Online monitoring alarm network system based on lightning protection environment

Abstract

The invention discloses an online monitoring alarm network system based on a lightning protection environment, and relates to the technical field of lightning protection monitoring, and the system comprises a data collection module which is disposed at an offshore wind power plant and is used for collecting multi-dimensional data including salt mist concentration, wind speed, lightning parameters and lightning protection equipment state parameters; the data processing module is in communication connection with the data acquisition module and is used for receiving, fusing and analyzing the multi-dimensional data, performing scoring calculation by constructing a quantitative scoring model and endowing each dimensional parameter with a weight, and outputting a quantitative risk level according to a total score interval judgment mode; the early warning and linkage module is in communication connection with the data processing module and is used for executing graded early warning and linkage control based on the risk grades; the data processing module is further used for calculating the health state index of the SPD and dynamically predicting the remaining effective life of the SPD based on the health state index and the real-time environment parameters. The system has the functions of self-adaption to environment change and lightning protection monitoring and early warning.

Description

Technical Field

[0001] This invention belongs to the field of lightning protection monitoring technology, specifically relating to an online monitoring and alarm network system based on lightning protection environment. Background Technology

[0002] Wind turbines in coastal areas are located on coastal mudflats or the sea surface, some exceeding 80-100 meters in height, making them prime targets for lightning strikes. Lightning damage to wind turbines in coastal areas accounts for more than 80% of all lightning accidents in the entire wind power industry. Offshore wind turbines stand on flat sea surfaces, and moisture and salt spray accumulate on the blade surface, making them highly susceptible to lightning strikes.

[0003] Most mainstream lightning protection monitoring solutions employ fixed-frequency data acquisition or a single response mechanism triggered only by lightning warning signals. Fixed acquisition frequencies cannot adapt to the drastic dynamic changes in the marine environment. In calm weather, fixed-frequency acquisition generates a large amount of redundant data, consuming valuable satellite communication bandwidth and storage resources; while before and after severe weather such as thunderstorms, high salt spray, and strong winds, critical data on gradual environmental changes and early equipment degradation may be lost due to insufficient acquisition frequency.

[0004] This application has the function of adapting to environmental changes and realizing lightning protection monitoring and early warning. Summary of the Invention

[0005] The purpose of this invention is to provide an online monitoring and alarm network system for lightning protection environment to solve the technical problems mentioned in the background art.

[0006] To achieve the above objectives, the specific technical solution of the present invention is as follows: An online monitoring and alarm network system based on lightning protection environment includes: The data acquisition module is deployed in the offshore wind farm and is used to collect multi-dimensional data including salt spray concentration, wind speed, lightning parameters and lightning protection equipment status parameters. The data processing module, which is communicatively connected to the data acquisition module, is used to receive and integrate the multi-dimensional data, and to calculate the score by constructing a quantitative scoring model and assigning weights to the parameters of each dimension, and to output a quantitative risk level based on the total score range. The early warning and linkage module is communicatively connected to the data processing module and is used to perform graded early warning and linkage control based on the risk level. The system, through the collaboration of the data acquisition module and the data processing module, implements an environmental adaptive data acquisition strategy based on salt spray concentration and wind speed, specifically including: The data acquisition module is used to acquire the salt spray concentration and wind speed values ​​of the monitoring area in real time. The data processing module has a preset acquisition frequency mapping rule embedded in it, which is used to determine the corresponding acquisition frequency level based on the real-time acquired salt spray concentration value and wind speed value; the mapping rule defines at least three states: normal, alert, and emergency, and their correspondence with salt spray concentration threshold and wind speed threshold. The data processing module is further configured to send the acquisition frequency level to the data acquisition module to control it to perform data acquisition at the corresponding frequency.

[0007] The data processing module is also used to calculate the health status index of the SPD, and dynamically predict the remaining effective lifespan of the SPD based on the health status index and real-time environmental parameters.

[0008] Optionally, the sampling frequency mapping rule is as follows: When the salt spray concentration is less than or equal to the first salt spray threshold and the wind speed is less than or equal to the first wind speed threshold, it corresponds to the normal state and the first sampling frequency. When the salt spray concentration is greater than the first salt spray threshold and less than or equal to the second salt spray threshold, or when the wind speed is greater than the first wind speed threshold and less than or equal to the second wind speed threshold, the corresponding alert state and the second sampling frequency are higher than the first sampling frequency. When the salt spray concentration is greater than the second salt spray threshold or the wind speed is greater than the second wind speed threshold, it corresponds to an emergency state and a third sampling frequency higher than the second sampling frequency.

[0009] Optionally, the first salt spray threshold is 50 mg / m³. 3 The second salt spray threshold is 100 mg / m³. 3 The first wind speed threshold is 10 m / s, and the second wind speed threshold is 20 m / s.

[0010] Optionally, the data processing module is further configured to: The data acquisition module receives and collects lightning activity signals. When lightning activity occurs, the current acquisition frequency level is ignored, a high-frequency acquisition command is generated and sent to the data acquisition module to control all monitoring units to acquire data in a predetermined high-frequency mode until the lightning activity ends and a preset recovery period has elapsed.

[0011] Optionally, the data acquisition module includes: The marine environmental parameter monitoring unit includes at least a salt spray concentration sensor for collecting the salt spray concentration value and a wind speed sensor for collecting the wind speed value; Lightning parameter monitoring unit, used to collect lightning parameters; The lightning protection equipment status monitoring unit is used to collect status parameters of the lightning protection equipment.

[0012] Optionally, the specific methods by which the data processing module outputs a quantitative risk level through fusion analysis include: A quantitative scoring model is constructed, and weights are assigned to lightning parameters, equipment status parameters, and environmental parameters, and scores are calculated. The risk level is determined based on the range to which the total score belongs.

[0013] Optionally, the specific methods by which the data processing module calculates the SPD health status index and dynamically predicts the remaining effective lifespan include: The basic health status index is calculated based on the leakage current, tripping status and ambient temperature and humidity parameters of the SPD. A real-time environmental corrosion factor calculated from real-time salt spray concentration and relative humidity is introduced to correct the cumulative equivalent loss time; The remaining effective lifetime is calculated based on the revised model.

[0014] Optionally, the calculation formula for the real-time environmental corrosion factor K_env is: K_env=α*(C / C0)+β*(H / H0), where C is the measured salt spray concentration, C0 is the reference concentration; H is the measured relative humidity, H0 is the reference humidity; α and β are weighting coefficients calibrated through accelerated corrosion tests.

[0015] Optionally, the hierarchical early warning and linkage control executed by the early warning and linkage module includes: When the risk level is set to warning, a warning message will be automatically sent. When the risk level is alarm, a remote load reduction command is triggered; When the risk level is emergency response, a remote shutdown command is triggered and backup power is activated. When the data processing module predicts that the remaining effective lifespan of the SPD is lower than a preset threshold, it automatically generates a preventive maintenance or replacement work order and pushes a reminder message.

[0016] Optionally, the sensor components used in the data acquisition module have a design to withstand harsh environments, specifically including a stainless steel shell and a double-layer PVD coating; the signal transmission cable connected to the sensor components adopts a combination structure of fluororubber protective sheath and double-layer tinned copper wire braided shielding layer.

[0017] Beneficial effects: 1. Improved data efficiency and quality: By adopting an adaptive acquisition strategy based on dual environmental parameters of salt spray concentration and wind speed, the system can automatically increase the sampling rate to capture key data in the early stage of environmental degradation, and reduce the sampling rate to reduce resource consumption during the stable period of environment. Thus, while ensuring the timeliness and integrity of data, the system significantly optimizes the utilization efficiency of data transmission and storage resources.

[0018] 2. Improvement in early warning accuracy: Based on high-quality multi-source data and a fusion analysis model, the risk levels output by the system are quantified and clearly graded, overcoming the ambiguity of traditional single-threshold alarms and providing a reliable basis for implementing scientific graded responses.

[0019] 3. Enhancement of system reliability: For the harsh marine environment, the sensors and cables and other hardware have been strengthened with anti-salt spray corrosion and anti-strong electromagnetic interference designs, effectively improving the long-term operation stability and service life of the entire monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the module structure of the present invention; SPECIFIC EMBODIMENTS

[0021] The following further elaborates on the specific embodiments of the present invention in conjunction with the appended Figure 1 drawings.

[0022] The system provided by the present invention includes a data acquisition module, a data processing module, and an early warning and linkage module, and each module interacts through an industrial Ethernet.

[0023] The data acquisition module includes a marine environmental parameter monitoring unit deployed on the top of the nacelle and the hub, a lightning parameter monitoring unit deployed at the booster station and the nacelle, and a lightning protection equipment status monitoring unit integrated in each cabinet. The initial acquisition frequency is 1 time per 5 minutes.

[0024] State mapping: The policy engine in the data processing module substitutes the real-time data pair (salt spray concentration C, wind speed V) into the mapping rule: If C ≤ 50 mg / m 3 and V ≤ 10 m / s, it is determined as the normal state, and an instruction is issued to set the acquisition frequency to the first acquisition frequency, which is 1 time per 5 minutes in the embodiment of the present application.

[0025] If 50 < C ≤ 100 mg / m 3 or 10 < V ≤ 20 m / s, it is determined as the warning state, and an instruction is issued to increase the acquisition frequency to the second acquisition frequency, which is 1 time per 1 minute in the embodiment of the present application.

[0026] If C > 100 mg / m 3 or V > 20 m / s, it is determined as the emergency state, and an instruction is issued to further increase the acquisition frequency to the third acquisition frequency, which is 1 time per 10 seconds in the embodiment of the present application.

[0027] Forced Trigger: When the lightning parameter monitoring unit (such as the lightning detection device in the field) captures a lightning signal, the data processing module immediately generates the highest priority instruction, forcing all monitoring units to enter the lightning tracking mode once per second, which continues until 30 minutes after the last lightning strike, to ensure that the entire lightning strike process and post-disaster equipment status data are captured.

[0028] The adaptive strategy ensures the timeliness of the input data, laying the foundation for subsequent accurate analysis. The risk quantification model of the data processing module is as follows in this embodiment: Model Construction: A weighted scoring method was adopted. The weights were allocated as follows: lightning parameters 30%, equipment status parameters 40%, and environmental parameters 30%.

[0029] In this embodiment, the scoring criteria for each core sub-item are as follows (those skilled in the art can adjust them according to actual application scenarios without affecting the core concept of the present invention): Major Indicator Categories Sub-item name score Corresponding parameter range Status Description Risk Explanation Lightning parameters Lightning distance 0 points > 10 km No impact Lowest risk 30 points 5 – 10 km Potential impact Low risk 70 points 2 – 5 km Moderate impact Medium risk 100 points ≤ 1 km direct threat Highest risk (danger limit) Lightning intensity 0 points < 100 kA Weak lightning strike Lowest risk 60 points 100 – 200 kA Moderate lightning strike Medium risk 100 points ≥ 200 kA Strong lightning strike Highest risk (danger limit) Equipment status parameters SPD leakage current 0 points ≤ 0.5 mA normal Lowest risk 40 points 0.5 – 1.0 mA Slight degradation Low risk 80 points 1.0 – 3.0 mA Severe deterioration High risk 100 points > 3.0 mA Failure Highest risk (danger limit) Grounding resistance 0 points ≤ 10 Ω excellent Lowest risk 20 points 10 – 20 Ω Slightly exceeding the standard Low risk 100 points > 20 Ω Seriously exceeding the standard Highest risk (danger limit) Environmental parameters Salt spray concentration 0 points ≤ 50 mg / m 3 ]] Normal state Lowest risk 70 points 50 - 100 mg / m 3 ]] alert status Medium risk 100 points > 100 mg / m 3 ]] State of emergency Highest risk (danger limit) Real-time wind speed 0 points ≤ 10 m / s Normal state Lowest risk 70 points 10 – 20 m / s alert status Medium risk 100 points > 20 m / s State of emergency Highest risk (danger limit) Scoring Example: The system scores each parameter sub-item (0-100 points) and then sums the scores using weighted averages to obtain a normalized risk level S. Upon receiving the risk level S, the early warning and linkage module executes a standardized response. Warning: If 4≤S<7, or if a single parameter shows a moderate anomaly or multiple parameters show a slight anomaly, an early warning message containing the expected risk window will be automatically pushed to the control center's large screen and the mobile terminals of maintenance personnel. An alarm is triggered if 7 ≤ S < 9, or if a single parameter exhibits a severe abnormality or multiple moderate abnormalities occur simultaneously. In such cases, a "load reduction" command is sent to the wind farm's SCADA system via the standardized Modbus-RTU protocol to control the target unit's power output to be reduced to 50% of its rated power, thereby reducing the electrical and mechanical impacts that may result from lightning strikes. In emergency situations, if S≥9 or any critical safety parameter reaches its limit threshold (0 or 100 points), an "emergency shutdown" command is immediately sent to the SCADA system to control the unit to feather and shut down. Simultaneously, the UPS backup power supply is activated to ensure the operation of the core monitoring loop. Within 10 seconds of a lightning strike, the system automatically retrieves the nearest video surveillance footage of the fault location, records and uploads the scene, providing first-hand visual evidence for subsequent fault diagnosis.

[0030] For example, lightning distance: 3km - 70 minutes (moderate impact); lightning intensity: 180kA - 60 minutes (moderate lightning strike); SPD leakage current: 2.5mA - 80 minutes (severe degradation, severe single-phase anomaly); grounding resistance: 8Ω - 0 minutes (excellent); salt spray concentration: 95mg / m³ 3 -70 minutes (alert status); Real-time wind speed: 18 m / s -70 minutes (alert status).

[0031] Total score calculation: The weights of each sub-item are equally distributed, and the weighted total score (out of 100) is calculated as S_percent = 70*0.15 + 60*0.15 + 80*0.2 + 0*0.2 + 70*0.15 + 70*0.15 = 56.5 points. After normalization, S≈5.65.

[0032] Although the total score S=5.65 falls within the "warning" range (4≤S<7), the SPD leakage current sub-item score reaches 80 points, constituting a "serious anomaly." According to the rules (alarm conditions: 7≤S<9, or a single parameter exhibiting a serious anomaly), the system determines the current risk level to be "alarm."

[0033] To support the long-term operation of the aforementioned intelligent strategy in harsh environments, the hardware is designed specifically for this purpose. In this embodiment, the sensor's protective housing is made of 316L stainless steel with a double-layer PVD coating (inner layer CrN, outer layer TiN). The connectors adopt a 20° self-draining oblique insertion structure to resist salt spray condensation and penetration.

[0034] The signal cable adopts a structure with a fluororubber sheath (2.2mm thick, resistant to -40℃~150℃) and a double-layer tinned copper wire braided shield (braiding density ≥92%).

[0035] As an in-depth application of equipment condition monitoring, the SPD health status index is defined in this embodiment as follows: SPD basic health status index HI_b = S_leak*40% + S_trip*30% + S_env*30%.

[0036] Among them, S_leak is the leakage current score based on the national standard threshold, S_trip is the tripping status score, and S_env is the cabinet temperature and humidity score. This HI_b reflects the real-time health of the equipment under standard conditions.

[0037] This invention defines the real-time environmental corrosion factor K_env = α*(C / C0) + β*(H / H0), where C is the measured salt spray concentration and C0 is the reference concentration (50 mg / m³). 3 H represents relative humidity, and H0 represents reference humidity (80%). α and β are weighting coefficients, calibrated through accelerated corrosion tests. In this embodiment, α = 0.6 and β = 0.4.

[0038] This invention employs a cumulative loss model for lifetime prediction. This model uses the real-time environmental corrosion factor K_env to correct for the cumulative equivalent loss time, specifically: L_remaining = L_rated -∫(K_env * HI_ratio) dt, where L_rated is the rated lifetime of the SPD, and HI_ratio is the health state degradation coefficient. By integrating the product of K_env and HI_ratio over time, the cumulative equivalent loss time of the SPD in actual harsh environments is calculated, thereby dynamically predicting its remaining effective lifetime.

[0039] In the embodiments of this application, the system calculates K_env and HI_b every hour and accumulates the integral. When the integral value reaches L_rated, the lifespan is considered exhausted. The system can display L_remaining in real time.

[0040] An alarm is triggered when L_remaining falls below a preset threshold (e.g., 6 months), and a preventative replacement work order is automatically generated.

[0041] In the first embodiment of this application, the applicant conducted a typhoon passage scenario simulation and a full-process system response test in Zhoushan.

[0042] Data Basis and Simulation Equivalence Explanation: Historical typhoon meteorological data was imported. Using salt spray generators positioned upwind, the salt spray concentration at the monitoring points was increased from the background level to 125 mg / m³. 3 The concentration distribution matches the salt spray characteristics of a real typhoon front. By adjusting the power of nearby operating wind turbines, a stable interfering wind field above 25 m / s was created at the target wind turbine (B07) to simulate typhoon wind speed. A broadband electromagnetic pulse sequence conforming to the characteristics of natural lightning was emitted from a mobile lightning signal simulator at a distance of 1.5 km to primarily verify the system's detection and response logic to the initial radiation field of lightning.

[0043] T+0:00: Salt spray concentration exceeds 100 mg / m³ for the first time. 3 The wind speed exceeded 20 m / s. According to the mapping rules, the data processing module immediately switched the collection frequency command of all sensors of the B07 wind turbine from "normal" (10 minutes / time) to "emergency" (1 time / second).

[0044] T+0:02: The lightning monitoring unit detects a simulated lightning signal, and the system determines that the lightning distance is within the "≤2km" range. The data processing module completes the weighted scoring calculation of all emergency frequency data for this round within 1 second: salt spray (100 points) + wind speed (100 points) + lightning distance (70 points). A single parameter exceeds the limit threshold, reaching the "emergency response" level.

[0045] T+0:03: The early warning and linkage module locks onto wind turbine B07 and sends an emergency shutdown command to SCADA. The command is transmitted via both the primary fiber optic link and the backup wireless link to ensure its effectiveness. At the same time, the system issues "early warning" and "recommended load reduction" prompts to the adjacent wind turbines B06 and B08.

[0046] Test results: System end-to-end response latency < 1.8 seconds. In a 2-hour high-intensity simulation test, the adaptive acquisition strategy reduced unnecessary data transmission by approximately 35% compared to fixed-frequency acquisition (1 time / minute), while capturing critical event data completely.

[0047] In the second embodiment of this application, the applicant conducts progressive degradation monitoring and predictive maintenance of SPD in Hangzhou Bay.

[0048] The test involved continuous monitoring of the SPD module inside the A16 wind turbine transformer in Hangzhou Bay New Area for 30 days.

[0049] Monitoring and Data Processing: The system records leakage current at a "normal" frequency and processes the raw data using a moving average filter (1-hour window) to eliminate transient interference. During the observation period, the filtered leakage current value showed an upward trend from 0.3mA.

[0050] Prediction Process: On day 12, the filter value stabilized above 0.8mA, and the system was marked as "slightly degraded." The lifetime prediction submodule was initiated. Using concurrent environmental data: average salt spray concentration 65 mg / m³ 3 The average relative humidity was 85%.

[0051] Calculate the environmental corrosion factor: K_env = 0.6*(65 / 50) + 0.4*(85 / 80) ≈ 1.23 (>1, indicating accelerated environmental aging).

[0052] Based on historical aging data and real-time correction factors, and using the cumulative loss model L_remaining = L_rated - ∫(K_env * HI_ratio) dt (the system performs discrete cumulative calculations in 1-hour increments), the dynamic prediction RUL is 35 days (confidence interval [32, 38] days).

[0053] Maintenance linkage: When RUL falls below the threshold, the system automatically generates and tracks maintenance work orders, achieving closed-loop management of predictive maintenance. Simultaneously triggered load reduction commands provide temporary protection.

[0054] The dynamically calculated predicted remaining useful life (RUL) is 35 days, with a confidence interval of [32, 38] days.

[0055] On days 24-25, a cold front caused a surge in wind speed and salt spray concentration, with real-time K_env instantly rising to 1.9. Based on this, the model immediately updated its forecast, revising the RUL down to 18 days (confidence interval [15, 21] days) and triggering an alert.

[0056] Maintenance linkage: When the predicted RUL value falls below the 30-day threshold, the system automatically generates a preventative maintenance work order and pushes it to the operation and maintenance platform. The work order status can be tracked in real time. Since the concurrent wind speed also triggered the "alarm" level, the system additionally executed a temporary protective command to "reduce load to 60%" for the A16 wind turbine.

[0057] Verification results: On day 33, the SPD triggered an alarm due to excessive leakage current, and its actual lifespan matched the predicted range. Maintenance work orders based on these predictions enabled the operations and maintenance team to complete the spare parts allocation and replacement plan a week ahead of schedule, avoiding unplanned downtime.

[0058] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A lightning protection environment online monitoring and alarm network system, characterized in that, include: The data acquisition module is deployed in the offshore wind farm and is used to collect multi-dimensional data including salt spray concentration, wind speed, lightning parameters and lightning protection equipment status parameters. The data processing module, which is communicatively connected to the data acquisition module, is used to receive and integrate the multi-dimensional data, and to calculate the score by constructing a quantitative scoring model and assigning weights to the parameters of each dimension, and to output a quantitative risk level based on the total score range. The early warning and linkage module is communicatively connected to the data processing module and is used to perform graded early warning and linkage control based on the risk level. The system, through the collaboration of the data acquisition module and the data processing module, implements an environmental adaptive data acquisition strategy based on salt spray concentration and wind speed, specifically including: The data acquisition module is used to acquire the salt spray concentration and wind speed values ​​of the monitoring area in real time. The data processing module has a preset acquisition frequency mapping rule embedded in it, which is used to determine the corresponding acquisition frequency level based on the real-time acquired salt spray concentration value and wind speed value; the mapping rule defines at least three states: normal, alert, and emergency, and their correspondence with salt spray concentration threshold and wind speed threshold. The data processing module is further configured to send the acquisition frequency level to the data acquisition module to control it to perform data acquisition at the corresponding frequency. The data processing module is also used to calculate the health status index of the SPD, and dynamically predict the remaining effective lifespan of the SPD based on the health status index and real-time environmental parameters.

2. The system according to claim 1, characterized in that, The sampling frequency mapping rule is as follows: When the salt spray concentration is less than or equal to the first salt spray threshold and the wind speed is less than or equal to the first wind speed threshold, it corresponds to the normal state and the first sampling frequency. When the salt spray concentration is greater than the first salt spray threshold and less than or equal to the second salt spray threshold, or when the wind speed is greater than the first wind speed threshold and less than or equal to the second wind speed threshold, the corresponding alert state and the second sampling frequency are higher than the first sampling frequency. When the salt spray concentration is greater than the second salt spray threshold or the wind speed is greater than the second wind speed threshold, it corresponds to an emergency state and a third sampling frequency higher than the second sampling frequency.

3. The system according to claim 2, characterized in that, The first salt spray threshold is 50 mg / m³ 3 The second salt spray threshold is 100 mg / m³. 3 The first wind speed threshold is 10 m / s, and the second wind speed threshold is 20 m / s.

4. The system according to claim 1, characterized in that, The data processing module is also used for: The data acquisition module receives and collects lightning activity signals. When lightning activity occurs, the current acquisition frequency level is ignored, a high-frequency acquisition command is generated and sent to the data acquisition module to control all monitoring units to acquire data in a predetermined high-frequency mode until the lightning activity ends and a preset recovery period has elapsed.

5. The system according to claim 1, characterized in that, The data acquisition module includes: The marine environmental parameter monitoring unit includes at least a salt spray concentration sensor for collecting the salt spray concentration value and a wind speed sensor for collecting the wind speed value; Lightning parameter monitoring unit, used to collect lightning parameters; The lightning protection equipment status monitoring unit is used to collect status parameters of the lightning protection equipment.

6. The system according to claim 1, characterized in that, The specific methods by which the data processing module outputs a quantitative risk level through fusion analysis include: A quantitative scoring model is constructed, and weights are assigned to lightning parameters, equipment status parameters, and environmental parameters, and scores are calculated. The risk level is determined based on the range to which the total score belongs.

7. The system according to claim 1, characterized in that, The specific methods by which the data processing module calculates the SPD health status index and dynamically predicts remaining effective lifespan include: The basic health status index is calculated based on the leakage current, tripping status and ambient temperature and humidity parameters of the SPD. A real-time environmental corrosion factor calculated from real-time salt spray concentration and relative humidity is introduced to correct the cumulative equivalent loss time; The remaining effective lifetime is calculated based on the revised model.

8. The system according to claim 7, characterized in that, The calculation formula for the real-time environmental corrosion factor K_env is: K_env=α*(C / C0)+β*(H / H0), where C is the measured salt spray concentration, C0 is the reference concentration; H is the measured relative humidity, H0 is the reference humidity; α and β are weighting coefficients calibrated through accelerated corrosion tests.

9. The system according to claim 1, characterized in that, The hierarchical early warning and linkage control executed by the early warning and linkage module includes: When the risk level is set to warning, a warning message will be automatically sent. When the risk level is alarm, a remote load reduction command is triggered; When the risk level is emergency response, a remote shutdown command is triggered and backup power is activated. When the data processing module predicts that the remaining effective lifespan of the SPD is lower than a preset threshold, it automatically generates a preventive maintenance or replacement work order and pushes a reminder message.

10. The system according to claim 1, characterized in that, The sensor components used in the data acquisition module are designed to withstand harsh environments, specifically including a stainless steel shell and a double-layer PVD coating; the signal transmission cable connected to the sensor components adopts a combination structure of fluororubber protective sheath and double-layer tinned copper wire braided shielding layer.

Images