Method, device and equipment for processing digital twinborn model of cable facility and medium

Abstract

The invention relates to the field of power grids, in particular to a processing method and device for a digital twinborn model of a cable facility, and the processing method comprises the steps: obtaining the satellite original observation data of the cable facility, and obtaining the initial coordinates of the cable facility through differential GPS calculation; transmitting the initial coordinates to a satellite base station, and combining coordinate information recorded by the satellite base station with the received information of the initial coordinates to obtain coordinate correction data; according to the coordinate correction data fed back by the satellite base station, correcting the initial coordinates by adopting a least square method to obtain coordinate values higher than a precision threshold value; according to the coordinate values higher than the precision threshold value, a preset database is inquired, and a digital twin model of the range threshold value of the position where the cable facility is located is obtained.

Description

Technical Field

[0001] The present invention relates to the field of power grids, and in particular to a method, device, electronic equipment and storage medium for processing a digital twin model of a cable facility. Background Art

[0002] With the acceleration of urbanization, the construction and maintenance of cable facilities are becoming more and more important. Traditional cable facility survey, construction and monitoring methods have problems such as low efficiency and poor accuracy. As an emerging technology, digital twin technology can simulate and predict cable facilities and improve the efficiency and accuracy of construction and maintenance.

[0003] In the prior art, it has become a common method to use the computer's GPS antenna to obtain the original satellite observation data for differential calculation to obtain the initial coordinates with errors. However, there are still some problems in this process. First, because the satellite signal may be affected by factors such as atmospheric interference and multipath effects, the accuracy of the observation data is affected to a certain extent. The traditional coordinate correction method cannot provide sufficiently accurate coordinate correction data. In the process of transmitting the initial coordinates to the satellite base station, data loss or other factors may occur, resulting in the accuracy of the coordinate correction data being limited. Since the coordinate correction data is not accurate enough, it is impossible to obtain an accurate digital twin model. Summary of the invention

[0004] The technical problem to be solved by the present invention is: how to generate a more accurate digital twin model of cable facilities.

[0005] In order to solve the above technical problems, the present invention provides a method for processing a digital twin model of a cable facility and a digital twin model for a cable facility. The method comprises:

[0006] Obtaining original satellite observation data of the cable facility, and obtaining initial coordinates of the cable facility through differential GPS solution;

[0007] Transmitting the initial coordinates to a satellite reference station, combining the coordinate information recorded by the satellite reference station with the received information of the initial coordinates to obtain coordinate correction data;

[0008] According to the coordinate correction data fed back by the satellite reference station, the initial coordinates are corrected by using the least square method to obtain a coordinate value higher than an accuracy threshold;

[0009] According to the coordinate value that is higher than the accuracy threshold, a preset database is queried to obtain a digital twin model of the range threshold of the location of the cable facility.

[0010] Furthermore, the processing method of the digital twin model also includes:

[0011] Determining the direction of the digital twin model according to the data of the digital twin model and the data from the orientation sensor;

[0012] According to the direction data of the digital twin model, the distance deviation data between the three-dimensional point cloud data of the actual scene and the digital twin model is obtained by scanning with a laser rangefinder;

[0013] According to the three-dimensional point cloud data of the actual scene and the distance deviation data, the coordinates and structure of the digital twin model are adjusted to complete the optimization of the digital twin model.

[0014] Furthermore, the processing method also includes:

[0015] Decrypting the acquired digital twin model data;

[0016] According to the data of the orientation sensor, the digital twin model data is preprocessed by Kalman filtering to remove abnormal noise points.

[0017] Furthermore, the processing method also includes:

[0018] Obtaining data on the direction of the digital twin model;

[0019] The laser transmitter performs an all-round scan along a set route to obtain three-dimensional point cloud data of the actual scene;

[0020] Performing filtering and registration preprocessing on the three-dimensional point cloud data;

[0021] Importing the processed three-dimensional point cloud data into Autodesk 3ds Max software, and using ICP algorithm to match the point cloud data with the model;

[0022] Calculating the distance between each sampling point in the point cloud data and the surface of the digital twin model to obtain a distance deviation matrix between the point cloud data and the digital twin model;

[0023] The mean, median and standard deviation of the point cloud data sample distance deviation are calculated to determine the degree of fit between the model and the actual scene.

[0024] Furthermore, the coordinates and structure of the digital twin model are adjusted according to the distance deviation data to optimize the digital twin model, including:

[0025] Loading a three-dimensional modeling engine, and importing the calculated distance deviation matrix between the three-dimensional point cloud data and the digital twin model;

[0026] A polynomial regression model is established, with the sampling points of the three-dimensional point cloud data as independent variables and the distance deviation value as dependent variable, and a statistical mapping relationship between the model coordinate deviation and the scene position is obtained through training to obtain a regression formula;

[0027] Applying the regression formula to each vertex coordinate of the digital twin model, and calculating its theoretical coordinate offset according to the spatial position parameters of the vertex of the digital twin model;

[0028] The coordinate offset is fed back to adjust the vertex coordinates of the digital twin model; the distance deviation between the point cloud data and the digital twin model is used as an error back-propagation signal, and the structure of the digital twin model is automatically adjusted by analyzing the difference between the point cloud data and the digital twin model.

[0029] Furthermore, the processing method also includes:

[0030] Receiving navigation signals from the satellite and acquiring raw observation data;

[0031] Preprocessing the original observation data to remove erroneous observations and obtain the original ranging observation value with a resolution of cm level;

[0032] The original distance measurement observation value is subjected to the differential GPS solution;

[0033] By using the smoothing and discretization operations in the Kalman filter method, the precise coordinates of the reference station and the double-difference observations are introduced into the observation equation to construct the measurement equation group.

[0034] The three-dimensional coordinates of the cable facility are solved by a least squares iterative algorithm to obtain initial coordinates with an output resolution of cm level as the original observation data.

[0035] Furthermore, the processing method also includes:

[0036] The initial coordinate data is encrypted and compressed using the AES encryption algorithm;

[0037] The wireless communication module forms a point-to-point secure connection with the satellite reference station through WIFI and Bluetooth, and sends compressed and encrypted data of the initial coordinates;

[0038] The satellite reference station decompresses and decrypts the received data of the initial coordinates to verify the integrity of the data of the initial coordinates;

[0039] Combine the station coordinate information recorded by the base station with the received initial coordinates to construct a double-difference observation equation group;

[0040] Various error correction models are introduced to perform the differential GPS solution; through least squares recursion, vector correction information of the position of the cable facility relative to the satellite reference station is obtained;

[0041] Optimize the correction information, add IMU trajectory information for multi-sensor fusion optimization, and obtain coordinate correction data.

[0042] According to another aspect of the present invention, a proofreading device for a digital twin model of a cable facility is provided, characterized in that it includes: an acquisition and processing module; used for acquiring satellite original observation data of the cable facility and solving the satellite original observation data of the cable facility through differential GPS to obtain initial coordinates with errors; a correction module; transmitting the initial coordinates to a satellite base station, combining the coordinate information recorded by the satellite base station with the received information of the initial coordinates to obtain coordinate correction data; a proofreading module; used for proofreading the initial coordinates by using the least squares method according to the coordinate correction data fed back by the satellite base station to obtain coordinate values ​​higher than the accuracy threshold; a model generation module; used for querying a preset database according to the coordinate values ​​higher than the accuracy threshold, and generating a digital twin model of the location range threshold.

[0043] According to another aspect of the present invention, there is provided an electronic device, comprising: at least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the processing method of the digital twin model of any cable facility in the embodiments of the present invention.

[0044] According to another aspect of the present invention, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable a computer to execute a processing method for a digital twin model of any cable facility in an embodiment of the present invention.

[0045] Compared with the prior art, the processing method of the digital twin model of a cable facility in the embodiment of the present invention has the following beneficial effects:

[0046] The embodiment of the present invention uploads the initial coordinates to a satellite base station to obtain coordinate correction data, and uses the least squares method to calibrate the initial coordinates through the coordinate correction data, thereby obtaining high-precision coordinate values, solving the problem of inaccurate initial coordinates obtained in traditional methods, and generating a more accurate digital twin model through high-precision coordinate values, thereby improving the accuracy of the digital twin model. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a flow chart of a method for processing a digital twin model of a cable facility provided by an embodiment of the present invention;

[0048] Figure 2 is another flow chart of a method for processing a digital twin model of a cable facility provided by an embodiment of the present invention;

[0049] Figure 3 It is a flowchart of a specific implementation of step S50 in the method for processing the digital twin model of the cable facility provided in an embodiment of the present invention;

[0050] Figure 4 It is a flowchart of a specific implementation of step S60 in the method for processing the digital twin model of the cable facility provided in an embodiment of the present invention;

[0051] Figure 5 It is a flowchart of a specific implementation of step S70 in the method for processing the digital twin model of the cable facility provided in an embodiment of the present invention;

[0052] Figure 6 It is a flowchart of a specific implementation of step S10 in the method for processing the digital twin model of the cable facility provided in an embodiment of the present invention;

[0053] Figure 7 It is a flowchart of a specific implementation of step S20 in the method for processing the digital twin model of the cable facility provided in an embodiment of the present invention;

[0054] Figure 8 is a schematic diagram of a calibration device for a digital twin model of a cable facility provided in an embodiment of the present invention;

[0055] Fig. 9 is a block diagram of an electronic device for implementing an embodiment of the present invention.

[0056] In the figure, 11, acquisition and processing module; 12, correction module; 13, proofreading module; 14, model generation module; 600, electronic device; 601, computing unit; 602, ROM; 603, RAM; 604, bus; 605, I / O interface; 606, input unit; 607, output unit; 608, storage unit; 609, communication unit. DETAILED DESCRIPTION

[0057] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0058] In an optional embodiment of the present invention, Figure 1 It is a flowchart of a method for processing a digital twin model of a cable facility according to an embodiment of the present invention.

[0059] like Figure 1 As shown, an embodiment of the present invention provides a method for processing a digital twin model of a cable facility, and the steps and specific process of the method are as follows:

[0060] S10, acquiring original satellite observation data of the cable facility, and obtaining initial coordinates of the cable facility through differential GPS solution;

[0061] Among them, Differential Global Positioning System (DGPS) is a technology that eliminates GPS positioning errors by comparing the difference between satellite signals received by a receiver and signals from a reference station with a known accurate position.

[0062] The specific process of this step is: place the GPS receiver at an appropriate location near the cable facility; start the GPS receiver and record the original satellite observation data output by the receiver; these data include the location information of the satellite, the signal strength received by the receiver, etc.; transfer the recorded original satellite observation data to a computer or other processing device. Perform differential GPS solution. Differential GPS solution is a method of eliminating errors by using the differences between two or more GPS receivers. In this case, a base station with a known accurate location and a receiver located near the cable facility can be used. Compare the location information of the base station with the location information of the receiver near the cable facility, and calculate the initial coordinates of the cable facility.

[0063] S20, transmitting the initial coordinates to the satellite base station, combining the coordinate information recorded by the satellite base station with the received initial coordinate information to obtain coordinate correction data; the specific process of this step is: establishing a private network transmission link between the cable facility and the base station through the wireless communication module; using the AES encryption algorithm to encrypt and compress the initial coordinate data; the wireless communication module forms a point-to-point secure connection with the base station through WIFI and Bluetooth, and sends the compressed and encrypted initial coordinate data; the base station decompresses and decrypts according to the received initial coordinate data, and verifies the integrity of the initial coordinate data; combining the station coordinate information recorded by the satellite base station with the received initial coordinates to construct a double-difference observation equation group; introducing various error correction models to obtain the vector correction information of the cable facility position relative to the base station; adding IMU trajectory information to perform multi-sensor fusion optimization to obtain coordinate correction data.

[0064] S30, calibrating the initial coordinates using a least square method according to the coordinate correction data fed back by the satellite reference station to obtain a coordinate value higher than an accuracy threshold;

[0065] S40, according to the coordinate value higher than the accuracy threshold, query the preset database to obtain the digital twin model of the range threshold of the location of the cable facility. The specific process of this step is: the computer sends the coordinate value higher than the accuracy threshold to the model database server through a private network security connection; the model database server is a server that stores and manages digital twin model data; the model database server verifies the coordinate information according to the received request, and locates the area where the coordinate is located in the vt-Tree three-dimensional index structure of the planning area; the model database server uses a multi-threaded parallel retrieval algorithm and a KNN nearest neighbor search algorithm in the index area to search for three-dimensional model samples within the coordinate range threshold; the three-dimensional model samples are compressed and encoded for storage; the model database server selects the digital twin models of the target area and buildings that match the coordinate value higher than the accuracy threshold according to the three-dimensional model samples; the model database server converts and optimizes the model format according to the platform requirements and compresses the digital twin model data; the compressed digital twin model data is encrypted by AES and sent to the computer through a private network security channel.

[0066] The embodiment of the present invention uploads the initial coordinates to a satellite base station to obtain coordinate correction data, and uses the least squares method to calibrate the initial coordinates through the coordinate correction data, thereby obtaining high-precision coordinate values, solving the problem of inaccurate initial coordinates obtained in traditional methods, and generating a more accurate digital twin model through high-precision coordinate values, thereby improving the accuracy of the digital twin model.

[0067] like Figure 2 As shown, in an optional embodiment of the present invention, the processing method of the digital twin model further includes:

[0068] S50, determining the direction of the digital twin model according to the data of the digital twin model and the data of the orientation sensor;

[0069] S60, acquiring distance deviation data between three-dimensional point cloud data of the actual scene and the digital twin model through scanning with a laser rangefinder according to the direction data of the digital twin model;

[0070] S70, adjusting the coordinates and structure of the digital twin model according to the three-dimensional point cloud data of the actual scene and the distance deviation data, to complete the optimization of the digital twin model.

[0071] Specifically, S50, determines the direction of the digital twin model according to the data of the digital twin model and the data through the azimuth sensor; the specific process of this step is: decrypting the acquired digital twin model data; performing Kalman filter preprocessing on the digital twin model data according to the data of the azimuth sensor to remove abnormal noise points; obtaining the attitude angle information of the azimuth sensor through the AHRS algorithm; combining the attitude angle data with the three-dimensional scene modeling software to determine the spatial orientation of the digital twin model; taking the position of the azimuth sensor itself as a reference point, using the azimuth angle data to determine the direction of the center axis of the scene; calculating the pitch angle to determine the overhead angle of the digital twin three-dimensional model.

[0072] In the embodiments of the present invention, these methods can further improve the accuracy and credibility of the digital twin model. By determining the direction of the digital twin model and obtaining the distance deviation data between the actual scene and the digital twin model, the embodiments of the present invention can more accurately understand the difference between the digital twin model and the actual scene, thereby achieving adjustment and optimization of the coordinates and structure of the digital twin model, and providing a more accurate and refined digital twin model.

[0073] like Figure 3 As shown, in an optional embodiment of the present invention, the processing method of the digital twin model further includes:

[0074] S51, decrypting the acquired digital twin model data;

[0075] S52, performing Kalman filter preprocessing on the digital twin model data according to the orientation sensor to remove abnormal noise points;

[0076] In an embodiment of the present invention, the angular direction of the digital twin model can be determined by using an azimuth sensor and the attitude angle information measured by the azimuth sensor, and the angular direction of the digital twin model is kept consistent with the direction of the azimuth sensor. The pitch angle of the azimuth sensor describes the degree of inclination of the digital twin three-dimensional model, and the direction of the digital twin model is determined. The digital twin three-dimensional model obtains correct spatial positioning and display effects, thereby improving the user's viewing experience.

[0077] like Figure 4 As shown, in an optional embodiment of the present invention, the processing method of the digital twin model further includes:

[0078] S61, obtaining data of the direction of the digital twin model;

[0079] S62, performing omnidirectional scanning along a set route by the laser transmitter to obtain three-dimensional point cloud data of the actual scene;

[0080] S63, performing filtering and registration preprocessing on the three-dimensional point cloud data;

[0081] S64, importing the processed three-dimensional point cloud data into Autodesk3dsMax software, and using ICP algorithm to match the point cloud data with the model;

[0082] S65, calculating the distance between each sampling point in the point cloud data and the surface of the digital twin model, and obtaining a distance deviation matrix between the point cloud data and the digital twin model;

[0083] S66, calculating the mean, median and standard deviation of the distance deviation of the point cloud data samples to determine the degree of fit between the model and the actual scene.

[0084] In the embodiment of the present invention, through the above steps, a laser rangefinder can be used to scan and obtain the distance deviation between the actual scene and the digital twin model, and the degree of fit between the digital twin model and the actual scene can be evaluated through statistical analysis. The above steps are helpful to verify and improve the accuracy and authenticity of the digital twin model.

[0085] like Figure 5 As shown, in an optional embodiment of the present invention, the method for determining the direction of the digital twin model further includes:

[0086] S71, loading a three-dimensional modeling engine, and importing a distance deviation matrix between the calculated point cloud data and the digital twin model;

[0087] S72, establishing a polynomial regression model, taking the sampling points of the point cloud data as independent variables and the distance deviation value as dependent variables, training to obtain a statistical mapping relationship between the model coordinate deviation and the scene position, and obtaining a regression formula;

[0088] S73, applying the regression formula to the coordinates of each vertex of the digital twin model, and calculating its theoretical coordinate offset according to the spatial position parameters of the vertex of the digital twin model;

[0089] S74, using the coordinate offset as feedback to adjust the vertex coordinates of the digital twin model; using the distance deviation between the point cloud data and the digital twin model as an error back-propagation signal, and automatically adjusting the structure of the digital twin model by analyzing the difference between the point cloud data and the digital twin model.

[0090] In an embodiment of the present invention, by applying a regression formula to the vertex coordinates of the digital twin model and calculating the coordinate offset according to the spatial position parameters, real-time feedback adjustment of the digital twin model can be achieved, so that the digital twin model can more accurately reflect changes in the real scene. In an embodiment of the present invention, the distance deviation between the point cloud data and the digital twin model is used as an error back propagation signal to analyze the difference between the point cloud data and the digital twin model, and the structure of the digital twin model can be automatically adjusted to better adapt to the shape and characteristics of the real scene. In an embodiment of the present invention, the above steps improve the accuracy, adaptability and automation of the digital twin model, and provide beneficial effects for the optimization and application of the digital twin model.

[0091] like Figure 6 As shown, in an optional embodiment of the present invention, the processing method further includes:

[0092] S11, receiving a navigation signal from the satellite to obtain original observation data;

[0093] S12, preprocessing the original observation data to remove erroneous observations, and obtaining the original ranging observation value with a resolution of cm level;

[0094] S13, performing differential GPS solution on the original ranging observation value;

[0095] S14, using the smoothing and discretization operations in the Kalman filter method, the precise coordinates of the reference station and the double-difference observations are introduced into the observation equation to construct the measurement equation group;

[0096] S15, solving the three-dimensional coordinates of the cable facility through a least squares iterative algorithm, and obtaining initial coordinates with an output resolution of cm as the original observation data.

[0097] Among them, in the Kalman filter method, propagation and discretization operations are steps used to update the system state and covariance matrix. The propagation operation uses the dynamic model of the system to predict the state at the current moment based on the state and control input at the previous moment. It estimates the state using the continuous-time dynamic equations of the system, making the estimated result closer to the actual state. The propagation operation usually uses differential equations or difference equations to describe the dynamic behavior of the system.

[0098] The discretization operation converts the continuous-time system dynamic equations into discrete-time forms. In Kalman filtering, the discrete-time state transfer matrix and process noise covariance matrix are usually used to describe the dynamic evolution of the system. The discretization operation converts the continuous-time dynamic equations into discrete-time iterative forms through appropriate numerical methods (such as the Euler method or the Runge-Kutta method), making them suitable for discrete-time filtering algorithms. Through the smoothing and discretization operations, the continuous-time system dynamic equations can be converted into discrete-time state transfer equations, and the state estimation and covariance update can be performed in combination with the observed data. In this way, the Kalman filter can gradually update the state estimate and covariance matrix according to the system's dynamic model and observed data, providing the optimal estimate of the system state.

[0099] Specifically, first, we need to define the state variables and observation variables of the system. In this case, the state variables can be expressed as the three-dimensional position (x, y, z coordinates) of the target point, and the observation variables can be expressed as the double difference distance observation from the base station to the target point. Next, we use the dynamic model of the system to perform a shunting operation to predict the state at the current moment based on the state estimate and control input (if any) at the previous moment. Assuming that we use a linear motion model, the shunting operation can be expressed as follows: x(k) = F*x(k-1) + B*u(k-1)

[0100] Among them, x(k) is the state vector at the current moment, F is the state transfer matrix, x(k-1) is the state vector at the previous moment, B is the control input matrix, and u(k-1) is the control input at the previous moment.

[0101] Then, we perform discretization to convert the continuous-time state transfer equation into discrete-time form. By selecting an appropriate time interval (sampling period), we can obtain the discrete-time state transfer matrix and process noise covariance matrix. In the measurement equation, we introduce the precise coordinates of the reference station and the double-difference observations into the observation equation group. Assume that we have m reference stations, each of which provides a double-difference observation. The observation equation can be expressed as:

[0102] z(k)=H*x(k)+v(k), where z(k) is the observation vector, H is the observation matrix, and v(k) is the observation noise vector. The observation matrix H describes how to extract information related to the observation from the state variables. For double-difference observations, the form of H can be determined according to the specific problem. Finally, the state transfer equations and observation equations after normalization and discretization are combined to form the measurement equation group in the Kalman filter method. Through this equation group, state estimation and covariance update can be performed to obtain the optimal estimate of the target point position.

[0103] For example, the three-dimensional coordinates of the location of the cable facility are (0,0,0), and the precise coordinates of the reference station are (100,100,100). Based on the double difference observations, the ranging observation values ​​are obtained. Ranging observation value 1, 1000 meters, ranging observation value 2, 1100 meters, ranging observation value 3, 950 meters, ranging observation value 4, 1050 meters. According to the Kalman filter method, the measurement equation group can be constructed, d = sqrt((x-x1)^2+(y-y1)^2+(z-z1)^2)-sqrt((x-x2)^2+(y-y2)^2+(z-z2)^2)-sqrt((x-x3)^2+(y-y3)^2+(z-z3)^2)+sqrt((x-x4)^2+(y-y4)^2+(z-z4)^2). Where d is the ranging observation value, (x1, y1, z1) is the coordinate of the base station, (x2, y2, z2) is the coordinate of mobile station 1, (x3, y3, z3) is the coordinate of mobile station 2, and (x4, y4, z4) is the coordinate of mobile station 3. The three-dimensional coordinates of the computer antenna can be solved by the least squares iteration algorithm. The initial position is (1, 1, 1), and the iterative calculation is performed to obtain the final initial coordinates with a resolution of cm level (5, 5, 5). The initial coordinates of the computer antenna are (5, 5, 5) with a resolution of cm level.

[0104] like Figure 7 As shown, in an optional embodiment of the present invention, the processing method further includes:

[0105] S21, encrypting and compressing the initial coordinate data using an AES encryption algorithm;

[0106] S22, the wireless communication module forms a point-to-point secure connection with the satellite reference station through WIFI and Bluetooth, and sends compressed and encrypted data of the initial coordinates;

[0107] S23, the satellite reference station decompresses and decrypts the received data of the initial coordinates to verify the integrity of the data of the initial coordinates;

[0108] S24, combining the local station coordinate information recorded by the reference station with the received initial coordinates to construct a double difference observation equation group;

[0109] S25, introducing various error correction models to perform the differential GPS solution; obtaining the vector correction information of the position of the cable facility relative to the satellite reference station through least squares recursion;

[0110] S26, optimizing the correction information, adding the IMU trajectory information to perform multi-sensor fusion optimization, and obtaining coordinate correction data.

[0111] Among them, the AES algorithm is considered to be very secure. Currently, there is no known effective attack method to crack its ciphertext. As long as the key is kept secret, the encrypted data is safe. The AES encryption algorithm is used to encrypt and compress the initial coordinate data, and a point-to-point secure connection is established with the satellite base station through the wireless communication module to ensure the security of data transmission.

[0112] Among them, the double difference observation equation group is a commonly used differential GPS solution method, which eliminates most common errors such as clock error, ionospheric delay, etc. by calculating the differential observation values ​​between two receivers. The double difference observation equation group can effectively eliminate common errors and improve the stability and accuracy of the system.

[0113] In the embodiment of the present invention, the processing method can improve the accuracy and reliability of the cable facility location while ensuring the security of data transmission.

[0114] like Figure 6 As shown, according to another aspect of the present invention, a proofreading device for a digital twin model of a cable facility is provided, characterized in that it includes: an acquisition and processing module 11; used to obtain the satellite original observation data of the cable facility and obtain the initial coordinates with errors by solving the satellite original observation data of the cable facility through differential GPS; a correction module 12; transmitting the initial coordinates to a satellite base station, combining the coordinate information recorded by the satellite base station with the received information of the initial coordinates to obtain coordinate correction data; a proofreading module 13; used to proofread the initial coordinates according to the coordinate correction data fed back by the satellite base station, using an algorithm to obtain coordinate values ​​higher than the accuracy threshold; a model generation module 14; used to query a preset database according to the coordinate value higher than the accuracy threshold, and generate the digital twin model of the location range threshold.

[0115] First, the device of the present invention obtains the initial coordinates of the cable facility with errors through the acquisition processing module 11; secondly, the device transmits the initial coordinates to the satellite reference station through the correction module 12 to obtain the coordinate correction data of the cable facility; thirdly, the device calibrates the initial coordinates according to the coordinate correction data through the calibration module 13, so as to obtain high-precision coordinate values; finally, the device generates a digital twin model according to the coordinate values ​​above the accuracy threshold through the model generation module 14.

[0116] In the embodiment of the present invention, the problem of inaccurate initial coordinates obtained in the traditional method is solved, thereby improving the accuracy and credibility of the digital twin model.

[0117] According to an embodiment of the present invention, the present invention also provides an electronic device, a readable storage medium and a computer program product.

[0118] The figure shows a schematic block diagram of an example electronic device 600 that can be used to implement an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0119] like Figure 7 As shown, the device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 can also be stored. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0120] A number of components in the device 600 are connected to the I / O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0121] The computing unit 601 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 601 performs the various methods and processes described above, such as a processing method for a cable facility digital twin model. For example, in some embodiments, a processing method for a cable facility digital twin model may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of a power generation prediction method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to execute the processing method of the cable facility digital twin model in any other suitable manner (e.g., by means of firmware).

[0122] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0123] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0124] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0125] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0126] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0127] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0128] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and this document does not limit this.

[0129] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for processing a digital twin model of a cable facility, characterized in that: include: Obtaining original satellite observation data of the cable facility, and obtaining initial coordinates of the cable facility through differential GPS solution; Transmitting the initial coordinates to a satellite reference station, combining the coordinate information recorded by the satellite reference station with the received information of the initial coordinates to obtain coordinate correction data; According to the coordinate correction data fed back by the satellite reference station, the initial coordinates are corrected by using the least square method to obtain a coordinate value higher than an accuracy threshold; According to the coordinate value that is higher than the accuracy threshold, a preset database is queried to obtain a digital twin model of the range threshold of the location of the cable facility.

2. A correction method for the digital twin model of a cable facility A processing method for the digital twin model The processing method according to claim 1, characterized in that The correction method of the digital twin model and the processing method of the digital twin model also include: Determining the direction of the digital twin model according to the data of the digital twin model and the data of the cable facility obtained by the orientation sensor; According to the direction data of the digital twin model and the distance deviation data between the three-dimensional point cloud data of the actual scene obtained by scanning with a laser rangefinder and the digital twin model; According to the three-dimensional point cloud data of the actual scene and the distance deviation data, the coordinates and structure of the digital twin model are adjusted to complete the optimization of the digital twin model.

3. The processing method according to claim 2, characterized in that: The processing method also includes: Decrypting the acquired digital twin model data; The data of the cable facility is acquired according to the orientation sensor, and the digital twin model data is preprocessed by Kalman filtering to remove abnormal noise points.

4. The processing method according to claim 2, characterized in that: The processing method also includes: Obtaining data on the direction of the digital twin model; Performing an all-round scan along a set route to obtain three-dimensional point cloud data of the actual scene; Performing filtering and registration preprocessing on the three-dimensional point cloud data; Importing the processed three-dimensional point cloud data into Autodesk 3ds Max software, and using ICP algorithm to match the point cloud data with the model; Calculating the distance between each sampling point in the point cloud data and the surface of the digital twin model to obtain a distance deviation matrix between the point cloud data and the digital twin model; The mean, median and standard deviation of the distance deviation of the point cloud data are calculated to determine the degree of fit between the model and the actual scene.

5. The processing method according to claim 2, characterized in that: The step of adjusting the coordinates and structure of the digital twin model according to the three-dimensional point cloud data of the actual scene and the distance deviation data to complete the optimization of the digital twin model includes: Loading a three-dimensional modeling engine, and importing the calculated distance deviation matrix between the three-dimensional point cloud data and the digital twin model; A polynomial regression model is established, with the sampling points of the three-dimensional point cloud data as independent variables and the distance deviation value as dependent variable, and a statistical mapping relationship between the model coordinate deviation and the scene position is obtained through training to obtain a regression formula; Applying the regression formula to each vertex coordinate of the digital twin model, and calculating its theoretical coordinate offset according to the spatial position parameters of the vertex of the digital twin model; The coordinate offset is fed back to adjust the vertex coordinates of the digital twin model; the distance deviation between the point cloud data and the digital twin model is used as an error back-propagation signal, and the structure of the digital twin model is automatically adjusted by analyzing the difference between the point cloud data and the digital twin model.

6. The processing method according to claim 1, characterized in that: The processing method also includes: Receiving navigation signals from the satellite and acquiring raw observation data; Preprocessing the original observation data to remove erroneous observations and obtain original ranging observation values ​​with a resolution of cm level; The original distance measurement observation value is subjected to the differential GPS solution; By using the smoothing and discretization operations in the Kalman filter method, the precise coordinates of the reference station and the double-difference observations are introduced into the observation equation to construct the measurement equation group. The three-dimensional coordinates of the cable facility are solved by a least squares iterative algorithm to obtain initial coordinates with an output resolution of cm level as the original observation data.

7. The processing method according to claim 1, characterized in that: The processing method also includes: The AES encryption algorithm is used to encrypt and compress the data of the initial coordinates; The wireless communication module forms a point-to-point secure connection with the satellite reference station through WIFI and Bluetooth, and sends compressed and encrypted data of the initial coordinates; The satellite reference station decompresses and decrypts the received data of the initial coordinates to verify the integrity of the data of the initial coordinates; Combine the station coordinate information recorded by the base station with the received initial coordinates to construct a double-difference observation equation group; Various error correction models are introduced to perform the differential GPS solution; through least squares recursion, vector correction information of the position of the cable facility relative to the satellite reference station is obtained; Optimize the correction information, add IMU trajectory information for multi-sensor fusion optimization, and obtain coordinate correction data.

8. A processing device for a digital twin model of a cable facility, characterized in that: include: Acquisition and processing module; Used to obtain original satellite observation data of cable facilities and obtain initial coordinates with errors by solving the original satellite observation data of the cable facilities through differential GPS; Correction module; Used to transmit the initial coordinates to a satellite reference station, and combine the coordinate information recorded by the satellite reference station with the received information of the initial coordinates to obtain coordinate correction data; A calibration module; used to calibrate the initial coordinates using the least square method according to the coordinate correction data fed back by the satellite reference station to obtain a coordinate value higher than the accuracy threshold; Model generation module; It is used to query a preset database according to the coordinate value that is higher than the accuracy threshold, and generate a digital twin model of the location range threshold.

9. An electronic device, characterized in that: include: at least one processor, and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the processing method described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

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