Three-dimensional power transmission channel reconstruction method and device combined with linear laser

Abstract

The invention discloses a three-dimensional power transmission channel reconstruction method and device combined with linear laser, and relates to the technical field of electric power engineering, and the method comprises the steps: collecting environment data of a target area, reading power transmission line design data, building a layout, planning a scanning path of a mobile platform, and configuring a mobile strategy. When the mobile platform moves, the laser and the camera are synchronously activated to capture laser ray projection to establish an image, a baseline distance and an equipment included angle are acquired, a two-dimensional coordinate is established according to the image, depth data are calculated, three-dimensional reconstruction is performed by using the two-dimensional coordinate and the depth data, and similar loss is analyzed to update a reconstruction result. The technical problem that in the prior art, due to interference of obstacles and light in a target area, the reliability and precision of a reconstruction result are insufficient is solved, and the technical effect of providing reliable support for monitoring and maintenance of a power transmission line is achieved through high-accuracy, high-reliability and high-precision reconstruction of the three-dimensional power transmission channel.

Description

Technical Field

[0001] The present application relates to the field of electric power engineering technology, and in particular to a method and device for reconstructing a three-dimensional power transmission channel in combination with a straight-line laser. Background Art

[0002] In the scenario of power transmission channel management, safe monitoring of transmission channels is crucial, but existing technologies have many shortcomings in this regard. Traditional transmission channel monitoring is often extensive, low in precision, greatly affected by environmental factors, and only relies on conventional monitoring methods. It is insufficient to control the overall condition of the transmission channel, lacks in-depth analysis and response to complex environmental factors, and is difficult to fully and accurately reflect the actual situation of the transmission channel. In terms of resource allocation, the existing monitoring technology is unreasonable, resulting in insufficient monitoring of some key areas and waste of resources in some areas. The monitoring scheme for transmission channels is relatively simple and fixed, and cannot cope well with the complex and changeable transmission environment. Therefore, there is an urgent need for a new three-dimensional transmission channel reconstruction method to improve the accuracy, reliability and precision of reconstruction, and provide strong guarantees for the safe operation of transmission lines.

[0003] At present, related technologies have technical problems such as insufficient reliability and accuracy of reconstruction results due to obstacles and light interference in the target area. Summary of the invention

[0004] The present application provides a method and device for reconstructing a three-dimensional power transmission channel in combination with a straight-line laser, collects target area environmental data (including obstacles and light characteristics), reads transmission line design data to establish a layout, plans a mobile platform scanning path and configures a mobile strategy (the platform integrates a straight-line laser and a monocular camera and is fixed), and when the mobile platform moves, the laser and camera are synchronously activated to capture the laser line projection to establish an image, obtain the baseline distance and the device angle, establish two-dimensional coordinates based on the image and calculate the depth data, use the two-dimensional coordinates and depth data to perform three-dimensional reconstruction and analyze similar losses to update the reconstruction results, thereby achieving a technical effect of providing reliable support for the monitoring and maintenance of transmission lines through high-accuracy, high-reliability and high-precision reconstruction of the three-dimensional transmission channel.

[0005] The present application provides a three-dimensional power transmission channel reconstruction method combined with a line laser, comprising: Perform regional environment acquisition of the target area and establish a regional environment data set, wherein the regional environment data set includes obstacle feature data and light feature data; read the design data of the transmission line, use the design data to establish the line layout of the transmission line, perform scanning path planning based on the line layout and the regional environment data set, and configure the mobile strategy of the mobile platform, wherein the mobile platform is integrated with a line laser and a monocular camera, and the line laser and the monocular camera are fixed on the mobile platform by preset relative positions; when the mobile platform starts to move based on the mobile strategy, the line laser and the monocular camera are synchronously activated, and the monocular camera is used to capture the laser line projection projected by the line laser on the transmission line of the target area to establish a projection image; the baseline distance and device angle of the line laser and the monocular camera are obtained by the preset relative position, the two-dimensional coordinates of the pixels are established according to the projection image, and the depth data is calculated by the baseline distance and the device angle; three-dimensional reconstruction is performed using the two-dimensional coordinates and the depth data, and the three-dimensional reconstruction result is subjected to similarity loss analysis of associated points, and the three-dimensional reconstruction result is updated with the similarity loss analysis result.

[0006] The present application also provides a three-dimensional power transmission channel reconstruction device combined with a line laser, comprising: A regional environment data set establishment module, the regional environment data set establishment module is used to perform regional environment acquisition of the target area and establish a regional environment data set, the regional environment data set includes obstacle feature data and light feature data; a mobile strategy configuration module, the mobile strategy configuration module is used to read the design data of the transmission line, use the design data to establish the line layout of the transmission line, use the line layout and the regional environment data set to perform scanning path planning, and configure the mobile strategy of the mobile platform, wherein the mobile platform is integrated with a line laser and a monocular camera, and the line laser and the monocular camera are fixed on the mobile platform by preset relative positions; a projection image establishment module, the projection image establishment module is used when the mobile When the platform starts to move based on the movement strategy, the straight-line laser and the monocular camera are synchronously activated, and the monocular camera is used to capture the laser line projection of the straight-line laser on the power transmission line in the target area to establish a projection image; a depth data calculation module is used to obtain the baseline distance and device angle of the straight-line laser and the monocular camera through a preset relative position, establish the two-dimensional coordinates of the pixel according to the projection image, and calculate the depth data through the baseline distance and the device angle; a three-dimensional reconstruction result update module is used to perform three-dimensional reconstruction using the two-dimensional coordinates and depth data, and perform similarity loss analysis of associated points on the three-dimensional reconstruction result, and update the three-dimensional reconstruction result with the similarity loss analysis result.

[0007] The method and device for reconstructing a three-dimensional transmission channel in combination with a straight-line laser proposed in this application first collect environmental data of the target area (including obstacles and light characteristics), read the transmission line design data to establish a layout, plan the scanning path of the mobile platform and configure the movement strategy (the platform integrates a straight-line laser and a monocular camera and is fixed), and when the mobile platform moves, the laser and camera are synchronously activated to capture the laser line projection to establish an image, obtain the baseline distance and the device angle, establish two-dimensional coordinates based on the image and calculate the depth data, use the two-dimensional coordinates and depth data to perform three-dimensional reconstruction and analyze similar losses to update the reconstruction results. Through the high-accuracy, high-reliability and high-precision reconstruction of the three-dimensional transmission channel, the technical effect of providing reliable support for the monitoring and maintenance of the transmission line is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the device according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0009] Figure 1 A schematic flow chart of a three-dimensional power transmission channel reconstruction method combined with a line laser provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of a three-dimensional power transmission channel reconstruction device combined with a line laser provided in an embodiment of the present application.

[0010] Explanation of reference numerals: regional environment data set establishing module 10 , movement strategy configuring module 20 , projection image establishing module 30 , depth data calculating module 40 , three-dimensional reconstruction result updating module 50 . DETAILED DESCRIPTION

[0011] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0012] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0013] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, device, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0014] The present application embodiment provides a method for reconstructing a three-dimensional power transmission channel by combining a line laser, such as Figure 1 As shown, the method includes: Step S100, execute regional environment collection of the target area, establish a regional environment data set, and the regional environment data set includes obstacle feature data and light feature data. Specifically, first determine the target area range for three-dimensional transmission channel reconstruction, then collect obstacle feature data through field survey, sensor detection and image recognition, including information such as the position, shape, and height of the obstacle, and use tools such as light sensors, sun position sensors and reflectivity meters to collect light feature data, such as light intensity, light direction and reflection characteristics, and finally organize and store the collected obstacle feature data and light feature data to establish a regional environment data set, which is managed in the form of a database to facilitate subsequent query and analysis, and provide basic information for three-dimensional transmission channel reconstruction.

[0015] Step S200, read the design data of the transmission line, use the design data to establish the line layout of the transmission line, plan the scanning path based on the line layout and the regional environmental data set, and configure the mobile strategy of the mobile platform, wherein the mobile platform is integrated with a line laser and a monocular camera, and the line laser and the monocular camera are fixed on the mobile platform by preset relative positions. Specifically, read the design data of the transmission line to establish the line layout, and use the tower position as a key node to construct the three-dimensional position information of the transmission line in space. Then, combine the obstacle characteristics and light characteristics in the line layout and the regional environmental data set to plan the scanning path, consider the mobility and stability of the mobile platform, try to make the scanning path parallel to the transmission line and avoid obstacles, and adjust the mobile strategy according to the light intensity and direction. Then, configure the mobile strategy of the mobile platform, determine the moving speed, set the pause position, and consider the impact of environmental changes on the scanning process. For example, the mobile platform performs regional scanning in a top-to-bottom scanning mode, using a 180-degree scanning angle to ensure full coverage of the transmission line area, and adjust the power of the laser according to the light intensity in this process to cope with different lighting conditions. Finally, the mobile platform integrates a straight-line laser and a monocular camera, and fixes the two on the mobile platform by presetting relative positions to ensure a firm installation while taking into account equipment heat dissipation and protection issues, providing reliable support for the reconstruction of three-dimensional power transmission channels.

[0016] In a possible implementation, design data of a transmission line is read, a line layout of the transmission line is established using the design data, a scanning path is planned based on the line layout and a regional environmental data set, and a mobile strategy of a mobile platform is configured, wherein the mobile platform is integrated with a line laser and a monocular camera, and the line laser and the monocular camera are fixed on the mobile platform by preset relative positions, and step S200 further includes step S210, obtaining a platform size of the mobile platform, performing a spatial impact analysis based on the platform size and obstacle feature data in the regional environmental data set, and establishing a passage angle adaptation value for each position point. Specifically, the platform size of the mobile platform is determined, including parameters such as length, width, and height. The size information provides data support for analyzing the mobility and spatial adaptability of the mobile platform in the target area. The obstacle feature data in the regional environment data set is combined to perform spatial impact analysis. The obstacle feature data includes the position, shape, size and other information of various obstacles in the target area. By analyzing the spatial relationship between the mobile platform and the obstacle, the passage angle of the mobile platform at different locations can be determined. For example, if there is a tall building near a certain location of the mobile platform, the passage angle of the mobile platform at this location may be restricted. According to the shape and position of the obstacle, the maximum angle range that the mobile platform can safely pass at this location can be calculated, thereby establishing the passage angle adaptation value of each location. The adaptation value reflects the spatial adaptability of the mobile platform to the obstacle at this location. The higher the value, the larger the passage angle, and the easier it is for the mobile platform to pass through the location.

[0017] Step S220, calling the light feature data, performing the light adaptation analysis of the layout angle of the mobile platform based on the light feature data and the preset relative position, and establishing the light angle adaptation value of each position point. Specifically, calling the light feature data in the regional environment data set, the data includes information such as light intensity and light direction. The light feature affects the working effect of the straight line laser and the monocular camera on the mobile platform. The layout angle light adaptation analysis of the mobile platform is performed based on the light feature data and the preset relative position. The preset relative position refers to the fixed position relationship between the straight line laser and the monocular camera on the mobile platform. According to the incident angle of the light and the preset relative position, the laser line projection effect of the straight line laser and the image capture effect of the monocular camera at different positions can be determined. For example, if the illumination direction does not match the layout angle of the mobile platform at a certain position point, it may cause the laser line projection to be unclear or the monocular camera cannot capture the image normally. By analyzing the light feature and the preset relative position, the optimal layout angle range of the mobile platform at the position point can be calculated, thereby establishing the light angle adaptation value of each position point. This adaptation value reflects the adaptability of the mobile platform to the light at that location. The higher the value, the more suitable the light angle is, and the better the laser line projection and image capture effects are.

[0018] Step S230, optimizing the scanning path of the mobile platform according to the passage angle adaptation value and the light angle adaptation value, and configuring the mobile strategy according to the scanning path optimization result. Specifically, the previously obtained passage angle adaptation value and light angle adaptation value are used as important parameters to optimize the scanning path of the mobile platform. The purpose of scanning path optimization is to find a path that enables the mobile platform to move efficiently and safely in the target area, while ensuring that the one-line laser and the monocular camera can obtain the best working effect. Optimization algorithms, such as genetic algorithms, simulated annealing algorithms, etc., can be used to find the optimal scanning path. In the optimization process, the passage angle adaptation value and the light angle adaptation value are used as part of the objective function. At the same time, other factors, such as path length, moving time, etc., are considered. Through continuous iterative optimization, a scanning path with the best comprehensive performance is found. The mobile strategy is configured according to the scanning path optimization result. The mobile strategy includes the moving speed, stop position, steering angle, etc. of the mobile platform. According to the characteristics and requirements of the scanning path, reasonable configuration of the mobile strategy can improve the reconstruction efficiency and accuracy. For example, if there are some narrow channels or complex obstacle areas on the scanning path, the moving speed can be appropriately reduced and the stop position can be increased to better control the movement of the mobile platform. If there are some areas with good lighting conditions on the scanning path, the layout angle of the mobile platform can be adjusted to obtain better laser line projection and image capture effects. For example, the mobile platform performs regional scanning from top to bottom, using a 180-degree scanning angle to ensure full coverage of the transmission line area. In this process, the power of the laser is adjusted according to the light intensity to cope with different lighting conditions. By obtaining the platform size of the mobile platform and combining it with obstacle feature data for spatial impact analysis, calling the light feature data for layout angle light adaptation analysis, and then optimizing the scanning path and configuring the mobile strategy based on the passing angle adaptation value and the light angle adaptation value, the efficiency and accuracy of the three-dimensional transmission channel reconstruction combined with the straight line laser can be improved.

[0019] In a possible implementation, the scanning path of the mobile platform is optimized according to the passage angle adaptation value and the light angle adaptation value, and the mobile strategy is configured according to the scanning path optimization result. Step S230 further includes step S231, establishing a comprehensive cost function, and performing scanning path optimization with the comprehensive cost function, as follows: ;in, is the comprehensive cost function, is the total number of fitting position points of the scanning path, Representing any location point, For the The passing angle adaptation value of each position point, For the The light angle adaptation value of each position point, For the The location point and The cost of the action coherence of the position point. Specifically, the comprehensive cost function formula is ,in Represents the comprehensive cost function used to measure the quality of the scan path. is the total number of scan path fitting position points, Represent any point, It is the first one obtained based on the mobile platform size and obstacle characteristic data. The passing angle adaptation value of each position point reflects the spatial adaptability of the mobile platform and obstacles at that position point; The first The light angle adaptation value of each position point reflects the adaptability of the laser line projection and image capture effect to the light at that position point; For the and The action continuity cost of the position point is , , are the weight coefficients of the passing angle, light angle and action coherence cost value respectively. When optimizing the scanning path with the comprehensive cost function, first determine the initial scanning path and calculate its value, and then use optimization algorithms such as genetic algorithms to continuously generate new path populations through operations such as crossover and mutation and calculate value to find the The optimal scanning path with the smallest value provides a better basis for the reconstruction of three-dimensional transmission channels.

[0020] Step S300, when the mobile platform starts to move based on the mobile strategy, the line laser and the monocular camera are synchronously activated, and the monocular camera is used to capture the laser line projection projected by the line laser on the power transmission line in the target area to establish a projection image. Specifically, when the mobile platform starts according to the mobile strategy, the line laser and the monocular camera are synchronously activated, the line laser projects a laser line to the power transmission line in the target area, and the monocular camera captures the laser line projection, and the projection image is established through the image capture of the monocular camera. In this process, the camera parameters and position need to be adjusted, and the image needs to be preliminarily processed and analyzed to provide basic data for subsequent depth data calculation and three-dimensional reconstruction.

[0021] Step S400, obtain the baseline distance and device angle of the line laser and the monocular camera through the preset relative position, establish the two-dimensional coordinates of the pixel according to the projected image, and calculate the depth data through the baseline distance and the device angle. Specifically, in the three-dimensional power transmission channel reconstruction method combined with the line laser, first, because the line laser and the monocular camera are fixed on the mobile platform through the preset relative position, the baseline distance (horizontal distance) and the device angle (the angle between the laser and the camera optical axis) between the two can be obtained. Then, when the monocular camera captures the laser line projection, it establishes a projection image, and each pixel in the image can be represented by the two-dimensional coordinates. Indicates that is the horizontal axis, is the ordinate, and the pixel position is determined by the image coordinate system to obtain the two-dimensional coordinate. Finally, the depth data is calculated based on the baseline distance, the device angle, and the two-dimensional coordinates of the projected image pixel using triangulation. The specific formula is: ,in, is the depth data, is the baseline distance, is the device angle, is the horizontal coordinate of the pixel point, is the horizontal coordinate of the image principal point, It is the focal length of the monocular camera. During the calculation process, it is necessary to ensure the accuracy of parameters, consider the camera distortion error, and filter and optimize the depth data to provide key depth information for 3D reconstruction.

[0022] In a possible implementation, the baseline distance and device angle of the line laser and the monocular camera are obtained by presetting the relative position, the two-dimensional coordinates of the pixels are established according to the projected image, and the depth data is calculated by the baseline distance and the device angle. Step S400 further includes step S410, performing image analysis on the projected image to determine the image principal point. Specifically, first, an in-depth image analysis is performed on the projected image captured by the monocular camera. The projected image is formed by the laser line projected by the line laser on the transmission line in the target area and captured by the monocular camera. The purpose of the image analysis is to determine the image principal point. The image principal point is a special point in the image, usually located at the center of the image or at a position corresponding to the optical axis of the camera. In the calculation of depth data, the position of the image principal point is very important because it affects the calculation of the deflection angle introduced by the pixel coordinates of the laser line in the projected image. A variety of image analysis methods are used to determine the image principal point, such as feature point detection, edge detection, Hough transform, etc., to help identify key features and structures in the image, thereby determining the position of the image principal point.

[0023] Step S420, depth data is calculated using the formula as follows: ;in, Represents pixel depth data, is the baseline distance, is the device angle, Characterizes the deflection angle introduced by the pixel coordinates of the laser line in the projected image, is the horizontal coordinate of the pixel, is the horizontal coordinate of the principal point of the image, is the focal length of the monocular camera. Specifically, , the formula is used to calculate the depth data of the pixel ,in, is the baseline distance, i.e., the horizontal distance between the line laser and the monocular camera; is the device angle, i.e. the angle between the laser and the camera optical axis; Characterizes the deflection angle introduced by the pixel coordinates of the laser line in the projected image, is the horizontal coordinate of the pixel, is the horizontal coordinate of the principal point of the image, is the focal length of the monocular camera. The principle of the formula is based on triangulation, which uses the known baseline distance, device angle, and the position of the pixel in the projected image (given by the horizontal coordinate and the horizontal coordinates of the image principal point Determine) and the camera focal length , the distance from the object to the camera can be calculated, that is, the depth data , determine the values ​​of each parameter in the formula, baseline distance Angle with equipment It is determined during the system design phase and can be obtained through measurement or known parameters. The focal length of the camera The horizontal coordinates of the image principal point can be obtained from the camera specification or camera calibration. The horizontal coordinates of the pixels are determined during the image analysis phase. The deflection angle can be calculated by performing pixel analysis on the projected image. The angle is the horizontal coordinate of the pixel point. and the horizontal coordinate of the image principal point and the focal length of the camera It is determined by the degree of deflection of the pixel coordinates of the laser line in the projected image relative to the principal point of the image. The value of represents the sum of the device angle and the deflection angle. The value of the baseline distance Divide this value to get the depth data of the pixel By analyzing the projection image to determine the main point of the image, and then using a specific formula to calculate the depth data, the depth information of the pixel point can be obtained, providing key data support for the reconstruction of the three-dimensional transmission channel combined with the one-line laser.

[0024] Step S500, 3D reconstruction is performed using 2D coordinates and depth data, and similarity loss analysis of associated points is performed on the 3D reconstruction result, and the 3D reconstruction result is updated with the similarity loss analysis result. Specifically, the 2D coordinates and depth data of the projected image pixels that have been obtained are used to convert the 2D coordinates into 3D space coordinates through calculation, so as to construct a preliminary 3D model of the transmission line in the target area, determine the associated points in the 3D reconstruction result, calculate the similarity loss of each pair of associated points in different reconstruction results, understand the stability and reliability of the reconstruction result by analyzing the similarity loss, determine the update strategy according to the similarity loss analysis result, and adjust the 3D model if the similarity loss is large, such as fine-tuning the coordinates of certain points or recalculating the depth data, etc. After adjustment, 3D reconstruction and similarity loss analysis are performed again, and the process is repeated until the similarity loss reaches an acceptable range or a preset number of iterations, so as to continuously improve the accuracy and reliability of the 3D transmission channel reconstruction.

[0025] In a possible implementation, three-dimensional reconstruction is performed using two-dimensional coordinates and depth data, and similarity loss analysis of associated points is performed on the three-dimensional reconstruction result, and the three-dimensional reconstruction result is updated with the similarity loss analysis result. Step S500 further includes step S510, obtaining the acquisition time of the same reconstruction pixel point in the three-dimensional reconstruction result, and using the acquisition time to establish a time-series reconstruction result. Specifically, for the three-dimensional reconstruction result that has been obtained, it is necessary to obtain the acquisition time of the same reconstruction pixel point. In the process of reconstructing the three-dimensional power transmission channel, as the mobile platform moves and data is collected, the acquisition time of different pixels is different. By recording the acquisition time of each pixel point, a basis can be provided for subsequent time-series analysis. Using the acquisition time, a time-series reconstruction result can be established, that is, the three-dimensional reconstruction results are arranged in chronological order to form a reconstruction sequence that changes with time. The state changes of the three-dimensional power transmission channel at different time points can be observed, providing more comprehensive information for further analysis.

[0026] Step S520, perform a time similarity loss analysis on the time series reconstruction results, and establish a time similarity loss analysis result. Specifically, for the established time series reconstruction results, a time similarity loss analysis is performed, the purpose of which is to evaluate the similarity between the three-dimensional reconstruction results at different time points. If the reconstruction results of two time points are very similar, it means that the state of the transmission channel has not changed significantly during this period of time; if the similarity is low, it means that some changes may have occurred. The specific analysis method can be to calculate the differences between the corresponding pixel points in the reconstruction results at different time points. For example, the coordinate differences and color differences of the pixel points can be calculated. Based on these differences, a time similarity loss value can be determined, which reflects the similarity between the reconstruction results of the two time points, and the time similarity loss analysis result is established to provide a basis for subsequent updates.

[0027] Step S530, establish positional neighbor associations for the pixels, and the positional neighbor associations include direct neighbor associations and indirect neighbor associations. Specifically, positional neighbor associations are established for the pixels in the three-dimensional reconstruction result. Direct neighbor associations refer to associations between pixels that are directly physically adjacent. For example, in an image, the eight pixels around a pixel are its directly adjacent pixels. Indirect neighbor associations are determined by taking a predetermined range area. If a pixel is within this predetermined range area, it is considered that it has indirect neighbor associations with other pixels in the area. Indirect neighbor associations can consider the degree of sociability of pixels in a larger range, not just directly adjacent pixels.

[0028] Step S540, using the positional adjacent association to perform positional similarity loss analysis of the pixel points, and establish the positional similarity loss analysis result. Specifically, using the established positional adjacent association, perform positional similarity loss analysis of the pixel points, and for the pixel points with adjacent associations, calculate the similarity between them. If the difference between the adjacent pixel points is small, it means that they have a high similarity in position; if the difference is large, it means that the positional similarity is low. The specific analysis method can be to calculate the coordinate difference, color difference, etc. of the adjacent pixel points. According to the difference, a positional similarity loss value can be determined, which reflects the positional similarity between the adjacent pixel points, indicating that they have a high similarity in position; if the difference is large, it means that the positional similarity is low. The specific analysis method can be to calculate the coordinate difference, color difference, etc. of the adjacent pixel points. According to the difference, a positional similarity loss value can be determined, which reflects the positional similarity between the adjacent pixel points. The positional similarity loss analysis result is established to provide a basis for subsequent updates.

[0029] Step S550, taking the position similarity loss analysis result and the time similarity loss analysis result as the similarity loss analysis result to update the three-dimensional reconstruction result. Specifically, taking the position similarity loss analysis result and the time similarity loss analysis result as the similarity loss analysis result, the two results respectively reflect the similarity of the three-dimensional reconstruction result from the two aspects of position and time. The three-dimensional reconstruction result can be updated by using the similarity loss analysis result. If the similarity loss is large, it means that there may be errors or inaccuracies in the reconstruction result, and it needs to be adjusted and optimized. The pixel points in the three-dimensional reconstruction result can be adjusted according to the size and distribution of the similarity loss, such as adjusting the coordinates, color and other attributes to improve the accuracy and reliability of the reconstruction result. By obtaining the acquisition time to establish the time series reconstruction result, performing the time similarity loss analysis and the position similarity loss analysis, and using the results to update the three-dimensional reconstruction result, the quality and accuracy of the three-dimensional power transmission channel reconstruction can be continuously improved.

[0030] In one possible implementation, the position similarity loss analysis results and the time similarity loss analysis results are used as similarity loss analysis results to update the three-dimensional reconstruction results. Step S550 further includes step S551, performing independent threshold verification of the time deviation threshold on the time similarity loss analysis results to establish a first reconstruction impact result. Specifically, first, the obtained time similarity loss analysis results are further processed. The time similarity loss analysis results reflect the similarity between the three-dimensional reconstruction results at different time points. A time deviation threshold is introduced for independent threshold verification. The time deviation threshold is a standard value pre-set according to actual conditions, which is used to determine whether the time similarity loss is within an acceptable range. If the time similarity loss is less than or equal to the time deviation threshold, it means that the reconstruction results at different time points have small changes in time and are within a reasonable range; if the time similarity loss is greater than the time deviation threshold, it means that the changes in time are large and there may be abnormal conditions. By comparing the time similarity loss analysis results with the time deviation threshold, a first reconstruction impact result is established. If the time similarity loss is within the threshold range, the first reconstruction impact result can be considered to have little impact on the three-dimensional reconstruction result, and a relatively positive evaluation can be given; if the time similarity loss exceeds the threshold range, the first reconstruction impact result indicates that the time factor has a large impact on the reconstruction result, which requires further attention and processing.

[0031] Step S552, perform a joint anomaly verification on the time similarity loss analysis result and the position similarity loss analysis result, and establish a second reconstruction impact result. Specifically, then, the time similarity loss analysis result and the position similarity loss analysis result are combined for joint anomaly verification. The position similarity loss analysis result reflects the degree of similarity of the pixel points in spatial position. The purpose of the joint anomaly verification is to comprehensively consider the factors of both time and space, and more comprehensively evaluate the accuracy and reliability of the three-dimensional reconstruction results. If the time similarity loss and the position similarity loss are both small, it means that the changes in time and space are relatively small, and the reconstruction results are relatively stable; if one or both of the similarity losses are large, it means that there may be an abnormality. By jointly analyzing the time similarity loss and the position similarity loss, a second reconstruction impact result is established. This result combines the influence of time and space factors on the reconstruction results, and can more accurately reflect the quality of the reconstruction results and the direction that needs to be improved.

[0032] Step S553, updating the three-dimensional reconstruction result according to the first reconstruction influence result and the second reconstruction influence result. Specifically, the three-dimensional reconstruction result is updated according to the first reconstruction influence result and the second reconstruction influence result. If both the first reconstruction influence result and the second reconstruction influence result indicate that the reconstruction result is relatively stable and accurate, no substantial update is required, or some fine-tuning is performed to further improve the accuracy of the result. If the first reconstruction influence result or the second reconstruction influence result indicates that there is a major problem, the three-dimensional reconstruction result needs to be substantially adjusted and optimized. According to the specific problem situation, the coordinates, color and other attributes of the pixel points may be adjusted, or some steps of the data acquisition and reconstruction process may be re-performed to improve the quality of the reconstruction result. By performing independent threshold verification on the time similarity loss analysis results, performing joint anomaly verification on the time and position similarity loss analysis results, and updating the three-dimensional reconstruction results according to the verification results, the accuracy and reliability of the three-dimensional power transmission channel reconstruction can be continuously improved.

[0033] In a possible implementation, three-dimensional reconstruction is performed using two-dimensional coordinates and depth data, and similarity loss analysis of associated points is performed on the three-dimensional reconstruction result, and the three-dimensional reconstruction result is updated with the similarity loss analysis result. Step S500 further includes step S560, establishing a reconstruction time window according to the similarity loss analysis result. Specifically, first, the similarity loss analysis result is obtained by performing multi-faceted analysis on the three-dimensional reconstruction result, including time similarity loss analysis result and position similarity loss analysis result, etc. The result reflects the accuracy and stability of the three-dimensional reconstruction result, as well as the change in time and space. The reconstruction time window is established according to the similarity loss analysis result. If the similarity loss is small, it means that the reconstruction result is relatively stable. At this time, a relatively short time window can be selected for subsequent operations. If the similarity loss is large, it means that the reconstruction result may have a large error or uncertainty, and a longer time window needs to be selected to obtain more data for analysis and correction. The determination of the reconstruction time window can be adjusted according to specific application requirements and actual conditions. For example, the appropriate time window length can be determined according to factors such as the importance of the transmission channel, the cost and efficiency of data acquisition, etc.

[0034] Step S570: additional data acquisition is performed within the reconstruction time window, and the three-dimensional reconstruction result is iterated based on the additional data acquisition result. Specifically, after determining the reconstruction time window, additional data collection is performed within this time window. The purpose of additional data collection is to obtain more information to further improve the accuracy and reliability of the three-dimensional reconstruction results. Additional data collection can be performed in a variety of ways, such as increasing the number of collection times of the mobile platform, adjusting the parameters of the one-line laser and the monocular camera, changing the collection position and angle, etc. During the collection process, it is necessary to ensure that the collected data is consistent and comparable with the previous data in order to perform effective iterations. The three-dimensional reconstruction results are iterated with the additional data collection results, the newly collected data are integrated with the previous three-dimensional reconstruction results, and the three-dimensional reconstruction calculation and analysis are performed again. Through continuous iterations, the quality of the reconstruction results can be gradually improved to make it closer to the actual transmission channel situation. During the iteration process, some optimization algorithms and techniques, such as weighted averaging, least squares method, etc., can be used to improve the efficiency and accuracy of the iteration, evaluate and verify the results of the iteration, ensure that the reconstruction results after the iteration meet the expected requirements, establish a reconstruction time window based on the similarity loss analysis results, and perform additional data collection within the time window. The three-dimensional reconstruction results are iterated with the additional data collection results, which can continuously improve the quality and accuracy of the three-dimensional transmission channel reconstruction.

[0035] The embodiment of the present application collects environmental data of the target area (including obstacles and light characteristics), reads the transmission line design data to establish a layout, plans the scanning path of the mobile platform and configures the mobile strategy (the platform integrates a straight-line laser and a monocular camera and is fixed), and when the mobile platform moves, the laser and camera are synchronously activated to capture the laser line projection to establish an image, obtain the baseline distance and the device angle, establish two-dimensional coordinates according to the image and calculate the depth data, use the two-dimensional coordinates and depth data to perform three-dimensional reconstruction and analyze similar losses to update the reconstruction results, thereby achieving a technical effect of providing reliable support for the monitoring and maintenance of transmission lines through high-accuracy, high-reliability and high-precision reconstruction of the three-dimensional transmission channel.

[0036] In the above, refer to Figure 1 The three-dimensional transmission channel reconstruction method combined with a line laser according to an embodiment of the present invention is described in detail. Figure 2 A three-dimensional power transmission channel reconstruction device combined with a line laser according to an embodiment of the present invention is described.

[0037] The three-dimensional transmission channel reconstruction device combined with a straight line laser according to an embodiment of the present invention is used to solve the technical problem of insufficient reliability and accuracy of reconstruction results due to obstacles and light interference in the target area in the prior art, and achieves the technical effect of providing reliable support for the monitoring and maintenance of transmission lines by reconstructing the three-dimensional transmission channel with high accuracy, high reliability and high precision. The three-dimensional transmission channel reconstruction device combined with a straight line laser includes: a regional environment data set establishment module 10, a mobile strategy configuration module 20, a projection image establishment module 30, a depth data calculation module 40, and a three-dimensional reconstruction result update module 50.

[0038] The regional environment data set establishing module 10 is used to execute regional environment acquisition of a target area and establish a regional environment data set, wherein the regional environment data set includes obstacle feature data and light feature data.

[0039] The mobile strategy configuration module 20 is used to read the design data of the transmission line, use the design data to establish the line layout of the transmission line, plan the scanning path based on the line layout and the regional environment data set, and configure the mobile strategy of the mobile platform, wherein the mobile platform is integrated with a line laser and a monocular camera, and the line laser and the monocular camera are fixed on the mobile platform by preset relative positions.

[0040] The projection image establishment module 30 is used to synchronously activate the straight line laser and the monocular camera when the mobile platform starts to move based on the mobile strategy, and use the monocular camera to capture the laser line projection projected by the straight line laser on the power transmission line in the target area to establish a projection image.

[0041] The depth data calculation module 40 is used to obtain the baseline distance and device angle of the line laser and the monocular camera through a preset relative position, establish the two-dimensional coordinates of the pixel according to the projected image, and calculate the depth data through the baseline distance and the device angle.

[0042] The 3D reconstruction result updating module 50 is used to perform 3D reconstruction using 2D coordinates and depth data, and to perform similarity loss analysis of associated points on the 3D reconstruction result, and to update the 3D reconstruction result using the similarity loss analysis result.

[0043] Next, the specific configuration of the mobile policy configuration module 20 will be described in detail. As described above, the design data of the transmission line is read, the line layout of the transmission line is established using the design data, the scanning path is planned based on the line layout and the regional environment data set, and the mobile strategy of the mobile platform is configured, wherein the mobile platform is integrated with a line laser and a monocular camera, and the line laser and the monocular camera are fixed on the mobile platform by preset relative positions, and the mobile strategy configuration module 20 further includes: a passage angle adaptation value construction unit, the passage angle adaptation value construction unit is used to obtain the platform size of the mobile platform, perform spatial impact analysis according to the platform size and the obstacle feature data in the regional environment data set, and establish the passage angle adaptation value of each position point; a light adaptation analysis unit, the light adaptation analysis unit is used to call the light feature data, perform the light adaptation analysis of the layout angle of the mobile platform with the light feature data and the preset relative position, and establish the light angle adaptation value of each position point; a scanning path optimization unit, the scanning path optimization unit is used to optimize the scanning path of the mobile platform according to the passage angle adaptation value and the light angle adaptation value, and configure the mobile strategy according to the scanning path optimization result.

[0044] Among them, the scanning path optimization of the mobile platform is performed according to the passage angle adaptation value and the light angle adaptation value, and the mobile strategy is configured according to the scanning path optimization result. The scanning path optimization unit further includes: a comprehensive cost function construction subunit, and the comprehensive cost function construction subunit is used to establish a comprehensive cost function, and the scanning path optimization is performed with the comprehensive cost function, as follows: ;in, is the comprehensive cost function, is the total number of fitting position points of the scanning path, Representing any location point, For the The passing angle adaptation value of each position point, For the The light angle adaptation value of each position point, For the The location point and The cost of the action continuity at each position point.

[0045] The specific configuration of the depth data calculation module 40 will be described in detail below. As described above, the baseline distance and device angle of the line laser and the monocular camera are obtained by preset relative positions, the two-dimensional coordinates of the pixels are established according to the projected image, and the depth data is calculated by the baseline distance and the device angle. The depth data calculation module 40 further includes: an image principal point determination unit, which is used to perform image analysis on the projected image and determine the image principal point; a depth data calculation unit, which is used to calculate the depth data using the formula as follows: ;in, Represents pixel depth data, is the baseline distance, is the device angle, Characterizes the deflection angle introduced by the pixel coordinates of the laser line in the projected image, is the horizontal coordinate of the pixel, is the horizontal coordinate of the principal point of the image, is the focal length of the monocular camera.

[0046] The specific configuration of the three-dimensional reconstruction result updating module 50 will be described in detail below. As described above, three-dimensional reconstruction is performed using two-dimensional coordinates and depth data, and similarity loss analysis of associated points is performed on the three-dimensional reconstruction result, and the three-dimensional reconstruction result is updated with the similarity loss analysis result. The three-dimensional reconstruction result updating module 50 further includes: a time series reconstruction result construction unit, the time series reconstruction result construction unit is used to obtain the acquisition time of the same reconstruction pixel point in the three-dimensional reconstruction result, and use the acquisition time to establish the time series reconstruction result; a time similarity loss analysis result establishment unit, the time similarity loss analysis result establishment unit is used to perform time similarity loss analysis on the time series reconstruction result, and establish a time similarity loss analysis result; a position adjacent association unit, the position adjacent association unit is used to establish position adjacent associations for pixel points, and the position adjacent associations include direct adjacent associations and indirect adjacent associations; a position similarity loss analysis result establishment unit, the position similarity loss analysis result establishment unit is used to perform position similarity loss analysis of pixel points using position adjacent associations, and establish a position similarity loss analysis result; a three-dimensional reconstruction result updating unit, the three-dimensional reconstruction result updating unit is used to use the position similarity loss analysis result and the time similarity loss analysis result as similarity loss analysis results to update the three-dimensional reconstruction result.

[0047] Among them, the position similarity loss analysis result and the time similarity loss analysis result are used as similarity loss analysis results to update the three-dimensional reconstruction result, and the three-dimensional reconstruction result updating unit further includes: a first reconstruction influence result construction subunit, the first reconstruction influence result construction subunit is used to perform independent threshold verification of the time deviation threshold on the time similarity loss analysis result, and establish a first reconstruction influence result; a joint anomaly verification subunit, the joint anomaly verification subunit is used to perform joint anomaly verification on the time similarity loss analysis result and the position similarity loss analysis result, and establish a second reconstruction influence result; an influence result updating subunit, the influence result updating subunit is used to update the three-dimensional reconstruction result according to the first reconstruction influence result and the second reconstruction influence result.

[0048] Among them, the three-dimensional reconstruction result update module 50 can further include: a reconstruction time window construction unit, which is used to establish a reconstruction time window according to the similarity loss analysis results; an additional data acquisition unit, which is used to perform additional data acquisition under the reconstruction time window, and iterate the three-dimensional reconstruction result with the additional data acquisition result.

[0049] The three-dimensional power transmission channel reconstruction device combined with a line laser provided in an embodiment of the present invention can execute the three-dimensional power transmission channel reconstruction method combined with a line laser provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0050] Although the present application makes various references to certain modules in the device according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0051] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A three-dimensional power transmission channel reconstruction method combined with a line laser, characterized in that: The method comprises: Execute regional environment collection of the target area and establish a regional environment data set, wherein the regional environment data set includes obstacle feature data and light feature data; Reading the design data of the transmission line, establishing the line layout of the transmission line using the design data, planning the scanning path based on the line layout and the regional environment data set, and configuring the mobile strategy of the mobile platform, wherein the mobile platform is integrated with a line laser and a monocular camera, and the line laser and the monocular camera are fixed on the mobile platform by preset relative positions; When the mobile platform starts to move based on the mobile strategy, the straight line laser and the monocular camera are synchronously activated, and the monocular camera is used to capture the laser line projection projected by the straight line laser on the power transmission line in the target area to establish a projection image; Obtain the baseline distance and device angle of the line laser and the monocular camera by presetting the relative position, establish the two-dimensional coordinates of the pixel according to the projected image, and calculate the depth data by the baseline distance and the device angle; The three-dimensional reconstruction is performed using the two-dimensional coordinates and depth data, and the three-dimensional reconstruction result is subjected to similarity loss analysis of associated points, and the three-dimensional reconstruction result is updated with the similarity loss analysis result.

2. The three-dimensional power transmission channel reconstruction method combined with a line laser as claimed in claim 1, characterized in that: The depth data is calculated by using the baseline distance and the device angle, and further includes: Performing image analysis on the projection image to determine the image principal point; The depth data is calculated using the formula as follows: ； in, Represents pixel depth data, is the baseline distance, is the device angle, Characterizes the deflection angle introduced by the pixel coordinates of the laser line in the projected image, is the horizontal coordinate of the pixel, is the horizontal coordinate of the principal point of the image, is the focal length of the monocular camera.

3. The three-dimensional power transmission channel reconstruction method combined with a line laser as claimed in claim 1, characterized in that: The performing similarity loss analysis on the associated points of the three-dimensional reconstruction result and updating the three-dimensional reconstruction result with the similarity loss analysis result also includes: Obtaining the acquisition time of the same reconstruction pixel point in the three-dimensional reconstruction result, and using the acquisition time to establish a time-series reconstruction result; Performing a time similarity loss analysis on the timing reconstruction result to establish a time similarity loss analysis result; Establishing positional neighbor associations for pixel points, wherein the positional neighbor associations include direct neighbor associations and indirect neighbor associations; Use positional proximity association to perform positional similarity loss analysis on pixels and establish positional similarity loss analysis results; The position similarity loss analysis results and the time similarity loss analysis results are used as similarity loss analysis results to update the three-dimensional reconstruction results.

4. The three-dimensional power transmission channel reconstruction method combined with a line laser as claimed in claim 3, characterized in that: The method of using the position similarity loss analysis result and the time similarity loss analysis result as the similarity loss analysis result to update the three-dimensional reconstruction result further includes: Performing independent threshold verification of a time deviation threshold on the time similarity loss analysis result to establish a first reconstruction impact result; Performing joint anomaly verification on the time-similar loss analysis result and the location-similar loss analysis result to establish a second reconstruction impact result; The three-dimensional reconstruction result is updated according to the first reconstruction influence result and the second reconstruction influence result.

5. The three-dimensional power transmission channel reconstruction method combined with a line laser as claimed in claim 1, characterized in that: The scanning path planning based on the line layout and the regional environment data set and configuring the mobile strategy of the mobile platform also includes: Obtaining the platform size of the mobile platform, performing a spatial impact analysis based on the platform size and obstacle feature data in the regional environment data set, and establishing a passage angle adaptation value for each location point; Calling light characteristic data, performing light adaptation analysis of the layout angle of the mobile platform based on the light characteristic data and the preset relative position, and establishing a light angle adaptation value for each position point; The scanning path of the mobile platform is optimized according to the passage angle adaptation value and the light angle adaptation value, and the mobile strategy is configured according to the scanning path optimization result.

6. The three-dimensional power transmission channel reconstruction method combined with a line laser as claimed in claim 5, characterized in that: The step of optimizing the scanning path of the mobile platform according to the passage angle adaptation value and the light angle adaptation value further includes: A comprehensive cost function is established to optimize the scanning path as follows: ； in, is the comprehensive cost function, is the total number of fitting position points of the scanning path, Representing any location point, For the The passing angle adaptation value of each position point, For the The light angle adaptation value of each position point, For the The location point and The cost of the action continuity of the position point.

7. The three-dimensional power transmission channel reconstruction method combined with a line laser as claimed in claim 1, characterized in that: The method further comprises Establish a reconstruction time window based on similar loss analysis results; Additional data acquisition is performed within the reconstruction time window, and the three-dimensional reconstruction result is iterated based on the additional data acquisition result.

8. A three-dimensional power transmission channel reconstruction device combined with a line laser, characterized in that: The device is used to implement the three-dimensional power transmission channel reconstruction method combined with a line laser according to any one of claims 1 to 7, and the device comprises: A regional environment data set establishment module, the regional environment data set establishment module is used to perform regional environment acquisition of the target area and establish a regional environment data set, the regional environment data set includes obstacle feature data and light feature data; A mobile strategy configuration module, the mobile strategy configuration module is used to read the design data of the transmission line, use the design data to establish the line layout of the transmission line, perform scanning path planning based on the line layout and the regional environment data set, and configure the mobile strategy of the mobile platform, wherein the mobile platform is integrated with a line laser and a monocular camera, and the line laser and the monocular camera are fixed on the mobile platform by preset relative positions; A projection image establishment module, wherein the projection image establishment module is used to synchronously activate the straight line laser and the monocular camera when the mobile platform starts to move based on the mobile strategy, and use the monocular camera to capture the laser line projection projected by the straight line laser on the power transmission line in the target area to establish a projection image; A depth data calculation module, the depth data calculation module is used to obtain the baseline distance and device angle of the line laser and the monocular camera through a preset relative position, establish the two-dimensional coordinates of the pixel according to the projected image, and calculate the depth data through the baseline distance and the device angle; The three-dimensional reconstruction result updating module is used to perform three-dimensional reconstruction using two-dimensional coordinates and depth data, and to perform similarity loss analysis of associated points on the three-dimensional reconstruction result, and to update the three-dimensional reconstruction result with the similarity loss analysis result.

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