Insulation degradation positioning device of cable terminal and control method

Abstract

The invention discloses an insulation degradation positioning device of a cable terminal and a control method, and relates to the technical field of cable terminal insulation detection and fault positioning. A signal sensing unit adopts a single built-in ultrahigh-frequency sensor to capture a high-frequency harmonic signal generated at the initial stage of insulation aging of the cable terminal to be detected; the signal acquisition and processing unit pre-processes the signal, then the pre-processed signal is injected into a preset cable terminal digital twin electromagnetic model by means of the digital twin and inversion analysis and calculation unit to carry out electromagnetic wave back propagation simulation, and total-space electromagnetic field distribution data is obtained based on simulation. The space coordinate of the insulation degradation point is determined through the preset positioning criterion, the positioning precision equivalent to that of a traditional multi-sensor system is achieved through a single-sensor scheme, the cost and the deployment difficulty are remarkably reduced, deep integration with a digital twin platform is achieved, and efficient and accurate technical support is provided for intelligent operation and maintenance of the cable terminal.

Description

Technical Field

[0001] This invention relates to the field of cable terminal insulation detection and fault location technology, and in particular to a cable terminal insulation degradation location device and control method. Background Technology

[0002] Cable terminals are critical equipment in power systems, and their insulation condition directly affects the reliability of power supply. During long-term operation, the insulation material of cable terminals inevitably ages and deteriorates due to electrical, thermal, and mechanical stresses, potentially leading to insulation breakdown and serious accidents. Therefore, early insulation condition assessment and deterioration point location of cable terminals are of paramount importance for preventing equipment failures and ensuring the safe operation of the power grid.

[0003] With the development of digital technology, establishing digital twin models of cable terminals has become possible. Digital twins, by constructing virtual models highly consistent with physical entities, provide a revolutionary platform for real-time perception, accurate mapping, and predictive maintenance of equipment status. However, providing accurate and real-time insulation status data for digital twin models, especially precisely locating the specific locations of insulation degradation, is crucial to realizing their value. Currently, traditional insulation status monitoring methods (such as UHF and ultrasonic methods) exhibit significant shortcomings when used in novel monitoring systems enabled by digital twin models. These methods typically require the deployment of at least three or more sensor arrays around the cable terminal and rely on high-precision (e.g., nanosecond-level) time synchronization devices, resulting in high system costs and cumbersome installation. They are redundant and uneconomical in digital twin scenarios, hindering large-scale application. Meanwhile, such multi-sensor solutions rely on signal time-difference analysis for positioning. However, due to the non-uniform structure of cable terminals and the complex electromagnetic environment, signals are susceptible to interference, and time-difference calculation errors are significant, making it difficult to accurately pinpoint the specific spatial location of minute insulation degradation points. The positioning accuracy cannot match the precision requirements of digital twin models for insulation status data. Furthermore, insulation materials generate characteristic high-frequency electromagnetic harmonic signals in the early stages of aging. Current technologies lack a low-cost, high-precision solution that can effectively capture such signals and directly integrate them deeply with digital twin models.

[0004] Therefore, there is an urgent need in this field for a new insulation state inversion method and device that can be adapted to digital twin cable terminals. It should be able to overcome the cost and complexity problems of traditional multi-sensor solutions and achieve rapid and accurate location of insulation degradation points. Summary of the Invention

[0005] This invention provides a cable terminal insulation degradation location device and control method, which solves the technical problems of traditional cable terminal insulation degradation location schemes, which require the deployment of multiple sensor arrays and high-precision time synchronization devices, resulting in high system costs and cumbersome on-site installation and operation. In addition, the schemes rely on multi-sensor signal time difference analysis for location, and the signals are easily interfered with in complex electromagnetic environments and non-uniform structures of cable terminals, leading to insufficient location accuracy.

[0006] The first aspect of the present invention provides an insulation degradation locating device for cable terminals, comprising:

[0007] The signal sensing unit is used to acquire high-frequency harmonic signals from the cable terminal under test through a single built-in ultra-high frequency sensor.

[0008] The signal acquisition and processing unit is used to preprocess the high-frequency harmonic signal to obtain a preprocessed signal;

[0009] The digital twin and inversion analysis calculation unit is used to perform electromagnetic wave back propagation simulation by injecting the preprocessed signal into the preset digital twin electromagnetic model of the cable terminal, and to determine the insulation degradation location result of the cable terminal under test according to the preset positioning criteria based on the simulation results.

[0010] Optionally, the preset positioning criterion is an energy focusing criterion or a minimum entropy criterion.

[0011] Optionally, the energy focusing criterion is specifically:

[0012] The simulation results include the three-dimensional coordinates, electric field strength modulus, and electromagnetic energy density of each model mesh node;

[0013] Extract all sampling point information within the effective analysis area of ​​the digital twin electromagnetic model of the pre-set cable terminal from the simulation results, and establish a coordinate-field quantity numerical mapping table.

[0014] When the grid type of the pre-set cable terminal digital twin electromagnetic model is a structured grid, the field quantity values ​​of all grid nodes are traversed based on the coordinate-field quantity value mapping table, and the three-dimensional coordinates corresponding to the maximum field quantity value are selected as the spatial coordinates of the insulation degradation point of the cable terminal under test.

[0015] When the grid type of the digital twin electromagnetic model of the pre-set cable terminal is an unstructured grid, the field quantity values ​​of all grid nodes are traversed based on the coordinate-field quantity value mapping table, and the grid cell containing the maximum field quantity value is selected as the target grid cell.

[0016] Interpolate the target grid cell and calculate the field quantity values ​​of each interpolated sampling point within the interpolated target grid cell;

[0017] The three-dimensional coordinates corresponding to the maximum field quantity value are selected from the interpolated target grid cells and determined as the spatial coordinates of the insulation degradation point of the cable terminal under test.

[0018] Optionally, the minimum entropy criterion is specifically:

[0019] The simulation results include the three-dimensional coordinates, electric field strength modulus, and electromagnetic energy density of each model mesh node;

[0020] Extract all sampling point information within the effective analysis area of ​​the digital twin electromagnetic model of the pre-set cable terminal from the simulation results, and establish a coordinate-field quantity numerical mapping table.

[0021] The sampling point information includes the three-dimensional coordinates, electric field strength modulus, and electromagnetic energy density of the effective grid nodes.

[0022] The preset sliding analysis window moves position by position within the effective analysis area, and the field quantity values ​​of multiple window sampling points within each sliding analysis window are obtained from the coordinate-field quantity value mapping table.

[0023] The field quantity values ​​at each sampling point of the window are normalized, and a probability distribution model of the field quantity values ​​corresponding to each sliding analysis window is constructed.

[0024] Based on the probability distribution model of the field value, calculate the entropy value corresponding to each sliding analysis window;

[0025] Based on the entropy values ​​described, the sliding analysis window corresponding to the minimum entropy value is selected as the insulation degradation location window;

[0026] The three-dimensional coordinates of the center of the insulation degradation positioning window are determined as the spatial coordinates of the insulation degradation point of the cable terminal under test.

[0027] Optionally, the preprocessing of the high-frequency harmonic signal to obtain a preprocessed signal includes:

[0028] The high-frequency harmonic signal is sequentially amplified, filtered, and converted from analog to digital to obtain a preprocessed signal.

[0029] Optionally, before performing electromagnetic wave backpropagation simulation using the pre-processed signal injected into the pre-set cable terminal digital twin electromagnetic model, the method further includes:

[0030] The preprocessed signal is denoised to obtain a new preprocessed signal.

[0031] Optionally, the step of denoising the preprocessed signal to obtain a new preprocessed signal includes:

[0032] Perform a short-time Fourier transform on the preprocessed signal to obtain the initial signal time-frequency matrix;

[0033] The initial signal time-frequency matrix is ​​subjected to soft threshold filtering to obtain the intermediate signal time-frequency matrix;

[0034] Singular value decomposition is performed on the intermediate signal time-frequency matrix to obtain the target signal time-frequency matrix;

[0035] The target signal time-frequency matrix is ​​subjected to inverse short-time Fourier transform, and the results of the inverse short-time Fourier transform are superimposed and added to obtain a new preprocessed signal.

[0036] A second aspect of the present invention provides a control method for an insulation degradation locating device applied to a cable terminal, comprising:

[0037] High-frequency harmonic signals from the cable terminal under test are acquired using a single built-in ultra-high frequency sensor.

[0038] The high-frequency harmonic signal is preprocessed to obtain a preprocessed signal;

[0039] The preprocessed signal is injected into a pre-set digital twin electromagnetic model of the cable terminal to simulate the back propagation of electromagnetic waves. Based on the simulation results, the insulation degradation location result of the cable terminal under test is determined according to the pre-set positioning criteria.

[0040] A third aspect of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the control method described above.

[0041] The fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the control method as described above.

[0042] As can be seen from the above technical solutions, the present invention has the following advantages:

[0043] This invention provides a device and control method for locating insulation degradation in cable terminals. A single built-in ultra-high frequency (UHF) sensor, used by a signal sensing unit, captures high-frequency harmonic signals generated during the early stages of insulation aging in the cable terminal under test. A signal acquisition and processing unit preprocesses the signal. Subsequently, a digital twin and inversion analysis unit injects the preprocessed signal into a pre-set digital twin electromagnetic model of the cable terminal to conduct electromagnetic wave backpropagation simulation. Based on the simulated full-space electromagnetic field distribution data, the spatial coordinates of the insulation degradation point are determined using pre-set positioning criteria. Addressing the drawbacks of traditional cable terminal insulation degradation location schemes, which require multiple sensor arrays and high-precision time synchronization devices, resulting in high system costs and cumbersome on-site installation, this invention relies solely on a single UHF sensor to effectively acquire the target signal, eliminating the need for additional sensor hardware and nanosecond-level time synchronization. Synchronization equipment not only significantly reduces the cost of hardware procurement and deployment, but also eliminates the complex operational procedures of multi-sensor on-site layout and synchronous calibration, making it better suited to the low-cost and easy-to-promote requirements of digital twin scenarios. Regarding the problems of traditional solutions relying on multi-sensor signal time-difference analysis for positioning, and the susceptibility to signal interference in complex electromagnetic environments and non-uniform cable terminal structures leading to insufficient positioning accuracy, this invention uses backpropagation simulation of the digital twin electromagnetic model to obtain electromagnetic field distribution data covering the entire space of the cable terminal. This fundamentally avoids the interference effects of complex environments and non-uniform structures during signal transmission. Combined with preset positioning criteria (energy focusing criteria or minimum entropy criteria), targeted analysis of this full-space electromagnetic field distribution data can accurately pinpoint the specific spatial location of minute insulation degradation points, effectively compensating for the accuracy shortcomings of traditional time-difference analysis methods in complex application scenarios. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a structural block diagram of the insulation degradation locating device for cable terminals according to an embodiment of the present invention;

[0046] Figure 2 This is a flowchart illustrating the overall process of insulation state inversion according to an embodiment of the present invention.

[0047] Figure 3 This is a schematic diagram of the detection system composition of the cable terminal insulation degradation locating device according to an embodiment of the present invention;

[0048] Figure 4This is a schematic diagram of high-frequency harmonic propagation and inversion focusing in insulation degradation according to an embodiment of the present invention;

[0049] Figure 5 This is a flowchart of the signal noise reduction algorithm according to an embodiment of the present invention;

[0050] Figure 6 This is a schematic diagram of the field application of the insulation degradation locating device for cable terminals according to an embodiment of the present invention;

[0051] Figure 7 This is a flowchart illustrating the steps of a control method for an insulation degradation locating device applied to a cable terminal, according to an embodiment of the present invention.

[0052] Figure 8 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0053] This invention provides a cable terminal insulation degradation location device and control method to solve the technical problems of high cost, complex deployment, and difficulty in accurately locating insulation degradation points in digital twin application scenarios using traditional monitoring methods.

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. It should be noted that in the optional embodiments of the present invention, the object information and other related data involved require the permission or consent of the object when the embodiments of the present invention are applied to specific products or technologies, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. That is to say, if the embodiments of the present invention involve data related to the object, it needs to be obtained with the authorization and consent of the object, the authorization and consent of the relevant departments, and in compliance with the relevant laws, regulations, and standards of the country and region. If personal information is involved in the embodiments, the acquisition of all personal information requires the consent of the individual. If sensitive information is involved, the separate consent of the information subject is required, and the embodiments also need to be implemented with the authorization and consent of the object.

[0055] Please see Figure 1 The present invention provides an insulation degradation locating device for cable terminals, comprising:

[0056] The signal sensing unit is used to acquire high-frequency harmonic signals from the cable terminal under test through a single built-in ultra-high frequency sensor.

[0057] The signal acquisition and processing unit is used to preprocess high-frequency harmonic signals to obtain preprocessed signals;

[0058] The digital twin and inversion analysis calculation unit is used to simulate the electromagnetic wave back propagation by injecting pre-processed signals into the digital twin electromagnetic model of the cable terminal, and to determine the insulation degradation location result of the cable terminal under test according to the pre-set positioning criteria based on the simulation results.

[0059] In this embodiment of the invention, the single built-in ultra-high frequency sensor in the signal sensing unit refers to a sensing device that can capture electromagnetic signals with frequencies in the range of 300MHz to 3GHz. Here, it is integrated into the preset monitoring area of ​​the cable terminal (such as near the terminal stress cone) so that it can efficiently collect high-frequency harmonic signals generated by physical effects such as partial discharge and charge migration in the early stage of aging and deterioration of the insulation material of the cable terminal under test. The high-frequency harmonic signal is a characteristic high-frequency electromagnetic signal excited by processes such as local breakdown and molecular chain breakage inside the insulation medium during the insulation deterioration process. Its frequency band and amplitude usually correspond to the degree and type of insulation deterioration. After acquiring the high-frequency harmonic signal, the signal acquisition and processing unit immediately performs preprocessing on the signal. This preprocessing refers to signal conditioning of the original acquired signal. Specifically, the unit first amplifies the high-frequency harmonic signal using a low-noise amplifier to improve the identifiability of the weak signal. Then, it filters out irrelevant electromagnetic interference signals from the environment using a bandpass filter adapted to the ultra-high frequency band. Subsequently, it uses an analog-to-digital converter to convert the conditioned analog signal into a digital preprocessed signal for compatibility with the digital interface of the subsequent digital twin simulation. Next, the digital twin and inversion analysis calculation unit calls the preset cable terminal digital twin electromagnetic... The model is a virtual model built using electromagnetic simulation software, based on the actual physical structure of the cable terminal (including parameters such as insulation material, geometric dimensions, and electrode distribution). It highly replicates the electromagnetic propagation patterns within the cable terminal. This unit uses a pre-processed signal as the excitation source, injecting it from the virtual position corresponding to the actual UHF sensor in the model to initiate the electromagnetic wave reverse propagation simulation. The electromagnetic wave reverse propagation simulation refers to reversing the signal's time axis and simulating its propagation from the receiving position to the signal source position in the virtual model. This process directs signal energy towards the insulation degradation point (i.e., the original signal source). (Initial excitation position) Focusing; After the simulation is completed, the unit obtains the simulation results including the three-dimensional coordinates of each grid node of the model, the electric field strength magnitude and the electromagnetic energy density value, and then determines the result according to the preset positioning criteria. The preset positioning criteria refer to the analysis rules for identifying the degradation point from the electromagnetic field distribution data. Specifically, the energy focusing criterion (selecting the coordinates of the grid node with the largest electromagnetic field energy density) or the minimum entropy criterion (quantifying the disorder of the local electromagnetic field distribution through a sliding window and taking the center coordinates of the region with the smallest entropy value) can be adopted. The final output insulation degradation positioning result is the physical three-dimensional position of the actual insulation degradation point of the cable terminal under test.

[0060] The cable terminal insulation degradation location device consists of three main parts: a signal sensing unit, a signal acquisition and processing unit, and a digital twin and inversion analysis and calculation unit.

[0061] The signal sensing unit employs a single ultra-high frequency sensor for non-invasive coupling and acquisition of high-frequency harmonic electromagnetic signals radiated from cable terminals due to aging or deterioration of insulation materials. This sensor preferably features an external antenna structure with a metal back cavity to shield against rear interference and enhance the receiving sensitivity of signals from the cable terminal direction. Its operating frequency band covers 300MHz to 3GHz to effectively capture the characteristic harmonics of insulation deterioration.

[0062] The signal acquisition and processing unit is connected to the signal sensing unit and is used to condition, amplify, and digitize the acquired high-frequency harmonic signals. This unit includes a signal conditioning circuit and a high-speed data acquisition card; the signal conditioning circuit consists of a bandpass filter and a cascaded amplifier, used to suppress out-of-band interference and increase the signal amplitude; the high-speed data acquisition card has a sampling rate of not less than 5GS / s and an analog bandwidth of not less than 2.5GHz to ensure distortion-free acquisition of ultra-high frequency signals.

[0063] The digital twin and inversion analysis calculation unit communicates with the signal acquisition and processing unit, serving as the core processing and decision-making center of the device. The digital twin and inversion analysis calculation unit includes: a digital twin model construction module, used to establish and maintain a three-dimensional electromagnetic model consistent with the physical cable terminal, containing the precise geometric structure of the cable terminal and the distribution of material dielectric constant and conductivity; a signal processing and TR (Time Reversal Transform) module, used to receive digitized high-frequency harmonic signals and perform noise reduction preprocessing and time reversal transformation on them; an EMTR (Electromagnetic Time Reversal Inversion Simulation Engine), used to inject the time-reversed signal into the digital twin model from the virtual location corresponding to the sensor, and simulate the backward propagation process of the signal within the model to calculate the time-varying electromagnetic field distribution (i.e., simulation results) in the entire model space; and a positioning and visualization output module, used to determine the spatial coordinates of insulation degradation points based on the backward propagation electromagnetic field distribution calculated by the EMTR inversion simulation engine, applying specific positioning criteria, and displaying and outputting the positioning results in the digital twin model.

[0064] like Figure 2As shown, the execution of this invention begins with the signal sensing unit. High-frequency electromagnetic signals generated by insulation degradation points are non-invasively acquired by a single sensor, enabling the acquisition of initial information about the insulation state in the physical world. Subsequently, the signal enters the acquisition and processing unit, where analog-domain conditioning (amplification and filtering) and high-speed analog-to-digital conversion are performed, transforming the physical signal into a digital signal stream that can be processed by the computing unit. Finally, the digital signal is sent to the digital twin and inversion analysis computing unit, where signal noise reduction, time-reversal transformation, backpropagation simulation in the digital twin model, and location analysis based on specific criteria are sequentially performed. The final location of the insulation degradation point is then visualized and output, forming a closed loop from the physical entity to the virtual model, and then back to accurate diagnostic information.

[0065] like Figure 3 As shown, the detection system of this invention consists of two major subsystems: hardware and software. The hardware subsystem is responsible for signal sensing and acquisition. Its signal sensing module includes an ultra-high frequency sensor and its auxiliary structures to ensure effective signal capture; the signal acquisition module, through professional conditioning circuits and a high-speed acquisition card, ensures high-fidelity digitization of the signal. The software subsystem, acting as the "intelligent brain," has a core processing module responsible for managing the digital twin model, executing signal processing algorithms (such as noise reduction and TR transform), and running the EMTR inversion simulation engine; the analysis and output module comprehensively utilizes a positioning algorithm library and a visualization rendering engine to intelligently analyze the simulation results and generate a final visualized diagnostic report, achieving deep synergy between hardware sensing and software intelligence.

[0066] like Figure 4 As shown, the principle of insulation degradation location is based on the reversibility of electromagnetic wave propagation. In the forward process (left side), the insulation degradation point acts as a radiation source, radiating high-frequency electromagnetic waves. These waves propagate through the complex insulation structure of the cable terminal and are then received by the sensor. In the reverse process (right side), the signal, after time-reversal transformation, is injected into the digital twin model, and the electromagnetic waves propagate backward within the model. Due to the spatiotemporal focusing characteristics of time reversal, the electromagnetic field energy propagating backward will reconverge at the original degradation point location (i.e., the wave source location), forming a highly concentrated energy focal point (based on the energy focusing criterion), thereby achieving precise spatial location of the insulation degradation point.

[0067] like Figure 5 As shown, preprocessing the original digital signal in a digital twin unit is a crucial step in ensuring positioning accuracy. This invention employs a noise reduction algorithm based on Short-Time Fourier Transform and Singular Value Decomposition (STFT-SVD) in the signal processing stage. The processing flow is as follows:

[0068] First, a short-time Fourier transform is performed on the noisy original signal to obtain a complex time-frequency matrix. Next, soft thresholding is applied to this time-frequency matrix to suppress low-amplitude noise components. Then, singular value decomposition is performed on the processed matrix, further separating the signal from noise by retaining the principal singular values ​​and discarding the minor ones. Finally, an inverse short-time Fourier transform is performed on the dimension-reduced matrix, and the denoised time-domain signal is obtained. This denoised signal is then subjected to a time-inverse transform to generate a TR signal that can be used for subsequent backpropagation simulations. This series of sophisticated digital processing steps provides a reliable data foundation for the inversion simulation.

[0069] like Figure 6 As shown, in practical field applications, the UHF sensor is installed near critical locations such as the cable terminal insulation basin or grounding box, and connected to the signal acquisition and processing unit installed in a field enclosure via an RF cable. This enclosure is typically deployed in field environments such as substations or cable tunnels. The acquisition unit uploads digital signals to a local server or cloud platform via a data cable, where the digital twin and inversion analysis unit completes all core calculations. This implementation diagram clearly demonstrates that the present invention can be easily integrated into existing cable terminal operating environments, possessing good engineering applicability and promotional value.

[0070] The present invention provides an insulation degradation location device for cable terminals, wherein the preset location criteria are energy focusing criteria or minimum entropy criteria.

[0071] It should be noted that the energy focusing criterion refers to searching for the spatial location of the maximum electric field intensity modulus or electromagnetic energy density in the spatial electromagnetic field distribution data of the digital twin model obtained by the digital twin and inversion analysis calculation unit through electromagnetic wave back propagation simulation (i.e., simulation results). Since the insulation degradation point is the original excitation source of high-frequency harmonic signals, energy will accumulate towards the signal source location during electromagnetic wave back propagation. Therefore, the location corresponding to the maximum value is determined as the insulation degradation point of the cable terminal under test. The minimum entropy criterion refers to selecting a specific region in the spatial electromagnetic field distribution data of the above digital twin model and calculating the entropy value of the electromagnetic field distribution in that specific region. The electromagnetic field at the insulation degradation point exhibits a concentrated distribution characteristic, and its distribution disorder is significantly lower than that of other regions. Therefore, the location with the minimum entropy value is determined as the insulation degradation point of the cable terminal under test.

[0072] The present invention provides an insulation degradation locating device for cable terminals, wherein the energy focusing criterion is specifically as follows:

[0073] The simulation results include the three-dimensional coordinates, electric field strength magnitude, and electromagnetic energy density of each model mesh node;

[0074] Extract information from all sampling points in the effective analysis area of ​​the digital twin electromagnetic model of the pre-set cable terminal from the simulation results, and establish a coordinate-field quantity numerical mapping table.

[0075] When the grid type of the pre-set digital twin electromagnetic model of the cable terminal is a structured grid, the field values ​​of all grid nodes are traversed based on the coordinate-field value mapping table, and the three-dimensional coordinates corresponding to the maximum field value are selected as the spatial coordinates of the insulation degradation point of the cable terminal to be tested.

[0076] When the grid type of the preset cable terminal digital twin electromagnetic model is an unstructured grid, the field quantity values ​​of all grid nodes are traversed based on the coordinate-field quantity value mapping table, and the grid cell with the maximum field quantity value is selected as the target grid cell.

[0077] Interpolate the target grid cell and calculate the field quantity values ​​of each interpolated sampling point within the interpolated target grid cell;

[0078] The three-dimensional coordinates corresponding to the maximum field quantity value are selected from the interpolated target grid cells and determined as the spatial coordinates of the insulation degradation point of the cable terminal under test.

[0079] In this embodiment of the invention, after the digital twin and inversion analysis calculation unit completes the electromagnetic wave back propagation simulation, the simulation results specifically include the three-dimensional coordinates of each grid node in the digital twin model, the electric field intensity magnitude (i.e., the magnitude of the electric field intensity vector, denoted as ), and the electric field intensity vector magnitude (i.e., the magnitude of the electric field intensity vector). ,in These represent the components of the electric field intensity in the three spatial dimensions of x, y, and z, respectively, and the electromagnetic energy density (i.e., the electromagnetic energy per unit volume, denoted as ). ,in The vacuum permittivity, The permeability of free space, (For magnetic field strength), the next step is to select all sampling point information within the effective analysis area of ​​the pre-set digital twin electromagnetic model of the cable terminal (i.e., the core area covering the insulation structure of the cable terminal, avoiding interference from invalid spatial data) from the simulation results, and establish a coordinate-field quantity numerical mapping table. This coordinate-field quantity numerical mapping table refers to a dataset that associates the three-dimensional spatial coordinates of each sampling point with the corresponding electric field strength modulus and electromagnetic energy density value, used for subsequent rapid retrieval of field quantity data corresponding to any coordinate. Then, the mesh type of the digital twin electromagnetic model is determined. A structured mesh refers to a mesh form where mesh nodes are arranged in regular rows and columns or voxels, and the connection relationship between adjacent nodes is fixed. The node coordinates of this type of mesh have regularity. When the mesh type is a structured mesh, based directly on the above coordinate-field quantity numerical mapping table, a traversal algorithm is used to sequentially read the field quantity values ​​(electric field strength modulus or electromagnetic energy density) corresponding to all mesh nodes. The field density value is recorded, and the three-dimensional coordinates corresponding to each field value are recorded simultaneously. After the traversal is completed, the magnitude of all field values ​​is compared, and the three-dimensional coordinates corresponding to the field value with the largest value are selected. These coordinates can be directly determined as the spatial coordinates of the insulation degradation point of the cable terminal under test. Unstructured meshes refer to meshes with no fixed rules for the arrangement of mesh nodes and can adapt to complex geometric structures. The node distribution of this type of mesh is more flexible, but the coordinates have no uniform pattern. When the mesh type is unstructured mesh, the field values ​​of all mesh nodes are traversed based on the coordinate-field value mapping table. First, the mesh node corresponding to the field value with the largest value is selected. The mesh cell where the node is located—that is, the basic geometric cell (such as tetrahedron or hexahedron) surrounded by adjacent nodes in the digital twin model—is determined as the target mesh cell. To improve the positioning accuracy under unstructured meshes, linear interpolation processing is required for the target mesh cell (for tetrahedral cells, the interpolation formula is...). ,in The three-dimensional coordinates of the interpolation sampling points. For the first The shape function of each node For the first The field quantity values ​​of each node are obtained by generating multiple uniformly distributed interpolation sampling points within the target grid cell, calculating the field quantity value corresponding to each interpolation sampling point, comparing the magnitudes of these interpolation sampling points, and selecting the three-dimensional coordinates corresponding to the largest field quantity value, which are the precise spatial coordinates of the insulation degradation point of the cable terminal under test.

[0080] The present invention provides an insulation degradation locating device for cable terminals, wherein the minimum entropy criterion is specifically as follows:

[0081] The simulation results include the three-dimensional coordinates, electric field strength magnitude, and electromagnetic energy density of each model mesh node;

[0082] Extract information from all sampling points in the effective analysis area of ​​the digital twin electromagnetic model of the pre-set cable terminal from the simulation results, and establish a coordinate-field quantity numerical mapping table.

[0083] The sampling point information includes the three-dimensional coordinates, electric field strength modulus, and electromagnetic energy density of the effective grid nodes;

[0084] The preset sliding analysis window moves position by position within the effective analysis area, and the field quantity values ​​of multiple window sampling points within each sliding analysis window are obtained from the coordinate-field quantity value mapping table.

[0085] The field quantity values ​​at each window sampling point are normalized, and a probability distribution model of the field quantity values ​​corresponding to each sliding analysis window is constructed.

[0086] Based on the probability distribution model of field values, calculate the entropy value corresponding to each sliding analysis window;

[0087] Based on each entropy value, the sliding analysis window corresponding to the minimum entropy value is selected as the insulation degradation location window;

[0088] The three-dimensional coordinates of the center of the insulation degradation location window are determined as the spatial coordinates of the insulation degradation point at the end of the cable under test.

[0089] In this embodiment of the invention, after the digital twin and inversion analysis calculation unit outputs the simulation results, the results include the three-dimensional coordinates of each model mesh node, the electric field intensity magnitude (i.e., the magnitude of the electric field intensity vector, denoted as ), and so on. ,in These represent the components of the electric field intensity in the three spatial dimensions of x, y, and z, respectively, and the electromagnetic energy density (i.e., the electromagnetic energy per unit volume, denoted as ). ,in The vacuum permittivity, The permeability of free space, (For magnetic field strength), then extract all sampling point information within the effective analysis area (i.e., the core area covering the cable terminal insulation structure, used to eliminate redundant data interference from irrelevant spaces) of the preset digital twin electromagnetic model of the cable terminal from the simulation results, and establish a coordinate-field quantity numerical mapping table. The coordinate-field quantity numerical mapping table is a dataset that associates the three-dimensional spatial coordinates of each sampling point within the effective analysis area with the corresponding electric field strength modulus and electromagnetic energy density values, facilitating the rapid retrieval of field quantity data within a specified spatial range. The sampling point information here specifically refers to the three-dimensional coordinates, electric field strength modulus, and electromagnetic energy density values ​​corresponding to the effective grid nodes (i.e., the model grid nodes located within the effective analysis area). Subsequently, according to the preset sliding analysis window... The sampling point moves position by position within the effective analysis area. The preset sliding analysis window is a fixed-size local area defined based on the typical characteristic dimensions of cable terminal insulation defects (such as the spatial scale of common micro-deterioration points). Its sliding step size is typically half the window size to ensure complete area coverage. During window movement, all sampling points within the current window range are selected by matching the window's spatial coordinate range with the sampling point coordinates in the coordinate-field quantity value mapping table, thereby obtaining the corresponding field quantity values. Then, the field quantity values ​​of each window sampling point are normalized. Normalization is a standardization operation that maps field quantity values ​​to the [0,1] interval. Here, the min-max normalization method is used, and the formula is... ,in This represents the field quantity value at a specific sampling point within the current window. These are the minimum and maximum values ​​of the field quantity values ​​at all sampling points within the window. After normalization, a probability distribution model of the field quantity values ​​corresponding to each sliding analysis window is constructed. This model is obtained by dividing the normalized field quantity values ​​into several continuous intervals and calculating the proportion of sampling points in each interval to the total number of sampling points in the window, thus obtaining the probability of each interval. ( (For interval indexing); Based on this probability distribution model, the entropy value corresponding to each sliding analysis window is calculated. Here, the information entropy formula is used for calculation, and the formula is: ,in This is the entropy value corresponding to the window. The entropy value represents the total number of intervals into which the field quantity values ​​are divided. The entropy value reflects the degree of disorder in the distribution of the field quantity values. The smaller the entropy value, the more concentrated the distribution of the field quantity values ​​within the window. After the entropy values ​​of all sliding analysis windows are calculated, the window with the smallest entropy value is selected as the insulation degradation location window. This is because the insulation degradation point is the excitation source of high-frequency harmonic signals, and the field quantity values ​​around it will show a significant concentrated distribution characteristic. The entropy value of the corresponding window will be much smaller than the entropy value of other area windows. Finally, the three-dimensional coordinates of the window center of the insulation degradation location window (i.e., the three-dimensional coordinates corresponding to the spatial geometric center of the sliding window at the current position) are determined as the spatial coordinates of the insulation degradation point of the cable terminal under test, thus completing the insulation degradation point location process based on the minimum entropy criterion.

[0090] This invention provides an insulation degradation locating device for cable terminals, which preprocesses high-frequency harmonic signals to obtain a preprocessed signal, including:

[0091] The high-frequency harmonic signal is amplified, filtered, and converted from analog to digital in sequence to obtain the preprocessed signal.

[0092] In this embodiment of the invention, the high-frequency harmonic signal (i.e., a weak electromagnetic signal in the 300MHz to 3GHz range excited by physical effects such as partial discharge and charge migration during the degradation of cable terminal insulation material) acquired by the signal sensing unit through a single built-in ultra-high frequency sensor typically has a low amplitude and is mixed with irrelevant components such as power frequency interference and low-frequency electromagnetic noise in the environment. Therefore, it needs to be preprocessed by the signal acquisition and processing unit. The first step is amplification, which uses a low-noise amplifier. A low-noise amplifier is an electronic device that introduces extremely low noise while increasing the signal amplitude. Its function is to increase the amplitude of the weak high-frequency harmonic signal to a range that subsequent equipment can stably identify and process, preventing the signal from being masked by noise in subsequent stages due to excessively low amplitude. After amplification, the signal is directly sent to a bandpass filter adapted to the ultra-high frequency band. The bandpass filter only allows signals of a specific frequency band (here matching the acquisition range of the ultra-high frequency sensor, i.e., 300MHz to 3GHz) to pass through and filters out other signals. For devices processing signals in other frequency bands, this filter can accurately remove interference components outside the ultra-high frequency band, ensuring the purity and effectiveness of the signal. Subsequently, the filtered analog signal is input to an analog-to-digital converter (ADC) for analog-to-digital conversion. An ADC is a device that converts continuously changing analog electrical signals into discrete digital signals. Since the subsequent digital twin and inversion analysis calculation unit can only process digital signals, this step is to adapt the signal form to the subsequent units. The ADC selected here must satisfy the Nyquist sampling theorem (i.e., the sampling rate is not less than twice the highest frequency of the signal; for ultra-high frequency signals of 3 GHz, the sampling rate must be not less than 6 GHz). At the same time, it is configured with 12 bits or more of quantization bits to ensure that the digital signal can accurately reproduce the characteristics of the original high-frequency harmonic signal. After this series of amplification, filtering, and analog-to-digital conversion operations, the final discrete digital signal is the preprocessed signal, which can be directly input into the digital twin and inversion analysis calculation unit to participate in the subsequent electromagnetic wave backpropagation simulation calculation.

[0093] The present invention provides an insulation degradation location device for cable terminals, which, before performing electromagnetic wave back propagation simulation by injecting a pre-processed signal into a pre-set digital twin electromagnetic model of the cable terminal, further includes:

[0094] The preprocessed signal is denoised to obtain a new preprocessed signal.

[0095] The preprocessed signal is denoised to obtain a new preprocessed signal, including:

[0096] The preprocessed signal is subjected to a short-time Fourier transform to obtain the initial signal time-frequency matrix;

[0097] The initial signal time-frequency matrix is ​​subjected to soft threshold filtering to obtain the intermediate signal time-frequency matrix;

[0098] Singular value decomposition is performed on the time-frequency matrix of the intermediate signal to obtain the time-frequency matrix of the target signal;

[0099] The inverse short-time Fourier transform (ISFT) is performed on the time-frequency matrix of the target signal, and the IFT results are superimposed and added to obtain a new preprocessed signal.

[0100] In this embodiment of the invention, the preprocessed signal obtained by amplification, filtering, and analog-to-digital conversion corresponds to... Figure 5 The original signal in Although the signal has undergone preliminary conditioning, it still retains interference components such as environmental electromagnetic noise and circuit background noise. Directly using it for signal injection into the subsequent digital twin model would reduce simulation accuracy; therefore, it needs to be adjusted accordingly. Figure 5 The process performs noise reduction on it:

[0101] First, the preprocessed signal The present invention performs a short-time Fourier transform, which is a time-frequency analysis method that divides the long-time-domain preprocessed signal into multiple overlapping short time periods and performs Fourier transforms segment by segment. The formula is as follows: (in For time frame indexing, For frequency point indexing, Hanning window to reduce spectrum leakage For frame shift, (where the number of Fourier transform points is the number of points), this operation yields the initial signal time-frequency matrix of the present invention, which corresponds to... Figure 5 Complex spectrum matrix in Its elements are complex values, and the modulus represents the signal amplitude at the corresponding time-frequency point; then the initial signal time-frequency matrix is... To perform the soft threshold filtering of this invention, the noise standard deviation must first be calculated based on the noise segment of the preprocessed signal. Then set a threshold. Perform the operation on each element in the matrix: ( (where λ is the sign function), noise elements with a magnitude less than λ are set to zero, while the effective signal elements retain their trend and noise is attenuated. After processing, the intermediate signal time-frequency matrix of this invention is obtained, corresponding to... Figure 5 Complex spectrum matrix in Subsequently, the time-frequency matrix of the intermediate signal was... Performing the singular value decomposition of this invention decomposes a matrix into... ( For left singular matrices, For diagonal singular value matrices, (This is the conjugate transpose of the right singular matrix). The inflection point is determined by observing the singular value decay curve, and the preceding value is selected. After setting the large singular values ​​to zero and the remaining small singular values ​​to reconstruct the matrix, the time-frequency matrix of the target signal of this invention is obtained, which corresponds to the complex spectrum matrix in the image. ; then the time-frequency matrix of the target signal The formula for performing the inverse short-time Fourier transform of this invention is as follows: The time-frequency domain matrix is ​​transformed back into multiple overlapping short-time domain signal segments, which is the "inverse short-time Fourier transform result" of this invention. Figure 5 Time-domain signal set Finally, the overlap-addition operation of this invention is performed on these short time-domain signal segments, and they are superimposed according to the time overlap regions (the formula is...). To eliminate segment discontinuities, the final signal obtained is the new preprocessed signal of this invention, corresponding to... Figure 5 Noise-reduced time-domain signal This signal can accurately preserve the high-frequency harmonic characteristics of cable terminal insulation degradation, ensuring the accuracy of electromagnetic wave backpropagation simulation in subsequent digital twin electromagnetic models.

[0102] Please see Figure 7 The present invention provides a control method for an insulation degradation locating device applied to cable terminals, comprising:

[0103] Step 701: Acquire the high-frequency harmonic signal of the cable terminal under test using a single built-in ultra-high frequency sensor.

[0104] Step 702: Preprocess the high-frequency harmonic signal to obtain the preprocessed signal.

[0105] Step 703: Use the pre-processed signal to inject into the pre-set digital twin electromagnetic model of the cable terminal to perform electromagnetic wave back propagation simulation, and based on the simulation results, determine the insulation degradation location result of the cable terminal under test according to the pre-set positioning criteria.

[0106] Based on the above-mentioned device, the present invention provides a control method for locating insulation degradation in cable terminals. The core of the method lies in acquiring high-frequency harmonic signals generated by insulation degradation in the cable terminal using a single sensor, and performing electromagnetic time inversion processing on this signal in a digital twin model of the cable terminal. Utilizing the principle of spatiotemporal focusing of the inverted wave at the source of insulation degradation, the precise location of the degradation point is achieved.

[0107] Specifically, the method first creates a high-fidelity three-dimensional electromagnetic model of the cable terminal using a digital twin model building module. Then, a signal sensing unit captures high-frequency harmonic signals, which are then conditioned and digitized by a signal acquisition and processing unit. The signal processing and TR transformation module then denoises the digital signal and performs a time-inverse transformation. Next, the EMTR inversion simulation engine simulates the backpropagation of the signal within the digital twin model. Finally, the positioning and visualization output module analyzes the electromagnetic field distribution during backpropagation and determines the specific location of insulation degradation based on either the energy focusing criterion or the minimum entropy criterion, and visualizes the results. The energy focusing criterion locates the point by finding the location of the maximum electric field strength during backpropagation; while the minimum entropy criterion calculates the spatial disorder of the electric field distribution and identifies the location with the minimum entropy as the insulation degradation point. This method effectively suppresses false focus interference in the near-field region of the sensor.

[0108] This invention has the following advantages:

[0109] Significantly reduced cost and complexity: This invention innovatively uses a single sensor to accurately locate insulation degradation points, eliminating the need for multi-sensor arrays and complex time synchronization systems required by traditional methods, thus greatly reducing the hardware cost of the device and the complexity of on-site deployment.

[0110] Achieving deep integration with digital twins: This invention deeply integrates real signals collected by physical sensors with digital twin models of cable terminals. By performing electromagnetic time reversal simulation in this model, virtual spatial mapping and precise positioning of insulation status are achieved. This allows maintenance personnel to intuitively examine the exact location of insulation degradation points in the three-dimensional model, greatly improving the intuitiveness of status assessment and decision-making efficiency.

[0111] High positioning accuracy and strong anti-interference capability: The electromagnetic time reversal technology used in this invention has adaptive focusing capability for electromagnetic wave propagation in complex structures, unaffected by the propagation path. Combined with positioning criteria such as energy focusing or minimum entropy, it can effectively overcome the pseudo-focus problem that may exist in single-sensor schemes, and improve the signal-to-noise ratio by using noise reduction algorithms, thus achieving high-precision positioning of insulation degradation points even in strong noise environments.

[0112] Possesses early warning potential: This invention monitors and analyzes high-frequency harmonic signals generated in the early stages of insulation material aging and accurately locates their source points, providing a new means for early detection and warning of insulation defects in cable terminals. This helps to eliminate faults in their infancy and prevent problems before they occur.

[0113] Please see Figure 8 , Figure 8 This is a structural block diagram of an electronic device provided in an embodiment of the present invention.

[0114] An electronic device according to an embodiment of the present invention includes: a memory 801 and a processor 802. The memory 801 stores a computer program; when the computer program is executed by the processor 802, the processor 802 performs the control method as described in the above embodiment.

[0115] Memory 801 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. Memory 801 has storage space 803 for program code 813 for performing any of the method steps described above. For example, storage space 803 for program code may include various program codes 813 for implementing the various steps in the methods described above. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, CDs, memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When run by a computing processing device, this code causes the computing processing device to perform the various steps in the methods described above. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, CDs, memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When this code is run by a computing device, it causes the computing device to perform the various steps in the virtual impedance control parameter optimization method described above.

[0116] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the control method as described in the above embodiments.

[0117] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0118] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0119] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A device for locating insulation degradation of cable terminals, characterized in that, include: The signal sensing unit is used to acquire high-frequency harmonic signals from the cable terminal under test through a single built-in ultra-high frequency sensor. The signal acquisition and processing unit is used to preprocess the high-frequency harmonic signal to obtain a preprocessed signal; The digital twin and inversion analysis calculation unit is used to perform electromagnetic wave back propagation simulation by injecting the preprocessed signal into the preset digital twin electromagnetic model of the cable terminal, and to determine the insulation degradation location result of the cable terminal under test according to the preset positioning criteria based on the simulation results.

2. The insulation degradation locating device for cable terminals according to claim 1, characterized in that, The preset positioning criterion is either the energy focusing criterion or the minimum entropy criterion.

3. The insulation degradation locating device for cable terminals according to claim 2, characterized in that, The energy focusing criterion is as follows: The simulation results include the three-dimensional coordinates, electric field strength modulus, and electromagnetic energy density of each model mesh node; Extract all sampling point information within the effective analysis area of ​​the digital twin electromagnetic model of the pre-set cable terminal from the simulation results, and establish a coordinate-field quantity numerical mapping table. When the grid type of the pre-set cable terminal digital twin electromagnetic model is a structured grid, the field quantity values ​​of all grid nodes are traversed based on the coordinate-field quantity value mapping table, and the three-dimensional coordinates corresponding to the maximum field quantity value are selected as the spatial coordinates of the insulation degradation point of the cable terminal under test. When the grid type of the digital twin electromagnetic model of the pre-set cable terminal is an unstructured grid, the field quantity values ​​of all grid nodes are traversed based on the coordinate-field quantity value mapping table, and the grid cell containing the maximum field quantity value is selected as the target grid cell. Interpolate the target grid cell and calculate the field quantity values ​​of each interpolated sampling point within the interpolated target grid cell; The three-dimensional coordinates corresponding to the maximum field quantity value are selected from the interpolated target grid cells and determined as the spatial coordinates of the insulation degradation point of the cable terminal under test.

4. The insulation degradation locating device for cable terminals according to claim 2, characterized in that, The minimum entropy criterion is specifically as follows: The simulation results include the three-dimensional coordinates, electric field strength modulus, and electromagnetic energy density of each model mesh node; Extract all sampling point information within the effective analysis area of ​​the digital twin electromagnetic model of the pre-set cable terminal from the simulation results, and establish a coordinate-field quantity numerical mapping table. The sampling point information includes the three-dimensional coordinates, electric field strength modulus, and electromagnetic energy density of the effective grid nodes. The preset sliding analysis window moves position by position within the effective analysis area, and the field quantity values ​​of multiple window sampling points within each sliding analysis window are obtained from the coordinate-field quantity value mapping table. The field quantity values ​​at each sampling point of the window are normalized, and a probability distribution model of the field quantity values ​​corresponding to each sliding analysis window is constructed. Based on the probability distribution model of the field value, calculate the entropy value corresponding to each sliding analysis window; Based on the entropy values ​​described, the sliding analysis window corresponding to the minimum entropy value is selected as the insulation degradation location window; The three-dimensional coordinates of the center of the insulation degradation positioning window are determined as the spatial coordinates of the insulation degradation point of the cable terminal under test.

5. The insulation degradation locating device for cable terminals according to claim 1, characterized in that, The preprocessing of the high-frequency harmonic signal to obtain a preprocessed signal includes: The high-frequency harmonic signal is sequentially amplified, filtered, and converted from analog to digital to obtain a preprocessed signal.

6. The insulation degradation locating device for cable terminals according to any one of claims 1-5, characterized in that, Before performing electromagnetic wave back propagation simulation by injecting the pre-processed signal into the pre-set digital twin electromagnetic model of the cable terminal, the following steps are also included: The preprocessed signal is denoised to obtain a new preprocessed signal.

7. The insulation degradation locating device for cable terminals according to claim 6, characterized in that, The step of denoising the preprocessed signal to obtain a new preprocessed signal includes: Perform a short-time Fourier transform on the preprocessed signal to obtain the initial signal time-frequency matrix; The initial signal time-frequency matrix is ​​subjected to soft threshold filtering to obtain the intermediate signal time-frequency matrix; Singular value decomposition is performed on the intermediate signal time-frequency matrix to obtain the target signal time-frequency matrix; The target signal time-frequency matrix is ​​subjected to inverse short-time Fourier transform, and the results of the inverse short-time Fourier transform are superimposed and added to obtain a new preprocessed signal.

8. A control method for an insulation degradation locating device applied to a cable terminal according to any one of claims 1-7, characterized in that, include: High-frequency harmonic signals from the cable terminal under test are acquired using a single built-in ultra-high frequency sensor. The high-frequency harmonic signal is preprocessed to obtain a preprocessed signal; The preprocessed signal is injected into a pre-set digital twin electromagnetic model of the cable terminal to simulate the back propagation of electromagnetic waves. Based on the simulation results, the insulation degradation location result of the cable terminal under test is determined according to the pre-set positioning criteria.

9. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor causes the processor to perform the steps of the control method as described in claim 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the control method as described in claim 8.

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