An overhead distribution line construction management and control method based on space-time sequence features

Abstract

The application provides an overhead distribution line construction management and control method based on space-time sequence characteristics, and realizes distribution line construction process and quality management. The method comprises the following steps: collecting an image of an overhead distribution line construction area at a certain moment and recording relevant information when the image is taken; using an identification algorithm model to identify target equipment in the image, marking the target equipment by a bounding box and recording the pixel coordinates of the target equipment; determining the spatial coordinates of the target equipment based on the pixel coordinates of the target equipment and the relevant information when the image is taken; based on the preset maximum allowed link distance of the tower and the spatial coordinates of the target equipment, using the nearest neighbor algorithm to generate the tower topology, and correlating the target equipment other than the tower to the adjacent tower to generate the overall topology; then obtaining the overall topology at other moments; and determining the construction process and construction quality of the distribution line by comparing and analyzing the overall topology at different moments and the target equipment on the overall topology at the same moment.

Description

Technical Field

[0001] This application relates to the field of overhead power line construction process control, specifically to an overhead power line construction control method, system, device, and storage medium based on spatiotemporal sequence characteristics. Background Technology

[0002] With the rapid growth of my country's national economy, the scale of power grid construction has continued to expand, and the construction of overhead distribution lines has become an important part of power system construction.

[0003] However, current progress control at construction sites relies primarily on manual reporting, leading to insufficient understanding of the overall line status. This lack of process control can result in construction quality issues, such as missed inspections or improper installation of key components. Failure to rigorously verify the consistency of insulator installation quantities with design drawings can lead to missing insulators on some towers. Furthermore, when tower erection and conductor stringing are handled by different teams, the boundaries of responsibility for insulator installation become blurred, creating "no-man's-land" areas. Deviations between actual line construction and planned routes are also frequent. Moreover, the lack of process control causes delays in construction progress, preventing timely completion, especially in regions like Northeast China where suitable construction periods are affected by severe weather such as rain, snow, and ice, further increasing the difficulty of distribution network construction. Every year, the overall completion rate is often below average, necessitating accelerated construction within the suitable construction period to ensure on-time completion.

[0004] Therefore, improving construction quality and schedule management efficiency, and reducing labor costs are pressing issues that need to be addressed. Summary of the Invention

[0005] This application provides a construction control method for overhead power distribution lines based on spatiotemporal sequence characteristics, enabling accurate assessment and efficient management of the construction quality and progress of overhead power distribution lines.

[0006] To achieve the above objectives, this application adopts the following technical solution:

[0007] Firstly, this application provides a method for construction management and control of overhead power distribution lines based on spatiotemporal sequence characteristics, the method comprising:

[0008] S101. The drone collects images of the overhead power distribution line construction area at a certain moment and records the drone's flight altitude, drone's shooting position, and pixel coordinates of the image center point at the time the image is captured. The number of images must be at least one.

[0009] S102. Use the recognition algorithm model to identify the target device in the image, select and mark the target device by using an identification box, and record the pixel coordinates of the target device. The target device includes towers, insulators, and conductors. The pixel coordinates of the target device are the pixel coordinates of the center point of the identification box.

[0010] S103. Determine the spatial coordinates of the target device based on the pixel coordinates of the target device, the flight altitude of the drone, the shooting position of the drone, and the pixel coordinates of the center point of the image.

[0011] S104. Based on the preset maximum allowable link distance of the poles and the spatial coordinates of the target equipment, the nearest neighbor algorithm is used to generate the pole topology, and the neighboring poles are associated with other target equipment besides the poles to generate the overall topology.

[0012] S105. Repeat steps S101-S104 until the overall topology of the overhead power distribution line construction area at other times is obtained.

[0013] S106. By comparing and analyzing the overall topology at different times and the target equipment on the overall topology at the same time, the construction progress and construction quality of the overhead power distribution line are determined.

[0014] One possible design approach, the first aspect of which also includes using the YOLO V5 framework for the recognition algorithm model, combined with the CBAM attention mechanism and the Mosaic-9 data augmentation strategy.

[0015] One possible design approach, the first aspect of which further includes determining the spatial coordinates of the target device based on the pixel coordinates of the target device, the drone's flight altitude, the drone's shooting position, and the pixel coordinates of the image center point, including:

[0016] The pixel resolution is obtained based on the pixel size of the fixed camera on the drone, the camera's imaging focal length, and the drone's flight altitude. The pixel size and camera's imaging focal length are obtained through the camera's hardware specifications.

[0017] The pixel offset of the target device is obtained based on the pixel coordinates of the target device and the pixel coordinates of the image center point;

[0018] Based on the pixel offset and pixel resolution of the target device, the spatial distance between the target device and the center point of the image is obtained;

[0019] Based on the spatial distance and the spatial coordinates of the image center point, the spatial coordinates of the target device are obtained, where the spatial coordinates of the image center point represent the drone's shooting position.

[0020] One possible design scheme, the first aspect of the method, further includes, after step S103 and before step S104, the following:

[0021] Based on the spatial coordinates of the target equipment, spatial coordinate sets of different types of target equipment are constructed respectively. Among them, the spatial coordinate sets of different types of target equipment include the spatial coordinate sets of towers, insulators, and conductors.

[0022] For different types of target devices, the parameters of the DBSCAN clustering algorithm are preset respectively. The parameters of the DBSCAN clustering algorithm include neighborhood radius and minimum number of points.

[0023] Based on the preset parameters of the DBSCAN clustering algorithm, the DBSCAN clustering algorithm is applied to the spatial coordinate sets of different types of target devices to obtain the deduplicated spatial coordinates of the target devices.

[0024] One possible design scheme, the first aspect of the method, further includes, based on a preset maximum allowable link distance between towers and the spatial coordinates of the target device, using a nearest neighbor algorithm to generate a tower topology, and associating other target devices besides the towers with nearby towers to generate an overall topology, including:

[0025] Based on the spatial coordinates of the target equipment, construct a set of spatial coordinates for the tower.

[0026] Select any tower as the initial tower, use the nearest neighbor algorithm to calculate the Euclidean distance between the spatial coordinates of the initial tower and other towers, and select the tower with the smallest Euclidean distance as the second tower. The Euclidean distance between the second tower and the initial tower satisfies the preset maximum allowable connection distance between towers.

[0027] For other towers, the nearest neighbor algorithm is continued until all towers are connected, generating a tower topology;

[0028] It also associates nearby poles with other target devices besides poles and towers to generate the overall topology.

[0029] One possible design scheme, the first aspect of the method, further includes, after step S104 and before step S105, the following:

[0030] The overall topology is manually reviewed. If the error between the distance between the poles and towers in the overall topology and the distance between the poles and towers in the overhead power distribution line construction design scheme is greater than the preset value, an early warning is triggered.

[0031] One possible design approach, the first aspect of which also includes determining the construction progress and quality of overhead power distribution lines by comparing and analyzing the overall topology at different times and the target equipment on the overall topology at the same time, including:

[0032] Analyze the overall topology at different times. If the spatial coordinate distance between towers at different times is less than 5m, they are determined to be the same tower.

[0033] When an isolated point exists on a pole, if the isolated point appears in the overall topology at a later time, it is considered a newly added pole. If the isolated point appears in the overall topology at an earlier time, manual intervention is required to determine whether it is a pole that has been demolished.

[0034] Secondly, this application provides a construction control system for overhead power distribution lines based on spatiotemporal sequence characteristics. The system includes: a drone, a ground remote control terminal, and a computer terminal, wherein...

[0035] The drone collects images of the overhead power line construction area at a certain moment and records the drone's flight altitude, shooting position, and pixel coordinates of the image center point at the time of image capture. The number of images must be at least one.

[0036] The ground remote control terminal is used to transmit the images collected and recorded by the UAV, the corresponding UAV flight altitude, UAV shooting position, and pixel coordinates of the image center point to the computer terminal.

[0037] A computer terminal includes an identification module, a processing module, and an analysis module, among which...

[0038] The recognition module is used to identify target devices in an image using a recognition algorithm model. It selects and marks target devices by using a bounding box and records the pixel coordinates of the target devices. The target devices include towers, insulators, and conductors. The pixel coordinates of the target devices are the pixel coordinates of the center point of the bounding box.

[0039] The processing module is used to determine the spatial coordinates of the target device based on the pixel coordinates of the target device, the flight altitude of the drone, the shooting position of the drone, and the pixel coordinates of the image center point; it is also used to generate the tower topology based on the preset maximum allowable connection distance of the towers and the spatial coordinates of the target device using the nearest neighbor algorithm, and to associate other target devices besides the towers with nearby towers to generate the overall topology; it is also used to obtain the overall topology of the overhead power distribution line construction area at other times;

[0040] The analysis module is used to determine the construction progress and quality of overhead power distribution lines by analyzing the overall topology at different times and the target equipment on the overall topology at the same time.

[0041] Thirdly, a construction control device for overhead power distribution lines based on spatiotemporal sequence characteristics is provided, which includes a module for performing the method described in the first aspect.

[0042] In one possible design, the overhead power distribution line construction control device based on spatiotemporal sequence characteristics in the third aspect may further include a transceiver. This transceiver can be a transceiver circuit or an interface circuit. The transceiver can be used for communication between the overhead power distribution line construction control device based on spatiotemporal sequence characteristics in the third aspect and other devices.

[0043] In one possible design, the overhead power line construction control device based on spatiotemporal sequence characteristics in the third aspect may further include a memory. This memory may be integrated with the processor or disposed separately. The memory may be used to store the instructions involved in the method of the first aspect.

[0044] Fourthly, a construction control device for overhead power distribution lines based on spatiotemporal sequence characteristics is provided. This device includes a processor coupled to a memory, the processor executing instructions stored in the memory to cause the device to perform the method of the first aspect.

[0045] In one possible design, the overhead power distribution line construction control device based on spatiotemporal sequence characteristics in the fourth aspect may further include a transceiver. This transceiver can be a transceiver circuit or an interface circuit. The transceiver can be used for communication between the overhead power distribution line construction control device based on spatiotemporal sequence characteristics in the fourth aspect and other devices.

[0046] Fifthly, a construction control device for overhead power distribution lines based on spatiotemporal sequence characteristics is provided, comprising: a processor and a memory; the memory is used to store instructions, and when the processor executes the instructions, the construction control device for overhead power distribution lines based on spatiotemporal sequence characteristics performs the method of the first aspect.

[0047] In one possible design, the overhead power distribution line construction control device based on spatiotemporal sequence characteristics in the fifth aspect may further include a transceiver. This transceiver can be a transceiver circuit or an interface circuit. The transceiver can be used for communication between the overhead power distribution line construction control device based on spatiotemporal sequence characteristics in the fifth aspect and other devices.

[0048] In a sixth aspect, a computer-readable storage medium is provided, the computer-readable storage medium including storage of a computer program or instructions, which, when executed, cause the overhead power line construction control method based on spatiotemporal sequence characteristics of the first aspect to be performed.

[0049] In this embodiment, by integrating high-precision UAV positioning data with UAV imaging principles and combining it with target detection algorithms, key components such as poles, crossarms, and insulators at the construction site are accurately identified. Through spatial calculation technology of target detection bounding boxes, the identification results in the image coordinate system are mapped to real three-dimensional space, establishing a precise association between pole components and poles / geographic information. Simultaneously, based on the pole coordinate calculation capability derived from image processing, real-time monitoring of line topology offsets is achieved, providing an automated method for verifying overhead power distribution line data and reducing errors and time costs associated with manual surveying. Finally, by matching the construction node status based on spatiotemporal feature sequences, control over construction progress and quality is realized.

[0050] Other features and advantages of this application will be described in detail in the following detailed description section. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 A flowchart illustrating the construction control method for overhead power distribution lines based on spatiotemporal sequence features provided in this application embodiment;

[0053] Figure 2 A schematic diagram illustrating the identification results of poles and their ancillary facilities provided in an embodiment of this application;

[0054] Figure 3 A reference diagram illustrating the principle of UAV imaging coordinate analysis provided in this application embodiment;

[0055] Figure 4 Reference diagram for imaging correction of UAV and gimbal provided in the embodiments of this application;

[0056] Figure 5 Example diagrams of different stages of pole and line construction provided in the embodiments of this application;

[0057] Figure 6 The multi-phase topology diagram of the line within the specific construction period provided in this application embodiment;

[0058] Figure 7 Images acquired at typical moments with distinct time characteristics within a specific construction period provided in this application embodiment;

[0059] Figure 8 A schematic diagram of the system configuration of the overhead power distribution line construction control system based on spatiotemporal sequence characteristics provided in this application embodiment;

[0060] Figure 9 A schematic diagram of the structure of the overhead power distribution line construction control device based on spatiotemporal sequence characteristics provided in this application embodiment. Figure 1 ;

[0061] Figure 10 A schematic diagram of the structure of the overhead power distribution line construction control device based on spatiotemporal sequence characteristics provided in this application embodiment. Figure 2 . Detailed Implementation

[0062] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. At the same time, in the description of the embodiments of this application, the terms "first," "second," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0063] Figure 1 This is a flowchart illustrating the construction control method for overhead power distribution lines based on spatiotemporal sequence characteristics provided in this application embodiment.

[0064] The process of the overhead power distribution line construction control method based on spatiotemporal sequence characteristics is as follows:

[0065] Step S101: The drone collects an image of the overhead power line construction area at a certain moment and records the drone's flight altitude, shooting position, and pixel coordinates of the image center point at the time the image was captured. The number of images is at least one.

[0066] The drone is equipped with a three-axis stabilized gimbal with a gimbal angle jitter better than ±0.01° and a high-precision positioning module (horizontal positioning accuracy ±10mm). It supports precise control with a hovering height error of less than 0.5m. The drone's latitude and longitude are based on the WGS84 coordinate system, and its altitude is based on the EGM96 elevation datum. The camera on the drone is stabilized by the gimbal and should have a resolution of at least 20 megapixels, a 1 / 1.7" CMOS sensor, an optical zoom range of 31.7-556.2mm (equivalent to 35mm focal length), digital zoom support of 10x extension, an aperture range of f / 2.8-f / 11, and an adjustable shutter speed from 1 / 8000s to 30s.

[0067] This application uses a drone to take aerial and hovering photos of the construction site. During the shooting process, the drone hovers horizontally, and the imaging height does not exceed 50m to ensure clear imaging.

[0068] In addition, for each captured image, the drone's flight altitude, shooting position, and pixel coordinates of the image's center point are recorded. The pixel coordinates of the image's center point can be understood as follows: assuming the image width is W and the height is H, the pixel coordinates of the image's center point are... .

[0069] It should also be noted that it can record the drone's attitude information and gimbal angle. Meanwhile, EXIF ​​records relevant parameters such as optical zoom, digital zoom, and imaging height for further data processing, which is not restricted here.

[0070] Step S102: The target device in the image is identified using the recognition algorithm model. The target device is selected and marked by the identification box, and the pixel coordinates of the target device are recorded. The target device includes towers, insulators, and conductors. The pixel coordinates of the target device are the pixel coordinates of the center point of the identification box.

[0071] It should be noted that the center point of the marker frame is the middle position of the frame. The center point pixel coordinates can be obtained by calculating the average of the pixel coordinates of the top left corner and the bottom right corner of the marker frame, and then the pixel coordinates of the target device can be obtained.

[0072] Since the construction progress survey focuses on the installation status of each pole and its ancillary facilities, and because drones fly at high altitudes and cannot identify detailed information, the monitoring of project progress does not require detailed confirmation of project quality acceptance, nor does it need to focus on equipment defects and construction techniques. Therefore, the identification algorithm only needs to identify key components, such as poles, conductors, insulators, transformers, crossarms, and other equipment and materials. Simultaneously, it needs to identify ground conditions, such as excavated but unbackfilled pits, as detailed below:

[0073] The recognition algorithm model adopts the YOLO V5 framework and combines the CBAM attention mechanism and Mosaic-9 data augmentation strategy to identify target devices in images. The target devices are selected and marked by bounding boxes, and the pixel coordinates of the target devices are recorded.

[0074] Optionally, for towers, features at the tower connection points can be extracted based on the fusion edge detection operator and gradient direction histogram to effectively distinguish the spatial positions of adjacent towers.

[0075] Optionally, for insulators, the results of Hough Circles detection algorithm and deep learning can be cross-validated, and cluster analysis of the center coordinates of the circles can be used to eliminate false detections caused by gimbal jitter.

[0076] Optionally, for conductors, the sag characteristics of the conductors can also be established based on Hough transform line detection and UAV flight altitude.

[0077] The target equipment may also include transformers, crossarms, excavated pits, etc., depending on the actual situation, and no restrictions are imposed here.

[0078] For example, such as Figure 2 As shown, different types of feature enhancement strategies are used to achieve the identification results of towers and their ancillary facilities (such as crossarms, insulators, conductors, and excavated but unbackfilled structures).

[0079] Step S103: Determine the spatial coordinates of the target device based on the pixel coordinates of the target device, the flight altitude of the drone, the shooting position of the drone, and the pixel coordinates of the center point of the image.

[0080] Step S103 specifically includes the following content, which can be combined with... Figure 3 Figure (a) and Figure 3 Understanding diagram (b) in the text.

[0081] Step 1: Based on the pixel size of the fixed camera on the drone Camera imaging focal length and drone flight altitude Through formula This yields the pixel resolution (also known as the spatial size per pixel). .

[0082] The camera's pixel size and focal length are determined by the camera's hardware specifications. If the camera has interchangeable lenses, the focal length will vary depending on the type of lens used. The camera's pixel size refers to the physical width and height of a single pixel on the sensor, typically measured in micrometers (µm). The smaller the pixel size, the higher the image resolution, the wider the field of view, and the smaller the target that can be detected.

[0083] Step 2: Based on the pixel coordinates of the target device and the pixel coordinates of the image center point Obtain the pixel offset of the target device. .

[0084] in, This is the horizontal pixel offset. This is the vertical pixel offset.

[0085] Step 3, based on the pixel offset of the target device and pixel resolution The spatial distance between the target device and the center point of the image is obtained. .

[0086] Step 4, based on spatial distance Spatial coordinates of the image center point Obtain the spatial coordinates of the target device. The spatial coordinates of the image center point represent the location where the drone took the picture.

[0087] It should be noted that the above content is based on the drone shooting from a vertical (90-degree) angle, with the camera lens pointing directly downwards, which is usually referred to as downward-looking shooting or vertical shooting. If the drone is not shooting from a vertical (90-degree) angle, image correction is required based on the recorded drone attitude information and gimbal angle, which is briefly introduced below.

[0088] The drone's coordinate system moves with the drone's movement, such as... Figure 4 As shown, the center of mass of the UAV is the origin. ahead of time The axis, facing right is The axis, vertically downwards is The axis satisfies the right-hand rule; if the target is in front of the drone, then... On the east side of the drone Below the drone ;

[0089] like Figure 4 As shown, in the gimbal coordinate system, the centroid of the gimbal is the origin. The camera's optical axis faces forward. The axis, to the right of the camera is Axis, below the camera axis;

[0090] Based on the UAV attitude angles φ and ψ, the transformation matrix from the UAV coordinate system to the geodetic coordinate system can be obtained.

[0091] Similarly, based on the gimbal's attitude angle, the transition matrix from the gimbal coordinate system to the UAV coordinate system can be obtained. The transition matrix from the camera coordinate system to the ground coordinate system is: .

[0092] Optionally, after step S103 and before step S104, the method further includes:

[0093] Based on the spatial coordinates of the target equipment, spatial coordinate sets of different types of target equipment are constructed respectively. Among them, the spatial coordinate sets of different types of target equipment include the spatial coordinate sets of towers, insulators, and conductors.

[0094] For different types of target devices, the parameters of the DBSCAN clustering algorithm are preset respectively. The parameters of the DBSCAN clustering algorithm include neighborhood radius and minimum number of points.

[0095] Based on the preset parameters of the DBSCAN clustering algorithm, the DBSCAN clustering algorithm is applied to the spatial coordinate sets of different types of target devices to obtain the deduplicated spatial coordinates of the target devices.

[0096] It is understandable that the same tower may appear in multiple images, leading to duplicate spatial coordinates of the tower and its associated facilities and equipment (such as crossarms, insulators, conductors, and excavated pits). Therefore, it is necessary to remove these duplicate coordinate data using a clustering algorithm, specifically the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm.

[0097] For example, for poles, the parameters of the DBSCAN clustering algorithm are set as follows: neighborhood radius (ε) is 5 meters, and minimum number of points (MinPts) is set. This means that if the spatial coordinates of two poles are less than 5 meters apart, they are considered to be the same pole. Since some poles may only appear in a single image and do not overlap with poles in other images, they cannot be directly clustered. Therefore, MinPts is set to 1. In other words, each spatial coordinate point will be clustered at least as a separate cluster.

[0098] The specific clustering steps are as follows:

[0099] (1) Start from any unvisited tower spatial coordinate point.

[0100] (2) Using the current spatial coordinate point as the center, search for all other spatial coordinate points in its neighborhood. The neighborhood range is determined by the set radius of 5 meters.

[0101] (3) If other tower spatial coordinate points are found within the neighborhood radius, add these points to the same cluster and continue searching their neighborhoods from these newly added points.

[0102] (4) The search process continues to expand until no more points satisfying the neighborhood conditions can be found.

[0103] (5) After a cluster search is completed, calculate the average coordinates of all points in the cluster and assume that they represent the same tower.

[0104] (6) Then, continue to find the next unvisited point and repeat the above process until all points have been visited.

[0105] (7) Finally, the points in the cluster represent the same tower.

[0106] For example, suppose we have two images, from which we have extracted the coordinates of several poles and their ancillary facilities. The pole coordinates in Image 1 are (10, 15) and (50, 60), and the pole coordinates in Image 2 are (10.1, 15.1) and (51, 61). Given a neighborhood radius of 5 meters, the distance between (10, 15) and (10.1, 15.1) is less than 5 meters, therefore they are considered to be the same pole. Similarly, (50, 60) and (51, 61) are also considered to be the same pole. Finally, we obtain the clustering results for the two poles: the first pole has coordinates of (10.05, 15.05) (average coordinates), and the second pole has coordinates of (50.5, 60.5) (average coordinates).

[0107] Similar to poles and towers, crossarms, insulators, conductors, and excavated pits will also appear repeatedly in the image. The same deduplication method used for poles and towers is employed to cluster the identifier boxes of these devices for deduplication, which will not be elaborated upon here.

[0108] Step S104: Based on the preset maximum allowable link distance of the poles and the spatial coordinates of the target device, the nearest neighbor algorithm is used to generate the pole topology, and the neighboring poles are associated with other target devices besides the poles to generate the overall topology.

[0109] The specific steps are as follows:

[0110] (1) Based on the spatial coordinates of the target equipment, construct a set of spatial coordinates of the tower.

[0111] (2) Select any tower as the initial tower, use the nearest neighbor algorithm to calculate the Euclidean distance between the initial tower and other towers, and select the tower with the smallest Euclidean distance as the second tower. The Euclidean distance between the second tower and the initial tower satisfies the preset maximum allowable connection distance between towers.

[0112] During the connection process, when two towers have similar Euclidean distances, the point with the smaller angular deviation from the current line segment (<30°) should be selected first to avoid abrupt changes in the path.

[0113] (3) For the second tower, the nearest neighbor algorithm is used repeatedly to calculate the Euclidean distance between the spatial coordinates of the second tower and other towers respectively. The tower with the smallest Euclidean distance is selected as the third tower. The Euclidean distance between the third tower and the second tower satisfies the preset maximum allowable connection distance between towers.

[0114] (4) For other towers, continue to use the nearest neighbor algorithm until all towers are connected to generate the tower topology.

[0115] (5) For other target devices besides poles and towers, perform neighboring pole and tower association to generate the overall topology.

[0116] After the topology of the towers is generated, if there are auxiliary components such as crossarms, insulators, and conductors in the identification frame, the adjacent towers are associated. In particular, for the association between the conductor identification frame and the tower, when the midpoint of the conductor identification frame is located at the midpoint of the line connecting the two towers, the conductor is associated with both towers respectively.

[0117] It should also be noted that setting a maximum link distance can effectively prevent the generation of excessively long, discontinuous, or unreasonable line connections in practical applications. It also helps improve the accuracy and reliability of the topology and avoids incorrect connections caused by calculation errors or data anomalies. For example, if two towers are incorrectly calculated to be hundreds of meters apart due to certain factors (such as sensor errors or data inconsistencies), the maximum allowable link distance will prevent such incorrect connections and ensure that the generated topology is more consistent with reality.

[0118] Optionally, after step S104 and before step S105, the method further includes:

[0119] The overall topology is manually reviewed. If the error between the distance between the poles and towers in the overall topology and the distance between the poles and towers in the overhead power distribution line construction design scheme is greater than the preset value, an early warning is triggered.

[0120] In other words, during the manual review of the entire tower topology, the actual generated tower distances (i.e., the actual distances between adjacent towers in the entire topology) are compared with the tower distances predetermined in the original design. If these distance differences exceed a preset threshold (error limit), the system will trigger an alert to prevent construction route deviations or other problems.

[0121] Step S105: Repeat steps S101-S104 until the overall topology of the overhead power distribution line construction area at other times is obtained.

[0122] Data collection and analysis are conducted based on different project timelines.

[0123] Step S106: By analyzing the overall topology at different times and the target equipment on the overall topology at the same time, the construction progress and construction quality of the overhead power distribution line are determined.

[0124] The overall topology at different times is analyzed. If the spatial coordinate distance between towers at different times is less than 5m, they are determined to be the same tower. If there are isolated points on the tower, if the isolated point appears in the overall topology at a later time, it is identified as a newly added tower. If the isolated point appears in the overall topology at an earlier time, manual intervention is required to determine whether it is a tower that has been demolished.

[0125] It is understandable that after conducting multi-phase project progress surveys, the obtained multi-phase topology data (topology data at multiple different times) are spatially and temporally compared, matched, and analyzed to evaluate the construction progress. At the same time, for target equipment on the overall topology at the same time, such as comparing the characteristics of all towers in the same area at the same time, it is determined whether all towers in the area have completed the characteristics of the current stage, and whether there are any missing equipment, thereby judging the construction quality.

[0126] For example, taking pole and line construction as an example, based on the features of the identification boxes in the collected images, the current status of the pole and line construction can be determined, such as... Figure 5 As shown.

[0127] Characteristics of the pre-construction stage: The collected images do not contain any identification frames for towers, crossarms, insulators, conductors, and pit foundations;

[0128] Characteristics of the pole erection stage: The acquired images show identification frames for poles and pit foundations, but no identification frames for crossarms, insulators, conductors, etc.

[0129] Characteristics of the auxiliary equipment installation stage: In the collected images, based on the characteristics of the pole erection stage, additional identification frames for crossarms, insulators, etc. have been added, but no identification frames for conductors have been added;

[0130] Characteristics of the overhead line stage: Based on the characteristics of the auxiliary facility installation stage, a conductor identification frame is added; for transformer substation construction, the construction process of pole-mounted equipment such as transformers, surge arresters, and primary and secondary integrated switches can also be expanded.

[0131] Upon completion of construction, the tower will be erected, the foundation pit will be backfilled, and the installation of ancillary facilities and the laying of conductors will be completed. By comparing the construction progress timeline based on the above-mentioned stage characteristics, if there is an estimated construction period, it can be compared with the planned construction period to determine the progress deviation. While making the expected construction period, the schedule can be adjusted.

[0132] Optionally, the construction process model built based on spatiotemporal sequence characteristics can also automatically generate structured construction logs, realize full-cycle digital archiving, and provide traceable historical data support for subsequent operation and maintenance by dynamically adjusting the progress baseline.

[0133] In summary, this embodiment of the application integrates high-precision positioning data from UAVs with UAV imaging principles, combined with target detection algorithms, to accurately identify key components such as poles, crossarms, and insulators at the construction site. Through spatial calculation technology of target detection bounding boxes, the identification results in the image coordinate system are mapped to real three-dimensional space, establishing a precise association between pole components and pole / geographic information. Simultaneously, based on the pole coordinate calculation capability derived from image processing, real-time monitoring of line topology offsets is achieved, providing an automated method for verifying overhead power distribution line data and reducing errors and time costs associated with manual surveying. Finally, by matching the construction node status based on spatiotemporal feature sequences, control over construction progress and quality is realized.

[0134] The above combination Figures 1-5 The construction management method for overhead power distribution lines based on spatiotemporal sequence characteristics provided in the embodiments of this application is described in detail. Specific application examples are given below.

[0135] At the State Grid UHV AC test base, on-site verification tests of the algorithm were conducted during the construction of overhead distribution lines. The construction period was from October 23, 2024 to November 26, 2024. During this period, on-site testing and verification of the invention's technology were carried out intermittently, including data collection from construction site surveys, identification of towers and their auxiliary equipment, resolution of marker frame coordinates, generation of tower topology, spatial-temporal comparison, and temporal analysis of the construction progress. Multi-phase topology diagrams of the line are shown below. Figure 6 As shown, typical images acquired at specific times with clear temporal characteristics are as follows: Figure 7 As shown.

[0136] in, Figure 7 Image ① shows the line before construction, and no pit foundation, towers, or related facilities and equipment are identified.

[0137] Figure 7 Figure ② in the image was acquired on October 28, 2024. The image was used to identify the tower equipment and structural components. The image shows features such as foundation excavation, towers, and crossarms. Therefore, it was determined that at the time of acquisition, the target line tower was in the stage of erecting the pole and installing the crossarm. The next step should be to carry out work such as insulator installation and conductor erection.

[0138] Figure 7 Image ③ in the image was acquired on November 5, 2024. The image was used to identify the poles, equipment and structural components. The image shows features such as foundation excavation, poles and crossarms. At the same time, a new type of insulator was added. Therefore, it was determined that the image was acquired at the time of acquisition, which was the installation stage of pole-mounted auxiliary facilities such as insulators. The next step should be to carry out line assumption and foundation backfilling.

[0139] Figure 7Image ④ in the image was acquired on November 13, 2024. The image was used to identify the tower equipment and structural components. The image shows features such as foundation excavation, towers, crossarms, and insulators. At the same time, a new feature type, conductors, was added. Therefore, it was determined that the acquisition time was during the line-laying stage. The next step should be to complete the line-laying work and the backfilling of the pit.

[0140] Figure 7 Table 1 shows the target equipment characteristics of each tower at different stages of construction.

[0141]

[0142] Table 1. Characteristics of Target Equipment at Different Construction Stages

[0143] The above analysis clearly shows the construction progress of overhead power distribution lines, enabling control over the construction process.

[0144] The above combination Figures 1-7 This application provides a detailed description of the construction control method and application of overhead power distribution lines based on spatiotemporal sequence characteristics, as described below. Figure 8 This document provides a detailed description of the overhead power distribution line construction control system based on spatiotemporal sequence characteristics provided in the embodiments of this application.

[0145] The system specifically includes: a drone, a ground remote control terminal, and a computer terminal, among which,

[0146] The drone collects images of the overhead power line construction area at a specific moment and records the drone's flight altitude, shooting position, and pixel coordinates of the image center point at the time the image was captured. The number of images must be at least one.

[0147] The ground remote control terminal is used to transmit the drone's flight altitude, shooting position, and pixel coordinates of the image center point to the computer terminal for the images captured and recorded by the drone.

[0148] The ground remote control terminal can transmit data wirelessly or via SD card to a computer terminal, or in other possible ways, without any restrictions.

[0149] A computer terminal includes an identification module, a processing module, and an analysis module, among which...

[0150] The recognition module is used to identify target devices in an image using a recognition algorithm model. It selects and marks target devices by using a bounding box and records the pixel coordinates of the target devices. The target devices include towers, insulators, and conductors. The pixel coordinates of the target devices are the pixel coordinates of the center point of the bounding box.

[0151] The processing module is used to determine the spatial coordinates of the target device based on the pixel coordinates of the target device, the flight altitude of the drone, the shooting position of the drone, and the pixel coordinates of the center point of the image; it is also used to generate the tower topology based on the preset maximum allowable connection distance of the towers and the spatial coordinates of the target device using the nearest neighbor algorithm, and to associate other target devices other than the towers with nearby towers to generate the overall topology; it is also used to obtain the overall topology of the overhead power distribution line construction area at other times.

[0152] The analysis module is used to determine the construction progress and quality of overhead power distribution lines by analyzing the overall topology at different times and the target equipment on the overall topology at the same time.

[0153] Furthermore, the specific implementation of the above system is basically similar to the method implementation, so the description is relatively simple. For relevant details, please refer to the description of the method implementation. Moreover, it should be noted that in the various modules of the system of this application, the components are logically divided according to the functions they are to perform. However, this application is not limited to this and can re-divide or combine the components as needed.

[0154] The above describes the construction control method and system for overhead power distribution lines based on spatiotemporal sequence characteristics provided in the embodiments of this application. The following, in conjunction with... Figures 9-10 This document provides a detailed description of the overhead power distribution line construction control device based on spatiotemporal sequence characteristics provided in the embodiments of this application.

[0155] Figure 9 This is a schematic diagram of the structure of the overhead power distribution line construction control device based on spatiotemporal sequence characteristics provided in the embodiments of this application. Figure 1 For example, such as Figure 9 As shown, the overhead power distribution line construction control device 900 based on spatiotemporal sequence characteristics includes: a transceiver module 901 and a processing module 902. For ease of explanation, Figure 9 Only the main components of the overhead power distribution line construction control device based on spatiotemporal sequence characteristics are shown.

[0156] The transceiver module 901 is used to perform the transceiver function of the above-mentioned overhead power distribution line construction control method based on spatiotemporal sequence characteristics, and the processing module 902 is used to perform other functions of the above-mentioned overhead power distribution line construction control method based on spatiotemporal sequence characteristics other than the transceiver function.

[0157] Optionally, the transceiver module 901 may include a transmitting module ( Figure 9 (not shown in the image) and receiving module ( Figure 9(Not shown in the image). The transmitting module is used to implement the transmitting function of the overhead power distribution line construction control device 900 based on spatiotemporal sequence characteristics, and the receiving module is used to implement the receiving function of the overhead power distribution line construction control device 900 based on spatiotemporal sequence characteristics.

[0158] Optionally, the overhead power distribution line construction control device 900 based on spatiotemporal sequence characteristics may also include a storage module ( Figure 9 (Not shown in the image), the storage module stores programs or instructions. When the processing module 902 executes the program or instruction, the overhead power distribution line construction control device 900 based on spatiotemporal sequence characteristics can execute the overhead power distribution line construction control method based on spatiotemporal sequence characteristics in the embodiments of this application.

[0159] The following is combined Figure 10 Each component of the overhead power distribution line construction control device 1000 based on spatiotemporal sequence characteristics is described in detail:

[0160] The processor 1001 is the control center of the overhead power distribution line construction control device 1000 based on spatiotemporal sequence characteristics. It can be a single processor or a collective term for multiple processing elements. For example, the processor 1001 can be one or more central processing units (CPUs), application-specific integrated circuits (ASICs), or one or more integrated circuits configured to implement the embodiments of this application, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0161] Optionally, the processor 1001 can execute various functions of the overhead power distribution line construction control device 1000 based on spatiotemporal sequence characteristics by running or executing software programs stored in the memory 1002 and calling data stored in the memory 1002, such as executing the overhead power distribution line construction control method based on spatiotemporal sequence characteristics in the embodiments of this application.

[0162] In a specific implementation, as one example, the processor 1001 may include one or more CPUs, for example... Figure 10 CPU0 and CPU1 are shown in the diagram.

[0163] In a specific implementation, as one example, the overhead power distribution line construction control device 1000 based on spatiotemporal sequence characteristics may also include multiple processors, for example... Figure 10The processors 1001 and 1004 shown are illustrated. Each of these processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). Here, "processor" can refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions). The memory 1002 is used to store the software program executing the scheme of this application, and its execution is controlled by the processor 1001. Specific implementation methods can be found in the above method embodiments, and will not be repeated here.

[0164] Optionally, the memory 1002 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 1002 may be integrated with the processor 1001 or may exist independently, and may be connected via the interface circuit of the overhead power distribution line construction control device 1000 based on spatiotemporal sequence characteristics (…). Figure 10 (Not shown in the image) is coupled to the processor 1001, but this embodiment does not specifically limit this.

[0165] The transceiver 1003 is used for communication with other communication devices. For example, in the case of the overhead power line construction control device 1000 based on spatiotemporal sequence characteristics, which is the first device, the transceiver 1003 can be used to communicate with a second device or a third device.

[0166] Optionally, transceiver 1003 may include a receiver and a transmitter. Figure 10 (Not shown separately). The receiver is used to implement the receiving function, and the transmitter is used to implement the transmitting function.

[0167] Optionally, the transceiver 1003 can be integrated with the processor 1001 or exist independently, and can be connected to the interface circuit of the overhead power distribution line construction control device 1000 based on spatiotemporal sequence characteristics. Figure 10(Not shown in the image) is coupled to the processor 1001, but this embodiment does not specifically limit this.

[0168] Understandable, Figure 10 The structure of the overhead power distribution line construction control device 1000 based on spatiotemporal sequence characteristics shown in the figure does not constitute a limitation on the overhead power distribution line construction control device based on spatiotemporal sequence characteristics. The overhead power distribution line construction control device based on spatiotemporal sequence characteristics may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0169] Furthermore, the technical effects of the overhead power distribution line construction control device 1000 based on spatiotemporal sequence characteristics can be referred to the technical effects of the method described in the above method embodiments, and will not be repeated here.

[0170] It should be understood that the processor in the embodiments of this application can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0171] It should also be understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0172] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

Claims

1. A method for construction management and control of overhead distribution lines based on spatiotemporal sequence features, characterized in that, The method comprises: S101, the unmanned aerial vehicle collects images of an overhead power distribution line construction area at a certain moment, and records the corresponding flight height of the unmanned aerial vehicle, the shooting position of the unmanned aerial vehicle and the pixel coordinates of the image center point when the image is taken, wherein the number of images is at least one; S102, using an identification algorithm model to identify target equipment in the image, and marking the target equipment by a marking box, and recording the pixel coordinates of the target equipment, wherein the target equipment includes a tower, an insulator and a wire, and the pixel coordinates of the target equipment are the pixel coordinates of the center point of the marking box; S103, based on the pixel size of the fixed camera on the unmanned aerial vehicle, the camera imaging focal length of the camera and the flight height of the unmanned aerial vehicle, the pixel resolution is obtained, and then based on the pixel coordinates of the target equipment and the pixel coordinates of the image center point, the pixel offset of the target equipment is obtained, and then based on the pixel offset of the target equipment and the pixel resolution, the spatial distance between the target equipment and the image center point is obtained, and then based on the spatial distance and the spatial coordinates of the image center point, the spatial coordinates of the target equipment are obtained, wherein the pixel size of the camera and the camera imaging focal length of the camera are obtained through the hardware specifications of the camera, and the spatial coordinates of the image center point are the shooting position of the unmanned aerial vehicle; S104, based on the preset maximum allowed linking distance of the tower and the spatial coordinates of the target equipment, a nearest neighbor algorithm is used to generate a tower topology, and the other target equipment except the tower is associated with the adjacent tower to generate an overall topology; S105, repeating steps S101-S104 until the overall topology of other moments of the overhead power distribution line construction area is obtained; S106, by comparing and analyzing the overall topology at different moments and the target equipment on the overall topology at the same moment, the construction progress and construction quality of the overhead power distribution line are determined; After step S103 and before step S104, the method further comprises: Based on the spatial coordinates of the target equipment, spatial coordinate sets of different types of target equipment are constructed respectively, wherein the spatial coordinate sets of different types of target equipment include a spatial coordinate set of towers, a spatial coordinate set of insulators and a spatial coordinate set of wires; For different types of target equipment, parameters of a DBSCAN clustering algorithm are preset respectively, wherein the parameters of the DBSCAN clustering algorithm include a neighborhood radius and a minimum number of points; Based on the preset parameters of the DBSCAN clustering algorithm, the spatial coordinate sets of the different types of target equipment are processed by the DBSCAN clustering algorithm to obtain the spatial coordinates of the de-duplicated target equipment.

2. The overhead distribution line construction management and control method based on spatiotemporal sequence features according to claim 1, characterized in that, The identification algorithm model uses a YOLO V5 framework, and combines a CBAM attention mechanism and a Mosaic-9 data enhancement strategy. 3.The overhead distribution line construction management and control method based on spatiotemporal sequence features of claim 1, characterized in that, The method comprises the following steps: Based on the preset maximum allowed linking distance of the tower and the spatial coordinates of the target device, a nearest neighbor algorithm is used to generate a tower topology, and other target devices except the tower are associated with the adjacent tower to generate an overall topology, including: Based on the spatial coordinates of the target device, a set of spatial coordinates of the tower is constructed; Any tower is selected as an initial tower, and a nearest neighbor algorithm is used to calculate the Euclidean distance between the spatial coordinates of the initial tower and other towers, and the tower with the smallest Euclidean distance is selected as a second tower, wherein the Euclidean distance between the second tower and the initial tower satisfies the preset maximum allowed linking distance of the tower; For other towers, the nearest neighbor algorithm is continued until all towers are connected to generate a tower topology; 4. The overhead distribution line construction management and control method based on spatiotemporal sequence features according to claim 1, characterized in that, And other target devices except the tower are associated with the adjacent tower to generate an overall topology. After step S104 and before step S105, the method further comprises:

5. The overhead distribution line construction management and control method based on spatiotemporal sequence features according to claim 1, characterized in that, The overall topology is manually audited, and if the error between the tower distance in the overall topology and the tower distance in the overhead distribution line construction design scheme is greater than a preset value, a warning is triggered. The construction progress and construction quality of the overhead distribution line are determined by comparing and analyzing the overall topology at different times and the target device on the overall topology at the same time, including: The overall topologies at different times are analyzed, and if the spatial coordinate distance of the tower at different times is less than 5m, it is determined that it is the same tower; 6. An overhead distribution line construction management and control system based on spatiotemporal sequence features, characterized in that, If the isolated point appears in the overall topology at a later time, it is determined to be a newly added tower, and if the isolated point appears in the overall topology at an earlier time, manual intervention is required to determine whether it is a removed tower. The system comprises: a UAV, a ground remote control end and a computer terminal, wherein, The UAV collects images of the overhead distribution line construction area at a certain time, and records the corresponding UAV flight height, UAV shooting position and pixel coordinates of the image center point when the image is taken, wherein the number of images is at least one; The ground remote control end is used to transmit the images collected by the UAV and the corresponding UAV flight height, UAV shooting position and pixel coordinates of the image center point when the image is taken to the computer terminal; The computer terminal comprises an identification module, a processing module and an analysis module, wherein, The identification module is used to identify the target device in the image by using an identification algorithm model, to frame and mark the target device by a marking box, and to record the pixel coordinates of the target device, wherein the target device includes a tower, an insulator and a conductor, and the pixel coordinates of the target device are the pixel coordinates of the center point of the marking box; The processing module is configured to: obtain a pixel resolution based on a pixel size of a fixed camera on the UAV, a camera imaging focal length of the camera, and a flight height of the UAV; obtain a pixel offset of the target device based on a pixel coordinate of the target device and a pixel coordinate of the image center point; obtain a spatial distance between the target device and the image center point based on the pixel offset of the target device and the pixel resolution; and obtain a spatial coordinate of the target device based on the spatial distance and a spatial coordinate of the image center point, wherein the pixel size of the camera and the camera imaging focal length of the camera are obtained based on hardware specifications of the camera, and the spatial coordinate of the image center point is a shooting position of the UAV; construct a spatial coordinate set of different types of target devices based on the spatial coordinate of the target device, wherein the spatial coordinate set of the different types of target devices includes a spatial coordinate set of towers, a spatial coordinate set of insulators, and a spatial coordinate set of conductors; preset parameters of a DBSCAN clustering algorithm for the different types of target devices, wherein the parameters of the DBSCAN clustering algorithm include a neighborhood radius and a minimum point number; perform DBSCAN clustering algorithm processing on the spatial coordinate set of the different types of target devices based on the preset parameters of the DBSCAN clustering algorithm, to obtain a spatial coordinate of a de-duplicated target device; generate a tower topology by using a nearest neighbor algorithm based on a preset maximum allowed linking distance of the tower and the spatial coordinate of the de-duplicated target device, and perform a near-tower association on target devices other than the tower to generate an overall topology; and obtain an overall topology of the overhead distribution line construction area at other times. The analysis module is configured to determine a construction progress and a construction quality of the overhead distribution line by analyzing target devices on the overall topology at different times and the overall topology at the same time.

7. An overhead distribution line construction management and control device based on spatiotemporal sequence features, characterized in that, The apparatus includes means for performing the method of any of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a computer program or instructions that, when executed, cause the method of any of claims 1-5 to be performed. The computer-readable storage medium includes a computer program or instructions that, when executed, cause the method of any of claims 1-5 to be performed.

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