Power transmission line repair decision-making method and system based on corona identification

Abstract

The invention relates to the technical field of power transmission line maintenance, in particular to a power transmission line repair decision-making method and system based on corona recognition, and the method specifically comprises the steps: importing a contact interface heat flux gradient, micromechanical vibration mode data and dynamic frequency domain corona fingerprint data into a robustness evaluation strategy for repairing a microgap breathing effect of a heterogeneous interface; calculating to obtain a dynamic stability weight index of the repair interface; establishing a kinetic model, inputting the dynamic frequency domain corona fingerprint data into the kinetic model, analyzing positive and negative half-cycle charge migration difference, and outputting a heterogeneous interface polarization discharge intensity index; and inputting the dynamic stability weight index of the repair interface and the polarization discharge intensity index of the heterogeneous interface into a repair quality subcritical evolution decision model, and identifying the false compliance risk of the power transmission line. According to the invention, the problem of flashover accidents caused by rapid degradation of insulation performance at the initial stage of commissioning of the repaired part in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of power transmission line maintenance technology, and is a power transmission line repair decision-making method and system based on corona recognition. Background Technology

[0002] With the increasing density of ultra-high voltage and extra-high voltage power grid construction in my country, transmission lines operate under complex multi-field coupling environments involving electricity, heat, and machinery. The quality of online repair of conductor strand breaks and hardware damage directly affects the safety baseline of the physical power grid. However, current repair assessment and decision-making methods still face the following technical bottlenecks when dealing with the heterogeneous interface formed by damaged conductors and repair pipes: First, existing detection methods mostly rely on the statistical analysis of the total number of ultraviolet photons or static infrared imaging, lacking in-depth exploration of the evolution and accumulation law of subcritical discharge pulses at the repair interface. This results in the inability to accurately identify deep-seated breakdown hazards caused by micro-displacement of the repair layer gap or thermodynamic mismatch. Second, existing assessment indicators often have a single dimensional system. Furthermore, the dimensionality imbalance makes it difficult to effectively correlate multi-dimensional physical indicators such as current density distribution, temperature rise gradient, and frequency domain corona fingerprint under a unified mathematical logic. This results in obvious logical breaks in cross-physical field coupling analysis, making it impossible to quantitatively characterize the nonlinear evolution process of the repair interface from slight degradation to avalanche failure. At the same time, the traditional repair process exhibits serious lag in the sensitivity identification of the repair layer shielding failure and the adaptive adjustment of repair parameters. It is difficult to provide accurate decision instructions under complex conductor galloping and load fluctuation conditions. This lack of dynamic evolution slope perception and multi-dimensional criterion coupling makes it very easy for the repaired part to experience flashover accidents due to rapid degradation of insulation performance in the early stage of operation. Summary of the Invention

[0003] The technical problem to be solved by this invention is that, in the prior art, flashover accidents occur in the repaired parts due to rapid degradation of insulation performance in the early stage of operation. The invention proposes a transmission line repair decision-making method and system based on corona identification.

[0004] To achieve the above objectives, the technical solution of the transmission line repair decision-making method based on corona identification of the present invention includes the following steps: Obtain the ideal corona distribution envelope of the transmission line under healthy operating conditions as the original comparison benchmark after repair; periodically collect dynamic frequency domain corona fingerprint data of the repaired area after grid connection; and simultaneously acquire the heat flux gradient of the contact interface and micromechanical vibration mode data of the repaired area. The heat flux gradient of the contact interface, micromechanical vibration modal data and dynamic frequency domain corona fingerprint data are imported into the robustness assessment strategy of microgap breathing effect for repairing heterogeneous interfaces, and the dynamic stability weight index of the repaired interface is calculated. A dynamic model of asymmetric space charge accumulation at the heterogeneous interface of new and old materials in the repair area is established. Dynamic frequency domain corona fingerprint data is input into the dynamic model to analyze the difference in charge migration between positive and negative half cycles and output the polarization discharge intensity index of the heterogeneous interface in the repair area. The dynamic stability weight index of the repair interface and the polarization discharge intensity index of the heterogeneous interface are input into the subcritical evolution decision model of repair quality to identify the false compliance risk of the transmission line and issue operation and maintenance decision instructions for the repair area.

[0005] Preferably, the ideal corona distribution envelope is specifically: a full-phase corona characteristic spectrum of the repaired region under ideal contact conditions based on Maxwell's electromagnetic field simulation, and the specific steps are as follows: S11: Extract the work function of the hardware material used in the repair area and the oxidation degree distribution of the old wire substrate to determine the range of contact potential difference at the repair interface; S12: Construct a three-dimensional electric field vector model of the repair area based on the line voltage level, and simulate and calculate the reference value of the electric field distortion rate at the junction of the new and old metals under the preset fastening pressure. S13: Calculate and obtain the symmetric distribution probability density function of the full-phase ultraviolet pulse under ideal repair conditions. , as a baseline spectrum.

[0006] Preferably, dynamic frequency domain corona fingerprint data of the repair area after grid connection is periodically collected; the heat flux gradient of the contact interface and micromechanical vibration mode data of the repair area are acquired simultaneously, specifically including: in the 240nm-280nm solar-blind ultraviolet band, the reference spectrum of the corona pulse within a unit period is collected, and the phase distribution skewness and the imbalance rate of the positive and negative half-cycle energy envelope of the corona pulse within a unit period are extracted; Real-time monitoring of the local temperature rise gradient at both ends of the repair pipe and the frequency of interfacial alternating stress caused by conductor galloping .

[0007] Preferably, the robustness assessment strategy for the micro-gap breathing effect of the repaired heterogeneous interface includes: S21: Calculate the micro-displacement variation coefficient of the heterogeneous interface based on the thermal cycle caused by load changes; S22: By using real-time phase maps Compared with the baseline spectrum Perform phase correlation matching to extract phase drift. Calculate the corona response following index of the repair interface; S23: Based on the evolution of the equivalent contact resistance at the interface of the repaired area, calculate the electrochemical shielding failure coefficient of the repaired area within the j-th unit time. .

[0008] Preferably, the calculation strategy for the dynamic stability weight index of the repair interface is as follows: First, obtain the corona response following index of the repair interface; The heterogeneous interface micro-displacement variation coefficient and the electrochemical shielding failure coefficient are then nonlinearly multiplied and coupled, and the risk penalty base of the transmission line repair interface is constructed by exponentializing the natural constant. Then, the corona response following index of the repaired interface is divided by the sum of the risk penalty base and 1 to obtain the dynamic stability weight index of the repaired interface. .

[0009] Preferably, the dynamic model of the asymmetric space charge accumulation includes: S31: Extract the energy level deviation at the maximum point of the discharge phase during the positive and negative half-cycles of the voltage, and calculate the polarization asymmetry component. ; S32: Based on the thermionic emission effect and combined with interfacial heat flux, calculate the subcritical discharge evolution slope induced by local defects. ; S33: Derive the polarization asymmetry component and the subcritical discharge evolution slope, and calculate the repair consistency evolution factor.

[0010] Preferably, the strategy for obtaining the heterojunction polarization discharge intensity index is as follows: First, the polarization asymmetry component and the subcritical discharge evolution slope are weighted and summed according to a preset weight ratio to construct the basic energy base of the interface discharge characteristics. Then, the basic energy base is multiplied by the natural constant exponential function with the participation of the repair consistency evolution factor to finally obtain the heterogeneous interface polarization discharge intensity index. .

[0011] Preferably, the subcritical evolutionary decision model for repair quality includes: S51: Construct a function to improve health and repair efficiency. ; S52: If If the value is less than 0.65, a latent defect alarm will be automatically triggered. S53: Based on Based on the rate of change of the monitoring cycle, predict the performance evolution trend within the next maintenance cycle and generate a prediction sequence for the effectiveness of repair quality. S54: Map the predicted sequence generated in S53 to specific on-site corrective actions.

[0012] In addition, the transmission line repair decision system based on corona recognition of the present invention includes the following modules: Heterogeneous interface fingerprint acquisition module, multi-field stability assessment module, asymmetric charge dynamic analysis module, and differentiated operation and maintenance instruction execution module; The heterogeneous interface fingerprint acquisition module is used to acquire the ideal corona distribution envelope of the transmission line under healthy operating conditions, as the original comparison benchmark after repair; periodically acquire dynamic frequency domain corona fingerprint data of the repair area after grid connection; and simultaneously acquire the heat flux gradient of the contact interface and micromechanical vibration mode data of the repair area. The multi-field stability assessment module is used to import the heat flux gradient of the contact interface, micromechanical vibration modal data and dynamic frequency domain corona fingerprint data into the robustness assessment strategy of micro-gap breathing effect for repairing heterogeneous interfaces, and calculate and obtain the dynamic stability weight index of the repair interface. The asymmetric charge dynamic analysis module is used to establish a dynamic model of asymmetric space charge accumulation at the heterogeneous interface of new and old materials in the repair area. The dynamic frequency domain corona fingerprint data is input into the dynamic model to analyze the difference in charge migration between positive and negative half cycles and output the polarization discharge intensity index of the heterogeneous interface in the repair area. The differentiated operation and maintenance instruction execution module is used to input the dynamic stability weight index of the repair interface and the polarization discharge intensity index of the heterogeneous interface into the subcritical evolution decision model of repair quality, identify the false compliance risk of the transmission line, and issue operation and maintenance decision instructions for the repair area.

[0013] Compared with the prior art, the technical effects of the present invention are as follows: 1. This invention breaks through the limitations of traditional methods that rely solely on photon count statistics or static images. By introducing deep frequency domain corona fingerprint data acquisition and subcritical evolution feature recognition, it achieves cross-time domain perception of subtle physical changes in repaired heterogeneous interfaces. It can keenly capture latent degradation trends caused by thermodynamic mismatch, micro-displacement changes, or charge accumulation, solving the problem of insufficient sensitivity of existing technologies for identifying early deep defects in repaired interfaces and significantly reducing false alarm and false negative rates.

[0014] 2. This invention constructs a dynamic stability assessment and discharge intensity coupling criterion. By mapping the interaction between mechanical follow-up compensation capability and ionization energy distribution in real time, it realizes the on-demand allocation and precise control of repair process parameters such as repair tube tightening torque and insulation coating thickness, which greatly improves the long-term reliability of physical and electrical connections at heterogeneous interfaces.

[0015] 3. By monitoring the nonlinear evolution process from micro-displacement changes to avalanche-like bursts of ion flow at the interface, this invention effectively curbs flashover and strand breakage accidents of transmission lines under complex large load fluctuations or extreme weather conditions. This not only maximizes the remaining service life of damaged conductors, but also significantly reduces the emergency operation and maintenance costs and the risk of large-scale power outages in UHV power grids, providing technical support for the refined maintenance of smart grid infrastructure. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments 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. Wherein: Figure 1 This is a flowchart illustrating the transmission line repair decision-making method based on corona recognition of the present invention. Figure 2 This is a schematic diagram of the transmission line repair decision system based on corona recognition according to the present invention. Detailed Implementation

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0018] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0019] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0020] Example 1: like Figure 1 As shown in the figure, the transmission line repair decision method based on corona recognition according to an embodiment of the present invention includes the following specific steps: Obtain the ideal corona distribution envelope of the transmission line under healthy operating conditions as the original comparison benchmark after repair; periodically collect dynamic frequency domain corona fingerprint data of the repaired area after grid connection; and simultaneously acquire the heat flux gradient of the contact interface and micromechanical vibration mode data of the repaired area. For example, in this embodiment, the repair area is the pre-twisted wire repair section or the joint of the repair pipe of the ultra-high voltage conductor; It should be noted that the dynamic frequency domain corona fingerprint data is used to capture the weak discharge characteristics of the interface between new and old materials; the heat flux gradient of the contact interface and the micromechanical vibration mode data of the repair area are used to characterize the mechanical stress and thermodynamic dynamics of the repair site. The ideal corona distribution envelope is specifically: a full-phase corona characteristic spectrum of the repaired region under ideal contact conditions based on Maxwell's electromagnetic field simulation, and the specific steps are as follows: S11: Extract the work function of the hardware material used in the repair area and the oxidation degree distribution of the old wire substrate to determine the range of contact potential difference at the repair interface; It should be noted that the extracted material work function and oxidation degree factor directly affect the initial discharge phase of the reference spectrum. and peak phase Initial discharge phase The specific method for determining it is as follows: Peak phase The determination method is as follows: the oxidation factor of the old conductor substrate is defined as [0,1]. When there is a significant oxide layer at the interface, the oxidation factor approaches 1, and the standard deviation is increased by 15%~25% based on the original simulation.

[0021] S12: Construct a three-dimensional electric field vector model of the repair area based on the line voltage level, and simulate and calculate the reference value of the electric field distortion rate at the junction of the new and old metals under the preset fastening pressure. In this embodiment, the ratio of the maximum local field strength to the uniform field strength at the boundary is calculated using simulation to obtain the reference value K of the field strength distortion rate. Mapping the field strength distortion rate benchmark value to a field strength correction coefficient based on the roughness vector of the repaired material. , .

[0022] S13: Calculate and obtain the symmetric distribution probability density function of the full-phase ultraviolet pulse under ideal repair conditions. , as a baseline spectrum.

[0023] In this embodiment, the formula for calculating the probability density function of the symmetric distribution of the full-phase ultraviolet pulse is as follows: ; in, The phase angle of the power frequency voltage; The reference starting discharge phase; The standard deviation of the phase distribution; This is the field strength correction coefficient based on the roughness vector of the repaired material.

[0024] Periodically collect dynamic frequency domain corona fingerprint data of the repair area after it is connected to the grid; simultaneously acquire the heat flux gradient of the contact interface and micromechanical vibration mode data of the repair area, specifically including: in the 240nm-280nm solar blind ultraviolet band, collect the reference spectrum of the corona pulse within a unit period, and extract the phase distribution skewness and the imbalance rate of the positive and negative half-cycle energy envelope of the corona pulse within a unit period; Real-time monitoring of the local temperature rise gradient at both ends of the repair tube using distributed optical fiber or acoustic wave sensors. and the frequency of interfacial alternating stress caused by conductor galloping .

[0025] The heat flux gradient of the contact interface, micromechanical vibration modal data and dynamic frequency domain corona fingerprint data are imported into the robustness assessment strategy of microgap breathing effect for repairing heterogeneous interfaces, and the dynamic stability weight index of the repaired interface is calculated. It should be noted that, in this embodiment, the robustness assessment strategy for repairing the micro-gap breathing effect of heterogeneous interfaces aims to quantify the degree of micron-level gap opening and closing caused by load fluctuations. The robustness assessment strategy for the micro-gap breathing effect of the repaired heterogeneous interface includes: S21: In this embodiment, considering that the repair parts of the transmission line are made of different materials than the conductor substrate, the micro-displacement variation coefficient of the heterogeneous interface is calculated based on the thermal cycle caused by load changes. It should be noted that the coefficient of variation of micro-displacement at the heterogeneous interface The computational strategy aims to quantify the fluctuations in physical gaps caused by the microgap breathing effect, as follows: ; in, The coefficient of linear expansion; This represents a local temperature gradient. The axial length of the contact surface For the thickness of the repair layer; The frequency of the interfacial alternating stress; This refers to the maximum permissible frequency for transmission lines. It should be noted that the term on the left side of the formula characterizes the theoretical shear strain caused by interfacial thermal mismatch through the product of the difference in linear expansion coefficients and the local temperature rise; combined with the geometric mapping of the axial length of the contact surface and the initial pressing gap, the weakening strength of the microgap breathing effect on the interface stability is quantified, and a frequency logarithmic correction term is introduced to reflect the nonlinear decay characteristics of the fatigue degradation rate of the metal heterogeneous interface due to high-frequency vibration.

[0026] S22: By using real-time phase maps Compared with the baseline spectrum Perform phase correlation matching to extract phase drift. Calculate the corona response following index of the repair interface; It should be noted that the corona response following the repair interface is exponential. It characterizes the degree to which discharge activity follows load thermal cycling, and aims to identify latent gaps affected by the microgap breathing effect. The specific calculation strategy is as follows: ; in, These are the load sensitivity factor and the phase offset weighting coefficient, respectively. For ultraviolet pulse counting, This represents the relative rate of change of the pulse. It is the relative rate of change of the load temperature rise dynamic; The reference phase width; It should be noted that the relative rate of change ratio is used in this embodiment to eliminate static interference such as environmental humidity. If the increase in synchronous pulses is caused by the increase in load, it indicates that the corona source is caused by the breathing gap generated by thermal expansion and contraction.

[0027] S23: Based on the evolution of the equivalent contact resistance at the interface of the repaired area, calculate the electrochemical shielding failure coefficient of the repaired area within the j-th unit time. ; In this embodiment, an electrochemical shielding failure coefficient is provided. The acquisition strategy is as follows: ; in, For real-time contact resistance; The resistance of the main conductor; For surface equivalent salt density; The baseline cleanliness coefficient.

[0028] It should be noted that in electrochemical corrosion, an increase in resistance means an exponential increase in the oxide layer or a decrease in the effective contact area. At the same time, salt is a catalyst for the formation of conductive liquid film and electrochemical corrosion. The higher the salt density, the worse the chemical stability of the shielding layer.

[0029] The calculation strategy for the dynamic stability weight index of the repair interface is as follows: First, obtain the corona response following index of the repair interface, which characterizes the corona discharge features of the repair interface and changes synchronously with load fluctuations, to determine the original controlled state of the repair interface in the electromagnetic environment. The coefficient of micro-displacement variation at the heterogeneous interface, which characterizes the thermal mismatch between the old and new materials, is coupled nonlinearly with the coefficient of electrochemical shielding failure caused by the evolution of contact resistance. The risk penalty base for the transmission line repair interface is then constructed by exponentializing the natural constant. Then, the corona response following index of the repaired interface is divided by the sum of the risk penalty base and 1 to obtain the dynamic stability weight index of the repaired interface. .

[0030] It should be noted that the dynamic stability weight index of the repair interface can comprehensively quantify the physical bonding force and electrical performance durability of the repair area under complex operating conditions.

[0031] A dynamic model of asymmetric space charge accumulation at the heterogeneous interface of new and old materials in the repair area is established. Dynamic frequency domain corona fingerprint data is input into the dynamic model to analyze the difference in charge migration between positive and negative half cycles and output the polarization discharge intensity index of the heterogeneous interface in the repair area. The dynamic model of the asymmetric space charge accumulation includes: S31: Extract the energy level deviation at the maximum point of the discharge phase during the positive and negative half-cycles of the voltage, and calculate the polarization asymmetry component. ; The polarization asymmetry component is used to reflect the difference in the interface work function, and its calculation strategy is as follows: ; in, For real-time ultraviolet energy density, it should be noted that... The aim is to detect pseudo-repair states that appear to be perfectly repaired but actually have internal electric field distortions; It should be noted that under alternating current, if the interface between the old and new materials is completely symmetrical (i.e. the work function is consistent), the discharge characteristics of the positive and negative half-cycles should be symmetrical. If there is a mismatch in the work function, the difficulty of electrons being emitted from the old material to the new material and in the opposite direction is different, which will lead to an imbalance in energy distribution. Subtraction is to extract the deviation caused by this polarity effect.

[0032] S32: Based on the thermionic emission effect and combined with interfacial heat flux, calculate the subcritical discharge evolution slope induced by local defects. ; The subcritical discharge evolution slope is intended to reflect the discharge growth rate, and its calculation strategy is as follows: ; Where A is Richardson's constant; k is Boltzmann's constant; and T is the real-time monitoring temperature of the repair interface. To fix the overall escape function of the interface; This is the Schottky correction term, where e is the elementary charge. It is the vacuum permittivity; The value represents the local field distortion at the interface simulated in S12. These are the reference current density and the reference pulse number, respectively. The rate of increase of the corona pulse over time; It should be noted that this parameter quantifies the risk of subcritical discharge caused by the microscopic contact points between new and old materials. Since the probability of electrons detaching from the metal surface increases exponentially with increasing temperature and electric field, the exponential part is used to capture the nonlinear characteristics of the interface deterioration caused by the temperature rise.

[0033] S33: The polarization asymmetry component and the subcritical discharge evolution slope are derived, and the repair consistency evolution factor is calculated as follows: ; in, This is the line's rated voltage. For real-time operating voltage, The preset critical breakdown slope is used. It should be noted that CEI, as the repair consistency evolution factor, reflects the rate at which the repair quality decays with the time it is connected to the grid.

[0034] It should be noted that, The degree of distortion representing the properties of the interface is a static indicator; The slope rate, representing defect growth, is a dynamic indicator, particularly important in multiphysics fusion. The time dimension is included, and the square is used to increase its weight in the evaluation model; for If the operating voltage It was very low, but significant discharge and evolution still occurred. This ratio will be very large, thus drastically amplifying the final repair consistency evolution factor.

[0035] The strategy for obtaining the polarization discharge intensity index at the heterogeneous interface is as follows: First, the polarization asymmetry component and the subcritical discharge evolution slope are weighted and summed according to a preset weight ratio to construct the basic energy base of the interface discharge characteristics. Then, the basic energy base is multiplied by the natural constant exponential function with the participation of the repair consistency evolution factor to finally obtain the heterogeneous interface polarization discharge intensity index. .

[0036] It should be noted that the heterojunction polarization discharge intensity index is used to assess whether there is an invisible subcritical discharge intensity at the repair site due to poor bonding of heterojunction materials.

[0037] The dynamic stability weight index of the repair interface and the polarization discharge intensity index of the heterogeneous interface are input into the subcritical evolution decision model of repair quality to identify the risk of false compliance of transmission lines caused by insufficient repair accuracy, and to issue operation and maintenance decision instructions for the repair area.

[0038] S51: Construct a function to improve health and repair efficiency. ; It should be noted that, Used to characterize the initial stability weights, while Used to characterize the health margin of transmission lines; S52: If If the value is less than 0.65, a latent defect alarm will be automatically triggered. S53: Based on Based on the rate of change of the monitoring cycle, predict the performance evolution trend within the next maintenance cycle and generate a prediction sequence for the effectiveness of repair quality. For example, in this embodiment, a specific implementation of step S53 is provided as follows: First, the time-domain difference algorithm is used to calculate... The first-order evolution slope within adjacent monitoring cycles is used to quantify the rate of performance degradation of the repaired part as the running time increases; Then, the first-order evolution slope is used as the input feature and substituted into the preset rolling time-domain prediction model (i.e., gray prediction model). Combined with the original performance state of the current cycle, the performance parameters of each time node in the future maintenance cycle are modeled nonlinearly. Then, the performance evaluation forecasts obtained from extrapolation at each discrete time point are linearly recombined along the time dimension to finally obtain the repair quality effectiveness prediction sequence.

[0039] S54: Map the predicted sequence generated in S53 to specific on-site corrective actions.

[0040] For example, in this embodiment, S54 includes: If the dynamic stability weight index of the interface is repaired If the value is below the threshold, a mechanical reinforcement command for secondary reinforcement of the pre-twisted wire is output. Specifically, it includes: ; in, This refers to the final mechanical fastening target torque value; The standard rated tightening torque reference value designed for the repaired part; This is the mechanical stiffness mapping coefficient; In this embodiment, The preferred value range is 0.2-0.6. Specifically, when the repair part is made of aluminum alloy, The value is 0.35; when high-strength steel is used, due to the material's high rigidity, The value is 0.5. This coefficient is obtained by fitting a pre-established preload-interface contact resistance mapping curve, which aims to ensure that torque compensation can both repair the instability loss and not exceed the yield limit of the material.

[0041] If the polarization discharge intensity index of the heterostructure interface If the value continues to rise, an instruction will be output to adjust the coating thickness of the sprayed semi-conductive interface. Specifically, it includes: ; The target coating thickness instruction for the electric field homogenization layer at the heterogeneous interface in the repair area; Preset minimum process coating thickness; The dielectric polarization compensation factor reflects the coating material's ability to neutralize charge accumulation. In this embodiment, This reflects the increase in shielding layer thickness required per unit discharge intensity, and a recommended value range is 0.01mm-0.1mm. For example, if a nano-silicon carbide-modified semiconductive coating is used, its dielectric polarization neutralization capability is strong. The value is 0.03 mm. In this embodiment, this value was obtained by measuring multiple sets of corona initiation voltage experimental data under different coating thicknesses in a laboratory environment.

[0042] Example 2: like Figure 2 As shown in the figure, the transmission line repair decision system based on corona recognition according to an embodiment of the present invention includes the following modules: Heterogeneous interface fingerprint acquisition module, multi-field stability assessment module, asymmetric charge dynamic analysis module, and differentiated operation and maintenance instruction execution module; The heterogeneous interface fingerprint acquisition module is used to acquire the ideal corona distribution envelope of the transmission line under healthy operating conditions, as the original comparison benchmark after repair; periodically acquire dynamic frequency domain corona fingerprint data of the repair area after grid connection; and simultaneously acquire the heat flux gradient of the contact interface and micromechanical vibration mode data of the repair area. The multi-field stability assessment module is used to import the heat flux gradient of the contact interface, micromechanical vibration modal data and dynamic frequency domain corona fingerprint data into the robustness assessment strategy of micro-gap breathing effect for repairing heterogeneous interfaces, and calculate and obtain the dynamic stability weight index of the repair interface. The asymmetric charge dynamic analysis module is used to establish a dynamic model of asymmetric space charge accumulation at the heterogeneous interface of new and old materials in the repair area. The dynamic frequency domain corona fingerprint data is input into the dynamic model to analyze the difference in charge migration between positive and negative half cycles and output the polarization discharge intensity index of the heterogeneous interface in the repair area. The differentiated operation and maintenance instruction execution module is used to input the dynamic stability weight index of the repair interface and the polarization discharge intensity index of the heterogeneous interface into the subcritical evolution decision model of repair quality, identify the false compliance risk of the transmission line, and issue operation and maintenance decision instructions for the repair area.

[0043] Example 3: This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the aforementioned transmission line repair decision-making method based on corona recognition by calling the computer program stored in memory.

[0044] The electronic device can vary considerably depending on its configuration or performance. It may include one or more Central Processing Units (CPUs) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the corona identification-based transmission line repair decision-making method provided in the above-described embodiment. The electronic device may also include other components for implementing its functions; for example, it may have wired or wireless network interfaces and input / output interfaces for data input and output. Further details are omitted in this embodiment.

[0045] Example 4: This embodiment proposes a computer-readable storage medium on which an erasable and rewritable computer program is stored. When the computer program runs on the computer device, it causes the computer device to execute the aforementioned power line repair decision-making method based on corona recognition.

[0046] For example, computer-readable storage media can be read-only memory (ROM), random access memory (RAM), compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage devices.

[0047] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0048] It should be understood that determining B based on A does not mean determining B solely based on A; it also means determining B based on A and / or other information.

[0049] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network and / or wireless network. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives (SSDs).

[0050] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0051] Those skilled in the art will 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.

[0052] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0053] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

Claims

1. A transmission line repair decision-making method based on corona recognition, characterized in that, The method includes: Obtain the ideal corona distribution envelope of the transmission line under healthy operating conditions as the original comparison benchmark after repair; periodically collect dynamic frequency domain corona fingerprint data of the repaired area after grid connection; and simultaneously acquire the heat flux gradient of the contact interface and micromechanical vibration mode data of the repaired area. The heat flux gradient of the contact interface, micromechanical vibration modal data and dynamic frequency domain corona fingerprint data are imported into the robustness assessment strategy of microgap breathing effect for repairing heterogeneous interfaces, and the dynamic stability weight index of the repaired interface is calculated. A dynamic model of asymmetric space charge accumulation at the heterogeneous interface of new and old materials in the repair area is established. Dynamic frequency domain corona fingerprint data is input into the dynamic model to analyze the difference in charge migration between positive and negative half cycles and output the polarization discharge intensity index of the heterogeneous interface in the repair area. The dynamic stability weight index of the repair interface and the polarization discharge intensity index of the heterogeneous interface are input into the subcritical evolution decision model of repair quality to identify the false compliance risk of the transmission line and issue operation and maintenance decision instructions for the repair area.

2. The transmission line repair decision-making method based on corona recognition according to claim 1, characterized in that, The ideal corona distribution envelope is specifically: a full-phase corona characteristic spectrum of the repaired region under ideal contact conditions based on Maxwell's electromagnetic field simulation, and the specific steps are as follows: S11: Extract the work function of the hardware material used in the repair area and the oxidation degree distribution of the old wire substrate to determine the range of contact potential difference at the repair interface; S12: Construct a three-dimensional electric field vector model of the repair area based on the line voltage level, and simulate and calculate the reference value of the electric field distortion rate at the junction of the new and old metals under the preset fastening pressure. S13: Calculate and obtain the symmetric distribution probability density function of the full-phase ultraviolet pulse under ideal repair conditions. , as a baseline spectrum.

3. The transmission line repair decision-making method based on corona recognition according to claim 2, characterized in that, Periodically collect dynamic frequency domain corona fingerprint data of the repair area after it is connected to the grid; simultaneously acquire the heat flux gradient of the contact interface and micromechanical vibration mode data of the repair area, specifically including: in the 240nm-280nm solar blind ultraviolet band, collect the reference spectrum of the corona pulse within a unit period, and extract the phase distribution skewness and the imbalance rate of the positive and negative half-cycle energy envelope of the corona pulse within a unit period; Real-time monitoring of the local temperature rise gradient at both ends of the repair pipe and the frequency of interfacial alternating stress caused by conductor galloping .

4. The transmission line repair decision-making method based on corona recognition according to claim 3, characterized in that, The robustness assessment strategy for the micro-gap breathing effect of the repaired heterogeneous interface includes: S21: Calculate the micro-displacement variation coefficient of the heterogeneous interface based on the thermal cycle caused by load changes; S22: By using real-time phase maps Compared with the baseline spectrum Perform phase correlation matching to extract phase drift. Calculate the corona response following index of the repair interface; S23: Based on the evolution of the equivalent contact resistance at the interface of the repaired area, calculate the electrochemical shielding failure coefficient of the repaired area within the j-th unit time. .

5. The transmission line repair decision-making method based on corona recognition according to claim 4, characterized in that, The calculation strategy for the dynamic stability weight index of the repair interface is as follows: First, obtain the corona response following index of the repair interface; The heterogeneous interface micro-displacement variation coefficient and the electrochemical shielding failure coefficient are then nonlinearly multiplied and coupled, and the risk penalty base of the transmission line repair interface is constructed by exponentializing the natural constant. Then, the corona response following index of the repaired interface is divided by the sum of the risk penalty base and 1 to obtain the dynamic stability weight index of the repaired interface. .

6. The transmission line repair decision-making method based on corona recognition according to claim 5, characterized in that, The dynamic model of the asymmetric space charge accumulation includes: S31: Extract the energy level deviation at the maximum point of the discharge phase during the positive and negative half-cycles of the voltage, and calculate the polarization asymmetry component. ; S32: Based on the thermionic emission effect and combined with interfacial heat flux, calculate the subcritical discharge evolution slope induced by local defects. ; S33: Derive the polarization asymmetry component and the subcritical discharge evolution slope, and calculate the repair consistency evolution factor.

7. The transmission line repair decision-making method based on corona recognition according to claim 6, characterized in that, The strategy for obtaining the polarization discharge intensity index at the heterogeneous interface is as follows: First, the polarization asymmetry component and the subcritical discharge evolution slope are weighted and summed according to a preset weight ratio to construct the basic energy base of the interface discharge characteristics. Then, the basic energy base is multiplied by the natural constant exponential function with the participation of the repair consistency evolution factor to finally obtain the heterogeneous interface polarization discharge intensity index. .

8. The transmission line repair decision-making method based on corona recognition according to claim 7, characterized in that, The subcritical evolutionary decision model for repair quality includes: S51: Construct a function to improve health and repair efficiency. ; S52: If If the value is less than 0.65, a latent defect alarm will be automatically triggered. S53: Based on Based on the rate of change of the monitoring cycle, predict the performance evolution trend within the next maintenance cycle and generate a prediction sequence for the effectiveness of repair quality. S54: Map the predicted sequence generated in S53 to specific on-site corrective actions.

9. A transmission line repair decision system based on corona recognition, used to implement the transmission line repair decision method based on corona recognition as described in any one of claims 1-8, characterized in that, The system includes: Heterogeneous interface fingerprint acquisition module, multi-field stability assessment module, asymmetric charge dynamic analysis module, and differentiated operation and maintenance instruction execution module; The heterogeneous interface fingerprint acquisition module is used to acquire the ideal corona distribution envelope of the transmission line under healthy operating conditions, as the original comparison benchmark after repair; periodically acquire dynamic frequency domain corona fingerprint data of the repair area after grid connection; and simultaneously acquire the heat flux gradient of the contact interface and micromechanical vibration mode data of the repair area. The multi-field stability assessment module is used to import the heat flux gradient of the contact interface, micromechanical vibration modal data and dynamic frequency domain corona fingerprint data into the robustness assessment strategy of micro-gap breathing effect for repairing heterogeneous interfaces, and calculate and obtain the dynamic stability weight index of the repair interface. The asymmetric charge dynamic analysis module is used to establish a dynamic model of asymmetric space charge accumulation at the heterogeneous interface of new and old materials in the repair area. The dynamic frequency domain corona fingerprint data is input into the dynamic model to analyze the difference in charge migration between positive and negative half cycles and output the polarization discharge intensity index of the heterogeneous interface in the repair area. The differentiated operation and maintenance instruction execution module is used to input the dynamic stability weight index of the repair interface and the polarization discharge intensity index of the heterogeneous interface into the subcritical evolution decision model of repair quality, identify the false compliance risk of the transmission line, and issue operation and maintenance decision instructions for the repair area.

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