A method and system for precise positioning and navigation of power line towers

Abstract

The present invention belongs to the technical field of electric power supply line positioning, and discloses a method and system for accurate positioning and navigation of power line towers. The method sets up RTK equipment at the measurement site, sets the observation time, observation interval and data storage according to the actual situation on site, and selects coordinates and elevations; uses RTK locators for all towers to be measured, obtains accurate tower positioning points of the towers, forms KML files, and provides basic information for drawing power supply line maps; uses Aowei software to draw line segments, and marks the line paths, saves the drawn line segment files into KML files, and marks the tower information; exports and stores the annotated tower information in the form of satellite image files, and forms power supply line picture information. The present invention is not only accurate, but also better solves the problem of tower information being exposed on conventional maps, and the towers can be accurately found on the mobile phones of internal personnel. The problem of rapid navigation of tower locations is solved.

Description

Technical Field

[0001] The invention belongs to the technical field of electric power supply line positioning, and in particular relates to a method and system for accurate positioning and navigation of a power line tower. Background Art

[0002] The safe operation of power supply lines is an important guarantee for improving the reliability and stability of power supply. With the increase of power lines, the workload of line inspection is increasing, which forms a sharp contradiction with the limited number of line inspection personnel. In order to improve the efficiency of line inspection, many personnel have to participate in the line inspection tasks during key seasons and important times. However, as power lines are widely distributed, it is impossible to obtain the accurate line inspection position without the guidance of professionals, and it is impossible to accurately locate under the pole tower, which cannot avoid finding the wrong line.

[0003] Power line tower positioning can better ensure that line inspection, emergency repair support, etc. can quickly locate the location through navigation, thereby improving the efficiency of the location. From the perspective of tower asset information confidentiality, there will be towers where anyone can find important assets through navigation, which poses a major risk. How to find the most reliable navigation method. A method that can achieve conventional precise navigation while preventing outsiders from discovering the location of important assets through navigation.

[0004] Furthermore, there are many high and low voltage line towers, and their distribution is complex. The patrol personnel can accurately determine the geographical location of the towers by relying on their patrol memory, and rush to the scene in time when problems occur. However, for the support department, only when the patrol team arrives and sends a location can the support department find the location of the tower. The efficiency of reaching the scene quickly is very low. Therefore, in order to allow people who are not familiar with the location of the tower to quickly reach the tower location, and to prevent unnecessary users from knowing the location of the important asset tower, it is necessary to propose a fast navigation and positioning method suitable for all internal personnel. Summary of the invention

[0005] In order to overcome the problems existing in the related art, the disclosed embodiments of the present invention provide a method and system for accurate positioning and navigation of power line towers.

[0006] The technical solution is as follows: A method for accurate positioning and navigation of a power line tower comprises:

[0007] S1, set up the RTK equipment at the measurement site, set the observation time, observation interval, data storage, select coordinates and elevation according to the on-site conditions; all measured towers use RTK positioning instruments to obtain the precise tower positioning points of the towers, form KML files, and provide basic information for drawing power supply line maps;

[0008] S2, draw the power supply line diagram, use Aowei software to draw line segments, mark the line path, save the drawn line segment file into a KML file, and mark the tower information;

[0009] S3, exporting and storing the injection tower information in the form of satellite image files to form power supply line image information.

[0010] In step S1, a KML file is formed, including:

[0011] Step 1: Set up the RTK equipment at the tower location to be measured;

[0012] Step 2: The mobile station receives satellite signals through the built-in GPS and transmits data to the base station through the wireless communication network;

[0013] Step three: The base station uses the received satellite signal and the data from the mobile station to perform differential calculations to obtain measurement data including satellite observation data, observation time, and coordinates. The base station analyzes and processes the measurement data to obtain measurement results, connects to the tower to be measured via Bluetooth, and forms a positioning information file.

[0014] In step three, the differential calculation uses pseudorange differential to calculate the true distance from each satellite to the mobile station based on the known coordinates of the mobile station and the coordinates of each satellite; the true distance is compared with the received pseudorange to obtain the pseudorange correction number, which is transmitted to the user receiver.

[0015] The method of using pseudo-range difference to calculate the true distance from each satellite to the mobile station based on the known coordinates of the mobile station and the coordinates of each satellite includes:

[0016] Step A, by extracting the feature map corresponding to two adjacent images of the distance from each satellite to the mobile station, constructing a pseudo-distance set from each satellite to the mobile station, and performing self-bias regression filtering of the pseudo-distance set from each satellite to the mobile station to construct a pseudo-distance network model for different divided areas;

[0017] Step B, using the training set to train the constructed pseudo-distance network model of different partitioned areas; and using The function measures the error between each predicted pseudo-deviation map and the true deviation map until the training model converges and saves the corresponding parameters;

[0018] Step C, input the 4D image into the trained pseudo-range network model of different partition areas, use the saved model parameters as the prediction parameters of the pseudo-range network model of different partition areas, and the deviation map of the fourth channel output of the pseudo-range network of different partition areas This is the deviation map result generated by the prediction.

[0019] In step A, the method for constructing a set of pseudo-ranges from each satellite to a mobile station includes:

[0020] By continuously changing the deviation value d, and at each deviation value d, aligning the feature vector of each pixel in the previous image from each satellite to the mobile station with the feature vector of the corresponding pixel in the next image from each satellite to the mobile station, and calculating the pseudo-distance vectors of different divided areas between the feature vectors, the 4D pseudo-distance set C of each satellite to the mobile station can be constructed. GD ; The size of the pseudo-distance set from each satellite to the mobile station in 4D is N g ×W4×H4×L4; L is the total number of deviations;

[0021] C GD (x,y,d)=GD(v l (x,y),v r (xd,y));

[0022] Among them, C GD (x, y, d) represents the pixel point p on the image before each satellite arrives at the mobile station l (x, y) matches the pseudo distance from each satellite to the mobile station under the deviation value d; GD(v l (x,y),v r (xd,y)) represents the feature vector v l (x,y) and v r Pseudo-distances of different partitioned areas of (xd,y);

[0023] The GD(v l (x,y),v r (xd,y)):

[0024]

[0025] In step B, the use The function measures the error between each predicted pseudo deviation map and the true deviation map:

[0026]

[0027] in, represents the set of pixels that provide the true deviation value, is the deviation graph The bias estimate of pixel p in , is the true deviation value of pixel p, The function definition is as follows:

[0028]

[0029] The weighted sum of all prediction deviation map losses is used as the loss function Loss of the pseudo-distance network in different partitioned areas, that is:

[0030]

[0031] Among them, λ k Representation Deviation Graph The loss weight.

[0032] Furthermore, the differential calculation uses carrier phase differential. The receiver receives the carrier signal sent by the satellite and calculates the distance from the satellite to the receiving station based on the received carrier phase; this distance is compared with the received pseudorange to obtain the carrier phase correction number, which is transmitted to the user receiver.

[0033] In step three, the measurement data is analyzed and processed, including:

[0034] Step i, data preparation: obtain accurate positioning information through differential calculation method;

[0035] Step ii, import data: import the positioning information into the built-in GIS software in the RTK device;

[0036] Step iii, check the data: after importing the data, the RTK self-checks whether the data is correct; the RTK self-check includes checking whether the coordinates of the data are correct and whether the attributes of the data are complete;

[0037] Step IV, creating a layer: In the GIS software, the KML formatted location information file is merged with the Aowei virtual earth layer, and the location information file is added to the layer to obtain location information on the map.

[0038] In step S1, basic information is provided for drawing a power supply line diagram, including:

[0039] On the interactive map, combined with the power supply system diagram, the measured pole tower positioning points are used to distinguish the voltage levels through different line segments, and the different pole tower positioning points are connected point to point to obtain a complete power supply line map within the power supply area.

[0040] In step S2, the power supply circuit diagram is drawn, including:

[0041] S201, using Aowei software to mark the geographical location of the collected positioning points, shrink the geographical location of the collected positioning points, customize the positioning point name, display mode, hide or highlight the specified positioning point;

[0042] S202, connecting various positioning points, measuring the relative horizontal distance of the points by using a satellite image measurement tool, drawing the angle of the points by measuring the azimuth, drawing and marking the line path by using the line segment drawing function in the Aowei software, saving the drawn line segment file into the positioning file, and marking the tower information;

[0043] S203, exporting the satellite image file to a PDF or PNG image format for storage to form route image information.

[0044] In step S201, before using the Aowei software to mark the geographical location of the collected positioning points, the following steps need to be performed:

[0045] Export the project file in the RTK device to a KML file via Bluetooth transmission to a computer device, open the KML file using map software, and select the satellite map for display. The satellite map will automatically jump to the KML file point.

[0046] In step S203, after the line image information is formed, the KML file in the map is used to edit, delete or create new positioning points in the software for later line modification and relocation.

[0047] Another object of the present invention is to provide a power line tower precise positioning and navigation system, the system implements the power line tower precise positioning and navigation method, the system comprises:

[0048] The KML file acquisition module is used to set up the RTK equipment at the measurement site, set the observation time, observation interval, data storage, select coordinates and elevation according to the on-site conditions; all measured towers use RTK locators to obtain the precise tower positioning points of the towers, form KML files, and provide basic information for drawing power supply line maps;

[0049] The power supply line diagram drawing module is used to draw the power supply line diagram, use Aowei software to draw line segments, mark the line path, save the drawn line segment file into the KML file, and mark the tower information;

[0050] The power supply line image information acquisition module is used to export and store the injection tower information in the form of satellite image files to form power supply line image information.

[0051] Combining all the above technical solutions, the beneficial effects of the present invention are as follows: the tower positioning and navigation method of the present invention is not only accurate, but also better solves the problem of tower information being exposed on conventional maps, and the tower can be accurately found on the mobile phones of internal personnel, solving the problem of rapid navigation of tower locations. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings herein are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description, serve to explain the principles of the present disclosure;

[0053] Figure 1 It is a flow chart of a method for accurate positioning and navigation of a power line tower provided by an embodiment of the present invention;

[0054] Figure 2 Schematic diagram of a precise positioning and navigation system for power line towers provided by an embodiment of the present invention;

[0055] In the figure: 1. KML file acquisition module; 2. Power supply line map drawing module; 3. Power supply line image information acquisition module. DETAILED DESCRIPTION

[0056] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific implementation disclosed below.

[0057] Embodiment 1, the method for accurate positioning and navigation of a power line tower provided by the embodiment of the present invention comprises:

[0058] S1, set up the RTK equipment at the measurement site, set the observation time, observation interval, data storage, select coordinates and elevation according to the on-site conditions; all measured towers use RTK positioning instruments to obtain the precise tower positioning points of the towers, form KML files, and provide basic information for drawing power supply line maps;

[0059] S2, draw the power supply line diagram, use Aowei software to draw line segments, mark the line path, save the drawn line segment file into a KML file, and mark the tower information;

[0060] S3, exporting and storing the injection tower information in the form of satellite image files to form power supply line image information.

[0061] like Figure 2 As shown, the present invention also provides a precise positioning navigation system for power line towers, the system comprising:

[0062] KML file acquisition module 1 is used to set up the RTK equipment at the measurement site, set the observation time, observation interval, data storage, select coordinates and elevation according to the on-site conditions; all measured towers use RTK locators to obtain the precise tower positioning points of the towers, form KML files, and provide basic information for drawing power supply line maps;

[0063] The power supply line diagram drawing module 2 is used for drawing the power supply line diagram, using Aowei software to draw line segments, marking the line paths, saving the drawn line segment files into KML files, and marking the tower information;

[0064] The power supply line image information acquisition module 3 is used to export and store the injection tower information in the form of a satellite image file to form power supply line image information.

[0065] Embodiment 2, the present invention is further described below in conjunction with the operating method.

[0066] Specific steps:

[0067] Step 1: Set up the RTK device at the measurement location, assemble the device, and turn on the host and handheld controller.

[0068] (1) Create a new project: In the "Project Star" software, click [Project], [New Project], enter the project name, click [OK], change the "Central Meridian" to 117, and click [OK].

[0069] (2) Point measurement:

[0070] When the letter P in the lower left corner of the screen indicates a fixed solution, click Measure, Point Measurement, Save, enter the point name (tower number), enter the code (tower number), enter the antenna height (1.800), adjust the pole so that the bubble on the level on the pole is within the circle, and click OK.

[0071] (3) Point Stakeout:

[0072] Click to measure, point stakeout, target, measurement point library, click to measure point, stakeout.

[0073] (4) Switch routes to check the locations:

[0074] Click [Project], [Open Project], select the name of the previously measured line, confirm, and perform the above point measurement steps.

[0075] Step 2, drawing of power supply system diagram: All towers to be measured must use RTK positioning instruments to obtain the precise tower positioning points of the towers, forming a KML file to provide basic information for drawing power supply line diagrams. On the interactive map, combined with the power supply system diagram, using the measured tower positioning points, different line segments to distinguish voltage levels, and connecting different tower positioning points point to point, finally a complete power supply line diagram in the power supply area is obtained.

[0076] Exemplarily, the process of forming a KML file (location information file) includes:

[0077] Step 1: Set up the RTK equipment at the tower location to be measured, set the observation time, observation interval and data storage according to the actual situation on site, and select the coordinates and elevation to ensure the accuracy and consistency of the measurement results;

[0078] Step 2: The mobile station receives satellite signals through the built-in GPS and transmits data to the base station through the wireless communication network;

[0079] Step three: The base station uses the received satellite signals and the data from the mobile station to perform differential calculations to obtain high-precision measurement data, including satellite observation data, observation time, coordinates, etc. The measurement data is analyzed and processed to obtain measurement results, and a positioning information file is formed by connecting to the tower to be measured via Bluetooth.

[0080] Exemplarily, generally, the differential calculation mainly includes the following steps:

[0081] Step 1: Set up a base station: Set up a base station at a location with a known precise position and install a GPS receiver on the base station.

[0082] Step 2, satellite observation: After observing 4 satellites near the base mobile station, perform three-dimensional positioning and calculate the measurement coordinates of the base station.

[0083] Step 3, compare measured coordinates: compare the measured coordinates of the reference mobile station with the known coordinates to find the error.

[0084] Step 4, sending error information: sending the error value to the differential GPS receiver within a range of about 100 kilometers.

[0085] Step 5, correcting the measurement data: After the receivers receive the error values, they can correct their respective measurement data.

[0086] On this basis, the present invention has made technical improvements through the following methods:

[0087] Using pseudorange differential: In pseudorange differential, the true distance from each satellite to the mobile station is first calculated based on the known coordinates of the mobile station and the coordinates of each satellite, and then this true distance is compared with the received pseudorange to obtain the pseudorange correction number, and finally this correction number is transmitted to the user receiver to improve the positioning accuracy.

[0088] The method of using pseudo-range difference to calculate the true distance from each satellite to the mobile station based on the known coordinates of the mobile station and the coordinates of each satellite includes:

[0089] Step A, by extracting the feature map corresponding to two adjacent images of the distance from each satellite to the mobile station, constructing a pseudo-distance set from each satellite to the mobile station, and performing self-bias regression filtering of the pseudo-distance set from each satellite to the mobile station to construct a pseudo-distance network model for different divided areas;

[0090] Step B, using the training set to train the constructed pseudo-distance network model of different partitioned areas; and using The function measures the error between each predicted pseudo-deviation map and the true deviation map until the training model converges and saves the corresponding parameters;

[0091] Step C, input the 4D image into the trained pseudo-range network model of different partition areas, use the saved model parameters as the prediction parameters of the pseudo-range network model of different partition areas, and the deviation map of the fourth channel output of the pseudo-range network of different partition areas This is the deviation map result generated by the prediction.

[0092] In step A, the method for constructing a set of pseudo-ranges from each satellite to a mobile station includes:

[0093] By continuously changing the deviation value d, and at each deviation value d, aligning the feature vector of each pixel in the previous image from each satellite to the mobile station with the feature vector of the corresponding pixel in the next image from each satellite to the mobile station, and calculating the pseudo-distance vectors of different divided areas between the feature vectors, the 4D pseudo-distance set C of each satellite to the mobile station can be constructed. GD ; The size of the pseudo-distance set from each satellite to the mobile station in 4D is N g ×W4×H4×L4; L is the total number of deviations;

[0094] C GD (x,y,d)=GD(v l (x,y),v r (xd,y));

[0095] Among them, C GD (x, y, d) represents the pixel point p on the image before each satellite arrives at the mobile station l (x, y) matches the pseudo distance from each satellite to the mobile station under the deviation value d; GD(v l (x,y),v r (xd,y)) represents the feature vector v l (x,y) and v r Pseudo-distances of different partitioned areas of (xd,y);

[0096] The GD(v l (x,y),v r (xd,y)):

[0097]

[0098] The pseudo-range network models of different division areas include:

[0099] The adjacent image feature extraction module is used to extract the feature map corresponding to two adjacent images of the distance from each satellite to the mobile station;

[0100] A module for constructing a set of pseudo-ranges from each satellite to a mobile station based on pseudo-ranges in different divided areas, for constructing a set of pseudo-ranges from each satellite to a mobile station based on the extracted feature graph;

[0101] A pseudo-range set filtering module from each satellite to the mobile station is used to filter the generated pseudo-range set from each satellite to the mobile station and generate a 4D pseudo-range set C from each satellite to the mobile station;

[0102] The deviation regression module is used to implement softmax mapping on each pixel p in the generated pseudo-distance set C from each satellite to the mobile station at the deviation d, and obtain the probability δ(p, d) that its deviation is d, and to calculate the final deviation of the element p through the soft argmin function.

[0103] The adjacent image feature extraction module includes: a convolution layer, a normalization processing and ReLU activation layer, a residual block and a post-processing convolution layer;

[0104] The convolution layer has a size of 3×3 and cascades three filters to preprocess the input image; wherein the step size of the first convolution layer is 2, which is used to change the size of the output feature image to 1 / 2 of the input image;

[0105] The normalization and ReLU activation layers are located after each convolutional layer;

[0106] The residual blocks are cascaded into three different types to process the preprocessed feature image; wherein the total number of the residual blocks is 25, each residual block contains 2 convolutional layers, and the step size of the first convolutional layer of the fourth residual block is set to 2, which is used to change the size of the output feature image to 1 / 4 of the input image; at the same time, the residual block is used to splice the generated feature map in the channel direction to generate a feature map with 384 channels;

[0107] The post-processing convolutional layer has a size of 3×3, and is used to post-process the fused feature map by cascading two filters to generate a feature map with 128 channels, and concatenate the input fused feature map with the output feature map to obtain a final feature map with 512 channels;

[0108] The pseudo-range set filtering module from each satellite to the mobile station includes:

[0109] A 4D convolutional residual block is used to calculate the pseudo-range set C of each satellite to the mobile station in 4D GD Perform pre-filtering processing;

[0110] Three cascaded 4D skip networks are used to filter the preprocessing results and add the previous filter result to the subsequent filter result through skip connections;

[0111] The output module is used to output the final filtering result and three intermediate filtering results. It is also used to perform post-processing using two cascaded 4D convolutional layers, change the number of channels to 1, generate a 4D pseudo-range set C of each satellite to the mobile station, and perform bilinear interpolation upsampling on the generated pseudo-range set of each satellite to the mobile station, and convert the size to W×H×L;

[0112] Each of the skip networks adopts the same 4D encoder-decoder structure, that is, firstly, a 4D convolution and down-sampling are performed on each satellite-to-mobile station pseudo-range set from top to bottom, and then a 4D deconvolution and up-sampling are performed on the encoder result from bottom to top; the single 4D skip network adds the feature map in the encoder to the corresponding feature map in the decoder through a skip connection, so as to fuse the feature map information in the encoder and the decoder;

[0113] The deviation regression module includes:

[0114] For each pixel p in the generated pseudo-distance set C from each satellite to the mobile station, the softmax mapping is performed on the pseudo-distance value C(p, d) from each satellite to the mobile station with a deviation of d to obtain the probability δ(p, d) of its deviation being d, that is:

[0115]

[0116] The final deviation of pixel p is calculated by the soft argmin function Right now:

[0117]

[0118] In step B, the use The function measures the error between each predicted pseudo deviation map and the true deviation map:

[0119]

[0120] in, represents the set of pixels that provide the true deviation value, is the deviation graph The bias estimate of pixel p in , is the true deviation value of pixel p, The function definition is as follows:

[0121]

[0122] The weighted sum of all prediction deviation map losses is used as the loss function Loss of the pseudo-distance network in different partitioned areas, that is:

[0123]

[0124] Among them, λ k Representation Deviation Graph The loss weight.

[0125] It can be understood that the present invention performs end-to-end training and learning of pseudo-range networks of different divided areas on a certain scene data set, and can directly use the trained network model to accurately predict the deviation map of the 4D image in the scene; the overall effect is that the present invention has strong robustness and high deviation calculation accuracy, and can effectively overcome many interference factors such as motion blur in the scene and complex and single scene occlusion relationship.

[0126] The present invention may use carrier phase differential: This is a more accurate differential method, mainly used to reduce atmospheric delay and other non-geometric errors. In carrier phase differential, the receiver receives the carrier signal sent by the satellite and calculates the distance from the satellite to the receiving station based on the received carrier phase. Then, this distance is compared with the received pseudorange to obtain the carrier phase correction number, and finally this correction number is transmitted to the user receiver to improve the positioning accuracy.

[0127] In another exemplary embodiment, in step three, the measurement data is analyzed and processed to obtain a measurement result, that is, the positioning information obtained by satellite differential calculation is processed as follows:

[0128] Step i, data preparation: obtain accurate positioning information through differential calculation method;

[0129] Step ii, import data: import the positioning information into the built-in GIS software in the RTK device;

[0130] Step iii, check the data: after importing the data, the RTK self-checks whether the data is correct; the RTK self-check includes checking whether the coordinates of the data are correct and whether the attributes of the data are complete;

[0131] Step IV, creating a layer: In the GIS software, the KML formatted location information file is merged with the Aowei virtual earth layer, and the location information file is added to the layer to obtain location information on the map.

[0132] In step 3, forming a positioning information file by connecting to the tower to be measured via Bluetooth involves the following steps:

[0133] Data collection: First, you need to collect some data about your geographic location. This data can be obtained in various ways, for example, you can use a GPS device to collect your location information.

[0134] Data preprocessing: After collecting the data, perform some preprocessing on it to delete duplicate location information or correct some erroneous location information.

[0135] Data writing: Write the data into the KML format positioning information file to eventually form a positioning file.

[0136] Exemplarily, the measurement data may be analyzed and processed using Engineering Star.

[0137] Step 3, power supply line diagram drawing method: First, export the project file in the RTK device to a KML file on the computer device via Bluetooth transmission, use the map software to open the KML project file, and select the appropriate satellite map for display. The satellite map is a built-in file of the software. After opening, the satellite map will automatically jump to the location of the positioning file. Use the Aowei software to mark the geographical location of the collected positioning points. You can customize the positioning point name, display mode, hide or highlight the specified positioning point;

[0138] Then connect each positioning point, use the satellite image measurement tool to map out the relative horizontal distance of the point, use the azimuth measurement to draw the point angle, use the line drawing function in the Aowei software to draw and mark the line path, save the drawn line segment file to the positioning file, and mark the tower information, such as height, tower model, conductor model, etc., and finally export the satellite image file to PDF or PNG image format for storage to form line image information.

[0139] If changes are needed later, you can directly edit, delete or create new positioning points in the software through the KML file in the map, which can be used for later line modification, relocation, etc., reducing the on-site measurement work of engineering personnel, while improving the overall line planning capabilities, and can comprehensively and specifically design line paths.

[0140] For example, the marked points are all digital, such as No. 5, No. 6, etc., without specific markings such as No. 5 pole of line Ⅰ and Ⅱ in a certain area, and No. 6 pole of line Ⅰ and Ⅱ in a certain area, so it is difficult for non-professionals to identify the pole tower.

[0141] Embodiment 3, illustratively, an operation process of a method for accurate positioning and navigation of a power line tower provided by an embodiment of the present invention includes:

[0142] Software support: First download the "Interactive Map" application APP on your mobile phone, and then download "Baidu" or "AutoNavi" map for use.

[0143] Navigation usage process: open the map, open the KML measurement file provided by the engineering and technical personnel with the interactive map, and the precise line tower location will be displayed on the map. Find the tower you want to go to, click the mark symbol, and use the obtained map route for navigation to accurately reach the tower location.

[0144] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0145] Since the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present invention, their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0146] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated in one processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment.

[0147] An embodiment of the present invention further provides a computer device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor implements the steps in any of the above-mentioned method embodiments when executing the computer program.

[0148] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0149] An embodiment of the present invention further provides an information data processing terminal, which, when executed on an electronic device, provides a user input interface to implement the steps in the above method embodiments. The information data processing terminal is not limited to mobile phones, computers, and switches.

[0150] An embodiment of the present invention further provides a server, which is used to provide a user input interface to implement the steps in the above method embodiments when executed on an electronic device.

[0151] An embodiment of the present invention provides a computer program product. When the computer program product runs on an electronic device, the electronic device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0152] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the camera / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk.

[0153] To further illustrate the effects of the embodiments of the present invention, the following experiment was conducted: An example of the transformation of the 110kV line in the intranet of a mining group. The transformation of the intranet line of a mining group is a huge project, involving 15 kilometers of existing lines and more than 80 pole towers. If each pole tower uses traditional information storage, it is impossible to intuitively and vividly describe the state of the pole tower, the path and the surrounding environment. Although the traditional line cross-section diagram can clearly describe the path direction, it is not conducive to the explanation of the solution path and cannot visually and intuitively display the engineering design. The use of positioning systems and satellite maps can intuitively express and accurately display the engineering solution design. The positioning distance, angle and other information can be viewed through the map, which greatly reduces the repeated on-site surveys, confirmations and path modifications, and provides strong data support for the project.

[0154] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principles of the present invention should be covered by the protection scope of the present invention.

Claims

1. A method for accurate positioning and navigation of power line towers, characterized in that: The method includes: S1, set up the RTK equipment at the measurement site, set the observation time, observation interval, data storage, select coordinates and elevation according to the on-site conditions; all measured towers use RTK positioning instruments to obtain the precise tower positioning points of the towers, form KML files, and provide basic information for drawing power supply line maps; S2, draw the power supply line diagram, use Aowei software to draw line segments, mark the line path, save the drawn line segment file into a KML file, and mark the tower information; S3, exporting and storing the injection tower information in the form of a satellite image file to form power supply line image information; In step S1, a KML file is formed, including: Step 1: Set up the RTK equipment at the tower location to be measured; Step 2: The mobile station receives satellite signals through the built-in GPS and transmits data to the base station through the wireless communication network; Step 3: The base station uses the received satellite signal and the data of the mobile station to perform differential calculation to obtain measurement data including satellite observation data, observation time, and coordinates. The base station analyzes and processes the measurement data to obtain measurement results, connects to the tower to be measured via Bluetooth, and forms a positioning information file. In step 3, the differential calculation uses pseudo-range differential to calculate the true distance of each satellite to the mobile station based on the known coordinates of the mobile station and the coordinates of each satellite; the true distance is compared with the received pseudo-range to obtain the pseudo-range correction number, which is transmitted to the user receiver; The method of using pseudo-range difference to calculate the true distance from each satellite to the mobile station based on the known coordinates of the mobile station and the coordinates of each satellite includes: Step A, extracting feature maps corresponding to two adjacent images of the distance from each satellite to the mobile station, constructing a pseudo-distance set from each satellite to the mobile station, and performing filtering deviation regression on the pseudo-distance set from each satellite to the mobile station to construct pseudo-distance network models for different divided areas; Step B, using the training set to train the constructed pseudo-distance network model of different partitioned areas; and using The function measures the error between each predicted pseudo-deviation map and the true deviation map until the training model converges and saves the corresponding parameters; The function definition is as follows: ； Step C, input the 4D image into the trained pseudo-range network model of different partition areas, use the saved model parameters as the prediction parameters of the pseudo-range network model of different partition areas, and the deviation map of the fourth channel output of the pseudo-range network of different partition areas This is the deviation map result generated by the prediction.

2. The method for accurate positioning and navigation of a power line tower according to claim 1, characterized in that In step A, the method for constructing a set of pseudo-ranges from each satellite to a mobile station includes: By continuously changing the deviation value d, and at each deviation value d, aligning the feature vector of each pixel in the previous image from each satellite to the mobile station with the feature vector of the corresponding pixel in the next image from each satellite to the mobile station, and calculating the pseudo-distance vectors of different divided areas between the feature vectors, the 4D pseudo-distance set of each satellite to the mobile station can be constructed. ; The size of the pseudo-distance set from each satellite to the mobile station in 4D is ; is the total number of deviations; ； in, Indicates the pixel point on the image before each satellite arrives at the mobile station In the deviation value Match the pseudo distance from each satellite to the mobile station under ; Represents the feature vector and Pseudo distances of different divided areas; Said : ； In step B, the use The function measures the error between each predicted pseudo deviation map and the true deviation map: ； in, represents the set of pixels that provide the true deviation value, is the deviation graph Medium Pixels Bias estimate, k=1,2,3,4, It's pixels The true deviation value of The weighted sum of all prediction deviation map losses is used as the loss function of the pseudo-distance network in different partitioned areas Loss ,Right now: ； in, Representation Deviation Graph The loss weight.

3. The method for accurate positioning and navigation of power line towers according to claim 1, characterized in that: In step S1, basic information is provided for drawing a power supply line diagram, including: On the interactive map, combined with the power supply system diagram, the measured pole tower positioning points are used to distinguish the voltage levels through different line segments, and the different pole tower positioning points are connected point to point to obtain a complete power supply line map within the power supply area.

4. The method for accurate positioning and navigation of power line towers according to claim 1, characterized in that: In step S2, the power supply circuit diagram is drawn, including: S201, using Aowei software to mark the geographical location of the collected positioning points, collect the geographical location of the positioning points, customize the positioning point name, display mode, hide or highlight the specified positioning point; S202, connecting various positioning points, measuring the relative horizontal distance of the points by using a satellite image measurement tool, drawing the angle of the points by measuring the azimuth, drawing and marking the line path by using the line segment drawing function in the Aowei software, saving the drawn line segment file into the positioning file, and marking the tower information; S203, exporting the satellite image file to a PDF or PNG image format for storage to form route image information.

5. The method for accurate positioning and navigation of power line towers according to claim 4, characterized in that: In step S201, before using the Aowei software to mark the geographical location of the collected positioning points, the following steps need to be performed: Export the project file in the RTK device to a KML file via Bluetooth transmission to a computer device, open the KML file using map software, and select the satellite map for display. The satellite map will automatically jump to the KML file point.

6. The method for accurate positioning and navigation of power line towers according to claim 4, characterized in that: In step S203, after the line image information is formed, the KML file in the map is used to edit, delete or create new positioning points in the software for later line modification and relocation.

7. A precise positioning and navigation system for power line towers, characterized in that: The system implements the method for accurate positioning and navigation of a power line tower as claimed in any one of claims 1 to 6, and the system comprises: The KML file acquisition module (1) is used to set up the RTK equipment at the measurement site, set the observation time, observation interval, data storage, and select coordinates and elevation according to the on-site conditions; all measured towers use RTK positioning instruments to obtain the precise tower positioning points of the towers, form a KML file, and provide basic information for drawing the power supply line map; A power supply line diagram drawing module (2) is used for drawing a power supply line diagram, using Aowei software to draw line segments, marking line paths, saving the drawn line segment files into a KML file, and marking tower information; The power supply line image information acquisition module (3) is used to export and store the injection tower information in the form of a satellite image file to form power supply line image information.

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