A power equipment maintenance scheduling method and system based on environmental salt mist concentration perception

Abstract

The application discloses a kind of power equipment maintenance scheduling methods and systems based on environmental salt fog concentration perception, it is related to salt fog online monitoring and intelligent operation and maintenance technical field, including based on fuse temperature rise voltage drop measured data, off-line calibration equipment initial electrothermal characteristic, construct the nonlinear dynamics model of the increment of contact resistance with salt fog corrosion;Real-time environmental load is collected, real-time high-sensing atmospheric salt fog concentration is detected through particle size distribution spectrum online detection device, combined with environmental temperature and humidity dynamic correction single particle mass, obtain real-time load;Real-time load obtained is injected into nonlinear dynamics model, cumulative calculation contact surface damage, and using neural network expert database assesses equipment health degree grade;According to the trend assessment temperature rise risk, execute load current derating operation, and trigger intelligent maintenance early warning when determining protection failure.The method provides reliable, intelligent technical support for the safe operation of power equipment.

Description

Technical Field

[0001] This invention relates to the field of salt spray online monitoring and intelligent operation and maintenance technology, specifically to a method and system for power equipment maintenance and scheduling based on environmental salt spray concentration sensing. Background Technology

[0002] In specific geographical environments, high concentrations of salt spray particles in the atmosphere are a core factor leading to corrosion and damage to power equipment. Salt spray particles deposit on metal contact surfaces and absorb moisture to form a liquid film, triggering a complex electrochemical corrosion process that results in an abnormally high contact resistance. For high-current-carrying equipment such as fuses and switchgear, even a small increase in contact resistance can produce a dramatic temperature rise effect according to Joule's law. Without timely intervention, this can easily lead to terminal burnout or equipment thermal failure.

[0003] Currently, the main challenges facing the operation and maintenance of power equipment in special environments are as follows: Lagging and inaccurate monitoring methods: Traditional salt spray monitoring is mostly offline, resulting in poor data timeliness; while existing online monitoring technologies (such as impedance methods) are easily affected by dust and other soluble corrosive media, making it impossible to accurately distinguish between dust and salt spray, leading to low prediction accuracy; Lack of predictive early warning logic: Most existing temperature rise monitoring systems are based on physical temperature rise alarms, meaning that warnings or shutdowns are only issued when the equipment has generated significant heat accumulation and reached the alarm threshold, failing to address issues proactively in the early stages of contact resistance evolution; Blind operation and maintenance strategies: Maintenance personnel often conduct indiscriminate on-site verification, lacking quantitative assessments and dynamic operational adjustments based on the actual degree of equipment damage, resulting in low operation and maintenance efficiency and difficulty in responding to sudden failure risks in extreme environments.

[0004] Therefore, how to utilize high-precision online salt spray monitoring technology and combine it with the internal electrothermal evolution model of the equipment to achieve closed-loop scheduling from "environmental load perception" to "temperature rise risk prediction" and then to "automatic derated operation" has become a key requirement for improving the reliable operation of power equipment in strong salt spray environments. Summary of the Invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the technical problem solved by this invention is that existing methods for monitoring corrosion and maintaining power equipment have problems such as low real-time load monitoring accuracy, delayed temperature rise warning, low operation and maintenance efficiency, and how to achieve real-time quantitative assessment of internal damage evolution.

[0007] To address the aforementioned technical problems, this invention provides the following technical solution: a power equipment maintenance and scheduling method based on environmental salt spray concentration sensing, comprising: offline calibration of the initial electrothermal characteristics of the equipment based on measured data of fuse temperature rise and voltage drop; constructing a nonlinear dynamic model of contact resistance increment with salt spray corrosion; acquiring real-time environmental loads; using an online particle size distribution spectrum detection device to sense atmospheric salt spray concentration in real time; dynamically correcting the mass of individual particles by combining environmental temperature and humidity to obtain real-time loads; injecting the acquired real-time loads into the nonlinear dynamic model to cumulatively calculate contact surface damage; and using a neural network expert database to assess the equipment health level; assessing the temperature rise risk based on predicted trends; implementing load current derating operation; and triggering intelligent maintenance early warning when protection failure is determined.

[0008] As a preferred embodiment of the power equipment maintenance and scheduling method based on environmental salt spray concentration perception described in this invention, the offline calibration of the initial electrothermal characteristics of the equipment includes: obtaining the static DC resistance of the power equipment when it is not corroded using a high-precision resistance tester; extracting the reference voltage drop and reference temperature rise of the equipment under rated current through temperature rise and voltage drop tests; and establishing the initial electrothermal characteristics.

[0009] As a preferred embodiment of the power equipment maintenance and scheduling method based on environmental salt spray concentration perception described in this invention, the nonlinear dynamic model includes: constructing a model by fitting the resistance change rate data at different time points in a neutral salt spray test within a fixed time period, and evolving the process of contact resistance increment increasing with cumulative salt spray deposition.

[0010] As a preferred embodiment of the power equipment maintenance and scheduling method based on environmental salt spray concentration sensing described in this invention, the online particle size distribution spectrum detection device includes: drawing air from the monitoring area into a pipeline via a fan, passing through a humidity adjustment section, a pre-drying measurement section, a drying section, and a post-drying measurement section; adjusting the humidity of the sampled air in the humidity adjustment section using a semiconductor cooler to prevent condensation; acquiring particle size distribution spectrum data of particulate matter before drying using a first scattering laser particle size distribution spectrum meter; performing non-absorption drying of the sampled air using an infrared heater; acquiring particle size distribution spectrum data of particulate matter after drying using a second scattering laser particle size distribution spectrum tester; comparing and analyzing the changes in particle size distribution spectrum before and after drying, removing dust particles from the atmosphere, and extracting the number and particle size distribution spectrum of salt spray particles.

[0011] As a preferred embodiment of the power equipment maintenance and scheduling method based on environmental salt spray concentration sensing described in this invention, the method includes: dynamically correcting the mass of a single particle by combining environmental temperature and humidity, which involves using a first temperature and humidity sensor to collect the relative temperature and humidity of the environment in real time, establishing the relationship between the concentration of salt spray particles and the environmental temperature and humidity based on the salt particle deliquescence theory, and obtaining the real-time load of the current atmospheric salt spray concentration based on the corrected mass of a single particle and the obtained number and particle size distribution spectrum of salt spray particles.

[0012] As a preferred embodiment of the power equipment maintenance and scheduling method based on environmental salt spray concentration sensing described in this invention, the real-time load further includes data layered transmission and synchronization processing; using signals collected by monitoring salt spray concentration, temperature, humidity and atmospheric pressure at the equipment layer, the signals are converted into digital signals conforming to communication protocols through the relay layer main IED, and transmitted to the station control layer online monitoring via Ethernet; the real-time load data is synchronized and aligned with the timestamp of the equipment real-time load current data, and forwarded to the status monitoring master station server for storage and analysis.

[0013] As a preferred embodiment of the power equipment maintenance and scheduling method based on environmental salt spray concentration perception described in this invention, the cumulative calculation of contact surface damage includes: the condition monitoring master station performs integration processing on the time series based on real-time load, and outputs the cumulative salt spray exposure of the equipment contact part; the cumulative salt spray exposure is injected into a nonlinear dynamic model to simulate the reduction of effective conductive area and resistance evolution trend caused by salt corrosion products generated on the contact surface.

[0014] As a preferred embodiment of the power equipment maintenance and scheduling method based on environmental salt spray concentration perception described in this invention, the method of evaluating the health level of equipment using a neural network expert database includes: employing an artificial neural network evaluation algorithm; dividing data features through a clustering algorithm; matching the simulated real-time resistance increment with historical fault feature curves; and automatically labeling the corrosion level, defect type, and corrosion location size of the equipment.

[0015] As a preferred embodiment of the power equipment maintenance and scheduling method based on environmental salt spray concentration perception described in this invention, the intelligent maintenance early warning includes: establishing a self-inspection process based on resistance monitoring, comparing the monitored voltage drop growth rate with the stability threshold determined by the salt spray test in real time; if the resistance change rate trend points to the change rate critical line defined by the initial electrothermal characteristics, it is automatically determined that the equipment sealing protection or superhydrophobic aging-resistant coating has failed; the station control layer online monitoring synchronously uploads the corrosion exceeding signal to the platform backup, and generates an intelligent decision instruction containing maintenance suggestions and sends it to the operation and maintenance terminal.

[0016] Another objective of this invention is to provide a power equipment maintenance and scheduling system based on environmental salt spray concentration sensing. This system can acquire real-time environmental loads by collecting data and using an online particle size distribution spectrum detection device to detect atmospheric salt spray concentrations in real time. It also dynamically corrects the mass of individual particles by combining environmental temperature and humidity data, thereby obtaining real-time loads. This solves the problem of low accuracy in current power equipment corrosion monitoring and maintenance scheduling that involves environmental load monitoring.

[0017] As a preferred embodiment of the power equipment maintenance and scheduling system based on environmental salt spray concentration sensing described in this invention, it includes: a benchmark modeling module, a load sensing module, a state evolution module, and an intelligent scheduling module; the benchmark modeling module is used to offline calibrate the electrothermal characteristics of the equipment under rated current based on the measured temperature rise and voltage drop data of the fuse, and construct a nonlinear dynamic model of the contact resistance increment with salt spray corrosion; the load sensing module is used to obtain the current real-time atmospheric salt spray concentration load by comparing the changes in particle size distribution spectrum before and after drying, eliminating dust interference, and correcting the mass of individual salt spray particles in combination with environmental temperature and humidity using an online particle size distribution spectrum monitoring device; the state evolution module is used to inject the real-time salt spray concentration load into the nonlinear dynamic model for integral processing, cumulatively output the physical damage and resistance increment of the conductive contact surface of the equipment, and evaluate the equipment health level using a neural network expert database; the intelligent scheduling module is used to assess the temperature rise risk based on the predicted trend, automatically execute the load current derating operation command when the total temperature rise approaches the safety bottom line, and trigger intelligent maintenance early warning and upload the data to the cloud for backup when the protection failure is determined.

[0018] The beneficial effects of this invention are: The power equipment maintenance and scheduling method based on environmental salt spray concentration sensing provided by this invention utilizes measured data of fuse temperature rise and voltage drop, offline calibration of the initial electrothermal characteristics of the equipment, and construction of a nonlinear dynamic model of the increase in contact resistance with salt spray corrosion. This quantifies the evolution of contact resistance with salt spray corrosion, enabling quantitative assessment of internal micro-damage and overcoming the problem of not being able to sense the degree of internal corrosion. Real-time environmental load is collected, and the atmospheric salt spray concentration is sensed in real time through an online particle size distribution spectrum detection device. Combined with dynamic correction of individual particle mass based on ambient temperature and humidity, the real-time load is obtained, solving the problem of difficulty in distinguishing between atmospheric dust and salt spray particles. The accurate real-time salt spray mass concentration load ensures accurate prediction. The accuracy of logical input data is ensured by injecting real-time loads into a nonlinear dynamic model to accumulate and calculate contact surface damage. A neural network expert database is used to assess the equipment's health level, and the system automatically labels the degree of equipment corrosion. This achieves an intelligent transformation from simple environmental monitoring to equipment health prediction. Based on predicted trends, the system assesses temperature rise risks, implements load current derating, and triggers intelligent maintenance warnings when protection failure is detected. Furthermore, it triggers intelligent early warnings and executes intelligent scheduling when protection failure is detected, significantly extending the service life of equipment in extreme environments. This invention achieves better results in terms of early warning proactivity and accuracy, environmental adaptability, anti-interference capabilities, and operational efficiency. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is an overall flowchart of a power equipment maintenance and scheduling method based on environmental salt spray concentration sensing, provided in Embodiment 1 of the present invention.

[0021] Figure 2 The image shows the test results of a first-type sample of a power equipment maintenance and scheduling method based on environmental salt spray concentration sensing, as provided in Embodiment 2 of the present invention.

[0022] Figure 3 The image shows the test results of a second type of sample of a power equipment maintenance and scheduling method based on environmental salt spray concentration sensing, provided in Embodiment 2 of the present invention. Detailed Implementation

[0023] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0024] Example 1, referring to Figure 1 As an embodiment of the present invention, a power equipment maintenance scheduling method based on environmental salt spray concentration sensing is provided, comprising: S1: Based on the measured data of fuse temperature rise and voltage drop, the initial electrothermal characteristics F of the equipment are calibrated offline, and a nonlinear dynamic model 100 is constructed for the contact resistance as a function of salt spray corrosion increment.

[0025] Specifically, the initial electrothermal characteristics F of the offline calibration equipment include obtaining the static DC resistance of the power equipment when it is not corroded using a high-precision resistance tester, extracting the reference voltage drop and reference temperature rise of the equipment under rated current through temperature rise and voltage drop tests, and establishing the initial electrothermal characteristics F.

[0026] The initial electrothermal characteristics F of the power equipment under test are calibrated under standard atmospheric conditions. Different gradient load currents are applied to the power equipment in the initial state, and the voltage drop and equilibrium temperature rise data of the key conductive parts of the equipment are collected and recorded in real time.

[0027] During the calibration process, the initial static DC resistance of the equipment, as well as the reference temperature rise and reference voltage values ​​between the terminal and the center of the insulating medium under rated current conditions, are obtained through the high-precision electrical strategy unit. These parameters are defined as the optimal operating state point of the equipment and are used as the absolute reference coordinates for subsequent determination of performance deviations caused by salt spray corrosion.

[0028] Furthermore, the nonlinear dynamic model 100 includes the construction of a process by fitting the resistance change rate data at different time points in a neutral salt spray test over a fixed time period, which evolves the process of the increase in contact resistance as the cumulative salt spray deposition increases.

[0029] The core of the nonlinear dynamic model 100, which correlates the increase in contact resistance with the external environmental load, lies in simulating the electrochemical corrosion behavior of metal contact surfaces under salt spray conditions. As non-conductive or low-conductive metal salt corrosion products are generated on the conductive surface, the microscopic conductive spots shrink, which in turn causes the macroscopic contact resistance to increase.

[0030] By introducing the material corrosion rate coefficient and environmental impact factors, a nonlinear correlation between the increase in contact resistance and the cumulative salt spray deposition is established. This reflects that under a specific atmospheric salt spray concentration, the internal contact resistance of the equipment exhibits a nonlinear evolution trend with the increase in exposure time, and the degree of external environmental pollution is converted into a quantitative indicator of internal electrical damage in real time.

[0031] It should be noted that after obtaining the incremental evolution logic of the group, the equipment operation risk assessment matrix is ​​further constructed through the principles of energy conservation and thermal balance. First, the safe range and failure threshold of equipment operation are defined. The resistance change rate reaching the preset threshold is defined as the logical critical line of system maintenance, and the absolute temperature rise of the key wiring part exceeding the safety threshold is defined as the physical failure bottom line.

[0032] Based on the real-time resistance calculated at the moment and combined with the real-time load current, the system predicts the steady-state temperature rise that the equipment may reach under the current heat exchange conditions. This provides data and logic support for subsequent proactive derating scheduling. By adjusting the current load, the system can artificially control the Joule heat generation rate, offset the temperature rise risk caused by the increase in resistance, and achieve dynamic and safe operation of the equipment under damaged conditions.

[0033] S2: Collect real-time environmental load 200, and obtain the real-time load by using the particle size distribution spectrum P online detection device to detect atmospheric salt spray concentration in real time, and dynamically correct the mass Q of a single particle by combining the ambient temperature and humidity H.

[0034] Specifically, the online particle size distribution spectrum (P) detection device includes: drawing air from the monitoring area into a pipeline via a fan, passing through a humidity adjustment section, a pre-drying measurement section, a drying section, and a post-drying measurement section; adjusting the humidity of the sampled air in the humidity adjustment section using a semiconductor cooler to prevent condensation; acquiring the particle size distribution spectrum (P) data of particulate matter before drying using a first scattering laser particle size distribution spectrum meter; performing non-absorption drying of the sampled air using an infrared heater; acquiring the particle size distribution spectrum (P) data of particulate matter after drying using a second scattering laser particle size distribution spectrum tester; comparing and analyzing the changes in particle size distribution spectrum (P) before and after drying; removing dust particles from the atmosphere; and extracting the number of salt spray particles and their particle size distribution spectrum (P).

[0035] First, an online monitoring device is deployed within the monitoring area where the power equipment is located. Utilizing the principle of scattering laser particle size distribution spectroscopy, high-precision acquisition of the real-time concentration load of salt spray particles in the sampled air is achieved. The device uses a built-in fan to draw air from the monitoring area into the salt spray pipeline at a constant flow rate. A humidity adjustment unit is installed before sampling, using semiconductor cooling to adjust the relative humidity of the sampled air to a controlled state above 85% without condensation. This pretreatment process ensures that the salt spray nuclei in the air can fully absorb moisture and transform into regularly shaped microdroplets, thereby eliminating interference from non-hygroscopic impurities on subsequent optical measurements and improving measurement accuracy.

[0036] Along the measurement path, the system is equipped with two sets of scattering laser particle size distribution spectrometers: First, the first scattering laser particle size distribution spectrometer acquires the initial particulate matter particle size distribution spectrum P data of the sampled air before drying; then, the sampled air passes through an infrared heating drying section, causing the salt mist microdroplets to rapidly dehydrate and revert to dry salt particles, and the second scattering laser particle size distribution spectrometer acquires the particle size distribution spectrum data after drying. The system analyzes the characteristic changes in particle size distribution before and after drying using a comparative algorithm. Utilizing the physical characteristics of salt mist particles easily dehydrating and shrinking while dust particles have stable particle sizes, the system effectively distinguishes and eliminates background dust interference, thereby accurately extracting the number of pure salt mist particles of different sizes.

[0037] Furthermore, the dynamic correction of the mass Q of a single particle in conjunction with the ambient temperature and humidity H includes: using a first temperature and humidity sensor to collect the relative temperature and humidity of the environment in real time; establishing the relationship between the concentration of salt spray particles and the ambient temperature and humidity H based on the salt particle deliquescence theory; and obtaining the real-time load 200 of the current atmospheric salt spray concentration based on the corrected mass Q of a single particle and the obtained number of salt spray particles and particle size distribution spectrum P.

[0038] Real-time load also includes data layered transmission and synchronization processing; using the signals collected by the equipment layer 201 salt spray concentration, temperature, humidity and atmospheric pressure monitoring, the signals are converted into digital signals that conform to the communication protocol through the relay layer 202 main IED, and transmitted to the station control layer 203 online monitoring via Ethernet. The real-time load data is synchronized and aligned with the timestamp of the equipment real-time load current data, and forwarded to the status monitoring master station server for storage and analysis.

[0039] It should be noted that the system synchronously collects ambient relative humidity and ambient temperature in real time through the first and second temperature and humidity sensors. Since the real-time mass of a single salt spray particle is closely related to the deliquescence or crystallization state of its surrounding atmosphere, an environmental parameter compensation and correction logic is introduced to calculate the real-time mass concentration of a single salt spray particle under the current temperature and humidity conditions. Referring to the salt particle deliquescence equilibrium theory, the measured RH and T are substituted as input variables into a preset empirical function, expressed as follows: , in, This represents the real-time mass concentration of a single salt spray particle. For ambient relative humidity, The ambient temperature.

[0040] By using dynamic correction coefficients to physically compensate for the laser measurement results, the system ensures that the salt spray mass concentration obtained under extreme climatic conditions such as high temperature and humidity or low temperature and dryness has extremely high physical accuracy, providing a core input load for subsequent simulation and deduction of the increase in contact resistance corrosion.

[0041] It should also be noted that a three-tiered open data communication channel is constructed. At the equipment layer 201, the collected analog signals are converted into highly interference-resistant digital signals and transmitted in real time to the main intelligent electronic device (IED) of the power distribution unit or the main IED in the main control room at the relay layer 202. After receiving the data, the relay layer 202 equipment encapsulates it into standard data packets that meet the requirements of the IEC 61850 communication protocol and uploads them to the online monitoring and integrated processing unit at the station control layer 203 via a high-speed Ethernet link. During transmission, the system establishes a strict timestamp synchronization mechanism to ensure that the environmental salt spray concentration data sensed remotely and the load current data of the locally collected power equipment achieve a one-to-one correspondence at the millisecond level on the time axis. This highly synchronized data stream supports in-depth electrothermal correlation analysis in the large database integrated by the condition monitoring master station, providing rigorous data support for subsequent health status assessment and derated operation scheduling.

[0042] S3: The acquired real-time load 200 is injected into the nonlinear dynamic model 100 to accumulate and calculate the contact surface damage, and the equipment health level 300 is evaluated using the neural network expert library.

[0043] Specifically, the cumulative calculation of contact surface damage includes the condition monitoring master station performing integral processing on the time series based on the real-time load, and outputting the cumulative salt spray exposure of the contact part of the equipment; the cumulative salt spray exposure is injected into the nonlinear dynamic model 100 to simulate the reduction of effective conductive area and resistance evolution trend caused by the generation of salt corrosion products on the contact surface.

[0044] Based on the atmospheric salt spray concentration collected by the real-time payload 200, combined with the flow parameters of the sampling control unit, the cumulative salt spray deposition at the key conductive contact parts of the equipment is continuously calculated. The status monitoring master station of the station control layer 203 integrates the status monitoring big data, performs integral processing on the real-time concentration data according to the time series, and simulates the exposure intensity of the equipment in a specific environment.

[0045] Based on the constructed nonlinear dynamic model 100, the system converts the cumulative deposition amount into a real-time evolution value of the contact resistance. This process fully considers the influence of ambient humidity on the deliquescence of salt particles, simulating the formation of a liquid film on the metal surface and its accelerating effect on the electrochemical corrosion rate. Through this simulation, the system can update in real time the reduction of the effective conductive area inside the equipment due to the accumulation of corrosion products.

[0046] Furthermore, after acquiring the real-time simulated resistance increment, the system injects it into the constructed nonlinear dynamic model 100 and performs electrothermal balance analysis in conjunction with the actual load current fed back from the current device layer 201. This invention does not rely on traditional hysteretic temperature rise alarms, but instead calculates the additional heat load caused by the increase in resistance to deduce the electrothermal imbalance tendency of the equipment under the current operating state. The system compares the baseline voltage drop data recorded in the experiment to estimate the current real-time voltage drop offset. If the simulated voltage drop growth rate exceeds the stability threshold determined in the salt spray experiment, the system will determine that the external seal or anti-corrosion coating of the equipment has functionally failed, resulting in the internal contact surface being directly exposed to a high-concentration salt spray environment.

[0047] It should be noted that the assessment of equipment health level 300 using a neural network expert database includes the use of artificial neural network assessment algorithms, the segmentation of data features through clustering algorithms, the matching of simulated real-time resistance increments with historical fault feature curves, and the automatic labeling of the equipment's corrosion level, defect type, and corrosion location and size.

[0048] The condition monitoring main station incorporates AI processing algorithms and an ANN (Artificial Neural Network) expert database to perform multi-dimensional evaluations of the simulated data. The expert database uses clustering algorithms to segment optimal data features and automatically labels the corrosion level of the equipment, including normal, mild corrosion, critical risk, and severe failure.

[0049] This assessment logic can automatically identify abnormal evolution points in the health status of equipment. For example, even if the current actual temperature rise is still below the physical red line of 130K, if the ANN expert database identifies an abnormally large increase in the slope of the resistance increment, the system will determine in advance that the equipment has entered a "pre-failure" state and automatically locate the location and size of possible corrosion, providing quantitative diagnostic basis for the generation of subsequent intelligent decision-making instructions.

[0050] S4: Assess the risk of temperature rise based on the predicted trend, implement load current derating operation, and trigger intelligent maintenance warning 400 when the protection fails.

[0051] Specifically, the intelligent maintenance early warning system 400 includes establishing a self-inspection process based on resistance monitoring, comparing the monitored pressure drop growth rate with the stability threshold determined by the salt spray test in real time; if the resistance change rate trend points to the critical line of change rate defined by the initial electrothermal characteristic F, it will automatically determine that the equipment sealing protection or superhydrophobic aging-resistant coating has failed; the station control layer 203 online monitoring will simultaneously upload the corrosion exceeding the standard signal to the platform backup, and generate intelligent decision instructions containing maintenance suggestions to be sent to the operation and maintenance terminal.

[0052] Furthermore, the system status monitoring master station executes dynamic load balancing logic based on the real-time resistance increment simulated and the potential additional temperature rise predicted by the model. Unlike traditional power-off protection that occurs after reaching a physical threshold, this invention adopts a proactive "derating operation" strategy. When the predicted total temperature rise approaches the safety threshold of 130K, the system automatically calculates the safe load limit and issues a current-limiting command to the main IED of the power distribution device. By actively reducing the operating current, the heat generation is reduced to compensate for the risk of thermal failure caused by the increase in resistance, ensuring that the temperature rise of the equipment's terminals is always controlled within a safe range during periods of excessive salt spray concentration or protection failure.

[0053] It should be noted that the protection status is determined by comparing the real-time voltage drop with the calibrated baseline voltage drop. If the monitored voltage drop growth rate or resistance change rate shows an abnormal non-linear increase, and the trend points towards the experimentally determined 5% stability threshold, the system will automatically determine that the equipment's sealing or hydrophobic coating has suffered physical failure. At this time, the station control layer 203 online monitoring integrated processing unit will immediately trigger a maintenance warning, automatically generate a diagnostic report containing the corrosion type, location, and suspected size, and simultaneously upload it to a third-party cloud platform for backup, providing the operation and maintenance department with accurate maintenance basis.

[0054] The artificial neural network expert database integrated into the status monitoring master station automatically formulates the optimal operation and maintenance plan based on the equipment health status score. For equipment judged to be pre-failure or severely failed, the system will generate intelligent decision instructions and issue them to the abnormal operation and maintenance terminal to achieve targeted and planned on-site verification and troubleshooting. After the operation and maintenance personnel complete the cleaning of salt spray deposits, repair of coatings, or replacement of parts, the system will re-collect static resistance through the main IED and send it back to the station control layer 203 for closed-loop evaluation. If the resistance value returns to the initial calibration range, the system will automatically remove the derating operation limit, restore full load operation, and use the maintenance data to correct the nonlinear dynamic model 100, realizing the self-iteration and evolution of the algorithm.

[0055] Example 2, refer to Figures 2-3 As an embodiment of the present invention, a power equipment maintenance and scheduling method based on environmental salt spray concentration sensing is provided. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0056] First, two types of fuses, RS306-01-T5Z-32A and RS306-01-T5Z-400A, were selected as experimental samples. The initial electrothermal characteristics of the samples were calibrated in an environment with a room temperature of 24.2℃ and a humidity of 48%. During the experiment, the test pieces were continuously sprayed with NSS spray at a spray rate of 1.1 ml / H. The laboratory temperature was set to 35±1℃. The test results were checked after 48 hours.

[0057] Next, the real-time environmental load sensing and damage simulation stage begins. The calibrated fuses are installed within the monitoring area of ​​the simulated environment, and an online monitoring device based on particle size distribution spectra is activated. The device draws sampled air into the pipeline via a fan, and in the humidity adjustment section, semiconductor cooling is used to adjust the humidity to above 85% to ensure sufficient wetting of salt spray particles. A dual-scattering laser particle size distribution spectrometer is used to compare the changes in particle size distribution spectra before and after drying, eliminating dust interference with stable particle spectra, and dynamically correcting the mass of individual particles based on measured ambient temperature and humidity (room temperature 24.2℃, humidity 48%) to obtain accurate real-time salt spray concentration load. The system injects this load into a nonlinear dynamic model to simulate and calculate the real-time damage to the fuse contact surface. Referring to Table 1, the system monitored that after experiencing high-concentration salt spray impact, the resistance of sample 400A (19#) increased from 0.280mΩ to 0.286mΩ, a change rate of 2.14%. Although this has not yet reached the 10% failure threshold, the neural network expert database has identified its resistance evolution trend and marked it as critical risk.

[0058] Table 1 Experimental Results

[0059] As shown in Table 1 andFigures 2-3 As shown, the sample showed no damage or change in appearance after the test, no oxidation, corrosion, discoloration, or sand leakage. The resistance change rate before and after the test was less than or equal to 10%. This small and stable resistance change characteristic proves that the nonlinear dynamic model provides reliable underlying empirical data.

[0060] Ultimately, dynamic scheduling decisions and maintenance early warnings are implemented. The system continuously assesses temperature rise risk by coupling Joule's law, predicting additional heat generation due to a 2.14% increase in resistance. When the calculated total temperature rise prediction approaches the physical safety threshold of 130K, the status monitoring master station immediately issues a current-limiting command to the main IED of the power distribution unit. By actively implementing load current derating, the system artificially reduces the heat generation intensity to compensate for the thermal failure risk caused by the increased resistance. Simultaneously, the system continuously compares the real-time voltage drop with the baseline value. If the voltage drop growth rate is abnormal, the system automatically determines that the equipment's sealing layer has functionally failed. At this point, the system triggers an intelligent maintenance early warning, generates a diagnostic report, and uploads it to the cloud for backup, guiding maintenance personnel to perform targeted repairs. This achieves a complete closed-loop maintenance scheduling system from load perception to proactive risk avoidance.

[0061] Example 3, an embodiment of the present invention, provides a power equipment maintenance and scheduling system based on environmental salt spray concentration sensing, including a baseline modeling module, a load sensing module, a state evolution module, and an intelligent scheduling module.

[0062] Among them, the benchmark modeling module is used to calibrate the electrothermal characteristics F of the equipment under rated current offline based on the measured data of temperature rise and voltage drop of the fuse, and to construct a nonlinear dynamic model 100 of the contact resistance increment with salt spray corrosion.

[0063] The load sensing module is used to obtain the real-time atmospheric salt spray concentration load by comparing the changes in the particle size distribution spectrum P before and after drying, eliminating dust interference, and correcting the mass of a single salt spray particle by combining the ambient temperature and humidity H.

[0064] The state evolution module is used to inject the real-time salt spray concentration load into the nonlinear dynamic model 100 for integration processing, accumulate the physical damage and resistance increment of the conductive contact surface of the equipment, and use the neural network expert library to evaluate the equipment health level 300.

[0065] The intelligent scheduling module is used to assess the risk of temperature rise based on the predicted trend. When the total temperature rise approaches the safety limit, it automatically executes the load current derating operation command. At the same time, when the protection fails, it triggers the intelligent maintenance warning 400 and uploads the data to the cloud for backup.

[0066] This embodiment also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the power equipment maintenance and scheduling method based on environmental salt spray concentration sensing as proposed in the above embodiment.

[0067] This embodiment also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the power equipment maintenance and scheduling method based on environmental salt spray concentration sensing as proposed in the above embodiment.

[0068] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0069] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0070] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0071] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0072] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A power equipment maintenance and scheduling method based on environmental salt spray concentration sensing, characterized in that, include: Based on the measured data of temperature rise and voltage drop of fuses, the initial electrothermal characteristics (F) of the equipment were calibrated offline, and a nonlinear dynamic model (100) of the contact resistance increment with salt spray corrosion was constructed. Real-time environmental load (200) is collected. The atmospheric salt spray concentration is detected in real time by an online particle size distribution spectrum (P) detection device. The mass of a single particle (Q) is dynamically corrected by combining the ambient temperature and humidity (H) to obtain the real-time load. The acquired real-time load (200) is injected into the nonlinear dynamic model (100) to accumulate and calculate the contact surface damage, and the equipment health level is evaluated using a neural network expert library (300). Based on the predicted trend, assess the risk of temperature rise, implement load current derating operation, and trigger intelligent maintenance warning (400) when the protection fails.

2. The power equipment maintenance and scheduling method based on environmental salt spray concentration sensing as described in claim 1, characterized in that: The initial electrothermal characteristics (F) of the offline calibration device include, A high-precision resistance tester is used to obtain the static DC resistance of the power equipment when it is not corroded. The reference voltage drop and reference temperature rise of the equipment under rated current are extracted through temperature rise and voltage drop test to establish the initial electrothermal characteristics (F).

3. The power equipment maintenance and scheduling method based on environmental salt spray concentration sensing as described in claim 1 or 2, characterized in that: The nonlinear dynamic model (100) includes, By fitting the resistance change rate data at different time points in a neutral salt spray test over a fixed period, the process of the increase in contact resistance with the cumulative salt spray deposition was constructed.

4. The power equipment maintenance and scheduling method based on environmental salt spray concentration sensing as described in claim 3, characterized in that: The online particle size distribution spectrum (P) detection device includes, The air in the monitoring area is drawn into the pipeline by a fan, and passes through a humidity adjustment section, a pre-drying measurement section, a drying section, and a post-drying measurement section. In the humidity adjustment section, a semiconductor cooler is used to adjust the humidity of the sampled air without condensation. The particle size distribution spectrum (P) of particulate matter before drying was obtained using a first scattering laser particle size distribution spectrometer, and the sampled air was dried non-absorption using an infrared heater; The particle size distribution spectrum (P) data of dried particulate matter was obtained using a second scattering laser particle size distribution spectrometer. By comparing and analyzing the changes in particle size distribution (P) before and after drying, dust particles in the atmosphere were removed, and the number of salt spray particles and their particle size distribution (P) were extracted.

5. The power equipment maintenance and scheduling method based on environmental salt spray concentration sensing as described in claim 1, 2, or 4, characterized in that: The dynamic correction of individual particle mass (Q) based on ambient temperature and humidity (H) includes, The ambient relative temperature and humidity are collected in real time using the first temperature and humidity sensor. Based on the salt particle deliquescence theory, the relationship between the concentration of salt spray particles and the ambient temperature and humidity (H) is established. The real-time load (200) of the current atmospheric salt spray concentration is obtained by combining the corrected mass of a single particle (Q) with the number of salt spray particles and the particle size distribution spectrum (P).

6. The power equipment maintenance and scheduling method based on environmental salt spray concentration sensing as described in claim 5, characterized in that: The real-time load also includes, Layered data transmission and synchronous processing; The signals collected by the equipment layer (201) for salt spray concentration, temperature, humidity and atmospheric pressure monitoring are converted into digital signals that conform to the communication protocol by the main IED of the relay layer (202), and transmitted to the station control layer (203) for online monitoring via Ethernet. The real-time load data is synchronized with the timestamp of the equipment real-time load current data and forwarded to the status monitoring master station server for storage and analysis.

7. The power equipment maintenance and scheduling method based on environmental salt spray concentration sensing as described in claim 1, 2, 4, or 6, characterized in that: The cumulative calculation of contact surface damage includes, The condition monitoring master station performs integral processing on the time series based on the real-time load and outputs the cumulative salt spray exposure of the contact parts of the equipment. The cumulative salt spray exposure is injected into a nonlinear dynamic model (100) to simulate the reduction of effective conductive area and the trend of resistance evolution caused by salt corrosion products generated at the contact surface.

8. The power equipment maintenance and scheduling method based on environmental salt spray concentration sensing as described in claim 7, characterized in that: The method of using a neural network expert database to assess the equipment health level (300) includes, An artificial neural network evaluation algorithm is adopted, which uses a clustering algorithm to divide data features and matches the real-time resistance increment obtained by simulation with historical fault feature curves to automatically label the corrosion level, defect type and corrosion location size of the equipment.

9. The power equipment maintenance and scheduling method based on environmental salt spray concentration sensing as described in claims 1, 2, 4, 6, or 8, characterized in that: The intelligent maintenance early warning (400) includes, Establish a self-testing process based on resistance monitoring, and compare the monitored voltage drop growth rate with the stable threshold determined by the salt spray test in real time; If the rate of change of resistance points to the critical line of the rate of change defined by the initial electrothermal characteristics (F), it is automatically determined that the equipment sealing protection or the superhydrophobic and aging-resistant coating has failed. The station control layer (203) simultaneously uploads the corrosion level exceeding the standard signal to the platform backup and generates intelligent decision instructions containing maintenance suggestions to the operation and maintenance terminal.

10. A power equipment maintenance and scheduling system based on environmental salt spray concentration sensing, employing the power equipment maintenance and scheduling method based on environmental salt spray concentration sensing as described in any one of claims 1 to 9, characterized in that: It includes a baseline modeling module, a load sensing module, a state evolution module, and an intelligent scheduling module; The benchmark modeling module is used to calibrate the electrothermal characteristics (F) of the equipment under rated current offline based on the measured temperature rise and voltage drop data of the fuse, and to construct a nonlinear dynamic model (100) of the contact resistance increment with salt spray corrosion. The load sensing module is used to obtain the real-time atmospheric salt spray concentration load by comparing the changes in particle size distribution spectrum (P) before and after drying, eliminating dust interference, and correcting the mass of a single salt spray particle by combining the ambient temperature and humidity (H). The state evolution module is used to inject the real-time salt spray concentration load into the nonlinear dynamic model (100) for integration processing, accumulate the physical damage and resistance increment of the conductive contact surface of the equipment, and use the neural network expert library to evaluate the health level of the equipment (300). The intelligent scheduling module is used to assess the risk of temperature rise based on the predicted trend. When the total temperature rise approaches the safety bottom line, it automatically executes the load current derating operation command. At the same time, when the protection is determined to be in failure, it triggers the intelligent maintenance warning (400) and uploads the data to the cloud for backup.

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