An overhead transmission line section map generation optimization method and device based on multi-source data and a storage medium

Abstract

The present application relates to overhead transmission line engineering survey design technical field, especially in kind of overhead transmission line section map generation optimization method, equipment and storage medium based on multi-source data. First, through multi-source data acquisition, get artificial measurement data set, based on overhead transmission line corner degree number and distance factor, artificial measurement multi-source data set is sorted automatically, then according to overhead transmission line engineering data generation artificial measurement overhead transmission line section point data set, then through digital elevation model data, the left, middle and right edge line section line data of overhead transmission line are extracted respectively by using bilinear interpolation method, digital elevation overhead transmission line section line data set is constructed, and automatic optimization is carried out based on overhead transmission line offset and terrain factor, finally, through graph data superposition, overhead transmission line section map is obtained, the method can greatly reduce the workload of artificial editing of section map, improve the quality of transmission line section map and the work efficiency of survey design.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of overhead transmission line engineering survey design, and particularly relates to an overhead transmission line section map generation optimization method and device based on multi-source data and a storage medium. BACKGROUND

[0002] In the process of overhead transmission line engineering survey design, the section map result of transmission line surveying and mapping is one of the important results, and is also one of the most important results of overhead transmission line engineering design. With the continuous development of surveying and mapping science and aerial survey technology, the high-precision digital elevation model of the project area can be obtained through aerial remote sensing technology, and the outline section map result of the transmission line engineering can be obtained through the digital elevation model. The result has been well applied in the feasibility study and preliminary design of overhead transmission line engineering, and has improved the work efficiency of line engineering survey design.

[0003] However, at present, due to the influence of vegetation and environment and the reason of aerial survey equipment technology, the section map result generated by the digital elevation model obtained through aerial remote sensing technology can only meet the requirements of feasibility study or preliminary design. The result cannot meet the precision requirements of the construction drawing design of the line engineering, and the data collected by manual GNSS or total station can meet the requirements of the construction drawing design.

[0004] At present, the common operation mode of overhead transmission line engineering section map generation is to complete the joint operation according to the section map obtained from the aerial digital elevation model combined with the field manual measurement data. The specific method is to complete the correction and editing of the section map by manual measurement point data at important places of the line. Since there are often differences between the aerial section line and the actual manual measurement data, the traditional operation mode is to manually edit and correct the section line according to the manual measurement point data. This makes the manual editing workload of the section map very large, which seriously affects the work efficiency of the line engineering survey design personnel.

[0005] Specifically, in the current overhead transmission line section map generation process, the manual measurement data result needs to be manually sorted first, then converted into section coordinates, then drawn on the section map generated by aerial survey, and finally edited according to the manual measurement data. Finally, the map is generated. This process not only consumes time and effort, but also easily introduces human errors, increasing the survey design cost and risk. Therefore, developing an overhead transmission line section automatic optimization mapping method based on manual measurement data and digital elevation model can efficiently and accurately improve the work efficiency of overhead transmission line engineering section map generation and survey design, and ensure the quality of survey section map results. SUMMARY

[0006] To solve the above technical problems, the application provides an overhead transmission line section map generation optimization method based on multi-source data, which comprises the following steps:

[0007] S1. Obtain overhead transmission line artificial measurement point coordinate data, collect multi-source data at the artificial measurement point, establish an artificial measurement data matrix of the overhead transmission line, and align the multi-source data matrix with the coordinate system and the elevation reference to obtain an artificial measurement multi-source data set;

[0008] S2. Based on the overhead transmission line corner angle and distance factor, automatically sort the artificial measurement multi-source data set;

[0009] S3. Based on the overhead transmission line engineering data, generate an artificial measurement overhead transmission line section point data set according to the artificial measurement multi-source data set after automatic sorting;

[0010] S4. Based on the digital elevation model data, extract left, middle and right overhead transmission line section line data respectively by bilinear interpolation method, and construct a digital elevation overhead transmission line section line data set;

[0011] S5. Based on the overhead transmission line offset and terrain factor, automatically optimize the digital elevation overhead transmission line section line data set according to the artificial measurement overhead transmission line section point data set and the optimized digital elevation overhead transmission line section line data set;

[0012] S6. Obtain the overhead transmission line section map by superimposing the artificial measurement overhead transmission line section point data set and the optimized digital elevation overhead transmission line section line data set.

[0013] Further, the artificial measurement multi-source data set comprises global navigation satellite system measurement data and total station data.

[0014] Further, in step S1, the artificial measurement data obtained by global navigation satellite system measurement and total station measurement by field artificial measurement is converted into the unified plane coordinate system and elevation reference of the overhead transmission line engineering, and the measurement point information of the field artificial measurement data is arranged to obtain the artificial measurement multi-source data set, wherein the measurement point information comprises measurement point number and measurement point code.

[0015] Further, step S2 comprises the following steps:

[0016] S201. Obtain the azimuth angle data of the artificial measurement point, and construct an azimuth angle constraint condition based on the azimuth angle and the corner angle of the overhead transmission line corner point, judge the azimuth angle of the measurement point, and obtain the artificial measurement point set meeting the azimuth angle constraint condition, wherein the azimuth angle constraint condition is expressed as:

[0017] ;

[0018] ;

[0019] wherein A is the small side corner number of the transmission line, B is the large side corner number of the transmission line, C is the artificial measurement point, is the small side corner number, is the large side corner number, right turn is positive and left turn is negative, is the azimuth angle of the direction line AB formed by the corner A pointing to the corner B, is the azimuth angle of the direction line BA formed by the corner B pointing to the corner A, is the azimuth angle of the direction line AC formed by the corner A pointing to the artificial measurement point C, is the azimuth angle of the direction line BC formed by the corner B pointing to the artificial measurement point C;

[0020] S202. According to the obtained artificial measurement point set meeting the azimuth angle constraint condition, a distance factor is constructed based on the vertical distance between the artificial measurement point and the tension section of the transmission tower, and according to the minimum distance theory, the tension section information data to which the artificial measurement point belongs is obtained, and the distance factor is represented as:

[0021] ;

[0022] wherein p is the distance factor, is the distance from the artificial measurement point C to the tension section straight line AB, is the distance from the artificial measurement point C to the tension section straight line EF, when , the artificial measurement point belongs to the AB tension section, otherwise the artificial measurement point belongs to the EF tension section;

[0023] S203. According to the artificial measurement point set and the tension section information data, the cumulative distance value of the artificial measurement point along the direction of the belonging tension section is calculated, and the artificial measurement data after automatic sorting is obtained by sorting according to the size relationship from the largest cumulative distance to the smallest cumulative distance.

[0024] Further, the overhead transmission line engineering data includes overhead transmission line cumulative distance data and overhead transmission line offset distance data.

[0025] Further, step S5 includes the following steps:

[0026] S501. According to the artificial measurement point offset distance, based on the preset overhead transmission line wind deflection influence data, the artificial measurement points located in the wind deflection influence range are determined as the artificial measurement points participating in the section line optimization, and an artificial measurement optimization point set is obtained;

[0027] S502. Based on the artificial measurement optimization point set, the profile line data set of the digital elevation profile is segmented by segment correction for profile line segmentation;

[0028] S503. According to the segmented profile line data, the profile line is automatically optimized based on the digital elevation model elevation, which can be expressed as:

[0029] ;

[0030] Wherein, is the automatic optimization correction number of the profile point T, is the cumulative distance from the measurement point M to the profile point T, is the cumulative distance from the measurement point M to the measurement point N, is the artificial measurement elevation data of the measurement point M, is the DEM grid interpolation elevation data of the measurement point M, is the cumulative distance from the measurement point N to the profile point T, is the artificial measurement elevation data of the measurement point N, is the DEM grid interpolation elevation data of the measurement point N;

[0031] S504. Repeat step S503 to obtain the optimized profile map of the left line profile, the center line profile and the right line profile.

[0032] A computer device, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to realize the optimization method for generating the profile map of the overhead transmission line based on the multi-source data according to any one of the above.

[0033] A storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to realize the optimization method for generating the profile map of the overhead transmission line based on the multi-source data according to any one of the above.

[0034] The present application automatically optimizes the profile map of the overhead transmission line generated by the digital elevation model according to the point data of artificial measurement, meets the requirements of the construction drawing design, greatly reduces the workload of manual editing of the profile map, improves the quality of the profile map of the overhead transmission line, significantly improves the work efficiency of the survey and design, and has the following beneficial effects:

[0035] (1) The present application is aimed at the overhead transmission line engineering construction drawing survey and design stage, how to use the artificial measurement data to automatically correct and optimize the profile map of the line generated by the digital elevation model, realize automatic mapping, meet the requirements of the construction drawing result, and greatly reduce the manual editing work and improve the work efficiency.

[0036] (2) The application is aimed at the characteristics of the path direction of the overhead transmission line, and realizes that the artificial measurement points can be automatically sorted according to the path of the transmission line corner by the azimuth angle and the corner degree number and the distance factor of the overhead transmission line path, and realizes the automatic drawing of the artificial measurement section points.

[0037] (3) The application is aimed at the section graph generated by the digital elevation model and the artificial measurement points, and realizes the automatic fitting of the section line by the deflection distance and the terrain factor of the artificial measurement points, generates the section graph by the digital elevation model, solves the difficulty that the traditional section graph mainly relies on the artificial correction and editing and needs to spend a large amount of manpower, and greatly improves the work efficiency of the generation of the transmission line section graph. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 It is a flow chart of an overhead transmission line section graph generation optimization method based on multi-source data according to an embodiment of the application.

[0039] Figure 2 It is an automatic sorting schematic diagram of artificial measurement data according to the corner degree number and the distance factor of the overhead transmission line according to an embodiment of the application.

[0040] Figure 3 It is an automatic sorting result schematic diagram of artificial measurement data according to the corner degree number and the distance factor of the overhead transmission line according to an embodiment of the application.

[0041] Figure 4 It is an automatic optimization schematic diagram of the section line segmentation based on the deflection distance and the terrain factor of the artificial measurement points according to an embodiment of the application.

[0042] Figure 5 It is an automatic optimization result schematic diagram of the section line segmentation based on the deflection distance and the terrain factor of the artificial measurement points according to an embodiment of the application.

[0043] Figure 6 It is a section graph before the overhead transmission line section optimization based on artificial measurement data according to an embodiment of the application.

[0044] Figure 7 It is a section graph after the overhead transmission line section automatic optimization based on artificial measurement data according to an embodiment of the application.

[0045] Figure 8 It is an internal structure schematic diagram of a computer device according to an embodiment of the application.

[0046] Figure 9 It is a schematic diagram of a storage medium according to an embodiment of the application.

[0047] In the diagram, 200 is the terminal device, 210 is the memory, 211 is the RAM, 212 is the cache, 213 is the ROM, 214 is the program / utility, 215 is the program module, 220 is the processor, 230 is the bus, 240 is the external device, 250 is the I / O interface, 260 is the network adapter, and 300 is the program. Detailed Implementation

[0048] To enable those skilled in the art to better understand the present invention and to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are for illustrative purposes only and are not intended to further limit the present invention.

[0049] Example 1:

[0050] like Figure 1 As shown, this embodiment of the invention provides a method for generating and optimizing cross-sectional diagrams of overhead transmission lines based on multi-source data, including the following steps:

[0051] S1. Obtain coordinate data of manual measurement points of overhead transmission lines. At the manual measurement points, establish a data matrix of manual measurement of overhead transmission lines through multi-source data acquisition. Align the multi-source data matrix with the coordinate system and the elevation datum to obtain a multi-source dataset of manual measurement.

[0052] S2. Automatically sort the multi-source dataset of manual measurements based on the rotation angle and distance factor of overhead transmission lines;

[0053] S3. Based on the automatically sorted multi-source dataset of manual measurements, generate a dataset of cross-sectional points of overhead transmission lines based on the engineering data of overhead transmission lines;

[0054] S4. Based on the digital elevation model data, the cross-sectional data of the left, middle and right sides of the overhead transmission line are extracted by bilinear interpolation to construct a digital elevation overhead transmission line cross-sectional data set.

[0055] S5. Based on the manually measured overhead transmission line cross-section point dataset and the digital elevation overhead transmission line cross-section line dataset, the digital elevation overhead transmission line cross-section line dataset is automatically optimized based on the overhead transmission line offset and terrain factor.

[0056] S6. Based on the manually measured cross-sectional point dataset of overhead transmission lines and the optimized digital elevation data set of overhead transmission line cross-sectional lines, the cross-sectional map of the overhead transmission line is obtained by overlaying the data.

[0057] Specifically, the artificially measured multi-source dataset includes global geographic information system data and total station data.

[0058] Specifically, step S1 mainly includes two parts: first, converting the data measured manually in the field using GNSS or total station into a unified plane coordinate system and elevation datum for power transmission line engineering; and second, organizing the point numbers and codes of the manually measured data in the field to prepare for the automatic generation of cross-section diagrams later.

[0059] Furthermore, step S2 includes the following steps:

[0060] S201. Obtain the azimuth data of manually measured points, and construct azimuth constraints based on the azimuth angle and turning angle of the overhead transmission line turning point. Perform angle judgment on the azimuth of the measured points to obtain a set of manually measured points that meet the azimuth constraints. The azimuth constraints are expressed as follows:

[0061] ;

[0062] ;

[0063] Where A represents the minor side angle number of the transmission line, B represents the major side angle number of the transmission line, and C represents the manually measured point. This refers to the small side turn angle. This represents the large side turn angle; a right turn is recorded as positive, and a left turn as negative. Let AB be the azimuth angle of the direction line AB formed by turning angle A and turning angle B. Let BA be the azimuth angle of the direction line BA formed by turning point B and turning point A. Let AC be the azimuth angle of the direction line AC formed by the turning angle A and the manually measured point C. The azimuth angle of the direction line BC formed by the turning point B and the manually measured point C;

[0064] S202. Based on the obtained set of artificial measurement points that meet the azimuth constraint conditions, a distance factor is constructed based on the vertical distance between the artificial measurement points and the tension section of the transmission tower. According to the minimum distance theory, the information data of the tension section to which the artificial measurement points belong is obtained. The distance factor is expressed as:

[0065] ;

[0066] Where p is the distance factor, The distance from point C (measured manually) to the straight line AB of the tension section. The distance from point C to the straight line EF of the tension section is measured manually. If the manual measurement point is within the AB tension section, then the manual measurement point belongs to the EF tension section; otherwise, the manual measurement point belongs to the EF tension section.

[0067] S203. Calculate the cumulative distance value of the manual measurement points along the direction of the tension section based on the manual measurement point set and the tension section information data, and sort them according to the size relationship from the largest cumulative distance to the smallest cumulative distance to obtain the automatically sorted manual measurement data.

[0068] Specifically, in order to realize the automatic generation of the cross-sectional diagram of the manual measurement data, it is necessary to carry out the automatic sorting of the manual measurement data according to the transmission line direction. The traditional working mode is to sort the manual measurement data according to manual operation. The present invention proposes a method for automatically sorting the manual measurement data of the transmission line based on the azimuth angle and distance constraint conditions according to the transmission line path. This method mainly consists of the following two parts: First, the transmission line is divided into different tension sections according to the turning angle. Second, each tension section classifies the manual measurement points according to the azimuth angle and turning angle of the line path. Third, finally, determine the last belonging tension section according to the minimum offset of the classified measurement points to the tension section. Fourth, after determining the tension section to which the measurement point belongs, calculate the cumulative distance from the manual measurement point to the tension section and sort it automatically from the smallest cumulative distance to the largest.

[0069] As Figure 2 shown, there is a transmission line composed of tension sections J1-J2, J2-J3, J3-J4, J4-J5, J5-J6, where J1, J2, J3, J4, J5, J6 respectively represent different turning angle numbers of the current transmission line, L1 represents the manual measurement point. At each turning angle, the manual measurement points are classified based on the azimuth angle and turning angle. It can be seen that the manual measurement point L1 can satisfy both the belonging tension section J3-J4 and the tension section J1-J2 according to this condition. D1 represents the offset of the manual measurement point L1 to the tension section J3-J4, and D2 represents the offset of the manual measurement point L1 to the tension section J1-J2. It can be seen from the figure that D1 < D2, and it can be concluded that the manual measurement point L1 should belong to the tension section J3-J4, which is in line with the actual situation.

[0070] As Figure 3 shown, the result of automatically sorting the manual measurement point data according to the turning angle and distance factor of the overhead transmission line. Here, the most special case of the transmission line incoming and outgoing line paths is also considered to verify the accuracy of this algorithm, and the grid point arrangement method is adopted for the manual measurement point data, and the most comprehensive data is used to verify the accuracy of the result. From Figure 3 it can be seen that theoretically it meets the requirements of the actual situation, further verifying the accuracy of the result.

[0071] Furthermore, in step S3, according to the automatically sorted data, generate the manual measurement transmission line cross-sectional point data file according to the transmission line coordinates, the line cumulative distance, and the offset.

[0072] This step mainly includes two parts: first, converting the automatically sorted manually measured coordinate data file into a line cross-section coordinate file, which typically includes information such as point number, cumulative distance, offset, and elevation; second, generating an automatically plotted cross-section diagram based on the converted cross-section data file. The overhead transmission line engineering data includes the cumulative distance data and offset data of the overhead transmission line.

[0073] Furthermore, in step S4, the cross-sectional data of the left, middle, and right sides of the transmission line are extracted based on the digital elevation model data using the bilinear interpolation method.

[0074] Specifically, the process begins by calculating the coordinates of the centerline, left side, and right side of the route based on the route alignment. Then, the plane coordinates of the centerline and sideline points are calculated using a fixed step size. These coordinates are then imported into a digital elevation model, typically using bilinear interpolation to obtain the elevations of the centerline and sideline points. Finally, the obtained centerline and sideline point coordinates are converted into a route cross-section coordinate data file. The centerline and sideline points are then plotted onto the cross-section drawing based on the cross-section coordinate file, and the centerline and left and right sidelines are connected to form the initial version of the cross-section drawing.

[0075] Furthermore, step S5 includes the following steps:

[0076] S501. Based on the offset of the manual measurement points and the preset wind deflection impact data of overhead transmission lines, the manual measurement points located within the wind deflection impact range are determined as the manual measurement points participating in the cross-section optimization, thus obtaining the set of manual measurement optimization points.

[0077] S502. Based on the optimized point set by manual measurement, the cross-section line dataset of digital elevation overhead transmission line is segmented by segmented correction.

[0078] S503. Based on the segmented cross-section data and the elevation of the digital elevation model, the cross-section is automatically optimized, which can be expressed as:

[0079] ;

[0080] in, For the automatic optimization correction number of section point T, The cumulative distance from measurement point M to section point T is... The cumulative distance from measurement point M to measurement point N. The elevation data for measurement point M is obtained through manual measurement. To interpolate elevation data within the DEM grid for measurement point M, Let N be the cumulative distance from the measurement point N to the cross-section point T. The elevation data for measurement point N is obtained through manual measurement. Interpolate elevation data for the DEM grid at measurement point N;

[0081] S504. Repeat step S503 to obtain all optimized cross-sectional results for the left, center, and right sides of the line.

[0082] Specifically, in step S5, the cross-section lines are automatically optimized based on the cross-section point data measured manually and the cross-section line data extracted from the digital elevation model, according to the offset and terrain factor.

[0083] Specifically, this part of the work mainly consists of the following steps:

[0084] (1) Determine the manual measurement points to participate in the automatic optimization of the cross section. First, determine the manual measurement points to participate in the optimization of the cross section based on the offset of the measurement points. Generally, any measurement point within the range of wind deflection can participate in the optimization of the cross section.

[0085] (2) Then, based on the determined measurement points to be optimized, the cross-section line is divided into segments. For measurement points that are close to each other, the distance parameter can be set to discard the points and select the measurement points that are closer to the center line to participate in the segmentation. The cross-section line is automatically optimized through segmentation optimization.

[0086] like Figure 4 As shown in the table, the cross-sectional line of section P1 of the line is automatically optimized. α represents a manually measured point, "right 8" represents a point 8 meters off-center from the line, β represents the right side line, γ represents the center line, and δ represents the left side line. The distance between the line edges is 8 meters. It is evident from the figure that, due to the influence of the accuracy of the digital elevation model, the automatically generated cross-sectional line often has a certain difference from the elevation of the manually measured points.

[0087] (3) For manually measured points that need to be optimized in segments, first use the digital elevation model to obtain the model elevation of the two ends, and then compare it with the manually measured elevation value to obtain the correction value of the two ends of the segment. For the correction value between the two ends of the section, the section line can be allocated according to the inverse ratio of distance. For a section with multiple points at one end, the correction value of the center line, left line and right line is allocated according to the distance to the edge line. The closer the point is to the section line, the greater the correction allocation authority, which is close to the manually measured value. If there are only measurement points on one side edge line, the other edge lines are executed with reference to the correction value of one side edge line.

[0088] Figure 4The distance between the edge and the centerline of section P1 is 8 meters. The correction for the left and right centerlines of section P1 is the elevation difference "D1" between the manually measured point "Right 8" and the right edgeline of the cross-section. The correction for the left centerline is the elevation difference "D2" between the manually measured point "Right 2" and the centerline of the cross-section. Since there are no manually measured centerline and edgeline points for reference, the correction for the right side of section P1 is based on the point "Right 21" closest to the centerline. First, the model elevation of "Right 21" is obtained through the digital elevation model, and then compared with the manually measured elevation to obtain the correction. The correction values ​​for the side line and center line of section P1 of the line are... For the correction of the section line between the two ends of the section, the correction can be allocated according to the inverse ratio of the distance.

[0089] like Figure 5 As shown, the cross-section diagram of section P1 of the line is automatically optimized by considering the offset of manually measured points and topographic factors. Here, α represents the manually measured point, "right 8" represents the point 8 meters away from the center of the line, β represents the right side line of the line, γ represents the center line of the line, and δ represents the left side line of the line. The automatically optimized cross-section can perfectly match the manually measured points.

[0090] (4) Repeat step S503 for the remaining cross sections, and optimize the cross section of the left line, the middle line and the right line respectively. This will achieve the optimization of the entire cross section result diagram.

[0091] Furthermore, in step S6, the cross-sectional result map of the overhead transmission line is synthesized based on the manually measured cross-sectional point data file and the automatically optimized cross-sectional line data.

[0092] Figure 6 The image shows a cross-sectional view of an overhead transmission line before optimization, based on manually measured data. Figure 7 The diagram shows the optimized cross-section of an overhead transmission line based on manually measured data. Here, α represents the manually measured point, β represents the right side line of the line, γ represents the center line of the line, and δ represents the left side line of the line. As can be seen from the diagram, the method of this embodiment can automatically optimize the line edge points and ensure that they match the manually measured data, which can greatly reduce the workload of manual editing.

[0093] Specifically, the workflow is as follows:

[0094] First, the manually measured data is converted into a new format. Then, the manually measured data is automatically sorted according to the transmission line path. A method is proposed to automatically sort the manually measured data according to the turning angle and distance factor of the overhead transmission line, which provides a foundation for the automatic drawing of cross-sectional maps of manually measured points. Then, the automatically sorted data is converted into a cross-sectional data file, and digital elevation model data is read in. The cross-sectional data of the left, middle and right sides of the transmission line are extracted using the bilinear interpolation method. A method is proposed to automatically optimize the cross-sectional lines based on the offset and the topographic factor of the digital elevation model. Finally, the cross-sectional data of the overhead transmission line is automatically optimized and synthesized based on the cross-sectional point data of the manually measured cross-sectional points to achieve one-click automatic optimization of the cross-sectional map of the overhead transmission line project, which improves the automation level of the cross-sectional map results of the transmission line project.

[0095] Example 2

[0096] Furthermore, as a preferred embodiment of the present invention, a terminal device for an optimization method for generating cross-sectional diagrams of overhead transmission lines based on multi-source data is proposed, such as... Figure 8 As shown, the terminal device 200 includes at least one memory 210, at least one processor 220, and a bus 230 connecting different platform systems.

[0097] The memory 210 may include a readable medium in the form of volatile memory, such as RAM 211 (random access memory) and / or cache 212, and may further include ROM 213 (read-only memory).

[0098] The memory 210 also stores a computer program that can be executed by the processor 220, causing the processor 220 to execute any of the above-described methods for generating and optimizing cross-sectional diagrams of overhead transmission lines based on multi-source data in this application embodiment. The specific implementation and technical effects achieved are consistent with the implementation methods and achieved in the above-described embodiments, and some details will not be repeated here. The memory 210 may also include a program / utility 214 having a set (at least one) of program modules 215. Such program modules include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment.

[0099] Accordingly, processor 220 can execute the aforementioned computer program, as well as executable program / utility 214.

[0100] Bus 230 can represent one or more of several types of bus structures, including a memory bus or memory controller, peripheral bus, graphics acceleration port, processor, or a local bus using any of the various bus structures.

[0101] Terminal device 200 can also communicate with one or more external devices 240, such as keyboards, pointing devices, Bluetooth devices, etc., and with one or more devices capable of interacting with it, and / or with any device that enables it to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication can be performed via input / output (I / O) interface 250. Furthermore, terminal device 200 can also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via network adapter 260. Network adapter 260 can communicate with other modules of terminal device 200 via bus 230. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with terminal device 200, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0102] Example 3

[0103] As a preferred embodiment of Example 1, a computer-readable storage medium is proposed for an optimization method for generating cross-sectional diagrams of overhead transmission lines based on multi-source data. The computer-readable storage medium stores instructions that, when executed by a processor, implement any of the aforementioned optimization methods for generating cross-sectional diagrams of overhead transmission lines based on multi-source data. Its specific implementation is consistent with the implementation methods and achieved technical effects described in the above embodiments, and some details will not be repeated.

[0104] like Figure 9As shown, the program 300 (program product) provided in this embodiment for implementing the above-described method for generating and optimizing cross-sectional diagrams of overhead transmission lines based on multi-source data can be a portable compact disc read-only memory (CD-ROM) and include program code, and can run on a terminal device, such as a personal computer. However, the program 300 (program product) of this invention is not limited thereto. In this document, a readable storage medium can be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus, or device. The program 300 (program product) can employ any combination of one or more readable media. A readable medium can be a readable signal medium or a readable storage medium. A readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0105] Computer-readable storage media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof. Program code for performing operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on a user computing device, partially on a user device, as a standalone software package, partially on a user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing devices can be connected to user computing devices via any type of network, including local area networks (LANs) or wide area networks (WANs), or they can be connected to external computing devices (e.g., via the Internet using an Internet service provider).

[0106] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for generating and optimizing cross-sectional diagrams of overhead transmission lines based on multi-source data, characterized in that, Includes the following steps: S1. Obtain coordinate data of manual measurement points of overhead transmission lines. At the manual measurement points, establish a data matrix of manual measurement of overhead transmission lines through multi-source data acquisition. Align the multi-source data matrix with the coordinate system and the elevation datum to obtain a multi-source dataset of manual measurement. S2. Automatically sort the multi-source dataset of manual measurements based on the rotation angle and distance factor of overhead transmission lines; S3. Based on the automatically sorted multi-source dataset of manual measurements, generate a dataset of cross-sectional points of overhead transmission lines based on the engineering data of overhead transmission lines; S4. Based on the digital elevation model data, the cross-sectional data of the left, middle and right sides of the overhead transmission line are extracted by bilinear interpolation to construct a digital elevation overhead transmission line cross-sectional data set. S5. Based on the manually measured overhead transmission line cross-section point dataset and the digital elevation overhead transmission line cross-section line dataset, the digital elevation overhead transmission line cross-section line dataset is automatically optimized based on the overhead transmission line offset and terrain factor. S6. Based on the dataset of manually measured cross-section points of overhead transmission lines and the optimized dataset of digital elevation overhead transmission line cross-sections, the cross-section map of the overhead transmission line is obtained by overlaying the data. Step S2 includes the following steps: S201. Obtain the azimuth data of manually measured points, and construct azimuth constraints based on the azimuth angle and turning angle of the overhead transmission line turning point. Perform angle judgment on the azimuth of the measured points to obtain a set of manually measured points that meet the azimuth constraints. The azimuth constraints are expressed as follows: ； ； Where A represents the minor side angle number of the transmission line, B represents the major side angle number of the transmission line, and C represents the manually measured point. This refers to the small side turn angle. This represents the large side turn angle; a right turn is recorded as positive, and a left turn as negative. Let AB be the azimuth angle of the direction line AB formed by turning angle A and turning angle B. Let BA be the azimuth angle of the direction line BA formed by turning point B and turning point A. Let AC be the azimuth angle of the direction line AC formed by the turning angle A and the manually measured point C. The azimuth angle of the direction line BC formed by the turning point B and the manually measured point C; S202. Based on the obtained set of artificial measurement points that meet the azimuth constraint conditions, a distance factor is constructed based on the vertical distance between the artificial measurement points and the tension section of the transmission tower. According to the minimum distance theory, the information data of the tension section to which the artificial measurement points belong is obtained. The distance factor is expressed as: ； Where p is the distance factor, The distance from point C (measured manually) to the straight line AB of the tension section. The distance from point C to the straight line EF of the tension section is measured manually. If the manual measurement point is within the AB tension section, then the manual measurement point belongs to the EF tension section; otherwise, the manual measurement point belongs to the EF tension section. S203. Based on the set of manually measured points and the information data of the tension section, calculate the cumulative distance value of the manually measured points along the direction of their respective tension sections, and sort them according to the relationship from the largest to the smallest cumulative distance to obtain the automatically sorted manually measured data.

2. The method for generating and optimizing cross-sectional diagrams of overhead transmission lines based on multi-source data according to claim 1, characterized in that, The artificially measured multi-source dataset includes global navigation satellite system measurement data and total station data.

3. The method for generating and optimizing cross-sectional diagrams of overhead transmission lines based on multi-source data according to claim 2, characterized in that, In step S1, the manual measurement data obtained by field workers through global navigation satellite system measurement and total station measurement is first converted into a unified plane coordinate system and elevation benchmark for overhead transmission line engineering. The measurement point information of the field manual measurement data is then organized to obtain a multi-source dataset of manual measurements. The measurement point information includes the measurement point number and measurement point code.

4. The method for generating and optimizing cross-sectional diagrams of overhead transmission lines based on multi-source data according to claim 1, characterized in that, The overhead transmission line engineering data includes cumulative distance data and offset data of overhead transmission lines.

5. The method for generating and optimizing cross-sectional diagrams of overhead transmission lines based on multi-source data according to claim 1, characterized in that, Step S5 includes the following steps: S501. Based on the offset of the manual measurement points and the preset wind deflection impact data of overhead transmission lines, the manual measurement points located within the wind deflection impact range are determined as the manual measurement points participating in the cross-section optimization, thus obtaining the set of manual measurement optimization points. S502. Based on manually measured and optimized point sets, segmentation of cross-section lines is performed on the digital elevation overhead transmission line cross-section line dataset through segmented correction. S503. Based on the segmented cross-section data and the elevation of the digital elevation model, the cross-section is automatically optimized, as shown below: ； in, For the automatic optimization correction number of section point T, The cumulative distance from measurement point M to section point T is... The cumulative distance from measurement point M to measurement point N. The elevation data for measurement point M is obtained through manual measurement. To interpolate elevation data within the DEM grid for measurement point M, Let N be the cumulative distance from the measurement point N to the cross-section point T. The elevation data for measurement point N is obtained through manual measurement. Interpolate elevation data for the DEM grid at measurement point N; S504. Repeat step S503 to obtain all optimized cross-sectional results for the left, center, and right sides of the line.

6. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for generating and optimizing cross-sectional diagrams of overhead transmission lines based on multi-source data as described in any one of claims 1 to 5.

7. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for generating and optimizing cross-sectional diagrams of overhead transmission lines based on multi-source data as described in any one of claims 1 to 5.

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