Lightning arrester insulation protection method

Abstract

The invention discloses a lightning arrester insulation protection method, and relates to the technical field of electric power insulation protection. The method comprises the following steps: generating a comprehensive insulation risk index based on collected insulation state parameters; determining repair permeability according to material structure characteristics, and constructing an electric field compensation factor in combination with running electric field distribution; performing periodic data accumulation and analysis on the comprehensive insulation risk index, the repair permeability strength and the electric field compensation factor to generate a long-term life prediction result covering the operation cycle, the material sub-region and the sampling point; and the service life prediction result corresponds to an insulation protection management module, and partition-level service life management and operation risk early warning are realized. Precise life prediction is realized through multi-dimensional data fusion, sub-region differential protection is supported, and the consistency of an operation period and a repair strategy is maintained, so that the reliability and stability of long-term operation of the lightning arrester are comprehensively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric power insulation protection, in particular to an insulating protection method for a lightning arrester. BACKGROUND

[0002] Lightning arresters play a key role in power systems, and their main function is to ensure the safe operation of power equipment and lines under lightning and overvoltage impact. Existing lightning arresters mainly rely on the performance and structure design of their own insulation materials to cope with the influence of electric field, temperature, humidity and other environmental factors. However, with the widespread application of high-voltage power transmission systems and the emergence of complex climate conditions, traditional lightning arresters still face significant technical challenges in long-term operation.

[0003] During operation, abnormal phenomena such as micro-cracks, local hot spots, charge accumulation or contamination may occur on the insulation surface, and existing technologies lack real-time monitoring means for these local conditions, making it difficult to discover local weakening and potential discharge risks in a timely manner. At the same time, environmental factors such as humidity, temperature, wind speed and rainfall have a complex nonlinear coupling effect on the performance of insulation materials, and existing technologies often do not fully consider the dynamic coupling effect of environment and materials when evaluating insulation state, making it difficult to accurately reflect the actual risk distribution on the insulation surface.

[0004] In addition, traditional insulation protection methods mainly rely on inherent material properties or regular maintenance, and lack active protection and repair mechanisms based on risk assessment. When the insulation surface damage or environmental stress accumulates to a certain extent, it is only then that it is discovered and handled, and this lag may lead to irreversible damage. Existing life prediction methods rely mainly on macroscopic empirical data or static models, and it is difficult to consider the comprehensive influence of local insulation state, environmental coupling conditions and historical repair records at the same time, so the prediction accuracy is limited, and it is difficult to provide reliable basis for operation and maintenance and replacement decisions.

[0005] Therefore, the existing technology cannot realize multi-dimensional real-time monitoring of the insulation surface state of the lightning arrester, local risk assessment, active repair and electric field optimization, and long-term life prediction. This technical deficiency limits the reliability and safety of high-voltage power system operation. In order to solve the above problems, an intelligent protection method that can integrate insulation state, environmental factors and repair mechanisms is urgently needed. SUMMARY

[0006] Based on the shortcomings of the existing technology described above, the purpose of the present application is to provide an insulating protection method for a lightning arrester to solve the above technical problems.

[0007] To achieve the above purpose, the present application provides the following technical solution: an insulating protection method for a lightning arrester, comprising: Multi-modal data of the insulating surface of the lightning arrester is collected, including surface geometric disturbance information, local heat distribution information and surface charge accumulation information obtained through sensors, and the collected multi-modal data is converted into a surface disturbance index; According to the surface disturbance index, the insulating surface of the lightning arrester is divided into a preset number of material sub-regions, and the surface disturbance index of each material sub-region is combined non-linearly to generate an insulating stress energy; Multi-dimensional data of the operating environment of the lightning arrester is obtained, including humidity, temperature, wind speed and rainfall, and the environmental data and the insulating stress energy of each material sub-region are fused to generate an environmental stress factor representing the coupling state of the environment and the material at the corresponding time and corresponding region; The environmental stress factor is accumulated and combined to generate a comprehensive insulating risk index, and when the comprehensive insulating risk index is greater than a preset protection threshold, a protection trigger signal is generated; According to the protection trigger signal, a repair mechanism is activated to process the insulating surface through a repair medium to generate a repair penetration strength, each repair penetration strength corresponding to a specific material sub-region and a sampling point, representing the distribution and degree of action of the repair medium at the position; The repair penetration strength and the environmental stress factor are combined to generate an electric field compensation factor, which is mapped to the coverage area corresponding to each electrode to determine the adjustment amplitude and direction of each electrode, and the output of the electrode is adjusted to optimize the electric field distribution of the insulating surface; Based on the comprehensive insulating risk index, the repair penetration strength and the electric field compensation factor, periodic data accumulation and analysis are performed to generate a local life attenuation index, the local life attenuation indexes are integrated to generate a life attenuation index, and the life attenuation index is non-linearly accumulated and mapped to a life prediction result, each life prediction result corresponding to an operating period, a material sub-region and a sampling point.

[0008] The application further provides that the conversion of the collected multi-modal data into the surface disturbance index comprises: A sampling grid of the insulating surface of the lightning arrester is established, the insulating surface of the lightning arrester is discretized into a preset number of sampling points, and a sampling point index set is generated; Surface geometric disturbance information, local heat distribution information and surface charge accumulation information are collected for each sampling point to generate an original data set for the corresponding sampling point; The original data of each sampling point is normalized and combined with non-linear mapping to generate unified dimension data; Based on the unified dimension data after normalization and non-linear mapping, the surface disturbance index of each sampling point is calculated to represent the abnormal strength of the local insulating surface.

[0009] The application further provides that the non-linear combination of the surface disturbance index of each material sub-region to generate the insulating stress energy comprises: dividing the insulating surface of the lightning arrester into a preset number of material sub-regions, each material sub-region containing a plurality of sampling points, and according to the three-dimensional position of each sampling point and the surface disturbance index, the sampling points are classified into the corresponding material sub-region; collecting a set of surface disturbance indexes of the sampling points in the material sub-region; nonlinearly combining the set of surface disturbance indexes of each material sub-region to generate the insulating stress energy of the region, reflecting the comprehensive state of the disturbance intensity and spatial distribution of the sampling points in the material sub-region.

[0010] The application further provides that the fusion of the environmental data and the insulating stress energy of each material sub-region to generate the environmental stress factor includes: obtaining environmental data during the operation of the lightning arrester, including humidity, temperature, wind speed and rainfall; nonlinearly mapping the environmental data at each sampling time to generate an environmental weight vector; nonlinearly coupling and fusing the insulating stress energy of each material sub-region and the environmental weight vector to generate a coupling matrix element; cumulatively and nonlinearly combining the coupling matrix elements of each material sub-region to generate the environmental stress factor.

[0011] The application further provides that when the comprehensive insulating risk index is greater than the preset protection threshold, a protection trigger signal is generated. cumulatively processing the environmental stress factors generated at all sampling times for each material sub-region to generate a local cumulative risk index; nonlinearly combining the local cumulative risk index of each material sub-region to generate a comprehensive insulating risk index covering the entire insulating surface, reflecting the overall risk level of the environmental coupling state of all material sub-regions at each sampling time; comparing the comprehensive insulating risk index with the preset protection threshold, and when the comprehensive insulating risk index is higher than the preset protection threshold, a protection trigger signal is generated.

[0012] The application further provides that the insulating surface is treated by a repair medium, and the treatment result is used to generate a repair penetration intensity. when the protection trigger signal is detected, the repair mechanism is activated, and an activation identifier is output; calculating the repair medium distribution of all sampling points of each material sub-region, combining the insulating stress energy and the environmental stress factor of each material sub-region within the sampling period, and calculating the repair penetration potential of each sampling point, reflecting the repair demand intensity and the environmental coupling state at that position; The repair penetration potential is combined with the activation mark of the corresponding material sub-area in a nonlinear manner to generate a repair penetration intensity of each sampling point, indicating the distribution range and action degree of the repair medium on the specific material sub-area and the sampling point.

[0013] The application further provides that the generating the electric field compensation factor and mapping the electric field compensation factor to the coverage area corresponding to each electrode comprises: The repair penetration intensity of each sampling point in each material sub-area is combined with the corresponding environmental stress factor in a nonlinear manner to generate a local electric field compensation factor of the sampling point. The local electric field compensation factors of all sampling points in the same material sub-area are integrated in a nonlinear manner to generate an overall electric field compensation factor of the material sub-area. According to the electrode coverage area mapping relationship, the overall electric field compensation factors of the material sub-areas are distributed to the corresponding electrode coverage areas to determine the preliminary compensation values of the electrodes.

[0014] The application further provides that the optimizing the electric field distribution on the insulating surface by adjusting the electrode output comprises: The preliminary compensation values of each electrode are adjusted in a nonlinear manner to generate a final adjustment amplitude of the electrode. The spatial gradients of the material sub-area repair penetration intensity and the environmental stress factor are combined to determine the adjustment direction of each electrode. According to the electrode adjustment amplitude and the adjustment direction, the electrode output is adjusted to optimize the electric field distribution on the insulating surface.

[0015] The application further provides that the generating the life decay index comprises: The comprehensive insulation risk index, the repair penetration intensity and the electric field compensation factor are periodically accumulated and analyzed for each material sub-area and sampling point to generate a local life decay index corresponding to each operation cycle. The local life decay indexes of the sampling points in the material sub-area are integrated to generate a regional life decay index.

[0016] The application further provides that the generating the life prediction result comprises: The accumulated decay indexes of each material sub-area in the historical operation cycle are accumulated in a nonlinear manner to generate a time accumulated decay result. According to the time accumulated decay result, a periodic life prediction value is mapped to each material sub-area, and the periodic life prediction value is distributed to each sampling point to generate a sampling point level life prediction. The life prediction results of all sampling points in all operation cycles are combined to generate a long-term life prediction result, and each long-term life prediction result corresponds to a specific operation cycle, a material sub-area and a sampling point.

[0017] The application provides an insulating protection method for a lightning arrester, which comprises the following steps: collecting multi-modal data of the insulating surface of the lightning arrester, including acquiring surface geometric disturbance information, local thermal distribution information and surface charge accumulation information through sensors, and converting the collected multi-modal data into a surface disturbance index; dividing the insulating surface of the lightning arrester into a preset number of material sub-regions according to the surface disturbance index, and generating an insulating stress energy by nonlinearly combining the surface disturbance index of each material sub-region; acquiring multi-dimensional data of the operating environment of the lightning arrester, including humidity, temperature, wind speed and rainfall, and fusing the environmental data and the insulating stress energy of each material sub-region to generate an environmental stress factor representing the coupling state of the environment and the material at the corresponding time and region; processing the environmental stress factor by accumulation and combination to generate a comprehensive insulating risk index, and generating a protection trigger signal when the comprehensive insulating risk index is greater than a preset protection threshold; activating a repair mechanism according to the protection trigger signal, processing the insulating surface through a repair medium to generate a repair penetration strength, each repair penetration strength corresponding to a specific material sub-region and a sampling point, representing the distribution and degree of action of the repair medium at the position; combining the repair penetration strength and the environmental stress factor to generate an electric field compensation factor, mapping the electric field compensation factor to the coverage area corresponding to each electrode to determine the adjustment amplitude and direction of each electrode, and optimizing the electric field distribution of the insulating surface by adjusting the electrode output; based on the comprehensive insulating risk index, the repair penetration strength and the electric field compensation factor, periodic data accumulation and analysis are performed to generate a local life attenuation index, the local life attenuation index is integrated to generate a life attenuation index, and the life attenuation index is nonlinearly accumulated and mapped into a life prediction result, each life prediction result corresponding to an operating period, a material sub-region and a sampling point, and the beneficial effects include: 1. Improved life prediction accuracy: By establishing a periodic data accumulation and analysis mechanism based on the comprehensive insulating risk index, the repair penetration strength and the electric field compensation factor, long-term life prediction results can be generated based on multi-dimensional data fusion, improving the accuracy of insulating state evaluation, and making the life prediction closely correspond to the operating period, material sub-region and sampling point. 2. Local differentiated protection: In the life prediction process, the material is divided into different sub-regions, and the prediction results of the sampling points are combined for partition management, so that more detailed protection measures can be taken for the differentiated aging and deterioration of the insulating material, avoiding distortion caused by overall judgment. 3. Enhanced long-term operation reliability: The life prediction results generated by periodic accumulation and dynamic analysis can provide continuous operation state judgment support for the insulating material of the lightning arrester, making the operating period and repair strategy consistent, thereby enhancing the overall reliability and stability of the lightning arrester in long-term operation.

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. 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 inventive efforts. In the drawings: Figure 1 The flowchart of a lightning arrester insulation protection method is shown as an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0020] The following describes the embodiments of the present invention with reference to the accompanying drawings and preferred embodiments. Those skilled in the art will readily appreciate the other advantages and benefits of the present invention from the disclosure herein. The present invention may also be implemented or applied through various other specific embodiments, and the various details in this specification may be modified or altered based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are intended only to illustrate the present invention and are not intended to limit the scope of protection of the present invention.

[0021] It should be noted that the illustrations provided in the following embodiments are merely schematic illustrations of the basic concept of the present invention. Therefore, the illustrations only show components related to the present invention and are not drawn according to the number, shape, and size of components in actual implementation. In actual implementation, the type, quantity, and proportion of each component may be changed arbitrarily, and the component layout may also be more complex.

[0022] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the embodiments of the present invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring the embodiments of the present invention.

[0023] Example 1: A lightning arrester insulation protection method, such as Figure 1 As shown, including: Perform multimodal data collection on the arrester insulation surface, including obtaining surface geometric disturbance information, local heat distribution information, and surface charge accumulation information through sensors, and converting the collected multimodal data into a surface disturbance index; According to the surface disturbance index, the insulating surface of the lightning arrester is divided into a preset number of material sub-regions, and the surface disturbance index of each material sub-region is combined non-linearly to generate an insulating stress energy; Obtain multi-dimensional data of the operating environment of the lightning arrester, including humidity, temperature, wind speed and rainfall, fuse the environmental data with the insulating stress energy of each material sub-region to generate an environmental stress factor representing the coupling state of the environment and the material at the corresponding time and corresponding region; The environmental stress factor is accumulated and combined to generate a comprehensive insulating risk index, and when the comprehensive insulating risk index is greater than a preset protection threshold, a protection trigger signal is generated; According to the protection trigger signal, a repair mechanism is activated to process the insulating surface through a repair medium to generate a repair penetration strength, each repair penetration strength corresponding to a specific material sub-region and a sampling point, representing the distribution and degree of action of the repair medium at the position; The repair penetration strength and the environmental stress factor are combined to generate an electric field compensation factor, which is mapped to the coverage area corresponding to each electrode to determine the adjustment amplitude and direction of each electrode, and the output of the electrode is adjusted to optimize the electric field distribution of the insulating surface; Based on the comprehensive insulating risk index, the repair penetration strength and the electric field compensation factor, periodic data accumulation and analysis are performed to generate a local life attenuation index, which is integrated to generate a life attenuation index, and the life attenuation index is non-linearly accumulated and mapped to a life prediction result, each life prediction result corresponding to an operating period, a material sub-region and a sampling point.

[0024] The application further provides that the collected multi-modal data is converted into a surface disturbance index, which includes: A lightning arrester insulating surface sampling grid is established, the insulating surface of the lightning arrester is discretized into a preset number of sampling points, and a sampling point index set is generated; specifically, the lightning arrester insulating surface sampling grid is a geometric division method for discretizing a continuous surface into a finite number of sampling points, which ensures the spatial positioning accuracy of physical quantity measurement, and the insulating surface is discretized into , wherein is the total number of preset sampling points, and each sampling point uniquely corresponds to three types of original physical quantities: geometric disturbance quantity , local thermal distribution value , and surface charge accumulation quantity This discretization step converts continuous surface information into a digital point set representation, ensuring that subsequent operations can be tracked; Surface geometric disturbance information, local thermal distribution information and surface charge accumulation information are collected for each sampling point to generate an original data set for the corresponding sampling point; specifically, the surface geometric disturbance information is the geometric disturbance quantity , which is collected by three-dimensional structure light scanning or laser scanning, represents the curvature or height deviation of the sampling point relative to the ideal surface, and the value range is mm, the local thermal distribution information is a thermal distribution value , which is collected by an infrared thermal imager, represents the insulation surface temperature of the sampling point, reflects thermal anomalies, and the value range is , the surface charge accumulation information is the surface charge accumulation amount , which is collected by a non-contact potential sensor, represents the charge density of the sampling point, characterizes the local electric field strength, and the value range is nC / cm², the original data set corresponding to the sampling point is generated, and a triple is formed: ; The original data of each sampling point is normalized and combined with nonlinear mapping to generate unified dimension data; specifically, by designing a complex numerator enhancement and denominator constraint form, the data in different physical domains is converted into comparable data of unified dimension, the influence of extreme values is suppressed, and the formula of the unified dimension data is , wherein, is a geometry-temperature coupling coefficient, the value range is [0.01, 1], is a temperature-charge coupling coefficient, the value range is [0.01, 1], is a charge-geometry-temperature three-coupling coefficient, the value range is [0.001, 0.5], the formula enhances the sensitivity of extreme values by squaring / cubing the numerator, amplifies abnormal signals, and introduces a cross-coupling term in the denominator to suppress the extreme dominance of a certain physical quantity, ensuring stability; Based on the unified dimension data after normalization and nonlinear mapping, the surface disturbance index of each sampling point is calculated, which characterizes the local insulation surface anomaly strength, specifically, the normalized data is nonlinearly combined to generate the surface disturbance index of the sampling point, which characterizes the comprehensive local insulation surface anomaly degree, , wherein, Square and cube are introduced at the same time to enhance the coupling effect of geometry-heat, charge-heat, and the constraint term is used to prevent extreme abnormal distortion, and the disturbance index is proportional to the local anomaly degree of the sampling point, is a geometry-charge coupling constraint coefficient, the value range is [0.001, 0.5], is a temperature constraint coefficient, the value range is [0.001, 0.5].

[0025] The application further provides that the nonlinear combination of the surface disturbance index of each material sub-region to generate insulation stress energy includes: The arrester insulation surface is divided into a preset number of material sub-regions, each material sub-region contains multiple sampling points, and the sampling points are classified into corresponding material sub-regions according to the three-dimensional position and surface disturbance index of each sampling point; specifically, the arrester insulation surface is divided into Preset material sub-areas: , specify the initial center coordinates for each region , using the center point set to provide a regional indexing benchmark to ensure that the subsequent distance-based spatial attribution has a reference and is repeatable; for each sampling point , its location , perturbation index , the index of the region with the minimum belongingness is determined according to the following nonlinear distance criterion: , the square of spatial distance Measure geometric proximity, In order to make the high disturbance points tend to belong to the more concerned area at the same distance, the coefficient Control the impact of disturbances on attribution. This judgment nonlinearly couples spatial and disturbance information to avoid decisions based solely on distance or pure disturbance. Regional division combines spatial proximity and local disturbance index, allowing high-abnormal points to be preferentially assigned to specific sub-regions, improving the accuracy of local stress calculations. Collect the surface disturbance index set of the sampling points in the material sub-region; specifically, for each region Collect the disturbance indices of the sampling points to form a set: ,gather is the original sample of disturbance in the region, which is used to characterize the local abnormal distribution of the region and serve as the input of energy aggregation. Only a single ; The surface disturbance index set of each material sub-region is nonlinearly combined to generate the insulation stress energy of the region, which reflects the comprehensive state of the disturbance intensity and spatial distribution of the sampling points in the material sub-region. Specifically, for each region Generate insulation stress energy using nonlinear operators , where the numerator contains The energy contribution of highly disturbed points is amplified cubically to ensure that severe local defects dominate the regional energy; molecular additional terms Considering the coupling between disturbance intensity and spatial deviation, the additional influence of high disturbance points farther from the regional center on local structural stress is emphasized. is the disturbance-space coupling coefficient, with a value range of [0.001, 1], and the denominator is , constructing strong suppression constraints with cubic spatial weights, is the nonlinear constraint coefficient, with a value range of [0.001, 1]. It limits the energy burst when there are extreme points, ensuring numerical stability and physical interpretability. This ratio is not a simple weighted summation, but a fractional nonlinear aggregation operator. It can achieve overall constraints while amplifying key points and output It can be directly used for the fusion calculation of environmental stress factors to achieve scale upgrade from sampling points to regions.

[0026] The present invention is further configured such that fusing the environmental data with the insulation stress energy of each material sub-region to generate the environmental stress factor comprises: Obtain environmental data during the operation of the arrester, including humidity, temperature, wind speed and rainfall; specifically, multi-dimensional operating environment data: , where the original environment vector at each moment is , , , ,in, is humidity, collected by on-site humidity sensors or weather stations, with a value range of [0, 100] (%), Temperature, measured by temperature sensor or infrared temperature, range [-40, 150] , is the wind speed, measured by an anemometer or weather station, with a value range of [0, 50] (m / s), is the rainfall, measured by a rain gauge or weather station, with a value range of [0, 200] (mm / h), and the material sub-area set is: , the insulation stress energy of each area , value ; Perform nonlinear mapping on the environmental data at each sampling moment to generate an environmental weight vector; specifically, for each moment Environmental data Perform nonlinear mapping to generate environment weight vector , where the numerator uses square to amplify the response sensitivity of extreme environmental values, making high humidity, extreme temperature, high wind speed or heavy rainfall more prominent after mapping; the denominator uses cross-coupling terms (such as temperature affecting humidity terms) to suppress the absolute dominance of any single high value on the mapping, reflecting the mutual constraints between environmental factors, and the mapping results is the four-dimensional environment weight vector, which is used as the environment representation at the moment level. , , and is the environmental coupling coefficient, which is calibrated by historical operating data and has a value range of [0.01, 1]; The insulation stress energy and the environment weight vector of each material sub-region are nonlinearly coupled and fused to generate a coupling matrix element; specifically, the insulation stress energy of each region is multiplied by the environment coupling combination to make the coupling value significantly increase when high-energy regions coexist with adverse environmental conditions with the time mapping vector nonlinear coupling to generate a coupling matrix element , The regional static energy is amplified in square and multiplied by the multi-environment coupling combination, so that the coupling value significantly increases when high-energy regions coexist with adverse environmental conditions, and the denominator contains two nonlinear constraints: one is coupling (for example, the direct constraint of rainfall on energy excitation), and the other is (environment interaction inhibition) for inhibiting the numerical expansion caused by extreme time, and the coupling matrix element characterizes the region at time The coupling strength with the environment constitutes a space-time matrix , is a material-environment coupling constraint coefficient, which is obtained by material testing and scene calibration, and the value range is [0.001, 0.5]; The coupling matrix elements of each material sub-region are accumulated and nonlinearly combined to generate an environmental stress factor, and specifically, the environmental stress factors of the regions in the coupling sequence at all times are nonlinearly accumulated in time sequence to obtain the regional environmental stress factors The numerator adopts to amplify the importance of high-coupling time, and a time weight term is added to emphasize the influence of recent or specific time period on the factor, and the denominator adopts a quadratic term and a linear time weighted cumulative constraint to limit the numerical out-of-control under long-time accumulation, and the environmental stress factor is an environmental coupling strength index of the material sub-region in the entire sampling period, is a time sequence cumulative coupling coefficient, which is fitted by long-term historical data or physical experiments, and the value range is .

[0027] The application further provides that when the comprehensive insulation risk index is greater than the preset protection threshold, the protection trigger signal is generated, including: The environmental stress factors generated at all sampling times of each material sub-region are accumulated to generate a local cumulative risk index; specifically, the environmental stress factors of each material sub-region are nonlinearly accumulated in time, and the local cumulative risk index is constructed in a time window with a length of , wherein, , , is a nonlinear accumulation coefficient, and the numerator contains With , taking into account high amplitude and time position: square term stably reflects general intensity, cubic term imposes greater weight on high intensity section, restricting early contribution to highlight recent persistence, denominator to constraint cumulative value, inhibit burst when window grows and intensity rises simultaneously, maintain index accurate and controllable, local cumulative risk index as a time cumulative representation of the region ; nonlinearly combining local cumulative risk indexes of each material sub-region to generate comprehensive insulation risk index covering entire insulation surface, reflecting overall risk level of all material sub-regions in environmental coupling state at each sampling time; specifically, nonlinearly combining all local cumulative risk indexes in spatial domain to obtain comprehensive insulation risk index covering entire insulation surface , , sub-region risk combination nonlinear coefficient, the numerator to amplify the influence of high-risk areas, and introduce express the structural influence of regional position index on overall risk, the denominator to nonlinearly constrained, avoid abnormal values of a single region leading to uncontrolled global rise, comprehensive insulation risk index as a risk characterization in the sense of surface integral, directly into threshold discrimination; comparing the comprehensive insulation risk index with the preset protection threshold, when the comprehensive insulation risk index is higher than the preset protection threshold, generating a protection trigger signal, the comprehensive insulation risk index compared with the preset protection threshold , a protection trigger signal is generated when the comprehensive risk exceeds the threshold, triggering the protection mechanism.

[0028] The application further provides that the insulation surface is treated by the repair medium, and the treatment result generates a repair penetration strength, including: when the protection trigger signal is detected, the repair mechanism is activated, and an activation identifier is output; specifically, when the protection trigger signal , the repair mechanism is activated, otherwise the repair mechanism remains standby, and the activation identifier is defined as: , if , , indicating that the sub-region is activated, if , , indicating that the sub-region remains silent, ensuring that the repair medium is only distributed when the risk exceeds the threshold, and outputting the activation identifier an activation mark for each material sub-region is set; For each material sub-region, all sampling points are subjected to repair medium distribution calculation, combined with the insulation stress energy and environmental stress factor of each material sub-region in the sampling period, the repair penetration potential of each sampling point is calculated, reflecting the repair demand intensity and environmental coupling state of the position; in the sub-region , the repair penetration potential of the sampling point is: , wherein, is a position weight coefficient, the value range is [0.01, 2], is a non-linear constraint coefficient, the value range is [0.001, 0.5], By amplifying the influence of higher insulation stress energy in the material sub-region, the environmental coupling factor is introduced, which embodies the comprehensive pressure of external humidity, temperature, wind speed, rainfall, etc. The sampling point serial number is localized, the position priority is introduced, for example, the edge point or special point enhances the repair demand, Through non-linear constraint, prevent some high value points from unlimited amplification, keep the distribution stable, Indicates the demand intensity of the repair medium at the sampling point, which is a comprehensive expression of risk intensity, environmental coupling and position weighting; The repair penetration potential and the activation mark of the corresponding material sub-region are combined non-linearly to generate the repair penetration intensity of each sampling point, which represents the distribution range and action degree of the repair medium in the specific material sub-region and sampling point. Specifically, the repair penetration potential is combined with the activation matrix to generate the actual repair penetration intensity , wherein, is a total amount constraint coefficient in the region, By squaring, the repair intensity of high potential sampling points is further enhanced, Indicates the cumulative constraint in the region, prevents a region from consuming too much repair medium, and ensures balanced distribution of repair among different sub-regions, the activation mark controls whether to enable the repair mechanism, if the sub-region is not activated, , Reflects the distribution rule of the repair medium in space, which not only considers the prominence of local demand, but also ensures global balance.

[0029] The application further sets that the generated electric field compensation factor is mapped to the coverage area corresponding to each electrode, including: The repair penetration intensity of each sampling point in each material sub-region is non-linearly fused with the corresponding environmental stress factor to generate the local electric field compensation factor of the sampling point; specifically, for each material sub-region Sampling points within , calculate the local electric field compensation factor ,in, is the permeability-environment coupling coefficient, with a value range of [0.01, 1], is the number of sampling points, is the spatial position weight coefficient, with a value range of [0.01, 2], is the nonlinear constraint coefficient, with a value range of [0.001, 0.5], represents the local electric field compensation factor at the sampling point, Emphasize high repair intensity sampling points, Introducing the coupling between repair intensity and environment, exponential term Introducing sampling point position weights to prioritize regional edges or specific sequence points. Suppress extreme point values ​​to avoid overcompensation; The local electric field compensation factors of all sampling points in the same material sub-region are nonlinearly integrated to generate the overall electric field compensation factor of the material sub-region; specifically, All sampling points of the region are integrated to obtain the regional overall compensation factor. ,in, Reflects the electric field compensation intensity of the entire sub-region, Amplify the dominant effect of high local compensation points on the overall The weighted constraint of sampling point sequence number is introduced to limit the over-expansion of the overall compensation of the region; According to the mapping relationship of the electrode coverage area, the overall electric field compensation factor of each material sub-region is allocated to the corresponding electrode coverage area, and the initial compensation value of the electrode is determined. Mapping relationship with electrode coverage area Sampling point by control , generate preliminary compensation values ​​for the electrodes , the overall compensation value of the region Assign to electrodes according to coverage relationship, weight Determined by the electrode coverage area and sampling point density, ensure reasonable distribution and output the preliminary compensation value of each electrode .

[0030] The present invention is further configured such that optimizing the electric field distribution on the insulating surface by adjusting the electrode output comprises: The initial compensation value of each electrode is nonlinearly adjusted to generate the final adjustment amplitude of the electrode; specifically, the initial compensation value of the electrode Perform nonlinear adjustment to obtain the final electrode amplitude , Prioritize the enhancement of high compensation electrodes, By electrode index Weighted, suppress global over-amplification, maintain system stability, As the final electrode amplitude parameter; Combine the spatial gradient of the repair penetration strength and the environmental stress factor of the material sub-region to determine the adjustment direction of each electrode; specifically, for each electrode, the adjustment direction is determined according to the gradient of the local area environmental stress factor and the repair penetration strength , Difference along the longitudinal direction Aggregate environmental stress and penetration strength, highlight the longitudinal risk gradient, Introduce transverse difference And through the coefficient Control, avoid infinite deviation of direction, The adjustment direction of the electrode is characterized, which is a dimensionless ratio; According to the electrode adjustment amplitude and the adjustment direction, adjust the electrode output, optimize the insulating surface electric field distribution, specifically, based on the amplitude And direction , the nominal value of the electrode is corrected, and the final output is generated: Wherein, is the decomposition vector of the electric field in two orthogonal basis directions, and is constructed by And Ensure that the amplitude of the direction vector is controlled, and the amplitude is combined to realize the spatial redistribution of the electrode output, As the final adjustment result.

[0031] The application further sets that the generation of the life attenuation index comprises: For each material sub-region and sampling point, the integrated insulation risk index, the repair penetration strength and the electric field compensation factor are periodically accumulated and analyzed to generate a local life attenuation index corresponding to each operation cycle; specifically, for each material sub-region And sampling point Calculate the local life attenuation factor In the operation cycle , wherein is the electric field compensation coupling coefficient, the value range is [0.001, 0.5], The square is used to amplify the contribution of high-risk sampling points to life attenuation, so that the risk intensity shows super-linear growth in response to attenuation, which facilitates early identification of significant risk points, The repair penetration strength ​Put in the cubic term (and keep 1 to avoid zero value degradation), embody the enhancement effect on the high permeability point; this cubic amplifies the contribution of the repair input to the mitigation or change of local life attenuation (which can be positively interpreted as the amplitude adjustment of delay or reverse effect, depending on the directionality of the index definition), , Adopt the product form to compensate the electric field factor , risk Coupling with position index As a nonlinear constraint; this term reflects the inhibitory effect of electric field compensation and risk interaction on local attenuation on the one hand, and introduces position weight to take into account spatial sensitivity on the other hand; parameter Control the strength of the constraint to prevent the molecule from causing non-physical burst due to extreme Or ; ; Integrate the local life attenuation index of each sampling point in the material sub-region to generate the regional level life attenuation index. Specifically, the local attenuation factor of all sampling points in each material sub-region Is accumulated to generate regional cumulative attenuation , The square of the local attenuation factor of all sampling points in the region is summed to highlight the dominance of high attenuation points in the region on the overall life of the region; this processing makes the contribution of a single high attenuation point to the regional index an amplification effect, Introducing a cumulative term linearly multiplied by the position index as a constraint, which reflects the spatial structure difference of sampling points in the region (for example, points close to key structural positions have higher weight), and controls the total inhibition through parameter Avoid numerical out of control in areas with high sampling density or large number of points, Characterize the regional level life attenuation intensity of the material sub-region At the running period moment .

[0032] The present application further provides that the generation of life prediction results comprises: Nonlinearly accumulate the cumulative attenuation index of each material sub-region in the historical running period to generate a time cumulative attenuation result; specifically, the regional cumulative attenuation of the region in the previous period Is nonlinearly time-cumulative to obtain the time cumulative attenuation up to : , Wherein, Cubic operation is adopted to highlight the strong influence of high attenuation period on long-term life (i.e. both "severe but short" and "moderate but persistent" are highlighted), Introducing time-weighted cumulative constraint Prevent long-term cumulative from causing magnitude out of control, Adjust historical cumulative sensitivity, For regional cutoff period Historical cumulative decay result; Map time cumulative decay result to periodic life prediction value for each material sub-region, assign periodic life prediction value to each sampling point, generate sampling point level life prediction; Specifically, map time cumulative decay to periodic life prediction value for region: Map cumulative decay to probability / life measure in inverse form, so that the greater the cumulative decay, the lower the life prediction, parameter Control mapping slope and sensitivity as life mapping coefficient, output Value is in (0, 1], used to assign to sampling point, assign regional periodic life prediction value back to sampling point, form sampling point level periodic life prediction. To avoid simple linear assignment, use power proportion mapping: , Exponent Make high decay sampling points have nonlinear amplification in assignment ratio, improve identification and attention to weak points, add constant 1 to denominator to avoid denominator being zero and limit assignment ratio not to exceed regional prediction measure, output Periodic life prediction for sampling point in cycle ; Combine life prediction results of all sampling points in all operation cycles to generate long-term life prediction results, each long-term life prediction result corresponds to a specific operation cycle, material sub-region and sampling point, specifically, for each sampling point, nonlinearly combine its periodic life prediction in all cycles to form long-term life prediction: , Emphasize those points that are consistently low in multiple cycles, making long-term weak points more easily identifiable, Introduce time-weighted cumulative constraint to control long-term cumulative effect, parameter Long-term cumulative constraint coefficient for sensitivity adjustment, output Long-term life prediction for sampling point.

[0033] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any skilled person in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A lightning arrester insulation protection method, characterized in that: include: Perform multimodal data collection on the arrester insulation surface, including obtaining surface geometric disturbance information, local heat distribution information, and surface charge accumulation information through sensors, and converting the collected multimodal data into a surface disturbance index; According to the surface disturbance index, the arrester insulation surface is divided into a preset number of material sub-regions, and the surface disturbance index of each material sub-region is nonlinearly combined to generate insulation stress energy; Acquire multi-dimensional data of the arrester's operating environment, including humidity, temperature, wind speed, and rainfall. Combine this environmental data with the insulation stress energy of each material sub-region to generate an environmental stress factor, representing the coupling state of the environment and material at the corresponding time and region. The environmental stress factors are accumulated and combined to generate a comprehensive insulation risk index. When the comprehensive insulation risk index exceeds the preset protection threshold, a protection trigger signal is generated. The repair mechanism is activated according to the protection trigger signal, and the insulation surface is treated with the repair medium to generate the repair penetration intensity. Each repair penetration intensity corresponds to a specific material sub-area and sampling point, indicating the distribution and effect of the repair medium at that location. The repair penetration strength is combined with the environmental stress factor to generate an electric field compensation factor. The electric field compensation factor is mapped to the coverage area corresponding to each electrode, and the adjustment amplitude and direction of each electrode are determined. The electric field distribution on the insulation surface is optimized by adjusting the electrode output. Based on the comprehensive insulation risk index, repair penetration strength and electric field compensation factor, periodic data accumulation and analysis are carried out to generate local life decay indicators, which are then integrated to generate life decay indicators. The life decay indicators are nonlinearly accumulated and mapped into life prediction results. Each life prediction result corresponds to an operating cycle, a material sub-area and a sampling point.

2. A lightning arrester insulation protection method according to claim 1, characterized in that: Converting the acquired multimodal data into surface disturbance indices involves: Establishing a sampling grid for the arrester insulation surface, discretizing the arrester insulation surface into a preset number of sampling points, and generating a sampling point index set; Collect surface geometric disturbance information, local thermal distribution information and surface charge accumulation information for each sampling point to generate the original data set of the corresponding sampling point; Normalize the raw data of each sampling point and generate uniform dimension data by combining nonlinear mapping; Based on the unified dimension data after normalization and nonlinear mapping, the surface disturbance index of each sampling point is calculated to characterize the intensity of local insulating surface anomaly.

3. A lightning arrester insulation protection method according to claim 2, characterized in that: The nonlinear combination of the surface disturbance index of each material sub-region generates the insulation stress energy including: The arrester insulation surface is divided into a preset number of material sub-regions, each material sub-region contains multiple sampling points, and the sampling points are classified into corresponding material sub-regions according to the three-dimensional position and surface disturbance index of each sampling point; Collect a set of surface disturbance indices of sampling points within the sub-region of the material; The surface disturbance index set of each material sub-region is nonlinearly combined to generate the insulation stress energy of the region, which reflects the comprehensive state of the disturbance intensity and spatial distribution of the sampling points in the material sub-region.

4. A lightning arrester insulation protection method according to claim 1, characterized in that: The environmental stress factors generated by fusing the environmental data with the insulation stress energy of each material sub-region include: Obtain environmental data during the operation of the arrester, including humidity, temperature, wind speed and rainfall; Perform nonlinear mapping on the environmental data at each sampling moment to generate an environmental weight vector; The insulation stress energy and the environmental weight vector of each material sub-region are nonlinearly coupled and fused to generate coupling matrix elements; The coupling matrix elements for each material subregion are accumulated and nonlinearly combined to generate the environmental stress factor.

5. A lightning arrester insulation protection method according to claim 4, characterized in that: When the comprehensive insulation risk index exceeds the preset protection threshold, a protection trigger signal is generated, including: The environmental stress factors generated at all sampling moments for each material sub-area are accumulated to generate a local cumulative risk index; The local cumulative risk index of each material sub-region is nonlinearly combined to generate a comprehensive insulation risk index covering the entire insulation surface, reflecting the overall risk level of the environmental coupling state of all material sub-regions at each sampling moment; The comprehensive insulation risk index is compared with a preset protection threshold, and when the comprehensive insulation risk index is higher than the preset protection threshold, a protection trigger signal is generated.

6. A lightning arrester insulation protection method according to claim 1, characterized in that: The insulation surface is treated with a repair medium, and the treatment results are used to generate the repair penetration strength including: When a protection trigger signal is detected, the repair mechanism is activated and an activation flag is output; The repair medium distribution is calculated for all sampling points in each material sub-area. The insulation stress energy and environmental stress factor of each material sub-area during the sampling period are combined to calculate the repair penetration potential of each sampling point, reflecting the repair demand intensity and environmental coupling status of the location. The repair penetration potential is nonlinearly combined with the activation flag of the corresponding material sub-region to generate the repair penetration intensity of each sampling point, which represents the distribution range and effect of the repair medium in the specific material sub-region and sampling point.

7. A lightning arrester insulation protection method according to claim 1, characterized in that: Generate an electric field compensation factor and map the electric field compensation factor to the coverage area corresponding to each electrode including: The repair penetration intensity of each sampling point in each material sub-region is nonlinearly fused with the corresponding environmental stress factor to generate the local electric field compensation factor of the sampling point; Perform nonlinear integration on the local electric field compensation factors of all sampling points in the same material sub-region to generate the overall electric field compensation factor of the material sub-region; According to the mapping relationship of the electrode coverage area, the overall electric field compensation factor of each material sub-region is allocated to the corresponding electrode coverage area to determine the preliminary compensation value of the electrode.

8. A lightning arrester insulation protection method according to claim 7, characterized in that: Optimizing the electric field distribution on the insulating surface by adjusting the electrode output includes: Perform nonlinear adjustment on the preliminary compensation value of each electrode to generate the final adjustment amplitude of the electrode; The adjustment direction of each electrode is determined by combining the spatial gradient of the repair penetration strength of the material sub-region and the environmental stress factor; According to the electrode adjustment amplitude and adjustment direction, the electrode output is adjusted to optimize the electric field distribution on the insulation surface.

9. The lightning arrester insulation protection method according to claim 1, characterized in that: Generate life decay indicators including: For each material sub-area and sampling point, the comprehensive insulation risk index, repair penetration strength and electric field compensation factor are periodically accumulated and analyzed to generate a local life attenuation index corresponding to each operating cycle; The local life decay index of each sampling point in the material sub-region is integrated to generate a regional level life decay index.

10. A lightning arrester insulation protection method according to claim 9, characterized in that: Generate life prediction results including: The cumulative attenuation index of each material sub-region in the historical operation cycle is nonlinearly accumulated to generate the time cumulative attenuation result; According to the time-accumulated attenuation results, the periodic life prediction value of each material sub-region is mapped, and the periodic life prediction value is assigned to each sampling point to generate the sampling point-level life prediction; The life prediction results of all sampling points in all operating cycles are combined to generate long-term life prediction results, each of which corresponds to a specific operating cycle, material sub-region and sampling point.

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