimensional modeling software, and use the three-dimensional modeling software to integrate the converted dynamic response results with the three-dimensional model of the transmission line for display.

[0087] For example, the displacement or deformation data of components such as wires and brackets are mapped to the three-dimensional model. The dynamic response of the components at different time points can be shown by modifying the shape of the three-dimensional model or defining an animation for each component.

[0088] Exemplarily, the change of temperature or stress is displayed on the three-dimensional model through color mapping or material effect.

[0089] For example, for influencing factors such as wind force and ice accumulation, their impact can be displayed by applying dynamic load animation to the components. For example, a physics engine can be used to simulate the effect of wind force on transmission lines and show the interaction between wind force and conductors.

[0090] In summary, by sorting and preprocessing the meteorological data, the dynamic response results of each component under different meteorological conditions can be obtained, so that the three-dimensional model can reflect more details of the actual transmission line.

[0091] In the following embodiments, when extreme weather scenarios occur, severe damage may be caused to the power transmission lines. In this case, additional simulation of the damage caused by extreme weather scenarios is required. The present application embodiment discloses a flow chart of a method for generating dynamic response results of extreme weather scenarios. Figure 3 , the method comprising: Step S301: extract and analyze meteorological parameter combinations from the organized and pre-processed meteorological data, and use a preset trained decision tree model to analyze and determine whether an extreme weather scenario occurs.

[0092] If an extreme weather scenario occurs, execute step S303; If no extreme weather scenario occurs, step S302 is executed.

[0093] The meteorological parameter combination is obtained by the type of weather scene. According to the type of weather scene, the corresponding preset mapping table is used to find the meteorological parameters corresponding to the aforementioned type to obtain the meteorological parameter combination. Taking the type of weather scene rain as an example, the meteorological parameter combination includes humidity, wind speed, wind direction and precipitation.

[0094] Step S302: If no, continue with the subsequent steps.

[0095] If no extreme weather scenario occurs, the following steps are performed, in which a preset environment update scheme is adopted for the satellite remote sensing image data to realize the surrounding environment update of the three-dimensional model of the transmission line.

[0096] Step S303: If yes, a pre-established scenario category judgment model is used to further analyze and determine the extreme scenario category, and a corresponding specific physical model is selected from a pre-established physical model library, and a numerical simulation method matching the specific physical model is used to perform calculations to obtain the dynamic response results of each component of the transmission line under the corresponding extreme weather scenario.

[0097] Optionally, the physical model is discretized in space and time to transform the complex continuous system into a numerical solution problem. Common methods include finite element method (FEM), finite difference method (FDM), boundary element method (BEM), etc. For example, for structural mechanics problems such as bending and deformation of wires, the finite element method is used to solve and handle complex geometric shapes and boundary conditions. For example, for fluid mechanics problems such as wind loads, CFD simulation is used to provide the flow field effect of wind on the wire, simulating the comprehensive effect of wind speed and wind direction on the wire.

[0098] Optionally, for the combined effects of wind load and icing, a coupled simulation approach can be used, for example, coupling structural mechanics and heat conduction models to simulate the icing process, or coupling electromagnetic fields and fluid mechanics to simulate lightning effects.

[0099] The dynamic response results of each component solved under extreme weather scenarios include but are not limited to displacement and deformation, stress and strain, temperature distribution, lightning current and voltage fluctuations, etc.

[0100] In summary, the model is endowed with dynamic response capabilities under extreme scenario categories, so that the three-dimensional model can also simulate details in extreme weather scenarios.

[0101] The present application embodiment discloses a flow chart of a scene modeling method for a power transmission line. Figure 4 , the scenario modeling method of the transmission line includes: Step S401: sorting and preprocessing the acquired satellite remote sensing image data.

[0102] The data sorting in this step is used to process or convert satellite remote sensing image data. For example, the satellite remote sensing image data is normalized, or the satellite remote sensing image data is classified, or the satellite remote sensing image data is upgraded or reduced in dimension.

[0103] The preprocessing in this step is used to process outliers in satellite remote sensing image data. The preprocessing method includes at least one of deleting outliers, modifying outliers, or replacing them with reasonable values.

[0104] Step S402: extracting features of ground objects from the pre-processed satellite remote sensing image data, and classifying the ground objects using a preset classification algorithm.

[0105] The characteristics of land objects refer to the specific manifestations and properties of various natural or man-made objects on the earth's surface. The characteristics of land objects include morphological characteristics, distribution characteristics, material and composition, geographical location, and temporal and spatial characteristics.

[0106] Exemplarily, after obtaining the pre-processed satellite remote sensing image data, the features of the ground objects are extracted from the satellite remote sensing image data using a trained feature extraction model.

[0107] Exemplarily, a preset classification algorithm is used to classify the features, which include natural features and man-made features. For example, natural features include mountains, rivers, forests, lakes, etc., and man-made features include buildings, roads, bridges, farmlands, etc.

[0108] Optionally, before classifying the objects, it is necessary to extract features related to the object type from the satellite remote sensing image. The extracted features include but are not limited to vegetation features, water body features, object texture features, object shape features, etc. Step S403: Compare and analyze the satellite remote sensing image data obtained at different times, calculate the degree of change of the ground objects, and extract the changed areas based on the comparative analysis results of the satellite remote sensing image data obtained at different times, and mark and record the changed areas to clarify the type and scope of the change. The types of change include new ground objects, disappeared ground objects, and changes in ground object attributes.

[0109] When the weather changes, the ground objects are prone to change due to extreme weather. For example, a mountain range may experience a mudslide due to heavy rain, and a lake may increase in area due to rainfall. For example, the satellite remote sensing image data acquired at the current moment is compared and analyzed with the satellite remote sensing image data acquired at the historical moment to obtain the degree of change of the ground objects.

[0110] Optionally, the feature change amount is calculated based on the spectral features or texture features of satellite remote sensing image data acquired at different times. Compare whether the feature change amount is greater than a preset change amount threshold. If so, it is confirmed that the ground object has changed, and the step of calculating the degree of change of the ground object is executed; if not, the subsequent steps are continued. The feature change amount can be a change in standard deviation or mean.

[0111] Step S404: updating the surrounding environment of the three-dimensional model of the power transmission line according to the calculated change degree of the ground feature and the type and range of the change.

[0112] In summary, the degree of change of the ground objects as well as the type and scope of the change can be used to update the surrounding environment of the three-dimensional model of the transmission line, realize the real-time update of the three-dimensional model, and ensure the availability of the three-dimensional model.

[0113] The present application embodiment discloses a flow chart of a method for monitoring changes in terrain around a power transmission line. Figure 5 , the method comprising: Step S501: Analyze whether the meteorological data determines the extreme scene category.

[0114] If the extreme scene category is determined by analyzing the meteorological data, step S502 is executed; If no extreme scenario category is determined by analyzing the meteorological data, step S503 is executed.

[0115] Set up a mapping table between meteorological data and extreme scene categories. Determine whether there is a corresponding grouping category for the meteorological data in the mapping table. If so, determine the extreme scene category in the mapping table; if not, maintain the original setting.

[0116] Step S502: If no, maintain the original setting.

[0117] When the extreme scenario category is not determined, the original satellite remote sensing impact data is maintained.

[0118] Step S503: If yes, then according to the correspondence between the extreme scene category and the monitoring and classification scheme for changes in land objects around power transmission lines under remote sensing images, analyze and determine the matching monitoring and classification scheme for changes in land objects around power transmission lines under remote sensing images, and execute the monitoring and classification scheme for changes in land objects around power transmission lines under remote sensing images.

[0119] Optionally, the potential landslide area and the potential vegetation damage area are analyzed and determined based on the comparative analysis results of satellite remote sensing image data obtained at different times in the mountain area and the vegetation-related area. The potential landslide area and the potential vegetation damage area determined by the analysis are specifically marked, and the relevant information of the changed area is recorded.

[0120] In summary, according to the correspondence between extreme scene categories and the monitoring and classification scheme of ground objects around transmission lines under remote sensing images, the monitoring and classification scheme of ground objects around transmission lines under remote sensing images is implemented. In addition, the potential landslide areas and potential vegetation destruction areas are specifically marked, and the relevant information of the change areas is recorded to ensure the accuracy of the three-dimensional model.

[0121] In the following embodiments, the three-dimensional model obtained by modeling can be used in the intelligent inspection system of the power transmission line to guide the moving route of the inspection equipment. The embodiment of the present application discloses a path finding method based on a three-dimensional model. Figure 6 , the pathfinding method based on the three-dimensional model includes: Step S601: Acquire inspection image data, where the inspection image data is provided by an inspection device.

[0122] The inspection image data is obtained by photographing the power transmission line using the inspection equipment. For example, when the inspection equipment is a drone, the transmission line is photographed by the drone to obtain the inspection image data. Furthermore, the inspection image data is transmitted in real time.

[0123] Step S602: extracting feature points of inspection image data.

[0124] Exemplarily, the feature points of the inspection image data are corner points or edges, such as the vertices of pole towers, the end points of transmission lines, the vertices of power transmission and transformation equipment, and the like.

[0125] Step S603: Determine virtual inspection points corresponding to the inspection image data in the three-dimensional model according to the feature points.

[0126] Exemplarily, the feature points are mapped to virtual inspection points using the three-dimensional coordinate system of the three-dimensional model. For example, point cloud data is used for accurate position matching, and combined with a volume light cue algorithm, the virtual inspection points are located in the three-dimensional model. This step needs to ensure the matching degree between the feature points and the points of the three-dimensional model to improve the inspection accuracy.

[0127] Exemplarily, the feature points are mapped to coordinate points in the virtual space using the coordinate system of the three-dimensional model. For example, a point cloud data projection algorithm is used to accurately match the feature points extracted from the image with the three-dimensional model to obtain virtual inspection points.

[0128] Step S604: Determine whether the difference between the virtual inspection point and the inspection image data is greater than a preset difference.

[0129] If the difference between the virtual inspection point and the inspection image data is greater than the preset difference, step S606 is executed; If the difference between the virtual inspection point and the inspection image data is not greater than the preset difference, step S605 is executed.

[0130] The preset difference is a preset constant.

[0131] Exemplarily, the pixel value difference between the virtual inspection point and the inspection image data is calculated, and the mean of the aforementioned pixel value difference is calculated to obtain the pixel value mean; and it is determined whether the pixel value difference is greater than a preset difference. In this case, the preset difference is a pixel value, and the pixel value difference is used to represent the visual difference between the inspection image and the three-dimensional model.

[0132] In some other embodiments, the pixel value difference between the virtual inspection point and the inspection image data is calculated, and the number of pixels with a pixel value difference greater than a preset difference is calculated; it is determined whether the number of pixels is greater than the preset number; if so, step S606 is executed; if not, step S605 is executed.

[0133] Optionally, the virtual inspection points and the inspection image data may be displayed in a superimposed manner, so that the user can intuitively see the difference between the virtual inspection points and the inspection image data.

[0134] Step S605: If not, a first instruction is sent to the inspection device, where the first instruction is used to instruct the inspection device to move along a preset inspection route.

[0135] If the difference between the virtual inspection point and the inspection image data is not greater than the preset difference, it means that there is no problem with the power transmission line in the inspection image taken by the inspection device, and the inspection device can continue to move along the preset inspection route.

[0136] Step S606: If yes, a second instruction is sent to the inspection device, where the second instruction is used to instruct the inspection device to approach the actual inspection point corresponding to the virtual inspection point.

[0137] If the difference between the virtual inspection point and the inspection image data is greater than the preset difference, it means that there is a problem with the power transmission line in the inspection image taken by the inspection equipment, and the inspection equipment needs to be moved closer to the actual inspection point corresponding to the virtual inspection point to obtain more information.

[0138] In summary, after obtaining the inspection image data collected by the inspection equipment, the three-dimensional model is used to determine whether there is a problem with the virtual inspection point. If there is a problem, the inspection equipment is moved closer to the real inspection point corresponding to the virtual inspection point to obtain more information. The three-dimensional model is used to instruct the inspection equipment to conduct inspections and promptly obtain the problems with the transmission line.

[0139] In the following embodiments, the movement of the inspection equipment is controlled by a three-dimensional model so that the inspection equipment is as close as possible to the actual inspection point to obtain as much information as possible. The present application embodiment discloses a path finding method based on a three-dimensional model. Figure 7 , the pathfinding method based on the three-dimensional model includes: Step S701: Acquire a first on-site image according to actual inspection points, where the first on-site image includes inspection equipment.

[0140] The first scene image is acquired by a first camera on the transmission line. Exemplarily, according to the location of the actual inspection point, a camera closest to the actual inspection point is selected as the first camera, and the first scene image is captured by the first camera.

[0141] The first on-site image needs to include the inspection equipment to guide the moving route of the inspection equipment.

[0142] Step S702: Acquire the real space position of the inspection device through the first on-site image.

[0143] The real space position refers to the position coordinates of the inspection equipment in the real space.

[0144] Exemplarily, internal parameters and external parameters of the first camera are obtained, the internal parameters include the focal length and principal point coordinates of the first camera, and the external coordinates include the rotation matrix and translation matrix of the first camera; the real coordinates of the feature points in the first scene image are determined, and the feature points are located on the transmission line; the three-dimensional structure of the inspection equipment is reconstructed through the internal parameters and external parameters and the real coordinates of the feature points; according to the correspondence between the three-dimensional structure and the pixel points in the first scene image, the inspection equipment is mapped to the real coordinate system to obtain the real spatial position of the inspection equipment.

[0145] Step S703: Map the real space position to the three-dimensional model to obtain the virtual space position.

[0146] For example, on the premise of obtaining the real space position, the distance between the real space position and the feature point can be calculated, and then the real space position can be mapped to the three-dimensional model to obtain the virtual space position.

[0147] Step S704: designing a moving route according to the positional relationship between the virtual space position and the virtual inspection point in the three-dimensional model, wherein the distance from each point on the moving route to the power transmission line is greater than a preset safety distance.

[0148] In actual scenarios, transmission lines often transmit ultra-high voltage or UHV electricity, so they will generate spatial electric fields, which will affect the normal operation of some components in the inspection equipment. Therefore, it is necessary to ensure that the distance from each point on the moving route to the transmission line is greater than the preset safety distance.

[0149] Optionally, a moving route is designed in the three-dimensional model by using any one of a graph theory-based algorithm, a heuristic search algorithm, a sampling-based algorithm, an intelligent bionic algorithm, and a probabilistic graph method.

[0150] Step S705: Generate a second instruction according to the moving route.

[0151] The second instruction is used to instruct the inspection device to move according to the moving route. The second instruction can be transmitted to the inspection device at one time, or the second instruction can be transmitted to the inspection device in segments.

[0152] In summary, the moving route of the inspection equipment is generated according to the three-dimensional model to ensure that the inspection equipment will not be affected by the transmission line during the movement.

[0153] In the following embodiments, when a problem occurs in a power transmission line, maintenance personnel are required to arrive at the site in time for maintenance. However, power transmission lines are set up in complex scenes such as the wild and the mountains. If maintenance personnel rashly enter for maintenance, they are likely to enter a dangerous area, posing a threat to the life and health of the maintenance personnel. To solve this problem, the embodiment of the present application discloses a method for setting a virtual fence. Figure 8, the method for setting a virtual fence includes: Step S801: generating an abnormal factor according to the inspection image data and the three-dimensional model, wherein the abnormal factor is used to indicate that the difference between the virtual inspection point and the inspection image data is greater than a preset difference.

[0154] Optionally, the abnormal factor is used to indicate a damaged part in the transmission line, wherein the damaged part can be obtained by comparing the inspection image data with the three-dimensional model.

[0155] Step S802: Acquire environmental factors through inspection image data, where the environmental factors are used to represent the actual environment in which the power transmission line is located.

[0156] Environmental factors include geographic tag information, object identification information, and meteorological condition information. For example, the geographic tag information includes longitude and latitude and geographic location, the object identification information is used to indicate the terrain, trees, buildings, roads, etc. in the inspection image data, and the meteorological condition information includes sunny days, rain, snow, ice, etc.

[0157] Optionally, environmental factors in the inspection image data are extracted by an image recognition algorithm. For example, large trees or buildings in the inspection image data are identified by target detection technology, and their distances from the transmission lines are determined. In other embodiments, meteorological condition information can be obtained by combining the inspection image data with an external meteorological data source.

[0158] Step S803: Determine the dangerous area in the three-dimensional model by combining abnormal factors and environmental factors.

[0159] The danger level of the virtual inspection point is set in combination with abnormal factors and environmental factors, and the danger area is set in the three-dimensional model according to the danger level. For example, the danger level includes low risk, medium risk and high risk. Furthermore, a correspondence between abnormal factors, environmental factors and danger levels is pre-set, and the danger level can be determined by the aforementioned correspondence. For example, when the abnormal factor is a broken transmission cable and the environmental factor is icing, the corresponding danger level is high risk; when the abnormal factor is a metal corrosion of a section of the tower and the environmental factor is a sunny day, the corresponding danger level is low risk.

[0160] Optionally, the area radius is set according to the danger level, with the virtual inspection point as the circle point and the area radius as the radius to form a circular danger area. The length of the area radius is related to the danger level. The higher the danger level, the longer the area radius.

[0161] Optionally, the danger zone is also related to environmental factors. For example, when environmental factors indicate that there is ice on the transmission cable, the area below the transmission cable is also classified as a danger zone. For another example, when environmental factors indicate that there are rivers, geological faults, swamps and other terrains in the environment, the area corresponding to the terrain is also classified as a danger zone. For another example, when environmental factors indicate that there are wild animals near the transmission line, the area where the wild animals are located is also classified as a danger zone.

[0162] Step S804: Setting a virtual fence in the three-dimensional model according to the edge of the dangerous area.

[0163] The edge information of the dangerous area is converted into coordinate data of the virtual fence, and these coordinate data are applied to the three-dimensional model to obtain the virtual fence.

[0164] Furthermore, different colors, line types or thicknesses may be used to represent virtual fences to enhance the user's visual perception. In addition, the virtual fence may need to be dynamically adjusted according to changes in the actual environment. For example, when the abnormal factor is a broken transmission cable, if the broken transmission cable moves, the virtual fence will also be updated in time to reflect the latest dangerous area information.

[0165] Step S805: Synchronize the virtual fence to the user terminal, and the user terminal is used to display the virtual fence in combination with the real scene.

[0166] Optionally, the user terminal is an MR (mixed reality) device. The user terminal can overlay the virtual fence with the real scene. The user terminal will synthesize the location and boundary information of the virtual fence with the image or video in the real environment, so as to display the virtual fence on the screen. Users can understand the location of the dangerous area through these virtual fences and take corresponding measures, such as adjusting the inspection route or strengthening inspections.

[0167] Furthermore, the user terminal also provides real-time alarm and prompt functions. When the user approaches the virtual fence of the dangerous area, the user terminal can issue an alarm or provide warning information to ensure the user's safety. In this way, the virtual fence not only helps to improve the inspection efficiency, but also effectively prevents potential safety hazards.

[0168] In summary, a virtual fence is set up using a three-dimensional model, and the virtual Weilang is synchronized to the user terminal. When the user uses the user terminal, the boundary of the dangerous area in the real environment can be known, and the user can be reminded to pay attention to safety and ensure the safety of the user.

[0169] In the following embodiments, when maintenance personnel are performing maintenance on actual inspection points, the operation process can be played on the user terminal to assist the maintenance personnel in their maintenance work and remind the maintenance personnel when errors occur, thereby protecting the personal health of the maintenance personnel. Fig. 9 , the operation process teaching method includes: Step S901: Based on the real scene image collected by the user terminal, a three-dimensional model is superimposed and displayed on the user terminal.

[0170] Exemplarily, feature points are extracted from a real scene image; the real scene image is aligned with the three-dimensional model through the feature points; after the alignment, the three-dimensional model is superimposed and displayed on the real scene image.

[0171] Optionally, the display interface on the user terminal should provide interactive functions, allowing the user to adjust the transparency, rotation angle and zoom ratio of the model to better view and analyze the overlay effect.

[0172] Step S902: When the real scene image includes real inspection points, the real inspection points are highlighted and abnormal factors are displayed around the real inspection points.

[0173] The method of highlighting the actual inspection point may be at least one of highlighting, adding an icon or superimposing a label.

[0174] Optionally, users can interact with actual inspection points to view detailed descriptions of abnormal factors.

[0175] Step S903: Generate a work flow based on abnormal factors and real scene images.

[0176] Exemplarily, the work flow includes specific operating steps, such as checkpoints, repair locations, required tools and materials, etc.

[0177] In some other embodiments, the workflow may be provided by a remote technician.

[0178] Step S904: Play the operation flow on the user terminal.

[0179] Furthermore, users can view detailed information of the job process, zoom in on a specific part, or return to the previous step as needed.

[0180] Optionally, the process of playing the job flow also supports pause, fast forward and replay functions.

[0181] Step S905: When it is detected that the user behavior does not match the operation process, an alarm signal is broadcasted through the user terminal.

[0182] Optionally, a camera is provided on the user terminal to capture user behavior and compare whether the user behavior matches the operation flow.

[0183] The alarm signal includes an audible alarm, a vibration prompt or a warning message on the screen. Furthermore, the user terminal will also provide error information and correction suggestions to help the user adjust the operation in time and return to the correct operation process.

[0184] In summary, the use of three-dimensional models allows users to intuitively discover problems with the equipment, and also provides an operating process for repairing the faults. It also reminds users when they behave inappropriately to ensure their personal safety.

[0185] In the following embodiments, the abnormal state data in the transmission line can also be searched through the three-dimensional model, and the current fault point can be determined through the abnormal state data. The embodiment of the present application discloses a method for determining the fault point. Fig.10 , the method for determining the fault point includes: Step S1001: Acquire real-time status data of the transmission line.

[0186] The real-time status parameters include at least one of electrical parameters, line temperature, conductor tension and meteorological parameters. The electrical parameters include at least one of current, voltage, resistance and conductance. The meteorological parameters include at least one of wind speed, wind direction, rainfall, humidity and snow volume.

[0187] Optionally, various sensors are provided on the transmission line to obtain real-time status data. For example, a voltmeter is provided on the transmission line to measure voltage. For another example, a force sensor is provided on the transmission line to measure conductor tension.

[0188] Step S1002: searching for preset status data in the three-dimensional model according to the real-time status data.

[0189] The real-time state data is the state parameters of the power transmission line in the real space. The preset state data is the state data corresponding to the real-time state data in the three-dimensional model. The preset state data represents the ideal state data of the power transmission line.

[0190] Step S1003: determining whether the difference between the preset status data and the real-time status data is greater than a data difference threshold.

[0191] The data difference threshold is a preset constant, and the specific value can be adjusted according to actual needs.

[0192] If the difference between the preset status data and the real-time status data is greater than the data difference threshold, the real-time status data indicates that there is a fault point in the transmission line, and step S1004 needs to be executed; If the difference between the preset status data and the real-time status data is not greater than the data difference threshold, the real-time status data indicates that there is no fault point in the transmission line for the time being, and the process can be terminated.

[0193] Step S1004: If yes, obtain a second scene image according to the real-time status data.

[0194] Optionally, determine a device in the power transmission line corresponding to the real-time status data; obtain a second camera closest to the device; and use the second camera to obtain a second on-site image.

[0195] Step S1005: Obtain the current fault point of the transmission line and the cause of the current fault point through the three-dimensional model, the second on-site image and the real-time status data.

[0196] Exemplarily, the generation cause analysis model is called to process the three-dimensional model, the second scene image and the real-time status data to obtain the generation cause. The generation cause analysis model is any one of a convolutional neural network, a recurrent neural network, a feedforward neural network and a hybrid neural network.

[0197] In summary, the 3D model is used to quickly locate the current fault point, and the cause of the current fault point is determined in combination with the second on-site image of the current fault point, which helps users to timely understand the current fault point in the transmission line and clarify the cause of the current fault point.

[0198] In the following embodiments, the potential fault point in the power transmission line can be determined by the current fault point. The present application embodiment discloses a method for determining a potential fault point. Fig.11 , the method for determining the potential failure point includes: Step S1101: searching for potential fault points in the three-dimensional model according to the generation cause, and obtaining status data of the potential fault points.

[0199] For example, if the generation reason is caused by meteorological parameters, the potential fault points with meteorological parameters similar to the current fault point are retrieved in the three-dimensional model. For example, if the current fault point is caused by ice and snow weather, the transmission line in ice and snow weather is searched in the three-dimensional model and is used as a potential fault point. For example, when the generation reason is caused by excessive line temperature, a potential fault point close to the line temperature of the current fault point is retrieved in the three-dimensional model. For example, if the line temperature of the current fault point is 60°C, a point with a line temperature above 55°C is searched in the three-dimensional model to obtain a potential fault point.

[0200] Exemplarily, when the generation cause is caused by both conductor tension and meteorological parameters, a potential fault point with the same conductor tension and meteorological parameters as the current fault point is retrieved in the three-dimensional model. For example, if the conductor tension of the current fault point is greater than 500N and the wind speed in the meteorological parameters is greater than 20m / s, then in combination with the guide tension and the wind speed, a point with a conductor tension greater than 500N and a wind speed greater than 20m / s is determined in the three-dimensional model as a potential fault point.

[0201] Step S1102: Acquire the actual position of the potential fault point according to the position of the potential fault point in the three-dimensional model.

[0202] According to the correspondence between the coordinate system of the three-dimensional model and the real coordinate system, the position of the potential fault point in the three-dimensional model is mapped to the real coordinate system to obtain the real point position of the potential fault point.

[0203] Step S1103: Acquire a potential fault point image corresponding to the actual point.

[0204] Exemplarily, the device in the power transmission line corresponding to the actual point is determined; the camera closest to the device is obtained; and the image of the potential fault point is obtained using the aforementioned camera.

[0205] Step S1104: combining the potential fault point image with the status data of the potential fault point, classifying the potential fault point to obtain a classification result of the potential fault point, wherein the classification result includes a normal point position and an abnormal point position.

[0206] A potential fault point only indicates that there is a hidden danger of a problem at that point, but it cannot be determined whether there is actually a problem at that point. Therefore, it is necessary to classify the potential fault point by combining the potential fault point image with the status data of the potential fault point to determine whether the potential fault point is a normal point or an abnormal point.

[0207] In summary, the three-dimensional model can be used to obtain potential fault points in the transmission line and determine whether the potential fault points are normal points or abnormal points.

[0208] Based on the same inventive concept, the present application embodiment provides a scene modeling system for a power transmission line, please refer to Fig.12 ,include: The acquisition module 1201 is used to acquire surveying and mapping data, meteorological data, satellite remote sensing image data, scene category judgment models, extreme scene categories, mountain areas and vegetation related areas; A memory 1202, used for storing a program of any one of the above-mentioned scenarios modeling methods for power transmission lines; Processor 1203, the program in the memory can be loaded and executed by the processor to implement any of the above-mentioned scene modeling methods for power transmission lines.

[0209] In summary, by modeling with multi-dimensional laser point cloud data and oblique photography data, surveying and mapping modeling is obtained, and the surveying and mapping modeling and parameter modeling are integrated to obtain a fusion model. After physically rendering the fusion model, a high-precision three-dimensional model is obtained. Since the three-dimensional model integrates the information of surveying and mapping modeling and parameter modeling, the accuracy of the three-dimensional model can be effectively improved. Moreover, the surveying and mapping modeling itself integrates multi-dimensional laser point cloud data and oblique photography data, making the surveying and mapping modeling closer to the actual transmission line, further improving the accuracy of the three-dimensional model.

[0210] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0211] An embodiment of the present application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and execute a high-precision three-dimensional modeling method for overhead transmission lines based on BIM.

[0212] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0213] Based on the same inventive concept, an embodiment of the present application provides an intelligent terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute a high-precision three-dimensional modeling method for overhead transmission lines based on BIM.

[0214] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0215] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A high-precision three-dimensional modeling method for overhead transmission lines based on BIM, characterized in that: The method comprises: Acquire surveying and mapping data, meteorological data, and satellite remote sensing image data, wherein the surveying and mapping data is obtained by surveying and mapping the real scene of the power transmission line, and the surveying and mapping data includes laser point cloud data and oblique photography data; Apply the trained power transmission line deep analysis model to the surveying and mapping data, automatically identify and segment the various parts of the power transmission line, and build a surveying and mapping model based on the identified and segmented parts of the power transmission line and the surveying and mapping data; A preset dynamic effect simulation scheme is used for meteorological data to realize dynamic effect simulation of the three-dimensional model of the power transmission line, and a preset environmental update scheme is used for satellite remote sensing image data to realize the surrounding environment update of the three-dimensional model of the power transmission line; Obtain parameter modeling for representing the logical relationship between the internal components of the transmission line, and adjust the fusion method of the logical relationship and structure of the internal components of the transmission line involved in the surveying and mapping modeling and parameter modeling according to the changes in the external characteristics of the model brought about by the completed dynamic effect simulation of meteorological data and the update of the surrounding environment of satellite remote sensing image data, and obtain a fusion model; The fused model is physically rendered to obtain a three-dimensional model of the transmission line.

2. The method according to claim 1, characterized in that The preset dynamic effect simulation scheme is used for meteorological data to realize the dynamic effect simulation of the three-dimensional model of the transmission line, including: Organize and pre-process the acquired meteorological data; The meteorological data that have been sorted and preprocessed are used as input parameters and are respectively input into the established physical models corresponding to different meteorological conditions. The physical models after the meteorological data are input are numerically simulated using the numerical simulation method that matches the established physical model to obtain the dynamic response results of each component of the transmission line under different meteorological conditions. The dynamic response results obtained from the numerical simulation calculation are processed and converted into a format that can be displayed in the three-dimensional modeling software, and the converted dynamic response results are integrated with the three-dimensional model of the transmission line using the three-dimensional modeling software.

3. The method according to claim 2, characterized in that The method further includes steps after the acquired meteorological data is sorted and preprocessed, and before the acquired meteorological data is sorted and preprocessed, which are specifically as follows: Extract and analyze meteorological parameter combinations from the organized and pre-processed meteorological data, and use the preset trained decision tree model to analyze and determine whether extreme weather scenarios occur; If no, continue with the next steps; If yes, a pre-established scenario category judgment model is used to further analyze and determine the extreme scenario category, and a corresponding specific physical model is selected from a pre-established physical model library. A numerical simulation method matching the specific physical model is used to perform calculations to obtain the dynamic response results of each component of the transmission line under the corresponding extreme weather scenario.

4. The method according to claim 3, characterized in that The preset environment update scheme is used for satellite remote sensing image data to update the surrounding environment of the three-dimensional model of the transmission line, including: Organize and preprocess the acquired satellite remote sensing image data; Extract the features of ground objects from the pre-processed satellite remote sensing image data, and classify the ground objects using a preset classification algorithm; Compare and analyze satellite remote sensing image data acquired at different times, calculate the degree of change of the objects, and extract the areas that have changed based on the comparative analysis results of satellite remote sensing image data acquired at different times, mark and record the changed areas, and clarify the type and scope of the change. The types of change include new objects, disappeared objects, and changes in object attributes; The surrounding environment of the three-dimensional model of the transmission line is updated according to the calculated degree of change of the ground object and the type and scope of the change.

5. The method according to claim 4, characterized in that It also includes the comparative analysis results of satellite remote sensing image data acquired at different times, extracting the areas that have changed, marking and recording the changed areas, and clarifying the types and scope of the changes, as follows: Analyze whether meteorological data determines the category of extreme scenarios; If not, maintain the original setting; If yes, then according to the correspondence between the extreme scene category and the monitoring and classification scheme of ground objects changes around the transmission line under remote sensing images, the matching monitoring and classification scheme of ground objects changes around the transmission line under remote sensing images is analyzed and determined, and the monitoring and classification scheme of ground objects changes around the transmission line under remote sensing images is executed.

6. The method according to claim 5, characterized in that If the extreme scene category is a rainstorm-related extreme scene, the monitoring and classification scheme for changes in objects around the transmission line under remote sensing images includes: Based on the comparative analysis results of satellite remote sensing image data obtained at different times in mountain areas and vegetation-related areas, potential landslide areas and potential vegetation destruction areas are analyzed and determined; The potential landslide areas and potential vegetation destruction areas determined through analysis are specifically marked, and relevant information of the changed areas is recorded.

7. A high-precision three-dimensional modeling system for overhead power transmission lines based on BIM, characterized in that: The system comprises: The acquisition module is used to obtain surveying and mapping data, meteorological data, satellite remote sensing image data, scene category judgment models, extreme scene categories, mountain areas and vegetation-related areas; A memory for storing a program of a high-precision three-dimensional modeling method for overhead transmission lines based on BIM according to any one of claims 1 to 6; The program in the memory can be loaded and executed by the processor to implement the high-precision three-dimensional modeling method of overhead transmission lines based on BIM as claimed in any one of claims 1 to 6.

8. An intelligent terminal, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes any one of the methods of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 6.

Images