Distribution line sag point determination method and device, equipment and medium

Abstract

The invention discloses a method, a device and equipment for determining a sag point of a distribution line, and a medium. The method comprises the following steps: obtaining distribution line information of a distribution line area, a plurality of first acquisition images corresponding to a plurality of spacers in the distribution line area, and a plurality of second acquisition images corresponding to a plurality of towers in the distribution line area; performing image enhancement processing on the plurality of first acquisition images to obtain a plurality of enhanced target acquisition images; determining a plurality of first three-dimensional coordinate data of a plurality of spacers and a plurality of second three-dimensional coordinate data of a plurality of towers in the distribution line area based on the plurality of target acquisition images and the plurality of second acquisition images; and based on the distribution line information, the plurality of first three-dimensional coordinate data and the plurality of second three-dimensional coordinate data, determining position information of a sag point of each span in the distribution line area. By means of the mode, the accuracy of sag point measurement and calculation is achieved, meanwhile, complex calculation of manual sag measurement through a theodolite is avoided, the measurement time is shortened, and the risk of manual errors is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution lines, and in particular, to a method, device, equipment and medium for determining the sag points of distribution lines. Background Art

[0002] The sag of a distribution line is one of the key parameters concerned in the operation and maintenance of distribution lines. At present, the most commonly used method for measuring sag is to manually measure and calculate with a theodolite. However, distribution lines are usually widely distributed, and the terrain along the line is complex and diverse. Manual measurement not only increases the walking burden on the measurement personnel, but also poses certain safety risks. Moreover, it may be difficult to conduct effective measurement due to the obstruction of the line of sight by obstacles, resulting in low accuracy and efficiency of the measurement results. Summary of the Invention

[0003] The present invention provides a method, device, electronic equipment and medium for determining the sag points of distribution lines, so as to solve the technical problems that the measurement method of manually measuring the sag points with a theodolite has a heavy walking burden on the measurement personnel, is difficult to conduct effective measurement due to the obstruction of the line of sight, and has low accuracy and efficiency of the measurement results.

[0004] In a first aspect, a method for determining the sag points of distribution lines is provided, including:

[0005] Obtaining distribution line information of a distribution line area, a plurality of first captured images corresponding to a plurality of spacer dampers in the distribution line area, and a plurality of second captured images corresponding to a plurality of poles and towers;

[0006] Performing image enhancement processing on the plurality of first captured images to obtain a plurality of enhanced target captured images;

[0007] Based on the plurality of target captured images and the plurality of second captured images, determining a plurality of first three-dimensional coordinate data of a plurality of spacer dampers and a plurality of second three-dimensional coordinate data of a plurality of poles and towers in the distribution line area;

[0008] Based on the distribution line information, the plurality of first three-dimensional coordinate data and the plurality of second three-dimensional coordinate data, determining the position information of the sag points of each span in the distribution line area.

[0009] In a second aspect, a device for determining the sag points of distribution lines is provided, including:

[0010] An obtaining module, configured to obtain distribution line information of a distribution line area, a plurality of first captured images corresponding to a plurality of spacer dampers in the distribution line area, and a plurality of second captured images corresponding to a plurality of poles and towers;

[0011] An image processing module, configured to perform image enhancement processing on the plurality of first captured images to obtain a plurality of enhanced target captured images;

[0012] The first determination module is configured to obtain multiple first three-dimensional coordinate data of multiple spacer dampers and multiple second three-dimensional coordinate data of multiple towers within the distribution line area based on multiple target acquisition images and multiple second acquisition images;

[0013] The second determination module is configured to determine the position information of the sag points of each span within the distribution line area based on the distribution line information, multiple first three-dimensional coordinate data, and multiple second three-dimensional coordinate data.

[0014] In a third aspect, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above method for determining the sag points of the distribution line are implemented.

[0015] In a fourth aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method for determining the sag points of the distribution line are implemented.

[0016] In the solution implemented by the above method, device, electronic device, and storage medium for determining the sag points of the distribution line, by performing high-precision positioning on the towers and spacer dampers within the distribution line area, collecting their images, and enhancing the images of the spacer dampers, the quality indicators such as the clarity and contrast of the images are improved. Subsequently, through the enhanced images of the spacer dampers and the tower images, the three-dimensional coordinate data of the spacer dampers and towers within the distribution line area are obtained. Finally, based on the distribution line parameters, the three-dimensional coordinate data of the spacer dampers and towers, the positions of the sag points of each span are calculated. In this way, each spacer damper and tower are automatically located, the corresponding coordinate data are collected, and based on the coordinate data of the spacer dampers and towers, the sag parameters are calculated in segments, effectively improving the accuracy of the sag point calculation while eliminating the cumbersome calculations of manual theodolite measurement of the sag, shortening the measurement time and reducing the risk of human error. Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments of the present invention. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 is a flowchart of a method for determining the sag points of a distribution line in an embodiment of the present invention;

[0019] Figure 2 is a schematic diagram of a tower photographed by an image acquisition device in an embodiment of the present invention;

[0020] Figure 3 It is a schematic structural diagram of a device for determining the sag point of a distribution line in an embodiment of the present invention. Detailed implementation manners

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It should be understood that the accompanying drawings in the present invention are only for the purposes of illustration and description, and are not used to limit the protection scope of the present invention.

[0022] In addition, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in the present invention illustrate the operations implemented according to some embodiments of the present invention. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical context relationships may be reversed or implemented simultaneously. In addition, those skilled in the art may add one or more other operations to the flowchart or remove one or more operations from the flowchart under the guidance of the content of the present invention.

[0023] In addition, the embodiments described in the present invention are only a part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and illustrated in the accompanying drawings here may be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed present invention, but merely represents the selected embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts fall within the protection scope of the present invention.

[0024] It should be noted that the term "including" will be used in the embodiments of the present invention to indicate the existence of the features stated thereafter, but does not exclude the addition of other features. It should also be noted that similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In the description of the present invention, it should also be noted that the terms "first", "second", "third", "fourth", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0025] The following will describe this case in detail with reference to the relevant drawings in the specification.

[0026] In the embodiments of this specification, the distribution line is a basic component of the power grid and also a carrier for power transmission. It has a very wide distribution range, and the surrounding environment of the distribution corridor is extremely complex. The safe operation of the distribution line is of great significance for ensuring the reliable operation of the power system. Among them, the distribution network is usually composed of numerous poles and overhead lines. Under the combined action of factors such as its own gravity, environmental temperature changes, and wind loads, these overhead lines will sag to a certain extent, forming a sag. Sag is one of the key parameters concerned in the operation and maintenance of distribution lines. As the coverage area of the distribution network continues to expand, the length and complexity of the lines are also increasing, and the changes in sag are more complex and diverse. An overly small sag value will cause excessive tension inside the distribution wire, which may lead to a wire breakage accident. An overly large sag value will cause insufficient distance between the distribution wire and objects below such as trees, resulting in a discharge trip accident. Currently, the most commonly used method for measuring sag in the power industry is regular manual inspection. By manually using a theodolite to measure and calculate, however, due to the usually wide distribution of distribution lines and the complex and diverse terrain along their routes, restricted by the terrain, it not only increases the walking burden on the measurement personnel, but also makes it difficult to conduct effective measurements due to line-of-sight obstruction, with low measurement efficiency, and it is very difficult to detect abnormal changes in sag in a timely manner during the inspection interval. Based on the above problems, this application proposes a method for determining the sag points of a distribution line. By automatically positioning each spacer and pole using an image acquisition device, collecting the corresponding coordinate data, and based on the spacer and pole coordinate data, segmentally calculating the sag parameters, it effectively improves the accuracy of calculating the sag points while eliminating the cumbersome calculations of manually measuring sag with a theodolite, shortening the measurement time and reducing the risk of human error.

[0027] Please refer to Figure 1 , this specification embodiment provides a method for determining the sag points of a distribution line, and the method specifically includes the following steps:

[0028] S10: Obtain the distribution line information of the distribution line area, multiple first acquisition images corresponding to multiple spacers in the distribution line area, and multiple second acquisition images corresponding to multiple poles.

[0029] It can be understood that the execution subject of the present invention can be a device for determining the sag points of a distribution line, or a terminal or a server. Specifically, no limitation is made here. This embodiment of the present invention is described by taking the server as the execution subject as an example.

[0030] Among them, the distribution line area is the area where the distribution line to be detected is located. The distribution line information includes the geographical location, terrain and landform, distribution line parameters (line orientation of the distribution line), pole tower information (including pole tower position, pole tower number, pole tower spacing), and spacer information (including spacer position, spacer number, and spacer spacing between two adjacent pole towers) corresponding to this area. Among them, the spacer is installed on the distribution line to fix the spacing between distribution lines, prevent the distribution lines from whipping each other, and suppress micro-vibrations, etc. Due to the influence of the spacer support between the spans formed by two adjacent pole towers in the distribution line area, a complete sag segment between the spans will be divided into discontinuous sag segments by several spacers. In order to obtain more accurate sag parameters, this application proposes to use an image acquisition device to separately photograph the spacers and pole towers to obtain a plurality of first acquisition images including all spacers in the area and a plurality of second acquisition images including all pole towers in the area, and then use the spacer positions and pole tower positions in the acquisition images to determine the sag points between the spans.

[0031] In an embodiment of the present application, a specific image acquisition scheme is provided. In S10, that is, to obtain the distribution line information of the distribution line area, a plurality of first acquisition images corresponding to a plurality of spacers in the distribution line area, and a plurality of second acquisition images corresponding to a plurality of pole towers, which specifically includes the following steps S11-S15:

[0032] S11: Obtain the distribution line information of the distribution line area.

[0033] In this step, according to the design drawings in the distribution line area, obtain the pole tower information of each pole tower in the distribution line area (including the position, number, and distribution of multiple pole towers, etc.), the spacer information of multiple spacers included in each span (including the position, number, and distribution of multiple spacers between each span, etc.), and the line direction information of the distribution line.

[0034] In the actual application scenario, in the design drawings during the construction of the distribution line, the specific position (latitude and longitude, relative position), height, type (such as straight tower, strain tower, etc.) of each pole tower, the length of the span, the installation position, model, etc. of the spacer are marked, and at the same time, the orientation of the distribution line is also clarified. By consulting these design drawings in combination with the final completion data, relatively accurate and comprehensive basic information can be directly obtained. In addition, it is also necessary to obtain the terrain and landform (such as buildings, etc.), meteorological conditions (such as wind speed, light, etc.), and surrounding obstacles (such as trees, buildings, etc.) in the distribution line area. The complex terrain and environment may affect the flight and survey effect of the unmanned aerial vehicle and need to be used as the basis for determining the shooting position.

[0035] S12: Determine multiple first shooting positions corresponding to multiple spacer dampers based on line direction information, tower information, and spacer damper information.

[0036] In this step, according to the spacer damper information of the spacer damper, determine the density of the spacer dampers distributed between spans. Furthermore, according to the distribution of the distribution wire direction, tower positions, tower distribution, as well as the density and distribution of the spacer dampers, divide the distribution line area to determine multiple first shooting positions for the image acquisition device to shoot the spacer dampers.

[0037] In an actual application scenario, the image acquisition device can be a drone. Considering the shooting angle, range, distribution of towers and spacer dampers, as well as the on-site terrain and obstacle distribution, set multiple first shooting positions required for the drone to shoot the spacer dampers to ensure that the images taken by the drone at multiple first acquisition devices can cover all the spacer dampers within the area.

[0038] Through the above method, according to the tower positions and spacer damper distribution within the area, plan the shooting positions of the spacer dampers in advance, so that the drone does not need to blindly search for the spacer dampers in a large area and can directly go to the predetermined shooting points for shooting, greatly saving the time for finding the target and improving the overall efficiency of the inspection work.

[0039] S13: Determine a second shooting position and a third shooting position for each tower based on tower information.

[0040] In this step, according to the position and distribution of each tower, set a second shooting position and a third shooting position required for the image acquisition device to shoot each tower, so that the image acquisition device shoots the tower at the second shooting position and the third shooting position respectively. Furthermore, construct a spatial geometric relationship based on the two images of each tower obtained, and accurately calculate the actual height of each tower.

[0041] Optionally, in order to comprehensively obtain information such as the appearance characteristics of the tower, shooting at different angles in the horizontal direction can supplement the side information missing from the directly above view. Therefore, select different angles on the circumference at a certain safe distance from the tower (such as the safe distance is set to 0.5 times the tower height) to determine the second shooting position and the third shooting position. For example, select 45° as the second shooting position of the tower, and select 0° (i.e., directly above the tower) as the third shooting position of the tower.

[0042] Through the above method, according to the position of each tower, plan two shooting positions in advance, so that the drone provides different perspectives through different shooting positions, thereby obtaining all-round information of the tower, reducing information omission, and ensuring accurate measurement and calculation of various parameters of the tower in the future.

[0043] S14: Obtain multiple first acquisition images corresponding to multiple spacer dampers based on multiple first shooting positions.

[0044] In this step, control the image acquisition device to shoot the spacer dampers at multiple first shooting positions, and receive the multiple first acquisition images fed back by the image acquisition device.

[0045] Optionally, after receiving all the first acquisition images, compare the spacer dampers in the first acquisition images with those in the design drawings to detect the spacer dampers in the first acquisition images, ensuring that all the spacer dampers are included in the images. If any spacer damper is detected to be missing in the acquisition images, re-design the first shooting positions so that the drone re-shoots the spacer dampers, ensuring that the multiple finally shot first acquisition images can completely cover all the spacer dampers in the area.

[0046] S15: Obtain multiple second acquisition images corresponding to multiple power transmission towers based on multiple second shooting positions and multiple third shooting positions.

[0047] In this step, control the image acquisition device to shoot the power transmission towers at the second shooting positions and the third shooting positions corresponding to each power transmission tower from different positions and angles, and receive the two second acquisition images corresponding to each power transmission tower sent by the image acquisition device.

[0048] In an actual application scenario, the drone's gimbal locks the top of the tower and flies horizontally, shooting images containing the top of the tower at two different positions, the second shooting position and the third shooting position, and then constructing the spatial geometric relationship of the power transmission tower based on the obtained images.

[0049] In the above manner, control the image acquisition device to automatically obtain the acquisition images of the spacer dampers and the power transmission towers according to the reasonably planned shooting positions and shooting routes, shortening the measurement time, reducing the input of manpower and material resources, and thus reducing the measurement cost.

[0050] S20: Perform image enhancement processing on multiple first acquisition images to obtain multiple enhanced target acquisition images.

[0051] In this step, all the spacer dampers in the power distribution line area are recorded in the multiple first acquisition images to achieve real-time positioning of the spacer dampers. However, in the actual shooting process, due to reasons such as poor lighting conditions, the spacer dampers captured in the first acquisition images may have problems such as blurring and unclear details. To ensure the clarity of the spacer damper contours in the images, this application proposes to perform image enhancement processing on the captured first acquisition images to obtain enhanced target acquisition images, effectively reducing noise and making the contours and structures of the spacer dampers clearly distinguishable, providing a reliable basis for subsequent data analysis.

[0052] In an embodiment of the present application, a specific image enhancement scheme is provided. In S20, that is, image enhancement processing is performed on a plurality of first captured images to obtain a plurality of enhanced target captured images, which specifically includes the following steps S21 - S26:

[0053] S21: Obtain a plurality of pixel values of a plurality of pixel points in each first captured image.

[0054] S22: Use the Laplacian pyramid method to perform sharpening processing on each first captured image based on the gamma correction factor and a plurality of pixel values to obtain a sharpened third captured image.

[0055] For steps S21 - S22, when the drone inspects the spacer target, due to external factors such as environmental light, angle, and flight speed, the captured images often appear blurred and have unclear boundaries. Therefore, the Laplacian is used to perform sharpening processing on the image to enhance the image contrast. At the same time, the gamma correction factor is applied to enhance the brightness and contrast of the image. Specifically, the expression of the enhanced image after the above operation is:

[0056]

[0057] In the formula, the above g′(x, y) is the pixel value of any pixel point in the sharpened third captured image; the above L(x, y) is the pixel value after Laplacian processing; the above γ is the gamma correction factor; the above g(x, y) is the pixel value of any pixel point in the first captured image; the above is the second-order differential derivative symbol.

[0058] S23: Obtain a plurality of pixel values of a plurality of pixel points in each third captured image;

[0059] S24: Based on a plurality of preset gradient directions and a plurality of pixel values, perform a convolution operation on each pixel point to determine the first gradient value of each pixel point in each preset gradient direction;

[0060] For steps S23 - S24, in order to obtain better image quality, the present application also proposes to enhance the image edge information. Specifically, obtain a plurality of pixel values of a plurality of pixel points in the sharpened third captured image, and perform a convolution operation on each pixel point according to a plurality of preset Sobel operator directions and a plurality of pixel values to obtain the gradient value of each pixel point in each preset Sobel operator direction, denoted as the first gradient value. Specifically, the expression after the above operation is:

[0061]

[0062] In the formula, the above θ is the preset gradient direction, the above G θ(x, y) is the first gradient value in the preset gradient direction θ; the above ω θ (i, j) is the convolution kernel weight in the preset gradient direction θ; the above I(x, y) is the pixel value of the third acquired image I at the pixel point (x, y).

[0063] Optionally, in order to better display the gradient information in multiple directions, the embodiments of the present application add six directions on the basis of the horizontal and vertical directions of the Sobel operator, including 0°, 45°, 90°, 135°, 180°, 225°, 270°, 315°. By replacing the basic Sobel operator with the Sobel operator in eight different gradient directions after expansion, the ability to extract complex edge feature information of the image is enhanced.

[0064] S25: Based on the preset attenuation factor and the first gradient value of each pixel point, determine the second gradient value corresponding to each pixel point.

[0065] In this step, in order to reduce the interference of gradient calculation on the overall characteristics of the image, the present application proposes to control the attenuation degree of the gradient value by introducing an attenuation factor, so as to pay more attention to the local edge details when extracting edge features. Specifically, the expression after the above operation is:[[]]

[0066]

[0067] In the formula, the above is the second gradient value of the third acquired image at the pixel point (x, y); the above κ is a preset attenuation factor between [0, 1]; the above G θ (x, y) is the first gradient value of the third acquired image at the pixel point (x, y).

[0068] Optionally, in order to ensure that the calculated gradient value will not be too large or too small due to local abnormal changes, the present application also proposes to pre-set a threshold range to restrict the gradient value. Specifically, after calculating the second gradient value of each pixel point, compare each second gradient value with the preset threshold range in turn. If the second gradient value is not within this preset threshold range, the preset value needs to be set as the second gradient value of this pixel point, where the preset value is set according to the preset threshold range. By introducing a threshold range to restrict the gradient value, it is ensured that the calculated gradient value keeps a relatively stable and consistent characteristic in the gradient calculation of the whole image, which helps to accurately extract and analyze the edge features of the image.

[0069] S26: Based on the second gradient value of each pixel point and multiple preset gradient directions, perform non-maximum suppression processing on each third acquired image to obtain the target acquired image.

[0070] In this step, each pixel point in the third acquired image is traversed. According to its gradient direction, two adjacent pixel points are checked in this direction. If the second gradient value of the current pixel point is less than the second gradient values of the two adjacent pixel points, the second gradient value of this pixel point is set to 0; otherwise, the second gradient value of this pixel point is retained. By performing the above operations, the target acquired image after non-maximum suppression can be obtained, which can effectively refine the edges and make the edges in the image clearer.

[0071] In an embodiment of the present application, in order to control the effectiveness of image enhancement, the present application also provides a specific image quality evaluation scheme. After S22, that is, using the Laplacian pyramid method, based on the gamma correction factor and multiple pixel values, each first acquired image is sharpened. After obtaining the sharpened third acquired image, the following steps S27 - S28 are further included:

[0072] S27: Determine the structural similarity index between each first acquired image and its corresponding third acquired image based on multiple pixel values of each first acquired image, multiple pixel values of each third acquired image, a preset brightness factor, a preset contrast factor, and multiple preset gradient factors;

[0073] S28: Compare the structural similarity index with a preset threshold. If the structural similarity index is greater than or less than the preset threshold, generate parameter adjustment prompt information and send the parameter adjustment prompt information to the terminal of the target person, so that the target person adjusts the sharpening parameters based on the parameter adjustment prompt information.

[0074] For steps S27 - S28, in order to evaluate the image quality after sharpening processing, the structural similarity index (SIM) is calculated through the pixel values of the images before and after sharpening enhancement. The calculation formula is as follows:

[0075] E SSIM (g, g′) = [I(g, g′)] μ1 ×[c(g, g′)] μ2 ×[s(g, g′)] μ3 ;

[0076] In the formula, the above E ssIM (g, g′) is the structural similarity index of the scalable gradient operator; the above (g, g′) are the images before and after sharpening enhancement, where g is the first acquired image before sharpening processing, and g′ is the third acquired image after sharpening enhancement; the above I is the brightness factor; the above c is the contrast factor; the above s is the total gradient factor of multiple preset gradient directions, s(g, g′) = ∑ θ s θ (g, g′), where s θis the θ-th preset gradient direction, where θ ∈ (1, n); μ1, μ2, and μ3 are weight coefficients respectively.

[0077] Furthermore, compare the calculated structural similarity index with a preset threshold. If the structural similarity index is greater than the preset threshold, it indicates that the two images before and after the sharpening process are more similar, the changes in the image structure, brightness, and contrast caused by the sharpening process are smaller, and the retention of the image quality in these key features is higher, and the enhancement effect is more ideal; if the structural similarity index is less than or equal to the preset threshold, it means that the sharpening enhancement process has caused greater damage to the structure, brightness, or contrast of the image. It may be that the original image structure has been severely changed due to oversharpening of the image, affecting the quality and usability of the image. At this time, it is necessary to generate parameter adjustment prompt information and feedback it to the terminal of the target person, so that the target person can modify the sharpening parameters according to the received parameter adjustment prompt information.

[0078] Optionally, the structural similarity index comprehensively considers the information of the brightness, contrast, and structure of the image. By comparing the similarities of the original image and the enhanced image in these three aspects, a value between 0 and 1 is obtained. The closer the value is to 1, the more similar the two images are, the smaller the changes in the image structure, brightness, and contrast caused by the enhancement process, and the higher the retention of the image quality in these key features. Therefore, the second preset threshold can be set by relevant personnel according to business requirements, and this application does not make specific limitations here.

[0079] S30: Based on multiple target acquisition images and multiple second acquisition images, determine multiple first three-dimensional coordinate data of multiple spacer dampers and multiple second three-dimensional coordinate data of multiple towers in the distribution line area.

[0080] In this step, automatically identify the spacer damper from each target acquisition image, obtain the first three-dimensional coordinate data of the spacer damper. At the same time, obtain the second three-dimensional coordinate data of the tower from each second acquisition image. By obtaining the position information of the spacer damper and combining it with the position information of the tower, the spatial form of the power distribution line between two towers can be accurately constructed, and then the actual trend and bending conditions of the power distribution line between spans can be fully considered, so as to accurately determine the position of the sag point.

[0081] Through the above method, automatically identify and obtain the coordinate data of the spacer damper and the tower, without manual measurement and judgment, reducing the influence of human factors on the measurement results and improving the accuracy of sag point measurement.

[0082] In an embodiment of the present application, a specific three-dimensional coordinate data acquisition scheme is provided. In S30, that is, based on multiple target acquisition images and multiple second acquisition images, determine multiple first three-dimensional coordinate data of multiple spacer dampers and multiple second three-dimensional coordinate data of multiple towers in the distribution line area, which specifically includes the following steps S31 - S35:

[0083] S31: Determine the first three-dimensional coordinate data of each spacer based on multiple first acquisition images.

[0084] In this step, since the sag between spans is affected by the support of spacers, a complete sag segment is divided into discontinuous vertical segments by several spacers. Therefore, the optimized calculation of the conductor sag is realized through segmented modeling and non-linear analysis. First, an unmanned aerial vehicle (UAV) is used for aerial inspection. Using image detection technology and neural network learning algorithms, spacers are automatically identified from the photos or videos taken by the UAV, and the first three-dimensional coordinate data of the center points of the spacers, including longitude, latitude, and geodetic height, are accurately obtained by using RTK (Real-Time Kinematic) technology, realizing the automatic acquisition of three-dimensional coordinates, simplifying the operation process and reducing human errors.

[0085] S32: For any tower, obtain the third three-dimensional coordinate data of the second shooting position and the fourth three-dimensional coordinate data of the third shooting position.

[0086] S33: Determine the shooting distance between the second shooting position and the third shooting position based on the third three-dimensional coordinate data and the fourth three-dimensional coordinate data of the tower.

[0087] S34: Obtain the shooting angle information of the second shooting position.

[0088] S35: Determine the second three-dimensional coordinate data at the top of the tower based on the third three-dimensional coordinate data, the shooting angle information, and the shooting distance.

[0089] For steps S32 - S35, during the process of obtaining the three-dimensional coordinate data of any tower, the third three-dimensional coordinate data of the second shooting position and the fourth three-dimensional coordinate data of the third shooting position are obtained. According to the third three-dimensional coordinate data and the fourth three-dimensional coordinate data, the shooting distance between two different shooting positions is calculated. Subsequently, the shooting angle information when the image acquisition device records the tower at the second shooting position is obtained. Using a spatial triangle, a system of equations is established to calculate the three-dimensional coordinate data of the top of the tower.

[0090] Optionally, the shooting angle information includes the pitch angle and the azimuth angle (in a three-dimensional coordinate system, the angle between the ground projection of the UAV flight direction and the x (or y) axis of the earth). As Figure 2 shown, it is a schematic diagram of the image acquisition device shooting the tower. Among them, through UAV inspection, the UAV reaches the second shooting position A to shoot the tower. Subsequently, it flies horizontally to the third shooting position B, that is, directly above the tower, and shoots the tower again. Subsequently, the UAV feeds the real-time acquisition images back to the server, and the gimbal records the shooting position and the shooting angle information of the UAV at the second shooting position A and feeds them back to the server.

[0091] Among them, the system of equations is as follows:

[0092]

[0093] In the formula, the above (x T , y T , z T ) are the second three-dimensional coordinate data of the pole tower vertex; the above (x A , y A , z A ) are the third three-dimensional coordinate data of the second shooting position; the above d is the shooting distance; the above α is the pitching angle of the second shooting position; the above β is the azimuth angle of the second shooting position.

[0094] In the above way, images at different angles are obtained by means of the drone gimbal, and the coordinates of the pole tower in the three-dimensional space are accurately calculated using the spatial triangle relationship. Errors caused by factors such as terrain and line of sight occlusion in traditional measurement methods are avoided, and accurate calculations are performed through data from multiple observation points to ensure the accuracy of the three-dimensional coordinates of the pole tower.

[0095] S40: Based on the distribution line information, multiple first three-dimensional coordinate data, and multiple second three-dimensional coordinate data, determine the position information of the sag points of each span within the distribution line area.

[0096] In this step, according to the distribution line information of the distribution line area, the three-dimensional coordinates of the spacer dampers, and the three-dimensional coordinates of the pole towers, the sag points of each span (i.e., the distance between two adjacent pole towers) within the distribution line area are located, and finally the position information of the sag points is obtained.

[0097] In an embodiment of the present application, a specific scheme for determining the sag points is provided. In S40, that is, based on the distribution line information, multiple first three-dimensional coordinate data, and multiple second three-dimensional coordinate data, determine the position information of the sag points of each span within the distribution line area, which specifically includes the following steps S41 - S45:

[0098] S41: Based on the pole tower information and the spacer damper information, determine the two target pole towers corresponding to each span and the multiple target spacer dampers included between each span.

[0099] In this step, according to the pole tower information and the spacer damper information within the distribution line area, determine the distribution of the pole towers and the spacer dampers in the distribution line area, and then determine the two adjacent starting and ending pole towers (target pole towers) that form each span and the multiple target spacer dampers between the two adjacent pole towers.

[0100] S42: For any span, based on the first three-dimensional coordinate data of each target spacer damper and the second three-dimensional coordinate data of each target pole tower corresponding thereto, determine the two-dimensional coordinate data of each target spacer damper.

[0101] In this step, within a span, the distribution line assumes a shape similar to a parabola due to its own weight. To accurately describe the perpendicular shape of the distribution line, the center of the spacer is selected as the characteristic point, and at the same time, the two point coordinates of the starting and ending poles are added. The parabolic equation of the distribution line is fitted through these characteristic points to solve the position of the sag point. However, during the calculation process, the amount of three-dimensional space coordinate data is relatively large and the processing process is more complex. To reduce the difficulty of data processing, this application proposes to convert the three-dimensional space coordinates of the spacer to a two-dimensional O-xy coordinate system, reducing the information of one dimension, making the data structure simpler, helping to reduce the difficulty and calculation amount of data processing, and improving the data processing efficiency.

[0102] S43: Determine the error function based on the multiple two-dimensional coordinate data of multiple target spacers and the parabolic equation.

[0103] S44: Solve the minimum error function value to determine the minimum value within multiple parabolic equations.

[0104] S45: Determine the position information of the sag point of the span based on the minimum value.

[0105] For steps S43 - S45, in the coordinate system, let the parabolic equation be y = ax 2 + bx + c. Import the two-dimensional coordinate data (x', y') of the multiple converted spacers into the parabolic equation, and fit the coefficients a, b, c of the parabolic equation by the least squares method. The goal of the least squares method is to minimize the error function value:

[0106]

[0107] In the formula, the above E is the error function value; the above n is the number of spacers; the above (x′ i , x′ i ) is the two-dimensional coordinate data of the i-th spacer, where i ∈ (1, n).

[0108] After that, take the partial derivatives of E with respect to a, b, c respectively, and set the partial derivatives to 0:

[0109]

[0110] By solving the above equations, the coefficients a, b, c of the parabolic equation can be obtained, thereby determining the parabolic equation of the distribution line within the span in the two-dimensional O-xy coordinate system, and then converting it to solving the minimum value within all parabolic segments by finding the minimum error function value, which is the sag point within the span. Finally, the position information of the sag point is determined according to this minimum value.

[0111] In the above manner, by using the position coordinates of the spacer dampers within each span and combining the parabola model with the least squares method for sag measurement, the actual shape of the distribution line can be better reflected, making the measurement result closer to the actual situation, and thus the sag position information can be measured more accurately.

[0112] In the actual application scenario, after obtaining the position information of the sag points through measurement, the calculated sag values are compared and analyzed with the design values or previous measurement values. If the difference is large, the inspection personnel need to check whether there are problems with the measurement data, whether the calculation process is correct, or whether there are other factors such as line transformation, new loads, and natural environment. At the same time, the final sag parameters are output in an intuitive form such as a table, a graph (sag curve), etc. Among them, the output results should include detailed information such as the measurement date, weather conditions, measured line section, and tower number. A detailed measurement report is generated based on the measurement and analysis results, including the measurement method, data processing process, result analysis, as well as conclusions and suggestions, etc., providing complete data support for subsequent line operation and maintenance, inspection, and design.

[0113] In an embodiment of the present application, a specific scheme for determining the sag points is provided. In S42, that is, for any span, based on the first three-dimensional coordinate data of each target spacer damper and the second three-dimensional coordinate data of each target tower, the two-dimensional coordinate data of each target spacer damper is determined, specifically including the following steps S421 - S423:

[0114] S421: For any target spacer damper, obtain the first target three-dimensional coordinate data of the first target tower on both sides of the target spacer damper and the second target three-dimensional coordinate data of the second target tower.

[0115] S422: Based on the first target three-dimensional coordinate data and the second three-dimensional coordinate data of the target spacer damper, determine the two-dimensional abscissa data of the target spacer damper in the two-dimensional coordinate system.

[0116] S423: Based on the first target three-dimensional coordinate data, the second target three-dimensional coordinate data, and the second three-dimensional coordinate data, determine the two-dimensional ordinate data of the target spacer damper in the two-dimensional coordinate system.

[0117] For steps S421 - S423, during the coordinate conversion of each target spacer damper within each span, obtain the first target three-dimensional coordinate data and the second target three-dimensional coordinate data of the starting and ending towers (i.e., the first target tower and the second target tower) of the span where the target spacer damper is located. Let a target three-dimensional coordinate data be T s (x Ts , y Ts , z Ts ), and the second target three-dimensional coordinate data be T e (xTe , y Te , z Te ) , the specific conversion process is as follows:

[0118] Let any target spacer be P i (x i , y i , z i ), and its x - coordinate in the two - dimensional O - xy coordinate system is x′ i :

[0119] x′ i =(x i -x Ts ).

[0120] After that, the conversion of the y - coordinate needs to be calculated through the projection relationship of vectors:

[0121]

[0122] According to the vector dot - product formula, we can get:

[0123]

[0124] where θ is the included angle between and , then:

[0125]

[0126]

[0127] By the above method, the three - dimensional space coordinates of the spacer are converted to the two - dimensional O - xy coordinate system, reducing the information of one dimension, making the data structure simpler, helping to reduce the difficulty and calculation amount of data processing, and improving the data processing efficiency.

[0128] It can be seen that in the above solution, by accurately positioning the poles and spacers in the distribution line area, collecting their images, and enhancing the images of the spacers collected, the quality indicators such as the clarity and contrast of the images are improved. After that, through the enhanced images of the spacers and the images of the poles, the three - dimensional coordinate data of the spacers and poles in the distribution line area are obtained. Finally, according to the distribution line parameters, the three - dimensional coordinate data of the spacers and poles, the positions of the sag points of each span are measured. By the above method, each spacer and pole are quickly and accurately positioned, the corresponding coordinate data are collected, and based on the coordinate data of the spacers and poles, the sag parameters are measured segment by segment, effectively improving the accuracy of sag point measurement while eliminating the cumbersome calculations of manual theodolite sag measurement, shortening the measurement time and reducing the risk of human error.

[0129] In one embodiment, a device for determining the sag points of a distribution line is provided, and the device for determining the sag points of the distribution line corresponds one-to-one with the method for determining the sag points of the distribution line in the above embodiment. As Figure 3 shown, the device 100 for determining the sag points of the distribution line includes: an acquisition module 101, an image processing module 102, a first determination module 103, and a second determination module 104. The detailed description of each functional module is as follows:

[0130] The acquisition module 101 is configured to acquire distribution line information of the distribution line area, a plurality of first acquisition images corresponding to a plurality of spacer dampers in the distribution line area, and a plurality of second acquisition images corresponding to a plurality of poles and towers;

[0131] The image processing module 102 is configured to perform image enhancement processing on the plurality of first acquisition images to obtain a plurality of enhanced target acquisition images;

[0132] The first determination module 103 is configured to obtain a plurality of first three-dimensional coordinate data of a plurality of spacer dampers and a plurality of second three-dimensional coordinate data of a plurality of poles and towers in the distribution line area based on the plurality of target acquisition images and the plurality of second acquisition images;

[0133] The second determination module 104 is configured to determine the position information of the sag points of each span in the distribution line area based on the distribution line information, the plurality of first three-dimensional coordinate data, and the plurality of second three-dimensional coordinate data.

[0134] In one embodiment, the acquisition module 101 is specifically configured to:

[0135] Acquire distribution line information of the distribution line area, where the distribution line information includes the pole and tower information of each pole and tower in the distribution line area, the spacer damper information of a plurality of spacer dampers included in each span, and the line direction information of the distribution line;

[0136] Determine a plurality of first shooting positions corresponding to the plurality of spacer dampers based on the line direction information, the pole and tower information, and the spacer damper information;

[0137] Determine a second shooting position and a third shooting position corresponding to each pole and tower based on the pole and tower information;

[0138] Acquire a plurality of first acquisition images corresponding to the plurality of spacer dampers based on the plurality of first shooting position information;

[0139] Acquire a plurality of second acquisition images corresponding to the plurality of poles and towers based on the plurality of second shooting positions and the plurality of third shooting positions.

[0140] In one embodiment, the image processing module 102 is specifically configured to:

[0141] Acquire a plurality of pixel values of a plurality of pixel points in each first acquisition image;

[0142] Using the Laplacian pyramid method, based on the gamma correction factor and multiple pixel values, perform sharpening processing on each first acquired image to obtain a sharpened third acquired image;

[0143] Obtain multiple pixel values of multiple pixel points in each third acquired image;

[0144] Based on multiple preset gradient directions and multiple pixel values, perform a convolution operation on each pixel point to determine the first gradient value of each pixel point in each preset gradient direction;

[0145] Based on the preset attenuation factor and the first gradient value of each pixel point, determine the second gradient value corresponding to each pixel point;

[0146] Based on the second gradient value of each pixel point and multiple preset gradient directions, perform non-maximum suppression processing on each third acquired image to obtain a target acquired image.

[0147] In one embodiment, the device further includes:

[0148] A third determination module, configured to determine the structural similarity index between each first acquired image and its corresponding third acquired image based on multiple pixel values of each first acquired image, multiple pixel values of each third acquired image, a preset brightness factor, a preset contrast factor, and multiple preset gradient factors;

[0149] A comparison module, configured to compare the structural similarity index with a preset threshold; a generation module, configured to generate parameter adjustment prompt information if the structural similarity index is less than or equal to the preset threshold; a sending module, configured to send the parameter adjustment prompt information to the terminal of the target person, so that the target person adjusts the sharpening parameters based on the parameter adjustment prompt information.

[0150] In one embodiment, the first determination module 103 is specifically configured to:

[0151] Based on multiple first acquired images, determine the first three-dimensional coordinate data of each spacer;

[0152] For any tower pole, obtain the third three-dimensional coordinate data of the second shooting position and the fourth three-dimensional coordinate data of the third shooting position;

[0153] Based on the third three-dimensional coordinate data and the fourth three-dimensional coordinate data of the tower pole, determine the shooting distance between the second shooting position and the third shooting position;

[0154] Obtain the shooting angle information of the second shooting position;

[0155] Based on the third three-dimensional coordinate data, the shooting angle information, and the shooting distance, determine the second three-dimensional coordinate data at the vertex of the tower pole.

[0156] In one embodiment, the second determination module 104 is specifically configured to:

[0157] Based on the tower information and spacer information, determine two target towers corresponding to each span and multiple target spacers included between each span;

[0158] For any span, based on the first three-dimensional coordinate data of each target spacer and the second three-dimensional coordinate data corresponding to each target tower, determine the two-dimensional coordinate data of each target spacer;

[0159] Based on the multiple two-dimensional coordinate data of the multiple target spacers and the parabola equation, determine the error function;

[0160] Solve the minimum error function value to determine the minimum value within the multiple parabola equations;

[0161] Based on the minimum value, determine the position information of the sag point of the span.

[0162] In one embodiment, the second determination module 104 is further specifically configured to:

[0163] For any target spacer, obtain the first target three-dimensional coordinate data of the first target tower on both sides of the target spacer and the second target three-dimensional coordinate data of the second target tower;

[0164] Based on the first target three-dimensional coordinate data and the second three-dimensional coordinate data of the target spacer, determine the two-dimensional abscissa data of the target spacer in the two-dimensional coordinate system;

[0165] Based on the first target three-dimensional coordinate data, the second target three-dimensional coordinate data, and the second three-dimensional coordinate data, determine the two-dimensional ordinate data of the target spacer in the two-dimensional coordinate system.

[0166] The present invention provides a device for determining the sag point of a distribution line. By performing high-precision positioning on the towers and spacers in the distribution line area, collecting their images, and enhancing the images of the spacers, the quality indicators such as the clarity and contrast of the images are improved. Subsequently, through the enhanced spacer acquisition images and tower images, the three-dimensional coordinate data of the spacers and towers in the distribution line area are obtained. Finally, according to the distribution line parameters, the three-dimensional coordinate data of the spacers and towers, the position of the sag point of each span is calculated. Through the above method, each spacer and tower can be quickly and accurately located, the corresponding coordinate data is collected, and based on the spacer and tower coordinate data, the sag parameters are calculated in segments, effectively improving the accuracy of sag point calculation, while eliminating the cumbersome calculations of manual theodolite measurement of sag, shortening the measurement time and reducing the risk of human error.

[0167] For the specific limitations of the device for determining the sag point of the distribution line, reference can be made to the limitations of the method for determining the sag point of the distribution line in the above text, which will not be elaborated here. Each module in the above device for determining the sag point of the distribution line can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the electronic device in the form of hardware or be independent of it, or can be stored in the memory of the electronic device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0168] In one embodiment, an electronic device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0169] Obtain the distribution line information of the distribution line area, multiple first captured images corresponding to multiple spacer dampers in the distribution line area, and multiple second captured images corresponding to multiple transmission towers;

[0170] Perform image enhancement processing on the multiple first captured images to obtain multiple enhanced target captured images;

[0171] Based on the multiple target captured images and the multiple second captured images, determine multiple first three-dimensional coordinate data of multiple spacer dampers and multiple second three-dimensional coordinate data of multiple transmission towers in the distribution line area;

[0172] Based on the distribution line information, the multiple first three-dimensional coordinate data, and the multiple second three-dimensional coordinate data, determine the position information of the sag point of each span in the distribution line area.

[0173] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0174] Obtain the distribution line information of the distribution line area, multiple first captured images corresponding to multiple spacer dampers in the distribution line area, and multiple second captured images corresponding to multiple transmission towers;

[0175] Perform image enhancement processing on the multiple first captured images to obtain multiple enhanced target captured images;

[0176] Based on the multiple target captured images and the multiple second captured images, determine multiple first three-dimensional coordinate data of multiple spacer dampers and multiple second three-dimensional coordinate data of multiple transmission towers in the distribution line area;

[0177] Based on the distribution line information, the multiple first three-dimensional coordinate data, and the multiple second three-dimensional coordinate data, determine the position information of the sag point of each span in the distribution line area.

[0178] It should be noted that for the functions or steps that can be achieved by the above computer-readable storage medium or electronic device, reference can be made to the relevant descriptions on the server side and the client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0179] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0180] Those skilled in the art can clearly understand that for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0181] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments or equivalently replace some of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention and should all be included in the protection scope of the present invention.

Claims

1. A method for determining the sag point of a distribution line, characterized in that: include: Acquire distribution line information of a distribution line area, a plurality of first acquired images corresponding to a plurality of spacers in the distribution line area, and a plurality of second acquired images corresponding to a plurality of pole towers; Performing image enhancement processing on the multiple first collected images to obtain multiple enhanced target collected images; Determine a plurality of first three-dimensional coordinate data of the plurality of spacers and a plurality of second three-dimensional coordinate data of the plurality of towers in the distribution line area based on the plurality of target acquisition images and the plurality of second acquisition images; Based on the power distribution line information, the plurality of first three-dimensional coordinate data and the plurality of second three-dimensional coordinate data, position information of the sag point of each span in the power distribution line area is determined.

2. The method according to claim 1, characterized in that The step of acquiring the distribution line information of the distribution line area, the multiple first collected images corresponding to the multiple spacers in the distribution line area, and the multiple second collected images corresponding to the multiple towers specifically includes: Acquire the distribution line information of the distribution line area, wherein the distribution line information includes the tower information of each tower in the distribution line area, the spacer information of a plurality of spacers included in each span, and the line direction information of the distribution line; Based on the line direction information, the tower information and the spacer information, determining a plurality of first shooting positions corresponding to the plurality of spacers; Based on the tower information, determining a second shooting position and a third shooting position corresponding to each tower; Based on the plurality of first shooting position information, acquiring the plurality of first acquisition images corresponding to the plurality of spacer bars; Based on the plurality of second shooting positions and the plurality of third shooting positions, the plurality of second collected images corresponding to the plurality of towers are acquired.

3. The method according to claim 1, characterized in that The step of performing image enhancement processing on the multiple first collected images to obtain multiple enhanced target collected images specifically includes: Acquire multiple pixel values ​​of multiple pixel points in each first acquired image; Using a Laplace pyramid method, based on a gamma correction factor and a plurality of pixel values, each of the first acquired images is sharpened to obtain a sharpened third acquired image; Acquire multiple pixel values ​​of multiple pixel points in each third acquired image; Based on multiple preset gradient directions and multiple pixel values, a convolution operation is performed on each pixel point to determine a first gradient value of each pixel point in each preset gradient direction; Determine a second gradient value corresponding to each pixel point based on a preset attenuation factor and the first gradient value of each pixel point; Based on the second gradient value of each pixel point and the multiple preset gradient directions, non-maximum suppression processing is performed on each third acquired image to obtain a target acquired image.

4. The method according to claim 3, characterized in that After the sharpening process is performed on each of the first acquired images by using the Laplace pyramid method based on the gamma correction factor and the plurality of pixel values ​​to obtain the sharpened third acquired image, the method further includes: Determining a structural similarity index between each first acquired image and its corresponding third acquired image based on a plurality of pixel values ​​of each first acquired image, a plurality of pixel values ​​of each third acquired image, a preset brightness factor, a preset contrast factor, and a plurality of preset gradient factors; The structural similarity index is compared with a preset threshold. If the structural similarity index is less than or equal to the preset threshold, parameter adjustment prompt information is generated and sent to the terminal of the target person, so that the target person adjusts the sharpening parameters based on the parameter adjustment prompt information.

5. The method according to claim 2, characterized in that: The step of determining a plurality of first three-dimensional coordinate data of the plurality of spacers and a plurality of second three-dimensional coordinate data of the plurality of towers in the distribution line area based on the plurality of target acquisition images and the plurality of second acquisition images specifically comprises: Based on the plurality of first acquired images, determining first three-dimensional coordinate data of each spacer bar; For any pole tower, obtaining third three-dimensional coordinate data of the second shooting position and fourth three-dimensional coordinate data of the third shooting position; Determine a shooting distance between the second shooting position and the third shooting position based on the third three-dimensional coordinate data and the fourth three-dimensional coordinate data of the tower; Acquiring shooting angle information of the second shooting position; Based on the third three-dimensional coordinate data, the shooting angle information and the shooting distance, the second three-dimensional coordinate data at the top of the tower is determined.

6. The method according to claim 2, characterized in that The step of determining the position information of the sag point of each span in the distribution line area based on the distribution line information, the plurality of first three-dimensional coordinate data and the plurality of second three-dimensional coordinate data specifically includes: Based on the tower information and the spacer information, two target towers corresponding to each span and a plurality of target spacers included between each span are determined; For any span, based on the first three-dimensional coordinate data of each target spacer and the second three-dimensional coordinate data corresponding to each target tower, determine the two-dimensional coordinate data of each target spacer; determining an error function based on a plurality of two-dimensional coordinate data of a plurality of target spacer bars and a parabola equation; Solve the minimum error function value and determine the minimum value in multiple parabolic equations; Based on the minimum value, the position information of the sag point of the span is determined.

7. The method according to claim 6, characterized in that The step of determining the two-dimensional coordinate data of each target spacer based on the first three-dimensional coordinate data of each target spacer and the second three-dimensional coordinate data corresponding to each target tower specifically includes: For any target spacer bar, obtaining first target three-dimensional coordinate data of a first target pole tower and second target three-dimensional coordinate data of a second target pole tower on both sides of the target spacer bar; Determine two-dimensional horizontal coordinate data of the target spacer in a two-dimensional coordinate system based on the first target three-dimensional coordinate data and the second three-dimensional coordinate data of the target spacer; Based on the first target three-dimensional coordinate data, the second target three-dimensional coordinate data and the second three-dimensional coordinate data, the two-dimensional longitudinal coordinate data of the target spacer in the two-dimensional coordinate system is determined.

8. A device for determining the sag point of a distribution line, characterized in that: include: An acquisition module, used to acquire distribution line information in a distribution line area, a plurality of first acquisition images corresponding to a plurality of spacers in the distribution line area, and a plurality of second acquisition images corresponding to a plurality of towers; An image processing module, used for performing image enhancement processing on the plurality of first collected images to obtain a plurality of enhanced target collected images; A first determination module, configured to obtain a plurality of first three-dimensional coordinate data of the plurality of spacers and a plurality of second three-dimensional coordinate data of the plurality of towers in the distribution line area based on the plurality of target acquisition images and the plurality of second acquisition images; The second determination module is used to determine the position information of the sag point of each span in the distribution line area based on the distribution line information, the multiple first three-dimensional coordinate data and the multiple second three-dimensional coordinate data.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for determining the sag point of a distribution line as claimed in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for determining the sag point of a distribution line as claimed in any one of claims 1 to 7 are implemented.

Images