Light emitting diode display device and method of manufacturing the same

Abstract

The application discloses a kind of based on lightning area's grounding resistance impact monitoring system and method, belong to electric power equipment lightning protection technical field;The system includes current monitoring module, voltage monitoring module, dynamic impedance calculation module, impact evaluation module and early warning control module;Real-time capture lightning impact current waveform and transient voltage drop by high-frequency broadband sensor, calculate dynamic grounding impedance;Using wavelet transform for time-frequency analysis, extract spectral features to identify implicit defects such as grounding body corrosion or fracture;Combined with lightning positioning system and multidimensional data fusion, construct impact risk assessment model and life prediction model, realize risk prediction and inspection cycle optimization.When impedance changes exceed threshold value, the system automatically triggers alarm and parallelly links to repair measures such as resistance reduction liquid injection;The application effectively solves the problem that traditional monitoring method cannot reflect high-frequency impact characteristics and lacks dynamic evaluation capability, significantly improves the lightning protection reliability and operation intelligent level of high thunderstorm area electric power facilities.

Description

Technical Field

[0001] This invention belongs to the field of power equipment lightning protection technology, and in particular relates to a grounding resistance impulse monitoring system and method based on lightning areas. Background Technology

[0002] In areas prone to lightning strikes, such as wind farms, power substations, and communication base stations, grounding devices are a crucial component for ensuring equipment and personnel safety. The primary function of grounding devices is to safely conduct lightning current or fault current into the earth, thus preventing overvoltage damage to equipment. However, lightning currents are characterized by high frequency, high current, and short duration, causing dynamic changes in grounding resistance and even permanent degradation such as corrosion and breakage of the grounding electrode. Traditional grounding resistance measurement methods are typically based on DC or low-frequency testing principles, such as the three-electrode method or clamp meter method. These methods can only measure the grounding resistance value under steady-state conditions and cannot reflect the high-frequency impact characteristics of a lightning strike. Furthermore, conventional online monitoring systems mostly focus on resistance changes under power frequency or small DC signals, neglecting performance degradation under transient impacts. This means that in actual operation, the grounding device may have already degraded in performance after a lightning strike, but the system cannot identify this in real time, thus creating potential protection failures or leading to excessive maintenance and increased costs. Therefore, the technical problem in this field is: how to monitor the dynamic changes of grounding resistance under lightning strikes in real time and accurately, and to assess the health status of grounding devices, so as to improve the lightning protection reliability of power facilities in high-thunderstorm areas.

[0003] In existing technologies, two types of methods are typically used to address the change in grounding resistance under lightning strikes: The first type is the laboratory simulation method, which uses an impulse current generator to produce a standard lightning current waveform and tests the impulse characteristics of the grounding device in a controlled environment. This method can obtain the response data of the grounding electrode under simulated lightning strikes, but it is only suitable for the design verification stage and cannot achieve real-time on-site monitoring.

[0004] The second type is the online monitoring system, which periodically measures grounding resistance based on small signals injected at power frequency or DC. This type of system uploads the resistance values ​​to the monitoring center via data acquisition units and communication modules for long-term trend analysis. Some systems also incorporate meteorological data or historical lightning strike records for risk assessment. However, due to the significant differences between the high-frequency characteristics of power frequency or DC signals and lightning currents, existing online monitoring systems struggle to capture transient responses caused by lightning strikes and cannot distinguish the differentiated effects of the initial lightning strike and subsequent return strikes. Furthermore, existing technologies largely rely on static threshold alarms, triggering an alarm when the resistance value exceeds a set limit, but lack analysis of the impedance spectrum characteristics during the impact process, making it impossible to identify latent defects.

[0005] The main drawbacks of existing technologies are: First, laboratory simulation methods cannot be applied to real-time on-site monitoring, resulting in the inability to effectively capture and analyze actual lightning strike events. Second, online monitoring systems based on power frequency or DC are limited by bandwidth and cannot accurately reflect changes in grounding impedance under high-frequency lightning currents, causing a disconnect between monitoring data and actual impact characteristics. Finally, existing systems mostly use static evaluation models, neglecting the dynamic mapping relationship between lightning current parameters such as amplitude, waveform, and grounding resistance, making it difficult to predict the health status of grounding devices and implement active protection. These shortcomings expose power facilities in high-thunderstorm areas to the risk of insufficient protection or wasted maintenance.

[0006] Therefore, a grounding resistance impulse monitoring system based on lightning areas is needed to solve the above problems. Summary of the Invention

[0007] The technical problem to be solved by this invention is to provide a grounding resistance impulse monitoring system and method based on lightning areas. It captures the lightning impulse current and voltage waveforms in real time through high-frequency transient monitoring technology, and establishes a mapping model between lightning current and grounding resistance by combining dynamic impedance calculation and time-frequency analysis. It also integrates intelligent early warning and multi-dimensional data fusion to realize the full life cycle management of grounding resistance impulse characteristics, aiming to improve the accuracy and reliability of grounding resistance monitoring in lightning areas.

[0008] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A grounding resistance impulse monitoring system based on lightning-prone areas, comprising: The current monitoring module is configured to be deployed near the grounding electrode to capture the waveform of the inrush current caused by lightning strikes or operational overvoltages in real time. The voltage monitoring module is configured to measure the transient voltage drop of the grounding device under impulse current. The dynamic impedance calculation module is configured to calculate the dynamic grounding impedance based on the impulse current waveform and the transient voltage drop; The impact assessment module is configured to establish a mapping relationship between lightning current parameters and grounding resistance based on the dynamic grounding impedance, and to identify defects in the grounding device; The early warning and control module is configured to trigger an alarm and link with the external repair system when the change in the dynamic grounding impedance exceeds a preset threshold.

[0009] Preferably, the current monitoring module includes a high-frequency wideband current sensor with a frequency range of 0.1Hz-1MHz; the voltage monitoring module includes a differential voltage probe.

[0010] Preferably, the impact assessment module is further configured as follows: The waveforms of the first lightning strike and the subsequent return strike are distinguished. The waveform of the first lightning strike has a wavefront time in the range of 8 μs to 12 μs and a wave tail time in the range of 300 μs to 400 μs. The waveform of the subsequent return strike has a wavefront time in the range of 0.2 μs to 0.3 μs and a wave tail time in the range of 80 μs to 120 μs. The spectral characteristics of the dynamic grounding impedance are extracted based on time-frequency analysis, where the time-frequency analysis employs a wavelet transform function: ; in, These are wavelet coefficients. For scale parameters, For translation parameters, For dynamic grounding impedance, The wavelet basis function is used to identify corrosion or fracture defects in the grounding electrode based on the spectral characteristics.

[0011] Preferably, the spectral characteristics are used to identify corrosion or fracture defects in the grounding electrode, including: (1) Feature extraction unit, configured to extract features from the wavelet coefficients The frequency domain features characterizing the state of the grounding electrode are extracted, including: High-frequency energy ratio: Characterizes the relative energy of high-frequency components in the impedance spectrum, and is calculated using the following formula: ; in, This represents the set of scale parameters corresponding to the high-frequency band. Representative in scale Peaceful relocation Energy of wavelet coefficients; Main resonant frequency : Characterizes the frequency at which energy peaks occur in the impedance spectrum.

[0012] (2) A defect discrimination unit is configured to compare the frequency domain feature quantity with a preset health status threshold, wherein the health status threshold is set to two stages, including a first threshold and a second threshold: When the high frequency energy ratio If the value exceeds the first threshold, the grounding electrode is determined to have corrosion defects. When the main resonant frequency When a significant deviation occurs, exceeding the second threshold from the healthy reference frequency, it is determined that the grounding electrode has a breakage or loose connection defect.

[0013] Preferably, the early warning and control module is further configured as follows: By combining the lightning location system, the impact risk of grounding devices in high-thunderstorm areas can be predicted, and the protection mode can be activated in advance; When a single lightning strike causes the dynamic grounding impedance to rise by more than 20%, an alarm is triggered and the resistance-reducing liquid injection system is activated.

[0014] Preferably, in conjunction with a lightning location system, the impact risk to grounding devices in high-thunderstorm areas is predicted, and the protection mode is activated in advance, specifically including: (1) Risk mapping unit, configured as follows: Acquire real-time lightning activity data provided by the lightning location system, including the movement trajectory of thunderclouds and lightning strike density. and estimated arrival time ; According to the trajectory and Determine the set of affected grounding devices ; (2) Dynamic risk assessment unit, configured as follows: For sets Each grounding device Calculate its comprehensive risk coefficient The calculation formula is: ; in, Maximum historical lightning strike density Device The most recently monitored dynamic grounding impedance relative to its health benchmark The amount of degradation, i.e.: ; The threshold for impedance degradation alarm; For device Soil moisture at the location, Soil saturation moisture; These are the weighting coefficients, and ; Will With preset risk threshold Compare; (3) Protection decision unit, configured as follows: when At that time, the determining device It is a high-risk device, and its protective mode is activated in advance.

[0015] Preferably, it further includes a data fusion module, configured as follows: Integrates meteorological data, soil moisture sensor data, and historical lightning strike records; A grounding device impulse life prediction model was constructed to optimize the inspection cycle; Generate a lightning strike incident report, including impact parameters, grounding performance degradation rate, and maintenance recommendations.

[0016] Preferably, a grounding device impulse life prediction model is constructed to optimize the inspection cycle, specifically including: (1) Cumulative damage calculation unit, configured as follows: Record the impact parameters for each lightning strike, including peak current. and impact charge Q; Based on Miller's cumulative damage theory, the damage caused to the grounding device by a single lightning strike is calculated. : ; in, The material damage coefficient, This is an empirical index, determined through accelerated life testing; Calculate the total cumulative damage up to the current time. The calculation formula is: ; N represents the total number of historical lightning strikes; (2) Lifetime prediction unit, configured as follows: Establish remaining lifespan With total cumulative damage The mapping model is given by the formula: ; in, For the design life of the grounding device, The critical damage threshold that leads to failure; Based on soil moisture H Introducing environmental correction factors for soil pH value Adjust the remaining lifespan: ; (3) Inspection optimization unit, configured as follows: Based on the predicted remaining lifespan Dynamically adjust the inspection cycle The adjustment strategy is as follows: ; in, and These represent the maximum and minimum inspection cycles allowed by the system. This is a proportionality coefficient, typically 0.1 to 0.2, to ensure increased inspection frequency towards the end of the device's lifespan.

[0017] Preferably, a grounding resistance impulse monitoring method based on lightning-affected areas is implemented using the aforementioned grounding resistance impulse monitoring system based on lightning-affected areas; the method includes the following steps: Current monitoring: The current monitoring module captures the impulse current waveform in real time. , where t represents time; Voltage monitoring: The voltage monitoring module measures the transient voltage drop of the grounding device under the impulse current. ; Dynamic impedance calculation: Based on the impulse current waveform, the dynamic impedance calculation module is used to calculate the dynamic impedance. and the transient voltage drop Calculate dynamic grounding impedance ; Impulse assessment: Based on the dynamic grounding impedance, the impulse assessment module is used to assess the impact. Establish the mapping relationship between lightning current parameters and grounding resistance, and identify defects in the grounding device; Early warning and control: Through the early warning and control module, when the dynamic grounding impedance is detected... When the change exceeds the preset threshold, an alarm is triggered and the external repair system is activated.

[0018] Preferably, the impact assessment step includes: Waveform region molecular steps: distinguish between the first lightning strike waveform and the subsequent return stroke waveform. The wavefront time of the first lightning strike waveform is in the range of 8μs to 12μs, and the wavetail time is in the range of 300μs to 400μs. The wavefront time of the subsequent return stroke waveform is in the range of 0.2μs to 0.3μs, and the wavetail time is in the range of 80μs to 120μs. Time-frequency analysis sub-step: For the dynamic grounding impedance... Time-frequency analysis is performed to extract its spectral features, wherein wavelet transform is used in the time-frequency analysis. Defect identification sub-step: Identify corrosion or fracture defects in the grounding electrode based on the spectral characteristics; specifically including: From the wavelet coefficients Extracting high-frequency energy ratio and the principal resonant frequency ; When the high frequency energy ratio If the value exceeds the first threshold, a corrosion defect is determined to exist. When the main resonant frequency When the deviation from the healthy reference frequency exceeds the second threshold, it is determined that there is a defect of breakage or loose connection; The early warning and control steps include: Risk prediction sub-step: Combining the lightning location system, predict the impact risk to grounding devices in high-thunderstorm areas; specifically including: Obtain lightning activity data and calculate the comprehensive risk coefficient of threatened grounding devices. ,when In such cases, activate the protection mode in advance; Linked alarm sub-step: When a single lightning strike causes the dynamic grounding impedance to rise by more than 20%, an alarm is triggered and the resistance-reducing liquid injection system is activated. The method further includes: Data fusion and lifetime prediction steps: Through the data fusion module, meteorological data, soil moisture data, and historical lightning strike records are integrated to construct an impact lifetime prediction model to predict the remaining lifetime of the grounding device. and based on Dynamically optimize inspection cycle .

[0019] The beneficial effects of this invention are as follows: 1. This invention utilizes lightning current coupling monitoring technology, including a high-frequency broadband current sensor and a differential voltage probe, to achieve real-time capture of the impulse current waveform and transient voltage drop caused by lightning strikes or switching overvoltages. This technology solves the problem that existing monitoring systems cannot reflect high-frequency impulse characteristics due to bandwidth limitations. Through broadband monitoring, it accurately acquires transient response data, providing a basis for dynamic impedance calculation. This avoids blind spots in lightning area monitoring using traditional methods and improves the completeness and real-time performance of data acquisition.

[0020] 2. This invention utilizes a dynamic assessment model of impulse resistance, based on the mapping relationship between lightning current amplitude, waveform, and grounding resistance, and employs time-frequency analysis to extract impedance spectrum characteristics, thereby enabling the identification of latent defects and health status assessment of grounding devices. This model addresses the lack of dynamic assessment capabilities in existing technologies. By distinguishing the differentiated impacts of the initial lightning strike and subsequent return strikes, it accurately reflects performance degradation under impulse, providing a scientific basis for early warning and maintenance decisions, and enhancing the system's intelligent analysis capabilities.

[0021] 3. This invention achieves proactive protection against grounding resistance degradation through an intelligent early warning and adaptive control module, combined with multi-dimensional data fusion and a lightning location system. When the dynamic grounding impedance change exceeds a threshold, the system triggers an alarm and links with an external repair system. Simultaneously, it predicts the impact risk in high-thunderstorm areas and activates the protection mode. This solution solves the problems of passive response and excessive maintenance in existing systems. Through real-time control and predictive maintenance, it improves the operational reliability and economy of power facilities under extreme weather conditions. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the system framework of the present invention; Figure 2 This is a schematic diagram of the process method in an embodiment of the present invention; Figure 3 This is a comparison curve of the impedance measurement performance of the method in this embodiment of the invention with the prior art; Figure 4This is a graph showing the relationship between lightning current and defect type between the method described in this embodiment of the invention and the prior art. Figure 5 This is a curve showing the lifespan prediction and inspection optimization of the method in this embodiment of the invention compared with the prior art; Figure 6 This is a risk level distribution diagram comparing the method in this embodiment of the invention with the prior art. Detailed Implementation

[0023] Example 1: like Figure 1 As shown, a grounding resistance impulse monitoring system based on lightning areas includes: The current monitoring module is configured to be deployed near the grounding electrode to capture the waveform of the inrush current caused by lightning strikes or operational overvoltages in real time. The voltage monitoring module is configured to measure the transient voltage drop of the grounding device under impulse current. The dynamic impedance calculation module is configured to calculate the dynamic grounding impedance based on the impulse current waveform and the transient voltage drop; The impact assessment module is configured to establish a mapping relationship between lightning current parameters and grounding resistance based on the dynamic grounding impedance, and to identify defects in the grounding device; The early warning and control module is configured to trigger an alarm and link with the external repair system when the change in the dynamic grounding impedance exceeds a preset threshold.

[0024] Preferably, the current monitoring module includes a high-frequency broadband current sensor with a frequency range of 0.1Hz-1MHz; the voltage monitoring module includes a differential voltage probe. In specific implementations, the high-frequency broadband current sensor and the differential voltage probe enable real-time capture of the impulse current waveform and transient voltage drop caused by lightning strikes or operational overvoltages. This technology solves the problem that existing monitoring systems cannot reflect high-frequency impulse characteristics due to frequency band limitations. Through broadband monitoring, transient response data can be accurately obtained, providing a basis for dynamic impedance calculation, thereby avoiding blind spots in lightning area monitoring using traditional methods and improving the completeness and real-time performance of data acquisition.

[0025] Preferably, the impact assessment module is further configured as follows: The waveforms of the first lightning strike and the subsequent return strike are distinguished. The waveform of the first lightning strike has a wavefront time in the range of 8 μs to 12 μs and a wave tail time in the range of 300 μs to 400 μs. The waveform of the subsequent return strike has a wavefront time in the range of 0.2 μs to 0.3 μs and a wave tail time in the range of 80 μs to 120 μs. The spectral characteristics of the dynamic grounding impedance are extracted based on time-frequency analysis, where the time-frequency analysis employs a wavelet transform function: ; in, These are wavelet coefficients. For scale parameters, For translation parameters, For dynamic grounding impedance, The wavelet basis function is used to identify corrosion or fracture defects in the grounding electrode based on the spectral characteristics.

[0026] In practical implementation, the impact assessment module can identify and assess the health status of grounding devices by using the mapping relationship between lightning current amplitude, waveform and grounding resistance, and extracting impedance spectrum characteristics through time-frequency analysis. This solves the problem of the lack of dynamic assessment capability in existing technologies. By distinguishing the differentiated effects of the first lightning strike and subsequent return strikes, it accurately reflects the performance degradation under impact, provides a scientific basis for early warning and maintenance decisions, and enhances the intelligent analysis level of the system.

[0027] Preferably, the spectral characteristics are used to identify corrosion or fracture defects in the grounding electrode, including: (1) Feature extraction unit, configured to extract features from the wavelet coefficients The frequency domain features characterizing the state of the grounding electrode are extracted, including: High-frequency energy ratio: Characterizes the relative energy of high-frequency components in the impedance spectrum, and is calculated using the following formula: ; in, This represents the set of scale parameters corresponding to the high-frequency band. Representative in scale Peaceful relocation Energy of wavelet coefficients; Main resonant frequency : Characterizes the frequency at which energy peaks occur in the impedance spectrum.

[0028] (2) A defect discrimination unit is configured to compare the frequency domain feature quantity with a preset health status threshold, wherein the health status threshold is set to two stages, including a first threshold and a second threshold: When the high frequency energy ratio If the value exceeds the first threshold, the grounding electrode is determined to have corrosion defects. When the main resonant frequency When a significant deviation occurs, exceeding the second threshold from the healthy reference frequency, it is determined that the grounding electrode has a breakage or loose connection defect.

[0029] In specific implementation, this embodiment identifies the hidden defects of the grounding body by analyzing the spectral characteristics of the dynamic grounding impedance. The physical basis is that when the grounding body is subjected to lightning current impact, its equivalent circuit model will change due to the change in its physical state, and this change will be directly reflected in the frequency domain response of the impedance.

[0030] (1) Identification of corrosion defects: When a grounding electrode corrodes, its effective conductive cross-sectional area decreases, leading to an increase in resistance per unit length. Under the influence of high-frequency lightning current, due to the skin effect, the current is mainly concentrated on the conductor surface. The surface deterioration and increased resistance caused by corrosion exacerbate the loss of high-frequency current. This phenomenon manifests in the frequency domain as a relative increase in the energy of high-frequency components.

[0031] Therefore, this embodiment calculates the high-frequency energy ratio as a characteristic quantity. For a healthy grounding electrode of fixed length, its high-frequency energy ratio is within a stable range. When corrosion occurs, the high-frequency energy ratio increases significantly. By setting a first threshold based on historical health data or theoretical calculations, the system can automatically determine the occurrence of corrosion.

[0032] (2) Identification of fracture defects: When a grounding electrode breaks or its connection becomes loose, it's equivalent to introducing a large discontinuity—an impedance abrupt change—into the original uniform transmission line. This causes electromagnetic waves to be strongly reflected at that point, thus altering the resonant characteristics of the entire grounding system.

[0033] In the frequency domain, this manifests as a shift in the main resonant frequency of the impedance spectrum. The closer the break point is to the measurement point, the more pronounced the additional inductance / capacitance effect it introduces, and the greater its impact on the resonant frequency.

[0034] Therefore, this embodiment identifies breaks by tracking changes in the main resonant frequency. The system records the main resonant frequency of the grounding device in a healthy state as a reference. When a deviation of the main resonant frequency exceeding the normal fluctuation range is detected, it can be determined that a break or poor connection defect may exist. Combining multi-node measurement data can further pinpoint the defect.

[0035] Preferably, the early warning and control module is further configured as follows: By combining the lightning location system, the impact risk of grounding devices in high-thunderstorm areas can be predicted, and the protection mode can be activated in advance; When a single lightning strike causes the dynamic grounding impedance to rise by more than 20%, an alarm is triggered and the resistance-reducing liquid injection system is activated.

[0036] In practical implementation, the intelligent early warning and adaptive control module, combined with multi-dimensional data fusion and a lightning location system, achieves proactive protection against grounding resistance degradation. When the dynamic grounding impedance change exceeds a threshold, the system triggers an alarm and links with an external repair system. Simultaneously, it predicts the impact risk in high-thunderstorm areas and activates the protection mode. This solution solves the problems of passive response and excessive maintenance in existing systems, improving the operational reliability and economy of power facilities under extreme weather conditions through real-time control and predictive maintenance.

[0037] Preferably, in conjunction with a lightning location system, the impact risk to grounding devices in high-thunderstorm areas is predicted, and the protection mode is activated in advance, specifically including: (1) Risk mapping unit, configured as follows: Acquire real-time lightning activity data provided by the lightning location system, including the movement trajectory of thunderclouds and lightning strike density. and estimated arrival time ; According to the trajectory and Determine the set of affected grounding devices ; (2) Dynamic risk assessment unit, configured as follows: For sets Each grounding device Calculate its comprehensive risk coefficient The calculation formula is: ; in, Maximum historical lightning strike density Device The most recently monitored dynamic grounding impedance relative to its health benchmark The amount of degradation, i.e.: ; The threshold for impedance degradation alarm; For device Soil moisture at the location, Soil saturation moisture; These are the weighting coefficients, and ; Will With preset risk threshold Compare; (3) Protection decision unit, configured as follows: when At that time, the determining device It is a high-risk device, and its protective mode is activated in advance.

[0038] In its implementation, this embodiment combines macroscopic early warning information from an external lightning location system with the microscopic health status of the grounding device monitored internally through data fusion, achieving a leap from "passive response" to "active prediction." The implementation process is as follows: (1) Matching of risk areas with equipment: The early warning and control module receives data packets from the lightning location system in real time via communication interfaces such as 4G / 5G and satellite communication. These data packets not only contain the location of the lightning strike, but more importantly, they include the movement vector of the thundercloud cluster, the probability density distribution map of lightning strikes over a future period, and the estimated arrival time.

[0039] The system overlays the predicted lightning activity path with the preset locations of grounding devices on an electronic map, dynamically identifying the set of risky devices that will be affected.

[0040] (2) Multi-factor dynamic risk assessment: The core of this prediction lies in not treating all risk devices the same, but rather conducting differentiated and precise assessments. This invention introduces a comprehensive risk coefficient. The model comprehensively considers risks in three dimensions: External threat level w1: energy and frequency threat from lightning itself, characterized by normalized lightning strike density.

[0041] Internal vulnerability (w2): The health status of the grounding device itself; a device that has already deteriorated is less able to withstand further impacts and is at higher risk. This item incorporates the cumulative effect of historical impacts into the assessment.

[0042] Item w3, Environmental Aggravation: Soil moisture directly affects soil resistivity. Higher moisture content results in lower soil resistivity, making it easier for lightning current to dissipate, but it may also exacerbate the electrolytic corrosion effect on the grounding electrode. This item reflects the amplification or mitigation effect of the current environment on the impact consequences.

[0043] By using weighted calculations, the comprehensive risk coefficient quantifies the immediate and individualized risk level faced by each device.

[0044] (3) Tiered early warning and active protection: The system is based on the comprehensive risk coefficient The numerical values ​​are used to classify the response: Low risk Log only, continuous monitoring.

[0045] Medium risk Send an early warning notification to the monitoring center, reminding them to pay close attention.

[0046] High risk If a device is identified as high-risk, the protection mode will be activated in advance. The protection mode may include: a) System self-protection: Enhance the protection of this device The monitoring sampling rate is set to the highest level to prepare for capturing the complete impact waveform.

[0047] b) Linking external systems: Sending a preparatory command to the associated "resistance-reducing liquid injection system" to put it into standby mode, so that it can immediately trigger repair once an impedance surge is detected.

[0048] c) Power grid dispatch recommendations: Send risk alerts to the power grid control system to provide a reference for adjusting the operation mode in extreme cases.

[0049] Preferably, it further includes a data fusion module, configured as follows: Integrates meteorological data, soil moisture sensor data, and historical lightning strike records; A grounding device impulse life prediction model was constructed to optimize the inspection cycle; Generate a lightning strike incident report, including impact parameters, grounding performance degradation rate, and maintenance recommendations.

[0050] Preferably, a grounding device impulse life prediction model is constructed to optimize the inspection cycle, specifically including: (1) Cumulative damage calculation unit, configured as follows: Record the impact parameters for each lightning strike, including peak current. and impact charge Q; Based on Miller's cumulative damage theory, the damage caused to the grounding device by a single lightning strike is calculated. : ; in, The material damage coefficient, This is an empirical index, determined through accelerated life testing; Calculate the total cumulative damage up to the current time. The calculation formula is: ; N represents the total number of historical lightning strikes; (2) Lifetime prediction unit, configured as follows: Establish remaining lifespan With total cumulative damage The mapping model is given by the formula: ; in, For the design life of the grounding device, The critical damage threshold that leads to failure; Based on soil moisture H Introducing environmental correction factors for soil pH value Adjust the remaining lifespan: ; (3) Inspection optimization unit, configured as follows: Based on the predicted remaining lifespan Dynamically adjust the inspection cycle The adjustment strategy is as follows: ; in, and These represent the maximum and minimum inspection cycles allowed by the system. This is a proportionality coefficient, typically 0.1 to 0.2, to ensure increased inspection frequency towards the end of the device's lifespan.

[0051] In practical implementation, this embodiment constructs an impact life prediction model based on cumulative damage theory, quantifying discrete and severe lightning strike events into continuous consumption of the grounding device's lifespan, thereby achieving long-term prediction of the device's health status and precise optimization of inspection strategies.

[0052] (1) Establishment of the cumulative damage model: The deterioration of grounding devices is not an overnight process, but rather the result of the accumulation of micro-damage from each lightning strike's energy. This invention draws on the "Mina criterion" from the mechanical field, analogizing the electrical impact of a lightning strike to a mechanical fatigue load.

[0053] Damage quantification: the degree of damage from each lightning strike. From peak current It is determined together with the charge Q. Coefficient The calibration was obtained by conducting accelerated aging tests with impulse current on similar grounding materials in the laboratory.

[0054] For example, by applying impact currents of different amplitudes and waveforms to galvanized flat steel, measuring its resistance increase rate and mechanical strength decrease rate, damage model parameters can be fitted.

[0055] Damage Accumulation: The system automatically accumulates the damage from each lightning strike. The total cumulative damage is obtained. This is a more scientific and intuitive degradation indicator, which reflects the true extent of damage better than simply recording the number of lightning strikes.

[0056] (2) Remaining life prediction: Model core: The lifetime prediction model is based on a simple yet effective principle: when the cumulative damage... Reaching the critical threshold At that time, the device's lifespan ends. Similarly, this information is obtained through accelerated aging tests or statistical analysis of a large number of decommissioned grounding conductors.

[0057] Environmental factor correction: The model also incorporates environmental correction factors. For example, in moist, acidic soils, the corrosion rate is accelerated, therefore This correspondingly shortens the predicted lifespan. In dry, neutral soil This makes the prediction results more closely match the actual operating environment.

[0058] (3) Dynamic optimization of inspection cycle: Traditional fixed-period inspections have obvious drawbacks: they may be insufficient for high-risk devices and excessive for low-risk devices; this embodiment realizes risk-based dynamic inspections.

[0059] Strategy Logic: Inspection Cycle With predicted remaining lifespan Proportional; for a brand-new device with low cumulative damage, its remaining lifespan is long, and the system will automatically adopt a longer inspection cycle, such as... Months, saving on operation and maintenance costs.

[0060] As cumulative damage increases and remaining lifespan decreases, the system will gradually shorten the inspection cycle, such as reducing it to... For a period of one month or even less, intensive monitoring is conducted at the end of the lifespan.

[0061] Upper and lower limit protection: The min and max functions in the formula ensure that the inspection cycle is always within a reasonable range. This helps avoid extreme situations caused by computational anomalies.

[0062] Example 2: like Figure 2 As shown, this embodiment provides a method for monitoring grounding resistance impulses in lightning-prone areas. The method includes the following steps: Current monitoring: The current monitoring module captures the impulse current waveform in real time. , where t represents time; Voltage monitoring: The voltage monitoring module measures the transient voltage drop of the grounding device under the impulse current. ; Dynamic impedance calculation: Based on the impulse current waveform, the dynamic impedance calculation module is used to calculate the dynamic impedance. and the transient voltage drop Calculate dynamic grounding impedance ; Impulse assessment: Based on the dynamic grounding impedance, the impulse assessment module is used to assess the impact. Establish the mapping relationship between lightning current parameters and grounding resistance, and identify defects in the grounding device; Early warning and control: Through the early warning and control module, when the dynamic grounding impedance is detected... When the change exceeds the preset threshold, an alarm is triggered and the external repair system is activated.

[0063] Preferably, the impact assessment step includes: Waveform region molecular steps: distinguish between the first lightning strike waveform and the subsequent return stroke waveform. The wavefront time of the first lightning strike waveform is in the range of 8μs to 12μs, and the wavetail time is in the range of 300μs to 400μs. The wavefront time of the subsequent return stroke waveform is in the range of 0.2μs to 0.3μs, and the wavetail time is in the range of 80μs to 120μs. Time-frequency analysis sub-step: For the dynamic grounding impedance... Time-frequency analysis is performed to extract its spectral features, wherein wavelet transform is used in the time-frequency analysis. Defect identification sub-step: Identify corrosion or fracture defects in the grounding electrode based on the spectral characteristics; specifically including: From the wavelet coefficients Extracting high-frequency energy ratio and the principal resonant frequency ; When the high frequency energy ratio If the value exceeds the first threshold, a corrosion defect is determined to exist. When the main resonant frequency When the deviation from the healthy reference frequency exceeds the second threshold, it is determined that there is a defect of breakage or loose connection; The early warning and control steps include: Risk prediction sub-step: Combining the lightning location system, predict the impact risk to grounding devices in high-thunderstorm areas; specifically including: Obtain lightning activity data and calculate the comprehensive risk coefficient of threatened grounding devices. ,when In such cases, activate the protection mode in advance; Linked alarm sub-step: When a single lightning strike causes the dynamic grounding impedance to rise by more than 20%, an alarm is triggered and the resistance-reducing liquid injection system is activated. The method further includes: Data fusion and lifetime prediction steps: Through the data fusion module, meteorological data, soil moisture data, and historical lightning strike records are integrated to construct an impact lifetime prediction model to predict the remaining lifetime of the grounding device. and based on Dynamically optimize inspection cycle .

[0064] Example 3: This embodiment provides a method for applying the grounding grid impact monitoring project of the substation in Mile West Wind Power in Yunnan Province. The project is located in an area with frequent thunderstorms, averaging 75 thunderstorm days per year, and has 50 wind turbine generators with a single unit capacity of 2MW installed on the site. The specific implementation process is as follows: Operating environment and initial parameter settings: Monitoring targets: The grounding devices of 15 units located on the ridge, windward side and other locations prone to lightning strikes were selected as monitoring points, numbered WT01-WT15.

[0065] Sensor deployment: A high-frequency broadband current sensor and a differential voltage probe are installed near the grounding lead at each monitoring point; the current sensor bandwidth is 0.1Hz-1MHz.

[0066] The sampling rate of the data acquisition unit is set to 100kHz to ensure accurate capture of the rapid transient process of lightning current.

[0067] System threshold settings: Warning threshold: The threshold for the instantaneous rise of dynamic grounding impedance relative to the health reference value is set at 20%; the health reference value is the stable measurement value at the beginning of the unit's operation.

[0068] Risk level threshold: The threshold for the comprehensive risk coefficient Ri is set as follows: Low risk Ri < 0.4, medium risk 0.4 ≤ Ri < 0.7, high risk Ri ≥ 0.7.

[0069] The weighting coefficients are tentatively set as w1=0.5 (lightning strike density), w2=0.3 (device health), and w3=0.2 (environmental factors).

[0070] Defect identification threshold: High-frequency energy ratio The first threshold is set to 1.5 times the healthy reference value; the second threshold for the deviation of the main resonant frequency fr is set to ±15% of the healthy reference frequency.

[0071] Comparison benchmark: The data for the traditional method comes from a conventional online grounding resistance monitoring system based on the power frequency injection method deployed at the same wind farm during the same period, which measures the grounding resistance at the same monitoring point.

[0072] 2. Data collection cycle: Data in this embodiment was collected over a complete rainy season, i.e., 6 months. The system ran continuously and recorded complete data on all lightning strike events that occurred during this period. The table below summarizes the system's response results to typical lightning strike events at each monitoring point during this period.

[0073] The actual operating data is shown in Table 1 below: Table 1: Operational data of the method of the present invention;

[0074] The comparison data between this method and the conventional online grounding resistance monitoring system based on the power frequency injection method are shown in Table 2 below: Table 2: Comparison data of traditional methods;

[0075] As shown in Tables 1 and 2 above, compared with the conventional online grounding resistance monitoring system based on the power frequency injection method, the system and method of this embodiment demonstrate significant technical advantages in practical applications in mountain wind farms. Figure 3 It can be seen that by using high-frequency broadband monitoring technology, the system accurately captures the dynamic impedance change at the moment of lightning strike, and the impedance measurement error is controlled within 5%, which is far lower than the error of more than 25% of the traditional method.

[0076] Depend on Figure 4 As can be seen, time-frequency analysis based on wavelet transform successfully identified corrosion or fracture defects in eight grounding devices, achieving a defect identification accuracy of 100%. Traditional methods, due to bandwidth limitations, are completely unable to identify such latent defects. The intelligent early warning system accurately classified 15 monitoring points based on a comprehensive risk coefficient and activated active protection modes for five high-risk points, effectively preventing potential faults.

[0077] Depend on Figure 5 and Figure 6 As can be seen, the lifespan prediction model provides a personalized maintenance plan for each device, optimizing the inspection cycle from a fixed 12 months to a dynamic adjustment of 3-24 months, which is expected to reduce operation and maintenance costs by more than 35%. Compared with the response delay of more than 300ms in traditional methods, this invention achieves high-speed monitoring at the 10ms level, providing a valuable time window for lightning protection.

Claims

1. A grounding resistance impulse monitoring system based on lightning-prone areas, characterized in that, include: The current monitoring module is configured to be deployed near the grounding electrode to capture the waveform of the inrush current caused by lightning strikes or operational overvoltages in real time. The voltage monitoring module is configured to measure the transient voltage drop of the grounding device under impulse current. The dynamic impedance calculation module is configured to calculate the dynamic grounding impedance based on the impulse current waveform and the transient voltage drop; The impact assessment module is configured to establish a mapping relationship between lightning current parameters and grounding resistance based on the dynamic grounding impedance, and to identify defects in the grounding device; The early warning and control module is configured to trigger an alarm and link with the external repair system when the change in the dynamic grounding impedance exceeds a preset threshold.

2. The grounding resistance impulse monitoring system based on lightning areas according to claim 1, characterized in that, The current monitoring module includes a high-frequency wideband current sensor with a frequency range of 0.1Hz-1MHz; the voltage monitoring module includes a differential voltage probe.

3. The grounding resistance impulse monitoring system based on lightning areas according to claim 1, characterized in that, The impact assessment module is also configured to: The waveforms of the first lightning strike and the subsequent return strike are distinguished. The waveform of the first lightning strike has a wavefront time in the range of 8 μs to 12 μs and a wave tail time in the range of 300 μs to 400 μs. The waveform of the subsequent return strike has a wavefront time in the range of 0.2 μs to 0.3 μs and a wave tail time in the range of 80 μs to 120 μs. The spectral characteristics of the dynamic grounding impedance are extracted based on time-frequency analysis, where the time-frequency analysis employs a wavelet transform function: ； in, These are wavelet coefficients. For scale parameters, For translation parameters, For dynamic grounding impedance, The wavelet basis function is used to identify corrosion or fracture defects in the grounding electrode based on the spectral characteristics.

4. The grounding resistance impulse monitoring system based on lightning areas according to claim 3, characterized in that, Identifying corrosion or fracture defects in the grounding electrode based on the aforementioned spectral characteristics includes: (1) Feature extraction unit, configured to extract features from the wavelet coefficients The frequency domain features characterizing the state of the grounding electrode are extracted, including: High-frequency energy ratio: Characterizes the relative energy of high-frequency components in the impedance spectrum, and is calculated using the following formula: ； in, This represents the set of scale parameters corresponding to the high-frequency band. Representative in scale Peaceful relocation Energy of wavelet coefficients; Main resonant frequency : Characterizes the frequency at which energy peaks occur in the impedance spectrum; (2) A defect discrimination unit is configured to compare the frequency domain feature quantity with a preset health status threshold, wherein the health status threshold is set to two stages, including a first threshold and a second threshold: When the high frequency energy ratio If the value exceeds the first threshold, the grounding electrode is determined to have corrosion defects. When the main resonant frequency When a significant deviation occurs, exceeding the second threshold from the healthy reference frequency, it is determined that the grounding electrode has a breakage or loose connection defect.

5. The grounding resistance impulse monitoring system based on lightning areas according to claim 1, characterized in that, The early warning and control module is also configured to: By combining the lightning location system, the impact risk of grounding devices in high-thunderstorm areas can be predicted, and the protection mode can be activated in advance; When a single lightning strike causes the dynamic grounding impedance to rise by more than a set percentage, an alarm is triggered and the resistance-reducing liquid injection system is activated.

6. The grounding resistance impulse monitoring system based on lightning areas according to claim 5, characterized in that, By combining lightning location systems, the impact risk to grounding devices in high-thunderstorm areas can be predicted, and protection modes can be activated in advance, specifically including: (1) Risk mapping unit, configured as follows: Acquire real-time lightning activity data provided by the lightning location system, including the movement trajectory of thunderclouds and lightning strike density. and estimated arrival time ; According to the trajectory and Determine the set of affected grounding devices ; (2) Dynamic risk assessment unit, configured as follows: For sets Each grounding device Calculate its comprehensive risk coefficient The calculation formula is: ； in, Maximum historical lightning strike density Device The most recently monitored dynamic grounding impedance relative to its health benchmark The amount of degradation, i.e.: ； This is the threshold for impedance degradation alarm; For device Soil moisture at the location, Soil saturation moisture; These are the weighting coefficients, and ; Will With preset risk threshold Compare; (3) Protection decision unit, configured as follows: when At that time, the determining device It is a high-risk device, and its protective mode is activated in advance.

7. The grounding resistance impulse monitoring system based on lightning areas according to claim 1, characterized in that, It also includes a data fusion module, configured as follows: Integrates meteorological data, soil moisture sensor data, and historical lightning strike records; A grounding device impulse life prediction model was constructed to optimize the inspection cycle; Generate a lightning strike incident report, including impact parameters, grounding performance degradation rate, and maintenance recommendations.

8. The grounding resistance impulse monitoring system based on lightning areas according to claim 7, characterized in that, A grounding device impulse life prediction model is constructed to optimize the inspection cycle, specifically including: (1) Cumulative damage calculation unit, configured as follows: Record the impact parameters for each lightning strike, including peak current. and impact charge Q; Based on Miller's cumulative damage theory, the damage caused to the grounding device by a single lightning strike is calculated. : ； in, The material damage coefficient, This is an empirical index, determined through accelerated life testing; Calculate the total cumulative damage up to the current time. The calculation formula is: ； N represents the total number of historical lightning strikes; (2) Lifetime prediction unit, configured as follows: Establish remaining lifespan With total cumulative damage The mapping model is given by the formula: ； in, For the design life of the grounding device, The critical damage threshold that leads to failure; Based on soil moisture H Introducing environmental correction factors for soil pH value Adjust the remaining lifetime: ; (3) Inspection optimization unit, configured as follows: Based on the predicted remaining lifespan Dynamically adjust the inspection cycle The adjustment strategy is as follows: ； in, and These represent the maximum and minimum inspection cycles allowed by the system. This is the proportionality coefficient.

9. A method for monitoring grounding resistance impulse in lightning-prone areas, characterized in that, The system described in any one of claims 1-8 is used for execution; the method includes the following steps: Current monitoring: The current monitoring module captures the impulse current waveform in real time. , where t represents time; Voltage monitoring: The voltage monitoring module measures the transient voltage drop of the grounding device under the impulse current. ; Dynamic impedance calculation: Based on the impulse current waveform, the dynamic impedance calculation module is used to calculate the dynamic impedance. and the transient voltage drop Calculate dynamic grounding impedance ; Impulse assessment: Based on the dynamic grounding impedance, the impulse assessment module is used to assess the impact. Establish the mapping relationship between lightning current parameters and grounding resistance, and identify defects in the grounding device; Early warning and control: Through the early warning and control module, when the dynamic grounding impedance is detected... When the change exceeds the preset threshold, an alarm is triggered and the external repair system is activated.

10. The grounding resistance impulse monitoring method based on lightning areas according to claim 9, characterized in that, The impact assessment steps include: Waveform region molecular steps: distinguish between the first lightning strike waveform and the subsequent return stroke waveform. The wavefront time of the first lightning strike waveform is in the range of 8μs to 12μs, and the wavetail time is in the range of 300μs to 400μs. The wavefront time of the subsequent return stroke waveform is in the range of 0.2μs to 0.3μs, and the wavetail time is in the range of 80μs to 120μs. Time-frequency analysis sub-step: For the dynamic grounding impedance... Time-frequency analysis is performed to extract its spectral features, wherein wavelet transform is used in the time-frequency analysis. Defect identification sub-step: Identify corrosion or fracture defects in the grounding electrode based on the spectral characteristics; specifically including: From the wavelet coefficients Extracting high-frequency energy ratio and the principal resonant frequency ; When the high frequency energy ratio If the value exceeds the first threshold, a corrosion defect is determined to exist. When the main resonant frequency When the deviation from the healthy reference frequency exceeds the second threshold, it is determined that there is a defect of breakage or loose connection; The early warning and control steps include: Risk prediction sub-step: Combining the lightning location system, predict the impact risk to grounding devices in high-thunderstorm areas; specifically including: Obtain lightning activity data and calculate the comprehensive risk coefficient of threatened grounding devices. ,when In such cases, activate the protection mode in advance; Linked alarm sub-step: When a single lightning strike causes the dynamic grounding impedance to rise by more than a set percentage, an alarm is triggered and the resistance-reducing liquid injection system is activated. The method further includes: Data fusion and lifetime prediction steps: Through the data fusion module, meteorological data, soil moisture data, and historical lightning strike records are integrated to construct an impact lifetime prediction model to predict the remaining lifetime of the grounding device. and based on Dynamically optimize inspection cycle .

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