A gas pressure indication alarm method for environmentally friendly gas-insulated ring network switchgear

Abstract

The present invention discloses a gas pressure indication alarm method for an environmentally friendly gas-insulated ring network switchgear, which specifically relates to the technical field of power equipment protection, and comprises the following steps: regularly detecting the contact resistance and gas composition changes of the environmentally friendly gas-insulated ring network switchgear to generate a detection data set; performing feature extraction and feature analysis based on the data set, inputting the analysis results into a pre-trained machine learning model to obtain a result of equipment operation quality division; judging whether to optimize the static preset gas pressure range according to the operation quality division result; finally, based on the static or optimized gas pressure range, performing a gas pressure indication alarm operation to ensure the safety and reliability of the equipment under different operating conditions; the present invention combines the moisture content quality index and the contact resistance quality index to design a gas pressure adjustment factor based on a nonlinear adjustment function, dynamically adjusts the upper and lower limits of the gas pressure through an optimization model, and better adapts to the needs of the equipment under different operating conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment protection, and more specifically to a gas pressure indication alarm method for environmentally friendly gas-insulated ring network switch equipment. Background Art

[0002] In modern power systems, ring network switchgear, as an important part of the power distribution system, is widely used in urban power grids and industrial power grids. In ring network switchgear, gas pressure directly affects the insulation performance and arc extinguishing ability of the equipment. When the gas pressure is too low, the insulation strength of the equipment may decrease, leading to accidents such as arc breakdown or short circuit; when the gas pressure is too high, it may damage the equipment structure and affect the stable operation of the equipment. Therefore, real-time monitoring of gas pressure and timely alarm have become key technologies to ensure the safe operation of equipment.

[0003] The main deficiencies of air pressure monitoring in the current existing technologies include:

[0004] The existing air pressure monitoring method usually only sets the pressure statically, and cannot dynamically adjust it according to the actual operation of the equipment. The existing air pressure alarm mechanism does not conduct a comprehensive analysis based on the equipment operation status, which easily leads to false alarms or missed alarms. In addition, the air pressure alarm mechanism lacks intelligence and dynamic adjustment capabilities, and is difficult to adapt to complex operating conditions. Therefore, the present invention proposes an air pressure indication alarm method for environmentally friendly gas insulated ring network switchgear, in order to solve the above problems. Summary of the invention

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A gas pressure indication alarm method for an environmentally friendly gas-insulated ring network switchgear comprises the following steps:

[0007] Regularly detect the use of contact resistance of the switchgear and the change of gas composition of the switchgear to obtain a set of detection data;

[0008] Feature extraction is performed based on the detection data set, followed by feature analysis. The result of the feature analysis is input into a pre-trained machine learning model to obtain the operation quality classification result of the environmentally friendly gas-insulated ring network switchgear.

[0009] Based on the operation quality classification results of the environmentally friendly gas-insulated ring network switchgear, determine whether to optimize the static preset gas pressure range;

[0010] The air pressure indication alarm operation is performed based on a static preset air pressure range or an optimized air pressure range.

[0011] In a preferred embodiment, feature extraction based on the detection data set refers to: extracting contact resistance usage feature data and gas composition change feature data respectively.

[0012] In a preferred embodiment, the characteristic analysis refers to: generating a contact resistance quality index based on the contact resistance characteristic data, and generating a moisture content quality index based on the gas composition change characteristic data.

[0013] In a preferred embodiment, the result of the feature analysis is input into a pre-trained machine learning model to obtain the operation quality classification result of the environmentally friendly gas insulated ring network switchgear, which means:

[0014] The moisture content quality index and the contact resistance quality index are input into a pre-trained machine learning model together, and the machine learning model outputs the result that the environmentally friendly gas insulated ring network switchgear is classified into a high-quality operating state or a low-quality operating state.

[0015] In a preferred embodiment, the machine learning model is a convolutional neural network model, and the output result of the convolutional neural network model is 1 or 0. When the output result of the convolutional neural network model is 1, the corresponding environmentally friendly gas insulated ring network switch equipment is classified as a high-quality operating state. When the output result of the convolutional neural network model is 0, the corresponding environmentally friendly gas insulated ring network switch equipment is classified as a low-quality operating state.

[0016] In a preferred embodiment, judging whether to optimize the static preset gas pressure range based on the operation quality classification result of the environmentally friendly gas insulated ring network switchgear refers to:

[0017] If the environmentally friendly gas-insulated ring network switch equipment is classified as a high-quality operating state, the static preset air pressure range will not be optimized. If the environmentally friendly gas-insulated ring network switch equipment is classified as a low-quality operating state, the static preset air pressure range will be optimized to obtain a dynamic standard air pressure range.

[0018] In a preferred embodiment, the logic for obtaining the moisture content quality index is:

[0019] The moisture content of the gas composition sample of the switchgear is measured by a preset standard detection method such as a standard drying method or near infrared spectroscopy, and is recorded as M in percentage;

[0020] By comparing with a known standard sample, the measurement error is calculated. Assume that the reference moisture content of the standard sample is ; ; is the measurement error;

[0021] Calculate the accuracy coefficient based on the absolute value of the error , the calculation formula is: ; is a preset non-zero constant, which indicates the sensitivity of the measurement error to the moisture content;

[0022] Calculate the environmental correction factor using the formula: ; Indicates the measured ambient temperature. Indicates the measurement of ambient humidity. represents the standard reference temperature, Indicates standard reference humidity, represents the environmental correction factor;

[0023] The moisture content quality index is calculated using the weighted average method as follows: ; , , are all preset non-zero scale factors, Indicates the moisture content quality index.

[0024] In a preferred embodiment, the logic for obtaining the contact resistance quality index is:

[0025] Temperature correction of contact resistance: ; Indicated at reference temperature The contact resistance under Indicates the current ambient temperature. represents a preset non-zero temperature correction factor, represents the reference temperature, It represents the contact resistance after temperature correction;

[0026] Pressure correction for contact resistance: ; is the pressure acting on the contact surface, represents the preset non-zero pressure correction factor, It represents the contact resistance after pressure correction;

[0027] Surface smoothness correction for contact resistance: ; represents the smoothness parameter of the contact surface, represents a preset non-zero surface smoothness correction factor, It represents the contact resistance after surface smoothness correction;

[0028] Oxide layer correction for contact resistance: ; represents the contact area, represents the oxide layer thickness, represents a preset non-zero oxide correction factor, It represents the contact resistance after surface smoothness correction;

[0029] Material property correction for contact resistance: ; Indicates the contact resistance material corresponding to the preset non-zero material property correction factor, The electrical conductivity of the contact resistance material, The contact resistance after

[0030] The actual contact resistance is defined as The value of the contact resistance after the test is recorded as RR, and the contact resistance quality index is obtained by dividing the value by the actual contact resistance RR.

[0031] In a preferred embodiment, the logic for obtaining the dynamic standard air pressure range is:

[0032] Assume the static preset air pressure range is , the pressure adjustment factor QY during optimization satisfies: ; , , These are all preset adjustment parameters. is the contact resistance quality index;

[0033] The dynamic standard pressure range is , satisfying the following formula: ; .

[0034] Technical effects and advantages of the present invention:

[0035] The present invention combines the moisture content quality index (MCQI) and the contact resistance quality index (CRQI) to design an air pressure adjustment factor (QY) based on a nonlinear adjustment function. The upper and lower limits of the air pressure are dynamically adjusted by optimizing the model to better adapt to the needs of the equipment under different operating conditions. The dynamic adjustment can accurately match the optimal air pressure range according to the multi-dimensional data monitored in real time, avoid the errors and inflexibility caused by the fixed air pressure range setting, and greatly enhance the operational adaptability of the equipment.

[0036] The present invention can comprehensively reflect the actual operating status of the equipment by incorporating multi-dimensional parameters such as gas moisture content and contact resistance into the air pressure monitoring and alarm logic. Through nonlinear analysis and correction of multi-dimensional parameters, the present invention effectively reduces the false alarm phenomenon caused by fluctuations in a single parameter, while more keenly capturing potential hidden dangers of the equipment and avoiding the occurrence of missed alarms. The alarm mechanism can provide more targeted and accurate alarm information based on the comprehensive evaluation results of the real-time status of the equipment, assisting operation and maintenance personnel to respond quickly.

[0037] The present invention introduces nonlinear functions (such as exponential functions and logarithmic functions) to model the air pressure adjustment factor and intelligently optimizes the air pressure range, so that the equipment can dynamically adapt to changes in operating conditions. Traditional methods require frequent manual adjustment of the air pressure range or inspection of equipment status, while the present invention realizes automated and intelligent monitoring and adjustment, greatly reducing the need for manual intervention.

[0038] The present invention effectively avoids the problems of insulation degradation caused by too low air pressure and equipment damage caused by too high air pressure by dynamically adjusting the air pressure range. By real-time monitoring of gas parameters and equipment status, potential hidden dangers can be discovered and alarmed in advance, reducing the occurrence rate of equipment failures. The high reliability of equipment operation provides an important guarantee for the safe and continuous operation of the power grid, especially in critical load scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0040] Figure 1 The present invention is a schematic diagram of a gas pressure indication alarm method for an environmentally friendly gas-insulated ring network switchgear. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Reference Figure 1 The following embodiments are obtained: Example

[0043] The air pressure indication alarm method of the environmentally friendly gas-insulated ring network switchgear refers to monitoring the air pressure changes inside the environmentally friendly gas-insulated ring network switchgear, detecting the air pressure status of the equipment in real time, and sending an alarm signal when the air pressure is abnormal, so as to help users discover possible hidden faults in time and ensure the safe operation of the equipment.

[0044] Environmentally friendly gas-insulated ring main switchgear is a key device used in power distribution systems. It uses gas insulation technology to improve the stability and safety of the equipment. The equipment is usually filled with environmentally friendly gas to maintain good insulation performance and prevent arcing. Therefore, the normality of gas pressure directly affects the operating safety and insulation effect of the equipment.

[0045] The air pressure indication alarm method monitors the air pressure value inside the equipment in real time. Once the air pressure is abnormally low or high, an alarm signal will be issued. Abnormal air pressure may mean that there is a gas leak or other fault inside the equipment. If this abnormality is not discovered and handled in time, it may cause the insulation performance of the equipment to deteriorate or even cause an electrical accident. This method usually installs an air pressure sensor to transmit the air pressure data to the central monitoring system. The air pressure data is analyzed in real time and compared with the preset air pressure range of the equipment. When the air pressure exceeds the normal range, the alarm system will be activated and a warning will be issued to the maintenance personnel. In this way, the staff can quickly check and repair the equipment to avoid potential safety hazards.

[0046] Based on this, the present invention proposes a gas pressure indication alarm method for an environmentally friendly gas-insulated ring network switchgear, comprising the following steps:

[0047] Regularly detect the use of the contact resistance of the switchgear and the changes in the gas composition of the switchgear to obtain a collection of detection data; by regularly monitoring the contact resistance and gas composition changes of the switchgear, the potential failure risk of the equipment can be discovered in time. Abnormal contact resistance or changes in gas composition usually indicate that there may be problems inside the equipment (such as excessive oxidation, contact surface wear, gas leakage, etc.). If these problems are not discovered in time, they may cause equipment failure and even affect the safety of the entire power grid.

[0048] Based on the detection data set, feature extraction is performed, followed by feature analysis. The results of the feature analysis are input into the pre-trained machine learning model to obtain the operating quality classification results of the environmentally friendly gas-insulated ring network switchgear. The machine learning model is used to analyze the contact resistance and gas composition data to more accurately determine whether the equipment is in a good operating state. Traditional detection methods may rely more on manual experience or a single indicator, while machine learning models can more comprehensively evaluate the health status of equipment by integrating multiple features.

[0049] Based on the operating quality classification results of the environmentally friendly gas-insulated ring network switchgear, determine whether to optimize the static preset air pressure range; according to the operating quality classification results of the equipment (i.e., high-quality operation or low-quality operation), the air pressure range can be intelligently adjusted. If the equipment is in good operating condition, the original air pressure range can be maintained; if the equipment is abnormal (such as increased contact resistance or abnormal gas composition), the working conditions of the equipment can be improved by optimizing the air pressure range, thereby extending the service life of the equipment and improving the operating stability. By adjusting the air pressure range (i.e., the dynamic standard air pressure range), the operating status of the equipment can be personalized. The equipment may require different air pressure environments under different operating conditions. By dynamically adjusting the air pressure range, the equipment can be ensured to operate under the best working conditions.

[0050] The pressure indication alarm operation is performed based on a static preset pressure range or an optimized pressure range. The pressure indication alarm can issue a warning when a potential problem occurs in the equipment, so that corresponding measures can be taken in advance. This helps to avoid sudden shutdown of equipment due to faults, reduce maintenance costs, and ensure the normal operation of the power grid. The operation quality classification based on the machine learning model can avoid the problems of excessive maintenance or premature replacement of parts in the traditional way. Only when the equipment is in a low-quality operation state will the pressure range be optimized, thus avoiding unnecessary maintenance and maintenance resource waste. The ring network switchgear uses environmentally friendly gas as the insulating medium, which is more environmentally friendly than traditional gas. The application of this technology helps to reduce the emission of harmful gases, meets the requirements of environmental protection policies, and also adopts a sustainable development strategy in the design and operation of the equipment. Combining the air pressure of the equipment with the use of environmentally friendly gas can ensure that the equipment operates efficiently in an environmentally friendly manner, avoiding negative impacts on the environment and equipment due to changes in gas composition or improper air pressure.

[0051] Feature extraction based on the detection data set refers to: extracting contact resistance usage feature data and gas composition change feature data respectively. Feature analysis refers to: generating a contact resistance quality index based on contact resistance usage feature data and generating a moisture content quality index based on gas composition change feature data.

[0052] Contact resistance is an important parameter commonly found in electronic devices, especially in the performance of electrical contact parts. When electrical equipment is in operation, changes in the resistance of the contact part may directly affect the efficiency and safety of the equipment. By extracting the characteristic data of contact resistance, the state of contact resistance can be monitored in real time to detect poor contact or other abnormal conditions. This is of great significance for maintaining equipment, extending service life, and reducing equipment failures. For example, by monitoring changes in contact resistance, equipment wear or poor contact problems can be identified in advance, avoiding serious equipment failures caused by abnormal contact resistance.

[0053] Gas composition changes (such as moisture content, oxygen concentration, etc.) are important quality control indicators in many industrial applications, especially in the fields of chemistry, environmental monitoring and energy. By extracting characteristic data of gas composition changes, it is possible to accurately reflect changes in gas quality, thereby helping to promptly detect abnormal conditions in the production process, such as excessive moisture. For example, in a gas monitoring system, changes in moisture content may indicate raw material problems or equipment failures in the production process. By analyzing these characteristic data in real time, early warnings can be issued to avoid serious consequences.

[0054] The results of feature analysis are input into the pre-trained machine learning model to obtain the operation quality classification results of environmentally friendly gas-insulated ring network switchgear, which refer to:

[0055] The moisture content quality index and the contact resistance quality index are input into a pre-trained machine learning model together, and the machine learning model outputs the result that the environmentally friendly gas insulated ring network switchgear is classified into a high-quality operating state or a low-quality operating state.

[0056] The machine learning model is a convolutional neural network model, and the output result of the convolutional neural network model is 1 or 0. When the output result of the convolutional neural network model is 1, the corresponding environmentally friendly gas insulated ring network switchgear is classified as a high-quality operating state. When the output result of the convolutional neural network model is 0, the corresponding environmentally friendly gas insulated ring network switchgear is classified as a low-quality operating state.

[0057] First, the performance characteristics of environmentally friendly gas-insulated ring network switchgear are analyzed to extract characteristics that are closely related to the equipment's operating quality (such as moisture content and contact resistance, etc.). These characteristics can directly reflect the health status of the equipment, and moisture content and contact resistance are important indicators for judging the failure or degradation of gas-insulated ring network switchgear.

[0058] Input to the machine learning model: These features are input into a pre-trained convolutional neural network model. During the training process, the convolutional neural network has learned how to identify the health status of the device from these input features and convert it into a classification result.

[0059] What does the Convolutional Neural Network (CNN) model do? Convolutional neural networks are a powerful deep learning algorithm that excels at processing data with spatial structures. Although convolutional neural networks are primarily used for image processing, they can also be used to process one-dimensional feature data (such as quality index). Through the filtering operation of the convolutional layer, CNN can automatically extract useful information from the input features and classify them through the subsequent fully connected layers.

[0060] In this application, the training data of the CNN model comes from historical operating data and equipment failure conditions. Through learning from a large amount of data, CNN can identify which feature combinations correspond to high-quality or low-quality states of the equipment.

[0061] Significance of the classification results: High-quality operating status (output 1): When the convolutional neural network model outputs 1, it indicates that the device is in a high-quality operating state, which means that the device is running stably and normally without obvious risk of failure or degradation.

[0062] Low-quality operation state (output 0): When the convolutional neural network model outputs 0, it means that the device is in a low-quality operation state, there may be a fault or potential equipment aging problem, and the equipment may need to be repaired or related parts replaced.

[0063] Practical application value: Equipment maintenance and management: This automated quality classification method can help operation and maintenance personnel promptly identify whether the equipment is in a high-quality or low-quality state, so as to formulate more targeted repair and maintenance plans and provide early warning of possible equipment failures.

[0064] Improve efficiency: Through the automatic prediction of machine learning models, the frequency and cost of manual inspections can be reduced, while improving the efficiency of monitoring and maintenance. Especially in some scenarios where equipment is widely distributed and the inspection cycle is long, automated analysis will greatly improve the management level.

[0065] Extending equipment life: By detecting low-quality equipment operation at an early stage, timely measures can be taken to prevent the fault from further deteriorating, thereby extending the service life of the equipment and reducing the occurrence of sudden failures.

[0066] Based on the operating quality classification results of environmentally friendly gas-insulated ring network switchgear, judging whether to optimize the static preset gas pressure range means:

[0067] If the environmentally friendly gas-insulated ring network switch equipment is classified as a high-quality operating state, the static preset air pressure range will not be optimized. If the environmentally friendly gas-insulated ring network switch equipment is classified as a low-quality operating state, the static preset air pressure range will be optimized to obtain a dynamic standard air pressure range.

[0068] Necessity for optimization: When a device is judged to be of low quality, it usually means that the device may be malfunctioning or its performance may be degraded. In this case, air pressure is a key monitoring indicator, especially in devices where air pressure changes have a greater impact on device function. Therefore, triggering alarms based on air pressure changes can detect device anomalies in a timely manner and avoid more extensive failures.

[0069] The operating status of the equipment may be affected by many factors, such as temperature, environmental conditions, etc. The preset air pressure range may be set based on the ideal working environment and historical data of the equipment, but the real-time operation of the equipment may change due to external or internal factors. In this case, the dynamically optimized air pressure range can be adjusted according to the fluctuation of real-time data, the working condition of the equipment and the changes in environmental factors, making the alarm mechanism more adaptive and intelligent, and avoiding ignoring possible risks due to the setting of fixed ranges.

[0070] The dynamically optimized pressure range can be adjusted according to the actual operating status of the equipment, so the alarm will be more accurate. Dynamic optimization not only provides a more sensitive alarm mechanism than a fixed pressure range, but also reduces the trouble caused by excessive or missed alarms, and improves the efficiency and safety of equipment maintenance.

[0071] The dynamically optimized air pressure range alarm can be used as part of fault prediction and prevention. Low-quality equipment may be on the verge of equipment aging, performance degradation or potential failure. Early warning through air pressure alarms allows maintenance personnel to take measures in advance to perform preventive repairs or adjustments, thereby reducing equipment downtime and maintenance costs.

[0072] The logic for obtaining the moisture content quality index is:

[0073] The moisture content of the gas composition sample of the switchgear is measured by preset standard detection methods such as standard drying method or near-infrared spectroscopy, denoted as M, in percentage. The moisture content is the core indicator for evaluating the quality of the gas inside the equipment. Excessive moisture will affect the gas insulation performance and even cause equipment failure.

[0074] By comparing with a known standard sample, the measurement error is calculated. Assume that the reference moisture content of the standard sample is ; ; is the measurement error in %. By calculating the difference between the actual moisture content and the reference value, the measurement error is quantified to help analyze the accuracy and deviation of the measurement.

[0075] Calculate the accuracy coefficient based on the absolute value of the error , the calculation formula is: ; is a preset non-zero constant, indicating the sensitivity of the measurement error to the moisture content; the accuracy coefficient indicates the impact of the measurement error on the moisture content quality, ranging from [0,1]. The closer the value is to 1, the closer the measurement result is to the standard value; the smaller the value is, the larger the measurement error is and the lower the credibility of the measurement result is.

[0076] Environmental factors (such as temperature, humidity, and air pressure) will affect the measurement of moisture content. Therefore, it is necessary to calculate the environmental correction factor. The formula for calculating the environmental correction factor is: ; Indicates the measured ambient temperature. Indicates the measurement of ambient humidity. represents the standard reference temperature, Indicates standard reference humidity, Represents environmental correction factor; the environmental correction factor is used to correct the impact of environmental conditions (such as changes in temperature and humidity) on the measured moisture content. Changes in environmental conditions may cause moisture measurement deviations, so the data needs to be adjusted using the correction factor.

[0077] The moisture content quality index is calculated using the weighted average method as follows: ; , , are all preset non-zero scale factors, Represents the moisture content quality index. The moisture content quality index is the final indicator for comprehensively measuring the quality of moisture content in gas. It combines the actual value of moisture content, measurement accuracy and environmental correction. By adjusting the weight of the proportional coefficient, the influence of different factors on the index can be highlighted. For example, when the measurement equipment has high accuracy, w2 (the weight of the accuracy coefficient) can be reduced, and the weights of w1 and w3 can be increased to highlight the role of moisture content value and environmental correction.

[0078] The logic for obtaining the contact resistance quality index is:

[0079] Temperature changes will cause resistance changes, and contact resistance is usually corrected for temperature: ; Indicated at reference temperature The contact resistance under Indicates the current ambient temperature. represents a preset non-zero temperature correction factor, represents the reference temperature, Represents the contact resistance after temperature correction, which introduces the influence of temperature changes into the calculation to make the result more in line with the actual operating environment.

[0080] Since pressure will affect the contact resistance, pressure correction is performed on the contact resistance: ; is the pressure acting on the contact surface, represents the preset non-zero pressure correction factor, Represents the contact resistance after pressure correction; the pressure on the contact surface affects the contact area and the current flow path. The greater the pressure, the smaller the contact resistance. By introducing the pressure correction formula, the contact resistance change caused by pressure change can be corrected.

[0081] Since the smoothness of the contact surface affects the contact resistance, the contact resistance is corrected for surface smoothness: ; represents the smoothness parameter of the contact surface, represents a preset non-zero surface smoothness correction factor, Indicates the contact resistance after surface smoothness correction; the smoothness of the contact surface directly affects the conductive performance of the contact point. The rougher the surface, the greater the resistance to current flow. Smoothness correction can effectively adjust the contact resistance deviation caused by improper contact surface treatment.

[0082] The thickness of the oxide layer affects the contact resistance. A thick oxide layer will increase the resistance. The oxide layer correction for the contact resistance is performed: ; represents the contact area, represents the oxide layer thickness, represents a preset non-zero oxide correction factor, It represents the contact resistance after surface smoothness correction. The thickness of the oxide layer has a significant effect on the contact resistance. The thicker the oxide layer, the more obstructed the current path is and the greater the contact resistance is. The formula introduces the relationship between the oxide layer thickness and the contact area, which can quantify the effect of the oxide layer on the contact resistance.

[0083] Material property correction for contact resistance based on the material's conductivity: ; Indicates the contact resistance material corresponding to the preset non-zero material property correction factor, The electrical conductivity of the contact resistance material, The contact resistance after the contact is formed; the conductivity of the contact material directly determines the size of the contact resistance. The material property correction formula can be used to correct the resistance change caused by the difference in conductivity of different materials.

[0084] The actual contact resistance is defined as The value of the contact resistance after calibration is recorded as RR. The contact resistance quality index is obtained by dividing the value by the actual contact resistance RR. The contact resistance quality index is defined as the reciprocal of the actual contact resistance. The smaller the actual contact resistance, the better the contact quality and the higher the index. Each correction step (temperature, pressure, smoothness, oxide layer, material properties) takes into account the influence of different physical factors on the contact resistance, thereby dynamically adjusting the calculated results of the contact resistance to make it more in line with the actual environment and working conditions.

[0085] The logic for obtaining the dynamic standard air pressure range is:

[0086] Assume the static preset air pressure range is The static pressure range is the preset working range of the equipment under ideal conditions and does not change with the real-time environment and equipment conditions. The dynamic pressure range is modified on this basis to adapt to the actual working conditions.

[0087] The air pressure adjustment factor QY during optimization satisfies: ; , , They are all preset adjustment parameters, which are used to control the weights or sensitivities of MCQI and CRQI to the gas pressure adjustment factor. MCQI: Moisture Content Quality Index, which reflects the quality level of gas moisture content; CRQI: Contact Resistance Quality Index, which reflects the state of contact quality of electrical equipment. This indicates the nonlinear effect of the moisture content index on the air pressure range, with higher MCQI leading to smaller adjustments.

[0088] The dynamic standard pressure range is , satisfying the following formula: ; .

[0089] The air pressure adjustment factor QY is a comprehensive indicator calculated based on MCQI and CRQI, which is used to dynamically correct the standard air pressure range. By combining MCQI and CRQI, it reflects the impact of the overall state of the equipment on the air pressure demand, and through exponential and logarithmic function processing, the adjustment is more in line with the actual equipment characteristics (i.e., the exponential downward trend of CRQI and the logarithmic increasing trend of MCQI). During dynamic adjustment, increasing the minimum value can ensure the operation stability of the equipment under low air pressure (avoiding the degradation of insulation performance caused by insufficient air pressure). At the same time, reducing the maximum value can prevent the equipment from being subjected to excessive air pressure, avoiding damage to equipment components or unstable operation due to excessive air pressure. This upper and lower limit adjustment logic reduces the range of air pressure fluctuations, making the equipment operation safer and more reliable.

[0090] The dynamically adjusted air pressure range is closer to the actual needs of the equipment, avoiding the negative impact of excessive or low air pressure on equipment performance, increasing the lower limit to ensure the stability of equipment operation at low air pressure, reducing accidents caused by decreased insulation performance, and lowering the upper limit to avoid equipment damage caused by excessive air pressure, thereby improving equipment safety. Through precise air pressure adjustment, the gas loss and energy consumption of the equipment are reduced, and the overall operating efficiency is improved. Air pressure adjustment avoids the impact of extreme air pressure conditions on the equipment, reduces the wear and aging of components, and thus extends the service life of the equipment. The dynamic air pressure range is based on real-time data (such as MCQI and CRQI), realizes intelligent management, and reduces the need for manual intervention.

[0091] After the dynamic range is reduced, the equipment always operates under the optimal gas pressure conditions, significantly reducing the possibility of equipment failure, especially in extreme cases where the gas pressure is too low or too high, effectively avoiding the risks of insulation breakdown or component overload. The dynamic adjustment range reduces the limitations brought by the fixed range setting, significantly reduces the false alarm phenomenon caused by environmental changes, and reduces the missed alarm caused by the failure to detect potential problems in time, reduces the maintenance frequency and repair costs, and improves the economic benefits. For example, the specific performance is as follows: the experimental data statistics are taken as an experimental object, namely the environmentally friendly gas insulated ring network switchgear, as shown in Table 1:

[0092] Table 1. Experimental data statistics

[0093]

[0094] The dynamically adjusted air pressure range is more in line with the actual operating status of the equipment. The false alarm rate is reduced from 12.5% ​​to 2.3%, and the missed alarm rate is reduced from 5.6% to 1.2%, indicating that the alarm is more accurate and the reliability is improved. The failure rate is reduced from 8.9% to 3.4%, reflecting the significant improvement of the stability and reliability of the equipment by the dynamic air pressure range. The average maintenance interval is extended from 120 days to 180 days, and the maintenance frequency is reduced. At the same time, in addition to the data in Table 1, the following information is also recorded. The environmental gas consumption under the traditional static air pressure range is measured as 100 units. The environmental gas consumption after the dynamic standard air pressure range is reduced by 15%. In the same time, 85 units of environmental gas are consumed, and the equipment replacement cycle is extended by no less than 3 years, which greatly improves the economic benefits. It can be seen from the experimental data that narrowing the preset air pressure range to the dynamic standard air pressure range effectively improves the safety, stability and economy of the equipment operation, while reducing gas waste and maintenance costs, reducing the impact on the environment, and providing important support for the promotion and application of environmentally friendly insulated ring network switchgear.

[0095] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0096] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0097] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0098] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0099] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A gas pressure indication alarm method for environmentally friendly gas-insulated ring network switchgear, characterized in that: The following steps are involved: Regularly detect the use of contact resistance of the switchgear and the change of gas composition of the switchgear to obtain a set of detection data; Feature extraction is performed based on the detection data set, followed by feature analysis. The result of the feature analysis is input into a pre-trained machine learning model to obtain the operation quality classification result of the environmentally friendly gas-insulated ring network switchgear. Based on the operation quality classification results of the environmentally friendly gas-insulated ring network switchgear, determine whether to optimize the static preset gas pressure range; Performing air pressure indication alarm operations based on a static preset air pressure range or an optimized air pressure range; Feature extraction based on the detection data set refers to: extracting contact resistance usage feature data and gas composition change feature data respectively; Characteristic analysis refers to: generating a contact resistance quality index based on the characteristic data of contact resistance, and generating a moisture content quality index based on the characteristic data of gas composition changes; The logic for obtaining the moisture content quality index is: The moisture content of the gas composition sample of the switchgear is measured by a preset standard detection method, which is recorded as M in percentage. By comparing with a known standard sample, the measurement error is calculated. Assume that the reference moisture content of the standard sample is ; is the measurement error; Calculate the accuracy coefficient based on the absolute value of the error , the calculation formula is: ; is a preset non-zero constant, which indicates the sensitivity of the measurement error to the moisture content; Calculate the environmental correction factor using the formula: ; Indicates the measured ambient temperature. Indicates the measurement of ambient humidity. represents the standard reference temperature, Indicates standard reference humidity, represents the environmental correction factor; The moisture content quality index is calculated using the weighted average method as follows: ; , , are all preset non-zero scale factors, Indicates the moisture content quality index; The logic for obtaining the contact resistance quality index is: Temperature correction of contact resistance: ; Indicated at reference temperature The contact resistance under Indicates the current ambient temperature. represents a preset non-zero temperature correction factor, represents the reference temperature, It represents the contact resistance after temperature correction; Pressure correction for contact resistance: ; is the pressure acting on the contact surface, represents the preset non-zero pressure correction factor, It represents the contact resistance after pressure correction; Surface smoothness correction for contact resistance: ; represents the smoothness parameter of the contact surface, represents a preset non-zero surface smoothness correction factor, It represents the contact resistance after surface smoothness correction; Oxide layer correction for contact resistance: ; represents the contact area, represents the oxide layer thickness, represents a preset non-zero oxide correction factor, It represents the contact resistance after surface smoothness correction; Material property correction for contact resistance: ; Indicates the contact resistance material corresponding to the preset non-zero material property correction factor, The electrical conductivity of the contact resistance material, The contact resistance after The actual contact resistance is defined as The value of the contact resistance after the test is recorded as RR, and the contact resistance quality index is obtained by dividing the value by the actual contact resistance RR.

2. The gas pressure indication alarm method for environmentally friendly gas insulated ring network switchgear according to claim 1 is characterized in that: The results of feature analysis are input into the pre-trained machine learning model to obtain the operation quality classification results of environmentally friendly gas-insulated ring network switchgear, which refer to: The moisture content quality index and the contact resistance quality index are input into a pre-trained machine learning model together, and the machine learning model outputs the result that the environmentally friendly gas insulated ring network switchgear is classified into a high-quality operating state or a low-quality operating state.

3. The gas pressure indication alarm method for environmentally friendly gas insulated ring network switchgear according to claim 2 is characterized in that: The machine learning model is a convolutional neural network model, and the output result of the convolutional neural network model is 1 or 0. When the output result of the convolutional neural network model is 1, the corresponding environmentally friendly gas insulated ring network switchgear is classified as a high-quality operating state. When the output result of the convolutional neural network model is 0, the corresponding environmentally friendly gas insulated ring network switchgear is classified as a low-quality operating state.

4. The gas pressure indication alarm method for environmentally friendly gas insulated ring network switchgear according to claim 3 is characterized in that: Based on the operating quality classification results of environmentally friendly gas-insulated ring network switchgear, judging whether to optimize the static preset gas pressure range means: If the environmentally friendly gas-insulated ring network switch equipment is classified as a high-quality operating state, the static preset air pressure range will not be optimized. If the environmentally friendly gas-insulated ring network switch equipment is classified as a low-quality operating state, the static preset air pressure range will be optimized to obtain a dynamic standard air pressure range.

5. The gas pressure indication alarm method for environmentally friendly gas insulated ring network switchgear according to claim 4, characterized in that: The logic for obtaining the dynamic standard air pressure range is: Assume the static preset air pressure range is , the pressure adjustment factor QY during optimization satisfies: ; , , These are all preset adjustment parameters. is the contact resistance quality index; The dynamic standard pressure range is , satisfying the following formula: ; .

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