UAV monitoring-based discharge early warning method for ultra-high voltage transmission line

Abstract

An ultra-high voltage transmission line discharge early warning method based on unmanned aerial vehicle monitoring, using an unmanned aerial vehicle to shoot aerial images of a target measurement area, generating three-dimensional point clouds and digital models, outputting corresponding digital orthographic images DOM and digital surface models DSM, using a digital model-based obstacle height extraction method and a point cloud information-based obstacle height extraction method to obtain corresponding obstacle height values, verifying the accuracy of the obstacle height values according to the obstacle height values and the obtained ground reference data, taking the obstacle height value with the highest accuracy as the final obstacle height calculation value, modeling the AC and DC transmission lines and the obstacles, determining the minimum safety distance between the transmission lines and the obstacles through finite element method-based calculation, and generating corresponding transmission line discharge early warning information according to the final obstacle height calculation value, the height value of the transmission line and the minimum safety distance value, so that electric power maintenance personnel can make corresponding treatment on the transmission line according to the transmission line discharge early warning information.

Description

Technical Field

[0001] This invention relates to the fields of unmanned aerial vehicle (UAV) monitoring and high-voltage engineering, and in particular to a method for early warning of discharge in ultra-high voltage transmission lines based on UAV monitoring. Background Technology

[0002] In the safe operation of power transmission lines, excessively high obstacles can threaten the safe operation of the power grid and cause accidents such as tripping and discharge. Therefore, it is of great significance to quickly and accurately estimate the height of obstacles in the transmission corridor to detect potential hazards in the operation of power transmission lines in advance and to ensure power supply.

[0003] Current methods for measuring obstacle height can be categorized into traditional measurement and remote sensing inversion. Traditional height measurement primarily relies on manual operation using altimeters or laser rangefinders, resulting in high labor costs, low efficiency, and accuracy affected by instrument quality and human factors. While current remote sensing inversion technologies, such as the developing Polarimetric Interferometric Synthetic Aperture Radar (Pol-InSAR), can retrieve obstacle height over large areas, most are still in the experimental stage and lack sufficient accuracy in practical applications. Airborne lidar and ground-based radar can extract obstacle height with relatively high precision, but their high cost and the need for multiple data acquisitions for large-scale measurements, particularly for airborne lidar, lead to substantial expenses. In contrast, UAV remote sensing, which has emerged in recent years, offers advantages such as low cost, high resolution, ease of operation, and flexible data acquisition cycles, and has been widely applied in fields such as topographic mapping and agricultural production. Currently, methods for extracting ground obstacle height using UAVs are mainly divided into two types: digital model-based extraction and point cloud-based extraction. Therefore, it is necessary to effectively verify the accuracy of these two mainstream UAV methods for tree height extraction to ensure they meet requirements.

[0004] Furthermore, regarding the safe operation of transmission lines, domestic standards often consider the maximum overvoltage gap when determining the minimum safe distance between overhead lines and obstacles. In recent years, noting the occurrence of discharge accidents in transmission lines due to excessively high obstacles under strong electric fields, some domestic standards and documents have begun to incorporate the electric field effect as a basis for determining the minimum safe distance between overhead lines and obstacles. Internationally, the minimum safe distance between overhead lines and obstacles is generally determined to meet the safe operation requirements of transmission lines. Since my country was the first country in the world to research and construct ultra-high voltage (UHV) projects, there are no international regulations specifying the distance between lines and obstacles at this voltage level. Summary of the Invention

[0005] In view of this, the present invention provides a method for early warning of discharge of ultra-high voltage transmission lines based on UAV monitoring, which can be used to realize timely early warning of discharge of transmission lines.

[0006] A method for early warning of discharge on ultra-high voltage transmission lines based on UAV monitoring includes the following steps:

[0007] Ground benchmark data acquisition: The height of different obstacles within the target measurement area is measured using a total station;

[0008] UAV aerial image data acquisition and processing: using UAVs to capture aerial images of the target measurement area, processing the aerial images with software to generate 3D point clouds and digital models, and then outputting the corresponding digital orthophotos (DOM) and digital surface models (DSM).

[0009] Obstacle height calculation: Obstacle height extraction methods based on digital models and point cloud information are used to obtain the corresponding obstacle height values ​​respectively;

[0010] Determine the final obstacle height calculation value: Verify the accuracy of the obstacle height value based on the obstacle height value and the obtained ground reference data, and take the obstacle height value with the highest accuracy as the final obstacle height calculation value;

[0011] Calculation of minimum safe distance for transmission lines: for different voltage levels AC / DC The transmission line and the selected target obstacle are modeled, and the minimum safe distance between the transmission line and the target obstacle is determined by calculation based on the finite element method.

[0012] Transmission line discharge warning: Based on the calculated final obstacle height corresponding to the target obstacle, the height of the transmission line, and the minimum safe distance, corresponding transmission line discharge warning information is generated so that power maintenance personnel can take appropriate measures to handle the transmission line according to the transmission line discharge warning information.

[0013] As can be seen from the above technical solution, this application utilizes a total station to measure the height of obstacles within the target measurement area. While measuring, it distinguishes obstacle types to obtain ground reference data. It uses a drone to capture aerial images of the target measurement area, processes these images using software to generate 3D point clouds and digital models, and outputs corresponding digital orthophotos (DOM) and digital surface models (DSM). It then uses obstacle height extraction methods based on digital models and point cloud information to obtain corresponding obstacle height values. The accuracy of the obstacle height values ​​is verified based on the obstacle height values ​​and the acquired ground reference data. The obstacle height value with the highest accuracy is used as the final calculated obstacle height value. Modeling is performed on AC / DC transmission lines and obstacles at different voltage levels. Through calculations based on the finite element method, the minimum safe distance between the transmission line and the obstacle is determined. Based on the final calculated obstacle height value, the transmission line height value, and the minimum safe distance value, corresponding transmission line discharge warning information is generated, enabling power maintenance personnel to take appropriate actions based on the transmission line discharge warning information, greatly reducing inspection costs. Attached Figure Description

[0014] Figure 1 This is a flowchart of the present invention.

[0015] Figure 2 The digital model obtained in this embodiment of the invention is obtained by subtracting the digital elevation model (DEM) from the digital surface model (DSM) within the measurement area.

[0016] Figure 3 This is a tree vertex extraction result image obtained by performing circular neighborhood analysis on CHM in an embodiment of the present invention.

[0017] Figure 4 This is a point cloud map of tree obstacles in an embodiment of the present invention.

[0018] Figure 5 This is an accuracy comparison chart comparing the extracted tree obstacle height values ​​based on CHM with the true values ​​measured by a total station in an embodiment of the present invention.

[0019] Figure 6 This is an absolute error graph comparing the extracted tree obstacle values ​​based on CHM with the true values ​​measured by the total station in an embodiment of the present invention.

[0020] Figure 7 This is a comparison chart of the overall accuracy of tree obstacle heights extracted using two methods and the true values ​​measured by a total station, as shown in this embodiment of the invention.

[0021] Figure 8 This is a flowchart of the steps for calculating the DC ion flow field based on finite element simulation in this invention.

[0022] Figure 9 This is a flowchart of the present invention for determining the minimum safe distance between a target obstacle and a transmission line based on the electric field strength calculation results obtained from simulation. Detailed Implementation

[0023] The technical solutions of this application will be further described in detail below through embodiments and in conjunction with the accompanying drawings. This will help the public understand the present invention, but the specific embodiments provided by the applicant should not and should not be regarded as limitations on the technical solutions of the present invention. Any changes to the definition of components or technical features or formal but not substantial changes to the overall structure should be considered as being within the scope of protection defined by the technical solutions of the present invention.

[0024] A method for early warning of power line discharge based on UAV monitoring includes the following steps:

[0025] Ground reference data acquisition: The height of obstacles within the target measurement area is measured using a total station, and the types of obstacles are identified during the measurement. In this step, a Nikon total station (±(2+2ppm×D)mm) is used. The height is measured and recorded from different directions using the suspension measurement method, and the average value is taken as the measured height. When measuring, obstacles need to be classified, including but not limited to trees or buildings. For ease of explanation, trees will be used as an example in the following description.

[0026] UAV aerial image data acquisition and processing: Using UAVs to capture aerial images of the target measurement area, the aerial images are processed by software to generate 3D point clouds and digital models, and the corresponding digital orthophotos (DOM) and digital surface models (DSM) are output. In this step, the drone used was a DJI PHANTOM 4RTK equipped with an integrated gimbal camera. The image acquisition time was in the afternoon, and the weather conditions were sunny with a light breeze. In order to generate sufficient point cloud density to improve the extraction accuracy, the experimental flight altitude was set to 80m, the forward overlap rate was 85%, and the lateral overlap rate was 75%. The coordinates of the control points in the aerial images were measured using carrier phase differential technology RTK. The aerial images were processed using Pix4D software. Since factors such as lighting, wind direction, and airflow can affect the aerial photography effect, resulting in information loss and geometric distortion in the images, invalid images were checked and removed before processing. Next, the aerial images were processed using Pix4D software. First, the coordinates were corrected using the previously measured control points in the aerial images, and the camera's interior and exterior orientation elements were optimized. Then, aerial triangulation was performed to generate a 3D point cloud and a 3D model. Finally, the digital orthophoto (DOM) and digital surface model (DSM) were output.

[0027] Obstacle height calculation: Obstacle height extraction methods based on digital models containing obstacle height information and point cloud information are used to obtain the corresponding obstacle height values. Specifically, "obtaining the corresponding obstacle height values ​​using the digital model-based obstacle height extraction method" involves subtracting the digital elevation model (DEM) (representing ground changes) from the digital surface model (DSM) within the measurement area to obtain a digital model reflecting changes in obstacle height. For example, the digital canopy model (CHM) for tree obstacles in this case is shown below. Figure 2 The obstacle height was calculated by performing neighborhood analysis on the digital model. Based on the obstacle's characteristics, a circular neighborhood was used for analysis. The neighborhood radius was determined through multiple trials based on the obstacle size and model resolution. The maximum value within the neighborhood was obtained through focal point statistics as the undetermined vertex. After removing erroneous vertices from the orthophoto image, the obstacle's height information was extracted to obtain the first obstacle height value. The vertex extraction results for the tree obstacle in this example are shown below. Figure 3 .

[0028] The specific operation method for "obtaining the corresponding obstacle height value using point cloud information" is as follows: First, the 3D point cloud is filtered and denoised to prevent isolated noise points from affecting the extraction results; next, a predetermined range is delineated and the point cloud of obstacles within this range is extracted. This range includes both ground point cloud and obstacle point cloud, and interference from other irrelevant objects is excluded as much as possible to prepare for extracting the required obstacle height. The point cloud image for the tree obstacle in this example is shown below. Figure 4 The ground point cloud and obstacle point cloud are distinguished based on the number distribution of point cloud height values. The average value of the ground point cloud is used to replace the elevation. The highest point of the obstacle point cloud is taken as the obstacle vertex. Finally, the ground elevation is subtracted to obtain the second obstacle height value of the measured obstacle.

[0029] Determining the final obstacle height calculation: The accuracy of the obstacle height values ​​is verified using the calculated heights of the first and second obstacles of the same type, along with acquired ground reference data. The obstacle height value with the highest accuracy is taken as the final obstacle height calculation value. In this step: The height values ​​of the first and second obstacles are compared with the true values ​​of the actual obstacle heights measured by the total station, and their accuracy is checked by calculating correlation and absolute error. For accuracy comparison based on the digital model, see [link to digital model]. Figure 5 The absolute error based on the digital model is shown below. Figure 6The correlation between tree height extracted using the CHM method and the measured height was 0.97. The absolute error values ​​for tree height were all below 110cm, with the largest absolute error being 104cm and the smallest being 0.1cm. The calculated mean absolute error (MAE) was 26.4cm. This indicates that the digital canopy model can effectively extract tree height. Furthermore, according to... Figure 6 The distribution of absolute errors reveals that most error values ​​are below 50cm, with only a few trees showing errors greater than 80cm. The larger errors occur in the first half of the data, primarily because some tree vertices were smoothed during DSM generation, and the large roots of banyan trees were mistakenly identified as ground level during DEM generation, leading to an inflated elevation and thus a lower extracted tree height. This is in contrast to the overall accuracy comparison. Figure 7 As can be seen, both the CHM-based and point cloud-based extraction methods have high accuracy overall, with the latter showing better accuracy in extracting tree height. Looking at the results from different methods, the tree height extracted by the CHM-based method is slightly lower than the actual value, possibly due to smoothing of the tree apex; while the tree height extracted by the point cloud method is close to the measured tree height. For different tree species, both methods are more accurate in extracting tree height for flat canopies than for conical canopies. The correlation coefficients between the two methods are 0.97 and 0.98, respectively. Therefore, the obstacle height extraction method using point cloud information to obtain the corresponding second obstacle height value is chosen as the final obstacle height calculation value.

[0030] Calculation of Minimum Safe Distance for Transmission Lines: Modeling AC / DC transmission lines at different voltage levels and selected target obstacles, the minimum safe distance between the transmission line and the obstacle is determined using the finite element method. Specifically, this step involves: establishing a three-dimensional high-voltage transmission line simulation model; using finite element software to calculate the maximum electric field intensity on the surface of different types of target obstacles below the AC transmission line, specifying input height and position values; selecting the corresponding relative permittivity as the physical parameter required for calculation based on the type of target obstacle; and determining the initiation field strength of the streamer discharge of the target obstacle based on a highly non-uniform rod-plate model; comparing the maximum electric field intensity on the surface of the target obstacle with the initiation field strength of the streamer discharge of the target obstacle; and calculating the minimum safe distance value based on the height of the transmission line and the input height value of the target obstacle when the maximum electric field intensity on the surface of the target obstacle is not less than the initiation field strength of the streamer discharge of the target obstacle. The following provides a detailed explanation of the above-mentioned "Calculation of minimum safe distance between transmission lines: Modeling AC / DC transmission lines and obstacles at different voltage levels, and determining the minimum safe distance between transmission lines and obstacles through calculations based on the finite element method":

[0031] AC transmission line simulation was performed using the electrostatics module of the finite element software COMSOL. A three-dimensional AC transmission line simulation model was established, and boundary conditions were set: the surface potential of the conductor was set to the actual operating voltage of the conductor, the ground potential was set to 0, and the target obstacle was considered a grounded conductor with its terminal voltage set to 0. A steady-state solver was used to directly obtain the spatial electric field distribution within the computational domain, i.e., the maximum electric field strength on the obstacle surface could be obtained. Different heights and horizontal distances of the target obstacle in the model resulted in different maximum electric field strengths on its surface.

[0032] The finite element method (FEM) and the Kaptzov assumption, the most widely used methods in DC composite field calculations, are employed for time-domain DC composite field calculations. The Kaptzov assumption states that after corona formation on a conductor, the surface field strength remains constant at the initial corona formation strength. Most current DC composite field calculation studies are based on this assumption. The electrostatic and rare matter transport modules in COMSOL Multiphysics are used. The Poisson equation and its boundary conditions are set in the electrostatic module, and the charge conservation equation and its boundary conditions are set in two rare matter transport modules (one for positive ions and one for negative ions). The electrostatic and rare matter transport modules are coupled to obtain the spatial electric field distribution. A period of time is required from the onset of corona on the conductor surface to the formation of a directional ion flow, during which the spatial charge density distribution changes significantly. The time-domain algorithm can demonstrate the changes in spatial charge density and spatial electric field strength. The conductor surface potential is set to the actual operating voltage of the conductor, the ground potential is set to 0, and the target obstacle is considered a grounded conductor with its surface potential set to 0. The equivalent corona formation field strength of the equivalent conductor is calculated using the principle of corona degree equivalence. The corona formation field strength of the split conductor is also calculated. Where E0' and m are empirical constants, m is the surface roughness coefficient of the conductor, δ is the relative density of air, and r eq Let E be the equivalent conductor radius. A model was built using Comsol software, and simulation calculations yielded the maximum working electric field E on the surface of the split conductor. max The maximum operating field strength E on the surface of the equivalent conductor maxeq Using formula The equivalent corona initiation field strength is calculated, where k1 is the ratio of the corona initiation field strength of the split conductor to the maximum working field strength on the surface, and k2 is the ratio of the equivalent conductor's corona initiation field strength to the maximum working field strength on the surface. When the surface field strength of the transmission line reaches the critical corona initiation field strength, the conductor begins to corrode. Therefore, a concentration boundary needs to be set for the conductor surface. The positive and negative charge densities here need to be set to maintain the corona initiation field strength on the conductor surface and keep it constant. Therefore, the conductor surface charge density needs to be iteratively adjusted in MATLAB using a predictive-correction method with an iterative charge density formula: after setting similar conductor surface charge densities, simulation calculations are started, and the conductor surface field strength is compared with the corona initiation field strength using the formula... The surface charge density of the conductor is corrected. The steady-state criterion used in the inner loop is the error in the combined field strength at ground level to measure whether the space charge distribution has reached a steady state. The Kaptzov hypothesis criterion used in the outer loop is to verify whether the error between the electric field strength on the conductor surface and the corona initiation field strength meets the requirements. The specific simulation calculation flowchart is as follows. Figure 8 As shown: Step 1, set the initial values ​​of the equivalent corona field strength of the positive and negative conductors and the initial values ​​of the surface charge density of the conductors; Step 2, solve the time-domain ion flow field control equations using the finite element method (FEM), specifically, calculate the Poisson equation and the current continuity equation using the FEM; Step 3, verify whether the space charge distribution has reached a steady state. If the steady-state verification is satisfied, obtain the surface electric field strength of the conductor at this time; if the steady-state verification is not satisfied, increment the time step (e.g., Δt = 0.05s), i.e., t i =t i-1 +Δt, where i is a natural number, jump to step 2 to perform the simulation calculation for the next time step, thus realizing the inner loop; Step 4, verify whether the obtained electric field strength on the conductor surface at this time satisfies the Kaptzov assumption; Step 5, if the Kaptzov assumption is satisfied, obtain the currently calculated electric field strength on the conductor surface and the maximum electric field strength on the surface of the target obstacle; if the Kaptzov assumption is not satisfied, use the prediction-correction method to successively correct the electric field density on the conductor surface using the charge density iteration formula. After correcting the electric field density on the conductor surface, jump to step 1 to execute, thus realizing the outer loop, that is, using the corrected electric field density on the conductor surface as the initial value of the electric field density on the conductor surface. Through the above steps, the maximum value of the electric field strength on the surface of the target obstacle can be simulated.

[0033] The process of determining the minimum safe distance is as follows: Figure 9Each time the position of the selected target obstacle is changed, i.e., the height H and horizontal distance S from the center of the transmission line are changed, the maximum electric field strength on the surface of the obstacle under the AC / DC transmission line at a specified voltage level is obtained through the above simulation. An initial height value H0 and an initial horizontal distance value S0 of the target obstacle are set; this initial height value is the input height value. These initial height and horizontal distance values ​​are used as the initial simulation conditions: the initial horizontal distance is 0, the obstacle is directly below the transmission line, and the maximum horizontal distance S0 is... max Two meters outside the edge conductor, assign an initial input height value to the target obstacle. The principle for specifying the input height value is neither too far from the transmission line to avoid increasing the number of searches, nor too close to the transmission line to avoid the maximum electric field strength on the obstacle surface exceeding the initial electric field strength of the streamer. Then, gradually increase the input height value of the target obstacle by ΔH. If the initial electric field strength of the streamer is not reached, increase the horizontal distance by ΔS until the maximum horizontal distance S is reached. max At different horizontal distances, a breakdown test is performed. If the maximum electric field strength on the surface of the target obstacle reaches the starting electric field strength of the streamer discharge, then the height of the target obstacle at this point is the critical height for the current voltage level. That is, critical height = input height value + i * ΔH, where i is the number of times ΔH is increased. If the breakdown electric field strength is not reached, that is, the maximum electric field strength on the surface of the target obstacle does not reach the starting electric field strength of the streamer discharge, then the height of the target obstacle continues to be increased based on ΔH, and the above process is repeated until the critical height of the target obstacle is calculated. Subtracting the critical height from the transmission line height gives the minimum safe distance.

[0034] Transmission line discharge warning: Based on the final calculated obstacle height, the transmission line height, and the minimum safe distance, corresponding transmission line discharge warning information is generated to enable power maintenance personnel to take appropriate actions. For example, an obstacle height warning cloud map can be created. In this cloud map, if the difference between the transmission line height and the final calculated obstacle height is greater than the minimum safe distance, the obstacle is displayed in green, indicating that it has no impact on the transmission line. If the difference is greater than the minimum safe distance, the obstacle is displayed in yellow, indicating that it has some impact on the transmission line. Yellow indicates that without action, the obstacle poses a discharge risk to the transmission line, requiring inspection of the area. If the difference is negative, the obstacle is displayed in red, indicating that it has affected the transmission line and poses a significant discharge risk, requiring immediate action.

[0035] The above-disclosed embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the invention. Those skilled in the art will understand that implementing all or part of the above-described embodiments and making equivalent changes in accordance with the claims of the present invention are still within the scope of the invention.

Claims

1. A power transmission line discharge early warning method based on unmanned aerial vehicle monitoring, comprising the following steps: ground reference data acquisition: using a total station to measure the height of different obstacles in the target measurement area; unmanned aerial vehicle aerial photograph data acquisition and processing: using an unmanned aerial vehicle to take aerial images of the target measurement area, using software to process the aerial images, generating three-dimensional point cloud and digital model, and then outputting corresponding digital orthophoto map DOM and digital surface model DSM; obstacle height value calculation: using an obstacle height extraction method based on a digital model and an obstacle height extraction method based on point cloud information to obtain corresponding obstacle height values; determining the final obstacle height calculation value: verifying the accuracy of the obstacle height value according to the ground reference data, and taking the obstacle height value with the highest accuracy as the final obstacle height calculation value; power transmission line minimum safety distance value calculation: modeling the AC and DC power transmission lines under different voltage levels and the selected target obstacles, and determining the minimum safety distance value between the power transmission lines and the target obstacles through finite element method-based calculation; power transmission line discharge early warning: generating corresponding power transmission line discharge early warning information according to the final obstacle height calculation value corresponding to the target obstacle, the height value of the power transmission line and the minimum safety distance value, so that the electric power maintenance personnel can make corresponding treatment to the power transmission line according to the power transmission line discharge early warning information; wherein the step of "power transmission line minimum safety distance value calculation: modeling the AC and DC power transmission lines under different voltage levels and the obstacles, and determining the minimum safety distance value between the power transmission lines and the obstacles through finite element method-based calculation" is specifically: establishing a three-dimensional high-voltage power transmission line simulation model, using finite element software to solve and calculate, calculating the maximum electric field intensity of the surface of the target obstacle under the AC power transmission line, which is of different types and has specified input height value and input position value; according to the different types of obstacles, different relative dielectric constants are selected as the required physical parameters for calculation, and the streamer discharge starting field strength of the corresponding category of obstacles is determined according to the extremely uneven rod-plate model; compare the maximum electric field intensity of the surface of the same type of obstacle with the streamer discharge starting field strength of the obstacle, when the maximum electric field intensity of the surface of the same type of obstacle is not less than the streamer discharge starting field strength of the obstacle, calculate the minimum safety distance value according to the height value of the power transmission line and the input height value of the same type of obstacle; The step of obtaining the maximum electric field intensity on the surface of the target obstacle is specifically: step 1, setting the positive and negative electrode wire equivalent corona field intensity and the initial value of the wire surface charge density; step 2, solving the time-domain ion flow field control equation by using the finite element method; step 3, checking whether the space charge distribution reaches a steady state, if the steady state check is satisfied, the wire surface electric field intensity at this time is obtained; if the steady state check is not satisfied, the time step is increased by one, that is, t i =t i-1 +Δt, i is a natural number, and the step 2 is jumped to for calculation of the next time step simulation; step 4, checking whether the wire surface field intensity obtained at this time satisfies the Kaptzov assumption; step 5, if the Kaptzov assumption is satisfied, the wire surface electric field intensity obtained in the current calculation and the maximum electric field intensity on the surface of the target obstacle are obtained; if the Kaptzov assumption is not satisfied, the wire surface charge density is corrected by using the charge density iterative formula by using the prediction-correction method, and then the step 1 is executed. wherein "checking whether the space charge distribution reaches a steady state" means using the error of the ground synthetic field strength to measure whether the space charge distribution reaches a steady state; wherein "whether the Kaptzov assumption is met" means using the kaptzov assumption criterion to test whether the error of the conductor surface electric field strength and the corona onset field strength meets the requirements; wherein "correcting the conductor surface charge density" is specifically: setting the conductor surface potential as the actual operating voltage of the conductor, setting the ground potential as 0, regarding the target obstacle as a grounded conductor, and setting the terminal voltage as 0; The equivalent corona inception field strength of the equivalent conductor is calculated by using the corona degree equivalent principle, specifically: the corona inception field strength of the split conductor wherein and is an empirical constant, is the surface roughness coefficient of the conductor, is the relative density of air, is the equivalent conductor radius; A model was built using Comsol software, and the maximum working electric field strength on the surface of the split conductor was calculated through simulation. and the maximum working field strength of the equivalent conductor surface Using formula The equivalent halo field strength is calculated, where... This is the ratio of the corona induction field strength of the split conductor to the maximum working field strength on the surface. It is the ratio of the corona induction field strength of the equivalent conductor to the maximum working field strength on the surface; The wire surface charge density is iterated in MATLAB, the wire surface charge density is corrected successively by using the charge density iteration formula with the prediction-correction method, simulation calculation is started after setting the similar wire surface charge density, the wire surface field strength is compared with the corona inception field strength, the wire surface charge density is corrected by the formula correction of the wire surface charge density. 2.The power transmission line electric discharge early warning method based on UAV monitoring of claim 1, wherein: The "obstacle height extraction method based on a digital model" comprises the following steps: subtracting a digital surface model (DSM) from a digital elevation model (DEM) in a measurement area to obtain a digital model reflecting the change in obstacle height; calculating the obstacle height value by performing neighborhood analysis on the digital model; using a circular neighborhood to analyze the obstacle according to its characteristics; and obtaining the maximum value in the neighborhood as the to-be-determined vertex by focal point statistics, and then extracting the height information of the obstacle to obtain the first obstacle height value after removing the false "vertex" in combination with an orthographic image. 3.The power transmission line electric discharge early warning method based on UAV monitoring of claim 1, wherein: The "obstacle height extraction method using point cloud information" comprises the following steps: filtering and denoising the three-dimensional point cloud to prevent isolated noise points from affecting the extraction result; circumscribing a predetermined range to extract the point cloud of the target obstacle, which includes the ground point cloud and the obstacle point cloud, and excludes the interference of other irrelevant objects to prepare for the extraction of the obstacle height; distinguishing the ground point cloud from the obstacle point cloud according to the number distribution of the height values of the point cloud, using the average value of the ground point cloud to replace the elevation, taking the highest point of the obstacle point cloud as the obstacle vertex, and finally subtracting the ground elevation to obtain the second obstacle height value of the measured obstacle.

4. The method for discharge pre-warning of power transmission line based on UAV monitoring according to claim 3, characterized in that: The second obstacle height value obtained by the "obstacle height extraction method using point cloud information" is selected as the final obstacle height calculation value.

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