Sf6 gas pressure early warning method, device, equipment, storage medium and program product

Abstract

The application relates to the technical field of leakage detection, and discloses an SF6 gas pressure early warning method, device, equipment, storage medium and program product.The SF6 gas pressure early warning method comprises the following steps: for a target electrical equipment, the measured pressure data of SF6 gas is compensated by using the ambient temperature data of the environment to obtain compensated pressure data; the corrected pressure change rate is calculated based on the compensated pressure data at multiple moments; if the compensated pressure data at the current moment does not meet the pressure standard and / or the corrected pressure change rate at the current moment does not meet the change rate standard, feature matching is performed based on the data set at the current moment and the data set at the historical moment, the target data set meeting the matching range is determined from the data set at the historical moment, and the SF6 gas leakage condition at the historical moment corresponding to the target data set is taken as the SF6 gas leakage condition at the current moment; early warning is performed based on the SF6 gas leakage condition at the current moment.The application can improve the SF6 gas early warning accuracy.

Description

Technical Field

[0001] This invention relates to the field of leak detection technology, specifically to SF6 gas pressure early warning methods, devices, equipment, storage media, and program products. Background Technology

[0002] With the widespread application of power systems, substations, as the core hubs for power transmission and distribution, directly affect the overall stability of the power system through their operational status. Among these, SF6 (sulfur hexafluoride) gas, due to its excellent insulation and arc-extinguishing capabilities, is widely used in substation equipment such as circuit breakers and disconnectors. However, changes in SF6 gas pressure directly affect the operating status of the equipment; in particular, SF6 leakage can lead to a decline in the insulation performance of the equipment, and in severe cases, may even cause electrical accidents.

[0003] Currently, in the field of SF6 gas pressure detection, methods such as online sensor monitoring systems, density relays or manual pressure gauges, and gas analyzers are mainly used to monitor changes in SF6 gas pressure. However, these methods all have certain limitations and cannot meet the requirements of modern electrical equipment for accurate, real-time, and reliable detection of SF6 gas pressure. Summary of the Invention

[0004] In view of this, the present invention provides an SF6 gas pressure early warning method, apparatus, device, storage medium and program product to improve the accuracy of SF6 gas early warning.

[0005] In a first aspect, the present invention provides an SF6 gas pressure early warning method, which includes: for a target electrical device, performing environmental compensation on the measured pressure data of SF6 gas using ambient temperature data of the surrounding environment to obtain compensated pressure data; calculating the corrected pressure change rate based on the compensated pressure data at multiple times; constructing a dataset based on the operating status data of the target electrical device, ambient temperature data, compensated pressure data, and corrected pressure change rate; if the compensated pressure data at the current time does not meet the pressure standard and / or the corrected pressure change rate at the current time does not meet the change rate standard, performing feature matching between the dataset at the current time and the datasets at historical times, determining a target dataset that meets the matching range from the datasets at historical times, and using the SF6 gas leakage status at the historical time corresponding to the target dataset as the SF6 gas leakage status at the current time; and issuing an early warning based on the SF6 gas leakage status at the current time.

[0006] In this implementation, by compensating SF6 gas pressure data with temperature data, the accuracy of pressure detection can be improved, avoiding misjudgments of leaks due to measurement errors. Furthermore, by comprehensively considering temperature, pressure change rate, and the degree of matching between the temperature-compensated pressure value and historical data, and combining this with historical equipment operating data to determine whether it is a genuine pressure anomaly, the accuracy, reliability, and timeliness of SF6 gas pressure detection can be improved, ensuring the safe and stable operation of electrical equipment.

[0007] In one optional implementation, the measured pressure data of SF6 gas is compensated for using the ambient temperature data of the surrounding environment to obtain compensated pressure data. This includes: constructing an SF6 gas temperature-pressure correction function; and inputting the ambient temperature data and the measured pressure data into the SF6 gas temperature-pressure correction function to obtain compensated pressure data.

[0008] In this implementation, by establishing an accurate temperature-pressure correction function to compensate for temperature changes, the influence of ambient temperature on SF6 gas pressure measurement is effectively eliminated, thus significantly improving measurement accuracy.

[0009] In one optional implementation, an SF6 gas temperature-pressure correction function is constructed, including: calculating the comprehensive correction value of ambient temperature data and measured pressure data to the measured pressure data under multiple time point factors; correcting the measured pressure data using the comprehensive correction value and performing integration calculation within a preset time window to obtain the average corrected pressure data; calculating a temperature compensation factor based on the influence of the periodic changes in ambient temperature data on the measured pressure data and the degree of difference between the measured pressure data and the pressure standard value; and multiplying the average corrected pressure data by the temperature compensation factor to obtain the SF6 gas temperature-pressure correction function.

[0010] In one optional implementation, calculating the comprehensive correction value of the measured pressure data based on ambient temperature data and measured pressure data under multiple time point factors includes: constructing an exponential function for multiple time point factors, and adjusting the factor weight coefficients of the corresponding time point factors using the exponential function to obtain a first data item; normalizing the measured pressure data based on an error function to obtain a second data item; mapping the ambient temperature data based on a Sigmoid function to obtain a third data item; multiplying the first, second, and third data items and summing them according to multiple time point factors to obtain a fourth data item; summing the first data items corresponding to multiple time point factors to obtain a fifth data item; calculating the ratio of the fourth and fifth data items to obtain a comprehensive correction value; correcting the measured pressure data using the comprehensive correction value, and performing integration calculation within a preset time window to obtain average corrected pressure data, including: The measured pressure data is added to the comprehensive correction value and integrated within a preset time window to obtain the average corrected pressure data. Based on the influence of the periodic changes in ambient temperature data on the measured pressure data and the degree of difference between the measured pressure data and the pressure standard value, the temperature compensation factor is calculated, including: normalizing the ambient temperature data within a preset temperature data range to obtain the sixth data item; calculating the influence of the periodic changes in ambient temperature data on the measured pressure data to obtain the seventh data item; calculating the degree of difference between the measured pressure data and the pressure standard value to obtain the eighth data item; multiplying the sixth, seventh, and eighth data items and integrating within the preset temperature data range to obtain the ninth data item; multiplying the seventh and eighth data items and integrating within the preset temperature data range to obtain the tenth data item; and calculating the ratio of the ninth and tenth data items to obtain the temperature compensation factor.

[0011] This implementation fully considers the intrinsic relationship between SF6 gas pressure and temperature, and compensates for temperature changes by establishing a precise mathematical model. It delves into the physical properties of SF6 gas, analyzes the pressure variation patterns under different temperature conditions, and constructs a temperature-pressure correction function based on extensive experimental data and theoretical analysis. This function dynamically corrects the SF6 gas pressure measurement value according to the real-time monitored ambient temperature, effectively eliminating measurement errors caused by changes in ambient temperature and thus preventing false alarms.

[0012] In one optional implementation, the SF6 gas pressure early warning method includes: acquiring a first pressure threshold and a second pressure threshold; if the compensated pressure data at the current moment is less than the first pressure threshold or greater than the second pressure threshold, then the compensated pressure data at the current moment does not meet the pressure standard; acquiring a first rate of change threshold; if the corrected pressure rate of change at the current moment is greater than the first rate of change threshold, then the corrected pressure rate of change at the current moment does not meet the rate of change standard.

[0013] In one optional implementation, feature matching is performed between the current dataset and historical datasets. A target dataset satisfying the matching range is determined from the historical dataset. The historical SF6 gas leakage status corresponding to the target dataset is used as the current SF6 gas leakage status. This includes: calculating the temperature matching range, pressure matching range, and rate of change matching range based on the current ambient temperature data, compensated pressure data, and corrected pressure change rate, as well as the corresponding temperature tolerance value, pressure tolerance value, and rate of change tolerance value; performing feature matching in the historical dataset according to the temperature matching range, pressure matching range, and rate of change matching range to obtain at least one target dataset; obtaining the historical SF6 gas leakage status corresponding to the target dataset, and selecting the historical SF6 gas leakage status with the largest proportion as the current SF6 gas leakage status; and issuing an early warning based on the current SF6 gas leakage status, including issuing an early warning when the current SF6 gas leakage status indicates a leakage fault.

[0014] In this implementation, when the detected pressure change rate exceeds a corresponding threshold and the temperature-compensated pressure value deviates from the normal range, historical operating data of the equipment is used to determine whether it is a genuine pressure anomaly. If an anomaly is determined, an alarm signal is issued promptly. This method can more accurately determine the true state of SF6 gas pressure and effectively avoid false alarms or missed alarms caused by relying solely on fixed thresholds.

[0015] Secondly, the present invention provides an SF6 gas pressure early warning device, which includes: a first calculation module for performing environmental compensation on the measured pressure data of SF6 gas using ambient temperature data of the surrounding environment for a target electrical device, thereby obtaining compensated pressure data; a second calculation module for calculating the corrected pressure change rate based on the compensated pressure data at multiple times; a construction module for constructing a dataset based on the operating status data of the target electrical device, ambient temperature data, compensated pressure data, and corrected pressure change rate; an analysis module for performing feature matching between the dataset at the current time and the dataset at historical times when the compensated pressure data at the current time does not meet the pressure standard and / or the corrected pressure change rate at the current time does not meet the change rate standard, determining a target dataset that meets the matching range from the dataset at historical times, and using the SF6 gas leakage status at the historical time corresponding to the target dataset as the SF6 gas leakage status at the current time; and an early warning module for issuing an early warning based on the SF6 gas leakage status at the current time.

[0016] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the SF6 gas pressure early warning method of the first aspect or any corresponding embodiment described above.

[0017] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the SF6 gas pressure early warning method of the first aspect or any corresponding embodiment described above.

[0018] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the SF6 gas pressure early warning method of the first aspect or any corresponding embodiment described above. Attached Figure Description

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

[0020] Figure 1 This is a flowchart of an SF6 gas pressure early warning method according to an embodiment of the present invention; Figure 2 This is a flowchart of another SF6 gas pressure early warning method according to an embodiment of the present invention; Figure 3 This is a structural block diagram of an SF6 gas pressure early warning device according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] In the field of SF6 gas pressure detection, the main methods used to monitor changes in SF6 gas pressure are online sensor monitoring systems, density relays or manual pressure gauges, and gas analyzers.

[0023] Among these methods, online sensor monitoring, while achieving a certain degree of real-time monitoring, suffers from high equipment costs, requires complex wiring and debugging by professional technicians during installation, and is also cumbersome in subsequent maintenance. More importantly, this method is extremely sensitive to changes in ambient temperature and humidity. SF6 gas pressure is closely related to temperature; fluctuations in ambient temperature cause corresponding changes in SF6 gas pressure, thus affecting measurement accuracy. For example, in outdoor substation environments with significant temperature variations, a 10°C temperature fluctuation can lead to a 5%-10% measurement error, significantly reducing the reliability of the measurement results and easily triggering false alarms.

[0024] Density relays are highly susceptible to environmental temperature fluctuations due to their measurement principle. Under extreme temperature conditions, such as extreme heat or cold, the internal structural characteristics of the density relay change, leading to a significant increase in measurement error. Furthermore, density relays can only monitor the density of SF6 gas; they cannot accurately and promptly reflect pressure changes caused by gas leaks. When a slow leak occurs in SF6 equipment, the density relay cannot react quickly enough due to the relatively slow density change, allowing the problem to escalate and potentially causing electrical equipment failure or even a safety accident.

[0025] Manual pressure gauge measurement: This method relies entirely on manual operation and cannot continuously monitor SF6 gas pressure in real time. Operators need to periodically go to the site to read the pressure gauge readings, which leads to the inability to detect dynamic pressure changes and sudden malfunctions in a timely manner. Moreover, the test results depend heavily on the operator's skill and sense of responsibility. If the operator's readings are inaccurate or if the test is not performed on time, potential problems may be overlooked, posing a threat to the safe operation of electrical equipment.

[0026] Gas analyzer testing: This method is relatively complex and requires professional personnel to operate according to specific procedures. The testing cycle is relatively long, potentially taking several minutes or even longer from sample collection to obtaining analysis results, and it cannot reflect gas pressure status in real time. Furthermore, gas analyzers have high maintenance costs, requiring regular calibration and component replacement, increasing operating costs.

[0027] In summary, existing SF6 gas pressure detection methods have many shortcomings in terms of accuracy, timeliness, reliability, and cost, failing to meet the demands of modern electrical equipment for precise, real-time, and reliable SF6 gas pressure detection. Therefore, this application proposes an SF6 gas pressure early warning method, designing an automated continuous detection system that uses high-precision pressure and temperature sensors to collect SF6 gas pressure and ambient temperature data in real time. The sensors transmit the collected data to a data processing unit in real time, which performs real-time analysis and processing according to the aforementioned temperature compensation mechanism and pressure change judgment method. Simultaneously, dynamic monitoring of the pressure data is achieved using data analysis algorithms, which not only reflects dynamic pressure changes in real time but also promptly detects sudden faults. For example, by performing real-time differential analysis on the pressure data, the rate of pressure change can be accurately calculated. Once an abnormal pressure change is detected, the system responds rapidly, achieving comprehensive, real-time, and dynamic monitoring of SF6 gas pressure.

[0028] According to an embodiment of the present invention, an embodiment of an SF6 gas pressure early warning method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0029] This embodiment provides an SF6 gas pressure early warning method. Figure 1 This is a flowchart of an SF6 gas pressure early warning method according to an embodiment of the present invention. It should be noted that if substantially the same result is obtained, this embodiment does not necessarily reflect that result. Figure 1 The illustrated process sequence is limited. For example... Figure 1 As shown, the process includes the following steps: Step S101: For the target electrical equipment, environmental compensation is performed on the measured pressure data of SF6 gas using the ambient temperature data of the surrounding environment to obtain compensated pressure data.

[0030] This application utilizes a pressure sensor to collect and measure pressure data, and a temperature sensor to collect ambient temperature data.

[0031] Specifically, pressure sensors are installed at key locations in SF6 electrical equipment to collect data in real time at different times. SF6 gas measurement pressure data The unit is MPa. Where, time... The pressure data is measured in minutes, providing a foundation for subsequent data processing. The pressure sensor should possess high sensitivity and stability, capable of accurately measuring minute pressure changes with a measurement accuracy of ±0.01 MPa.

[0032] In one specific implementation, the pressure sensor is a capacitive pressure sensor. Capacitive pressure sensors measure pressure based on the principle of capacitance change, and are characterized by fast response and high accuracy, meeting the requirement for real-time and accurate measurement of SF6 gas pressure.

[0033] Specifically, a temperature sensor is installed near the pressure sensor to synchronously collect ambient temperature data T(u) at the corresponding time u, in °C. The ambient temperature data reflects the influence of environmental factors on SF6 gas pressure. The temperature sensor needs to have a wide temperature measurement range and high measurement accuracy.

[0034] In one specific implementation, the temperature sensor is a thermocouple temperature sensor. The thermocouple temperature sensor has a measurement range of -200℃ to 1300℃ and an accuracy of ±0.5℃. It can adapt to various complex environmental temperature conditions and provide accurate temperature data for subsequent temperature compensation.

[0035] The pressure and temperature sensors transmit the collected data to the SF6 gas pressure early warning device via wired or wireless means, where it is processed by the data processing unit of the SF6 gas pressure early warning device.

[0036] Specifically, for sensors that are close to the data processing unit, wired transmission can be achieved using shielded twisted-pair cables to ensure the stability and accuracy of data transmission; for sensors that are far away or where wiring is inconvenient, wireless communication technologies such as ZigBee and Bluetooth can be used for data transmission to achieve remote and real-time data transmission.

[0037] Furthermore, the ambient temperature data of the surrounding environment is used to compensate the measured pressure data of SF6 gas for ambient temperature, thereby obtaining compensated pressure data.

[0038] In one implementation, a temperature-pressure correction function is pre-established to compensate for ambient temperature changes in the measured pressure data. Assume the temperature-pressure correction function is... .in, The data represents the compensated pressure after temperature compensation. T represents the measured pressure data obtained from the pressure sensor, and T represents the ambient temperature data obtained from the temperature sensor. Here, k represents the standard temperature, and k is a correction coefficient obtained by fitting experimental data. The data processing unit will process the data acquired in real time. Substituting T into the function, we can calculate... .

[0039] Step S102: Calculate the corrected pressure change rate based on the compensation pressure data at multiple times.

[0040] Specifically, the data processing unit in the SF6 gas pressure early warning device records the compensation pressure data obtained from temperature compensation in real time, performs differential calculations on multiple consecutive compensation pressure data, and obtains the corrected pressure change rate as follows: .

[0041] Step S103: Construct a dataset based on the operating status data, ambient temperature data, compensation pressure data, and correction pressure change rate of the target electrical equipment.

[0042] The dataset includes datasets from the current moment and datasets from historical moments. Each dataset corresponds to operational status data, ambient temperature data, compensation pressure data, and correction pressure change rate at a specific moment.

[0043] Step S104: If the compensation pressure data at the current moment does not meet the pressure standard and / or the rate of change of the corrected pressure at the current moment does not meet the rate of change standard, feature matching is performed based on the dataset at the current moment and the dataset at the historical moment. A target dataset that meets the matching range is determined from the dataset at the historical moment, and the SF6 gas leakage status at the historical moment corresponding to the target dataset is used as the SF6 gas leakage status at the current moment.

[0044] Pressure and rate of change standards are set in advance based on the historical operating data and safety standards of the target electrical equipment.

[0045] In one implementation, the SF6 gas leakage status and corresponding pressure data and pressure change rate data of the target electrical equipment at historical moments are obtained. Based on the pressure data and pressure change rate data when there is an SF6 gas leakage fault and when there is no leakage fault, and with established safety standards, pressure standards and change rate standards for the target electrical equipment are determined.

[0046] Understandably, when there is a leak in SF6 gas, the corresponding pressure data or pressure change rate data may not meet the pressure standard or change rate standard. Conversely, when there is no leak in SF6 gas, the corresponding pressure data and pressure change rate data may meet the pressure standard and change rate standard, respectively.

[0047] Understandably, for different target electrical devices, the pressure standard and pressure change rate standard will differ under different temperature environments. In one implementation, the pressure standard and pressure change rate standard are determined separately for different ambient temperature data ranges.

[0048] If the current compensation pressure data does not meet the pressure standard and / or the current correction pressure change rate does not meet the change rate standard, the target electrical equipment may be at risk of SF6 gas leakage, and further analysis of the target electrical equipment data at the current moment is required.

[0049] For example, under normal circumstances, the pressure standard range is: ,when or ,and When the rate of change exceeds the set standard, the data processing unit determines that there may be an abnormal pressure situation.

[0050] Furthermore, when a possible pressure anomaly is detected, the data processing unit compares and analyzes the current dataset with the historical dataset to eliminate misjudgments caused by momentary interference or other non-fault factors.

[0051] In one implementation, if the historical dataset shows that a similar brief pressure change occurred under certain specific conditions but was not a fault, the data processing unit can determine whether the pressure change is a real fault by comparing relevant conditions such as temperature and equipment operating status.

[0052] In one implementation, feature matching is performed between the data in the current dataset and the data in the historical dataset. The higher the feature matching degree, the more similar the data in the current dataset is to the data in the historical dataset, and the more similar the SF6 gas state of the electrical equipment in the current and historical datasets.

[0053] The dataset with the highest matching degree at least one historical moment is selected as the target dataset, and the SF6 gas leakage status at the historical moment corresponding to the target dataset is used as the SF6 gas leakage status at the current moment.

[0054] The historical SF6 gas leakage status includes whether an early warning was issued and whether an SF6 gas leakage failure actually occurred. If an early warning and a gas leakage failure occurred at the target time corresponding to the target dataset, it indicates that the SF6 gas leakage is abnormal at the current time; if no early warning and no gas leakage failure occurred at the target time corresponding to the target dataset, it indicates that the SF6 gas is normal at the current time.

[0055] Step S105: Issue an early warning based on the current SF6 gas leakage status.

[0056] When the SF6 gas pressure is determined to be abnormal at the current moment, the early warning module is triggered to issue an early warning.

[0057] Among them, early warning methods can be adopted in various ways, such as audible and visual alarms, SMS alarms, and remote signal transmission, to notify relevant personnel.

[0058] In one feasible approach, an audible and visual alarm is installed at the electrical equipment site, emitting bright flashes and loud alarm sounds to attract the attention of on-site personnel. Simultaneously, a text message containing detailed information about the abnormal situation, such as pressure values, temperature values, and pressure change rates, is sent to equipment maintenance personnel via a text messaging platform, enabling them to take timely measures. In addition, the alarm signal can be remotely transmitted to the monitoring center, where an alarm prompt window pops up on the monitoring system interface, displaying information such as the location of the abnormal equipment and the type of abnormality, facilitating unified scheduling and management by monitoring personnel.

[0059] The SF6 gas pressure early warning method provided in this embodiment improves the accuracy of pressure detection by compensating for SF6 gas pressure data with temperature data, thus avoiding false leak detections due to measurement errors. Furthermore, by comprehensively considering temperature, pressure change rate, and the degree of matching between the temperature-compensated pressure value and historical data, and combining this with historical equipment operating data to determine whether a pressure anomaly is genuine, the accuracy, reliability, and timeliness of SF6 gas pressure detection are improved, ensuring the safe and stable operation of electrical equipment.

[0060] This embodiment provides an SF6 gas pressure early warning method. Figure 2 This is a flowchart of another SF6 gas pressure early warning method according to an embodiment of the present invention. It should be noted that if substantially the same result is obtained, this embodiment does not necessarily reflect that result. Figure 2 The illustrated process sequence is limited. For example... Figure 2 As shown, the process includes the following steps: Step S201: For the target electrical equipment, environmental compensation is performed on the measured pressure data of SF6 gas using the ambient temperature data of the surrounding environment to obtain compensated pressure data.

[0061] Specifically, step S201 includes: Step S2011: Construct the SF6 gas temperature-pressure correction function.

[0062] In one implementation, a comprehensive correction value for the measured pressure data is calculated based on ambient temperature data and measured pressure data under multiple time-point factors. This comprehensive correction value is used to correct the measured pressure data, and integration is performed within a preset time window to obtain the average corrected pressure data. A temperature compensation factor is calculated based on the influence of periodic variations in ambient temperature data on the measured pressure data and the degree of difference between the measured pressure data and the pressure standard value. The average corrected pressure data is multiplied by the temperature compensation factor to obtain the SF6 gas temperature-pressure correction function.

[0063] Specifically, the formula for the SF6 gas temperature-pressure correction function is as follows:

[0064] Where, on the left side of the formula This is the final SF6 gas pressure value after temperature compensation and comprehensive processing, used to accurately determine the actual pressure state of SF6 gas.

[0065] Among them, the first term on the right side of the formula This is for averaged pressure data.

[0066] For the average corrected pressure data, calculations are performed using a complex summation method. Within the time window... Within this process, multiple time-dependent temperature and pressure factors are summed. Each factor is assigned a weighting coefficient. Exponential function Error function and the Sigmoid function The system comprises several components. An exponential function adjusts the weights of each factor based on time correlation; an error function normalizes the pressure value and extracts features; and a sigmoid function maps the temperature value to a suitable range to reflect the nonlinear relationship between temperature and pressure. Through this complex combination, the influence of multiple factors on the pressure measurement is comprehensively considered, resulting in a comprehensive correction value. This corrected pressure measurement value is then applied within a time window. Integrate within the time window and divide by the time window length. This yields an average corrected pressure value to smooth out fluctuations in pressure data and reflect the overall pressure trend over the time period.

[0067] Specifically, the process of constructing the average corrected stress data includes: 1. Weight adjustment based on time correlation: Construct an exponential function for factors at multiple time points, and use the exponential function to adjust the factor weight coefficients of the corresponding time points to obtain the first data item. .

[0068] Specifically, within the time window To comprehensively consider the impact of multiple relevant factors, i.e., factors at multiple time points, on the pressure value, a complex summation function is introduced. Among them, This represents the current time, expressed in minutes, and is used to determine the time base for data processing. The time window length for pressure data processing is set to 10 minutes based on actual testing requirements, which limits the time range of pressure data used in the calculation. This is the integration variable, used to iterate through the time window. Each moment within the time frame is in minutes.

[0069] For each relevant factor, an exponential function is used. To adjust its weight, For the second data item The relevant time points, in minutes, are used to determine the time correlation of the influence of each factor on the pressure value. Their values ​​are determined based on historical data and equipment operating characteristics. To control the shape of the exponential function, the weight distribution of the influence of each time point on the pressure value is determined. Set the values ​​according to the actual situation, for example, within... Between. Based on this, the distance from the current moment. The more recent the time point, the higher the weight of the corresponding factor, highlighting the importance of recent data in judging the current stress state.

[0070] 2. Pressure Feature Extraction and Normalization: The measured pressure data is normalized based on the error function to obtain the second data item. .

[0071] in, For at any time The SF6 gas pressure value measured by the pressure sensor is the measured pressure data, which is in MPa, and the measurement accuracy can reach ±0.01MPa.

[0072] Specifically, combining the error function of the second data term The pressure measurements were normalized and features were extracted. This is the average of historical stress data. In one possible implementation, the standard deviation of historical stress data is given. Set as , Set as Error functions can map pressure measurements to a specific range, extracting key features from the pressure data, which facilitates subsequent comprehensive analysis with other factors.

[0073] Wherein, for the error function: .

[0074] The error function is a special function that maps the input value to an integral form. Range. In this invention, the pressure measurement value is... Subtract the mean and divide by As input to the error function, it is used to normalize the pressure measurements to a specific range, highlighting the deviation of the pressure data from the mean.

[0075] SF6 gas pressure measurements fluctuate, with inconsistent magnitudes and distribution ranges among different measurements, making direct comprehensive analysis difficult. The error function, through normalization, unifies pressure measurements to a comparable range, facilitating comprehensive consideration with other factors. This solves the problems of pressure data feature extraction and standardization, enabling subsequent calculations to more accurately reflect pressure changes.

[0076] 3. Nonlinear mapping of temperature effects: Based on the Sigmoid function, ambient temperature data is mapped to obtain a third data item. .

[0077] in, For at any time The ambient temperature value measured by the temperature sensor, in units of The measurement accuracy can reach ±0.5℃.

[0078] Specifically, the third data item utilizes the Sigmoid function. Map temperature values ​​to The range is used to highlight the nonlinear characteristics of the effect of temperature on pressure. Among them, Temperature threshold As a temperature scaling factor, in one possible implementation, Set as , Set as The influence of different temperature ranges on pressure is not a linear relationship. The Sigmoid function can effectively capture this nonlinear change, making the temperature factor more accurately reflected in pressure calculations.

[0079] 4. Calculation of comprehensive correction value: Multiply the first, second, and third data items together, and sum them according to multiple time point factors to obtain the fourth data item. The fifth data item is obtained by summing the first data items corresponding to multiple time point factors. .

[0080] Specifically, each relevant factor is also multiplied by a weighting coefficient. Its value range is within The values ​​are obtained through machine learning algorithms trained on historical data, used to adjust the relative importance of each factor on stress levels. These factors are then combined and analyzed... from arrive The summations yield a comprehensive correction value that comprehensively reflects the influence of multiple factors on the pressure measurement within the time window. In one possible implementation, Setting it to 15 means that the influence of multiple related factors on the pressure value is taken into account.

[0081] For the Sigmoid function: .

[0082] The Sigmoid function maps the real number field to... The characteristics of the interval, and the non-linear shape of the function. In this invention, the temperature value... After being compared with the threshold and scaling factor The result is used as input to the Sigmoid function after calculation, and its nonlinear mapping characteristics are used to highlight the nonlinear relationship between temperature and pressure.

[0083] The effect of temperature on SF6 gas pressure is not a simple linear relationship, and traditional linear methods cannot accurately describe this complex relationship. The Sigmoid function can capture the nonlinear characteristics of temperature effects, allowing temperature factors to be more realistically reflected in pressure calculations, thus solving the problem of nonlinear modeling of the effect of temperature on pressure.

[0084] 5. Integral Calculation: Calculate the ratio of the fourth data item to the fifth data item to obtain the comprehensive correction value. Add the measured pressure data to the comprehensive correction value and perform integral calculation within the preset time window to obtain the average corrected pressure data.

[0085] Specifically, the pressure measurement values, after complex summation and correction, are applied within a time window. Integrating the data within a given time window smooths out fluctuations and reflects the overall pressure trend over that period. The integral result is then divided by the length of the time window. This yields an average corrected pressure value, which provides a relatively stable pressure data basis for subsequent temperature compensation.

[0086] Among them, the second term on the right side of the formula This is the temperature compensation factor.

[0087] Among them, for the temperature compensation factor, within the temperature range Inside, integral operations are performed on temperature-related functions. First, through... The temperature was normalized and then compared with... as well as Multiply. Simulate the effect of periodic temperature changes on pressure. The temperature compensation is then further adjusted based on the pressure value. Dividing the integral result by the integral of the same function yields a temperature-related correction factor, which is used to compensate for the temperature of the previously obtained average corrected pressure value.

[0088] Specifically, the process of constructing the temperature compensation factor includes: 1. Temperature Normalization: Within a preset temperature data range, the ambient temperature data is normalized to obtain the sixth data item. .

[0089] in, and These represent the lower and upper limits for temperature data processing, respectively. In one possible implementation, they are set according to the actual temperature measurement range. , . In order to be in The average temperature within the range is calculated by the arithmetic mean of the temperature values ​​within that range.

[0090] Specifically, within the temperature range Inside, through The temperature is normalized so that the normalized temperature value can reflect the effect of temperature change on pressure on a uniform scale.

[0091] 2. Temperature Periodic Adjustment: The impact of periodic changes in ambient temperature data on the measured pressure data is calculated, resulting in the seventh data item. .

[0092] in, The period of temperature change, in one possible implementation, is set to 24 hours, which translates to 1440 minutes. The function simulates the effect of periodic temperature changes on pressure.

[0093] 3. Pressure Correlation Adjustment: Calculate the difference between the measured pressure data and the pressure standard value to obtain the eighth data item. .

[0094] in, The pressure threshold, As a scaling factor, in one possible implementation, Set as , Set as .

[0095] Specifically, The eighth data item is used to highlight the degree of deviation between the pressure value and the pressure threshold. It only affects the results when the pressure value exceeds the threshold, thereby allowing for further adjustments to the temperature compensation based on the pressure value.

[0096] Among them, for function: .

[0097] The ReLU function has a one-sided suppression characteristic; the output is the input value when the input is greater than 0, and 0 otherwise. In this invention, the pressure measurement value is compared with a threshold value. The deviation after scaling factor After processing, it is used as input to the ReLU function, which utilizes its characteristics to highlight the degree of deviation between the pressure value and the threshold, and only affects the result when the pressure value exceeds the threshold.

[0098] In temperature compensation calculations, the effect of abnormal pressure conditions on temperature compensation needs to be considered. The ReLU function can effectively highlight the impact of abnormal pressure conditions, avoiding interference from this factor in temperature compensation when the pressure is normal, thus solving the problem of making targeted adjustments in temperature compensation based on abnormal pressure conditions.

[0099] 4. Integration calculation: Multiply the sixth, seventh, and eighth data items together and perform integration calculation within the preset temperature data range to obtain the ninth data item; multiply the seventh and eighth data items together and perform integration calculation within the preset temperature data range to obtain the tenth data item.

[0100] Specifically, the normalized temperature value and as well as Multiply, and then apply the product over the temperature range. Integrating within the range yields the ninth data term. as well as Multiply, and then apply the product over the temperature range. Integrating within the range yields the tenth data item.

[0101] 5. Temperature compensation factor calculation: Calculate the ratio of the ninth data item to the tenth data item to obtain the temperature compensation factor.

[0102] This correction factor takes into account the temperature variation range, periodicity, and correlation with pressure values, and is used to compensate for the temperature of the previously obtained average corrected pressure value.

[0103] Furthermore, for the right side of the formula, multiplying the average corrected pressure value obtained through integration by the temperature compensation factor yields the final result. That is, the SF6 gas temperature-pressure correction function constructed in this application takes into account temperature compensation and the combined influence of multiple factors, and is used to accurately determine the actual pressure state of SF6 gas.

[0104] This application's SF6 gas temperature-pressure correction function comprehensively considers the influence of multiple factors on SF6 gas pressure measurement. It acquires real-time pressure and temperature data through data acquisition and processes this data using complex mathematical functions. In the time dimension, it selects data through time windows and performs integral calculations to smooth pressure fluctuations and reflect trends. Regarding influencing factors, it comprehensively considers the inherent characteristics of temperature and pressure, as well as the time correlation of various factors. Through different functions, it performs normalization, feature extraction, and nonlinear mapping on the pressure and temperature data, ultimately obtaining the pressure value after temperature compensation and comprehensive processing. .

[0105] Specifically, this study delves into the physical properties of SF6 gas, analyzes the pressure variation patterns under different temperature conditions, and constructs a temperature-pressure correction function based on extensive experimental data and theoretical analysis. This function dynamically corrects the measured SF6 gas pressure based on real-time monitored ambient temperature, effectively eliminating measurement errors caused by changes in ambient temperature and thus preventing false alarms. For example, by experimentally obtaining the deviation data between the true and measured SF6 gas pressure values ​​at different temperatures, and using mathematical methods such as regression analysis to fit the correction function, the measurement accuracy can be improved to within ±2% even in environments with large temperature fluctuations.

[0106] Traditional SF6 gas pressure detection methods do not fully consider the impact of ambient temperature changes and various complex factors on pressure measurement, resulting in large measurement errors and an inability to accurately determine the gas pressure status. This formula, by comprehensively considering temperature compensation and the combined effects of multiple factors, solves the measurement error problem caused by temperature changes, improves detection accuracy, and can more accurately determine whether SF6 gas pressure is abnormal, ensuring the safe and stable operation of electrical equipment.

[0107] Step S2012: Input the ambient temperature data and measured pressure data into the SF6 gas temperature-pressure correction function to obtain the compensated pressure data.

[0108] Step S202: Calculate the corrected pressure change rate based on the compensation pressure data at multiple times.

[0109] Specifically, the data processing unit in the SF6 gas pressure early warning device records the compensation pressure data obtained from temperature compensation in real time, performs differential calculations on multiple consecutive compensation pressure data, and obtains the corrected pressure change rate as follows: .

[0110] Step S203: Construct a dataset based on the operating status data, ambient temperature data, compensation pressure data, and correction pressure change rate of the target electrical equipment.

[0111] The dataset includes datasets from the current moment and datasets from historical moments. Each dataset corresponds to operational status data, ambient temperature data, compensation pressure data, and correction pressure change rate at a specific moment.

[0112] Step S204: If the compensation pressure data at the current moment does not meet the pressure standard and / or the rate of change of the corrected pressure at the current moment does not meet the rate standard, feature matching is performed based on the dataset at the current moment and the dataset at the historical moment. A target dataset that meets the matching range is determined from the dataset at the historical moment, and the SF6 gas leakage status at the historical moment corresponding to the target dataset is used as the SF6 gas leakage status at the current moment.

[0113] Specifically, step S204 includes: Step S2041: Calculate whether the compensation pressure data at the current moment meets the pressure standard, and calculate whether the rate of change of the corrected pressure at the current moment meets the rate of change standard.

[0114] In one implementation, a first pressure threshold and a second pressure threshold are obtained; if the compensation pressure data at the current moment is less than the first pressure threshold or greater than the second pressure threshold, then the compensation pressure data at the current moment does not meet the pressure standard; a first rate of change threshold is obtained; if the rate of change of the corrected pressure at the current moment is greater than the first rate of change threshold, then the rate of change of the corrected pressure at the current moment does not meet the rate of change standard.

[0115] If the current compensation pressure data does not meet the pressure standard and / or the current correction pressure change rate does not meet the change rate standard, proceed to step S2042.

[0116] Step S2042: Based on the current ambient temperature data, compensated pressure data, and corrected pressure change rate, as well as the corresponding temperature tolerance value, pressure tolerance value, and change rate tolerance value, calculate the temperature matching range, pressure matching range, and change rate matching range.

[0117] For each ambient temperature data, compensation pressure data, and correction pressure change rate, a tolerance value is determined, i.e., the detection error tolerance range.

[0118] For any rightful anomalies to be detected at the current moment, extract information such as ambient temperature data, compensation pressure data, and the current operating status of the equipment, as well as the corrected pressure change rate, from the current moment's dataset. Calculate the matching range for the current moment according to the detection error tolerance range.

[0119] For example, the pressure tolerance is ±0.05 MPa, the temperature tolerance is ±5℃, and the rate of change tolerance is ±0.01 MPa / min. The detected ambient temperature data at the current moment is 30℃, the compensated pressure data is 0.55 MPa, and the corrected pressure change rate is 0.02 MPa / min. Therefore, the calculated temperature matching range is 25℃-35℃, the pressure matching range is 0.50 MPa-0.60 MPa, and the rate of change matching range is 0.01 MPa / min-0.03 MPa / min.

[0120] Step S2043: According to the temperature matching range, pressure matching range, and rate of change matching range, perform feature matching in the dataset at historical time points to obtain at least one target dataset.

[0121] Specifically, the historical data stored by the data processing unit includes multiple dimensions, such as ambient temperature data, compensation pressure data, correction pressure change rate, and whether alarms have occurred. The historical data is categorized according to different equipment operating states, such as normal operation, equipment load changes, and equipment startup or shutdown phases. For example, all relevant data from the equipment startup phase is grouped into one subset, and data from the normal operation phase is grouped into another subset. This categorization helps to more accurately identify historical scenarios similar to the current situation during subsequent comparative analysis.

[0122] Search historical data for records where pressure, temperature, and rate of change fall within the specified temperature, pressure, and rate of change matching ranges, obtaining at least one matching dataset. Simultaneously, ensure that the equipment operating status corresponding to the selected historical data is the same as or similar to the current equipment operating status.

[0123] For example, historical data is searched for values ​​with temperatures ranging from 25℃ to 35℃, pressure values ​​ranging from 0.50MPa to 0.60MPa, and change rates ranging from 0.01MPa / min to 0.03MPa / min, ensuring that the corresponding equipment is operating normally. After filtering, 10 sets of historical timeframes matching the specified features are obtained.

[0124] Step S2044: Obtain the historical SF6 gas leakage status corresponding to the target dataset, and obtain the historical SF6 gas leakage status with the largest proportion as the current SF6 gas leakage status.

[0125] After filtering out historical data sets with similar key characteristics, these historical data are comprehensively analyzed. The analysis examines whether alarms occurred at the corresponding time and the subsequent actual operation of the equipment, such as whether malfunctions occurred and the type of malfunction. The SF6 gas leakage situation at that time is used as the current SF6 gas leakage situation.

[0126] In one implementation, the historical SF6 gas leakage status with the largest proportion is obtained and used as the current SF6 gas leakage status.

[0127] Understandably, if the selected historical dataset shows that alarms occurred under similar pressure, temperature, and pressure change rate conditions, and subsequent confirmation of equipment leakage, then the likelihood of a genuine fault in the current situation is higher. Conversely, if historical data shows that no alarms occurred under similar conditions and the equipment operated normally, the current pressure change may be caused by non-fault factors.

[0128] For example, a detailed review of 10 historical data records revealed that 8 records showed alarms at the time, and subsequent testing confirmed an SF6 gas leak. The other 2 records, while showing similar pressure, temperature, and pressure change rates, did not trigger alarms, and the equipment subsequently operated normally. Based on this analysis, the currently detected pressure change matches most similar historical scenarios, indicating that pressure changes are accompanied by alarms and may indicate a gas leak. Therefore, it is highly likely that the current pressure change is a genuine fault. In other words, it is determined that an SF6 gas leak has occurred at the current moment.

[0129] This application abandons the traditional method of using fixed thresholds as judgment indicators and establishes a completely new pressure change judgment method that considers temperature compensation. It no longer relies solely on a single pressure value to determine whether to alarm, but comprehensively considers factors such as the pressure change rate, the temperature-compensated pressure value, and historical equipment operating data. Specifically, firstly, different pressure change rate thresholds are set based on equipment type, operating environment, and historical data. When the detected pressure change rate exceeds the corresponding threshold, and the temperature-compensated pressure value deviates from the normal range, the system combines historical equipment operating data to determine whether it is a genuine pressure anomaly. If an anomaly is determined, an alarm signal is issued promptly. This method can more accurately determine the true state of SF6 gas pressure and effectively avoid false alarms or missed alarms caused by relying solely on fixed thresholds. For example, for a certain type of SF6 electrical equipment, the pressure change rate is usually within 0.01 MPa per minute during normal operation. When the detected pressure change rate exceeds 0.03 MPa per minute, and the temperature-compensated pressure value is below 95% of the lower limit of the normal range, the system judges that there may be an anomaly such as gas leakage.

[0130] Step S205: Issue an early warning based on the current SF6 gas leakage status.

[0131] Based on this judgment result, the data processing unit can further determine whether to trigger the alarm module. If the SF6 gas leakage status is a leakage fault at the current moment, it will issue an early warning to remind relevant personnel to deal with possible equipment failures in a timely manner.

[0132] This application can effectively improve the accuracy of judging whether pressure changes are real faults, reduce the occurrence of misjudgments, and ensure the stable operation of SF6 electrical equipment.

[0133] In actual SF6 electrical equipment monitoring scenarios, the first priority is to ensure that high-precision pressure and temperature sensors are functioning properly and that pressure values ​​are collected in real time. and temperature value For example, in high-voltage switchgear in substations, pressure and temperature sensors should be installed in locations that accurately reflect the state of SF6 gas. The sensors collect data at minute intervals to ensure timeliness and continuity, providing the foundational input for subsequent formula calculations.

[0134] This application establishes a temperature-pressure correction function based on the physical properties of SF6 gas and extensive experimental data, achieving precise compensation for temperature changes, which is key to improving measurement accuracy. An innovative pressure alarm method, comprehensively considering the pressure change rate, the temperature-compensated pressure value, and historical equipment operating data, is crucial for accurately identifying pressure anomalies and reducing false alarm rates. High-precision pressure and temperature sensors are employed, and a rational data acquisition, transmission, and processing workflow is implemented to achieve real-time continuous monitoring and dynamic analysis of SF6 gas pressure. This application solves the technical problems existing in current SF6 gas pressure detection methods, such as measurement errors and false alarms caused by temperature influences, and the inability to promptly and accurately identify pressure anomalies and achieve continuous dynamic monitoring. It improves the accuracy, reliability, and timeliness of SF6 gas pressure detection, ensuring the safe and stable operation of electrical equipment.

[0135] The method of this application can be applied to different operating scenarios, including normal operation scenarios, temperature fluctuation scenarios, and scenarios with leakage.

[0136] 1. Normal operating scenario.

[0137] Formula application: During normal equipment operation, the data collected in real time will be... and Substitute the values ​​into the formula for calculation. The parameters are as follows: , , , , , These settings are based on the equipment's historical operating data and design standards. For example, and This was derived through statistical analysis of pressure data from long-term stable operation of the equipment; and The determination is based on the common temperature range of the equipment's operating environment and experimental data on the effect of temperature on pressure. At this point, the complex summation functions and integral functions in the formula are calculated step by step to obtain the results. .

[0138] Value range and threshold determination: During normal operation, The value range should fall within the normal pressure range preset by the equipment (e.g., )Inside. like Within this range, it indicates that the equipment is operating normally and the SF6 gas pressure is stable. This is because the formula comprehensively considers temperature compensation and the influence of various factors on pressure; under normal circumstances, the calculation results should conform to the stable operating state of the equipment.

[0139] 2. Temperature fluctuation scenario.

[0140] Formula application: When the ambient temperature fluctuates, the temperature value Changes in this factor will directly affect multiple parts of the formula. For example, during periods of high temperatures in summer or low temperatures in winter, This may exceed the normal operating temperature range of the equipment. In this case, the temperature-related function in the formula, such as... , These functions adjust their pressure values ​​based on temperature changes. As the temperature rises or falls, the output values ​​of these functions change, thus affecting... The calculation results.

[0141] Value range and threshold determination: Due to temperature fluctuations, The value range may vary. However, thanks to the temperature compensation mechanism in the formula, as long as the temperature fluctuation is within the equipment's tolerance range, It should still be maintained within the normal pressure range as much as possible. If An error exceeding the normal range may not be due to abnormal pressure on the equipment itself, but rather to excessive temperature fluctuations causing insufficient or excessive compensation. In this case, maintenance personnel can further check the accuracy of the temperature sensor based on the formula calculation results and temperature changes, or adjust the temperature-related parameters in the formula (such as...). , (etc.) to ensure the accuracy of temperature compensation.

[0142] 3. There is a possibility of leakage.

[0143] Formula application: When there is a potential SF6 gas leak in the equipment, the pressure value It will gradually decrease. The complex summation function in the formula takes into account the time correlation of pressure changes (through...). and (parameters), and the effect of pressure changes on temperature compensation (through... (e.g., functions). As the pressure decreases, the output of these functions will change accordingly, ultimately affecting... The calculation.

[0144] Value range and threshold judgment: If The pressure continued to decline and fell below the lower limit of the normal range, combined with The function's prominent effect on the deviation between pressure and threshold indicates a possible gas leak. At this point, The change in the value range reflects an abnormal decrease in pressure. Maintenance personnel can use this result to promptly perform leak detection and repair on the equipment, preventing further leakage. Simultaneously, by analyzing the effects of various factors in the formula... The contribution of changes can roughly determine the severity of the leak and its possible causes.

[0145] Furthermore, in actual operation, the operating status and environmental conditions of the equipment will change over time, requiring updates to the model data and optimization of the parameters.

[0146] Data Updates: Regularly update relevant data in the formula, such as the average of historical stress data. and standard deviation Every so often, such as once a month, the newly collected pressure data is statistically analyzed and recalculated. and This is to adapt to slow changes in equipment performance. Meanwhile, temperature-related parameters such as... , Adjustments should also be made according to seasonal changes or changes in the equipment's operating environment.

[0147] Parameter optimization: As equipment operating time increases and data accumulates, other parameters in the formula can be optimized. For example, by analyzing a large amount of operating data, machine learning algorithms can be used to optimize the weighting coefficients. Optimize the formula to more accurately reflect the influence of each factor on the pressure value. Furthermore, if a discrepancy is found between the calculated results and the actual equipment condition, adjustments can be made. , , , The threshold parameters are fine-tuned to improve the formula's adaptability and accuracy to real-world situations.

[0148] Through the application and analysis of the formula under different practical conditions, maintenance personnel can use the formula of the SF6 gas pressure detection method and device that takes temperature compensation into account to more accurately monitor the operating status of SF6 electrical equipment, promptly identify potential problems and take corresponding measures to ensure the safe and stable operation of the equipment.

[0149] The SF6 gas pressure detection method and apparatus considering temperature compensation proposed in this invention have the following significant advantages compared with the prior art: Improving Detection Accuracy: By establishing a precise temperature-pressure correction function to compensate for temperature changes, the influence of ambient temperature on SF6 gas pressure measurement is effectively eliminated, significantly improving measurement accuracy. Compared to traditional detection methods that may have an error of 5%-10% when temperature fluctuates, this invention can control the measurement accuracy within ±2%, greatly improving the accuracy of the detection results and providing reliable data support for the safe operation of electrical equipment. This means that the actual pressure state of SF6 gas can be more accurately grasped, avoiding misjudgments of equipment operating conditions due to measurement errors.

[0150] Reduced false alarm rate: The innovative pressure alarm method no longer relies solely on fixed thresholds, but comprehensively considers factors such as the rate of pressure change, the pressure value after temperature compensation, and historical equipment operating data. This method can more accurately identify real pressure anomalies and effectively avoid false alarms caused by changes in environmental factors or other interference. According to actual tests, compared with traditional threshold-based alarm methods, the false alarm rate can be reduced by 70%-80%, reducing the unnecessary workload of maintenance personnel caused by false alarms and improving the reliability of the alarm system.

[0151] Early fault warning: The system can sensitively detect pressure changes during the initial leakage of SF6 gas. When an initial leak occurs, through real-time monitoring and analysis of the pressure change rate and the pressure value after temperature compensation, the system can quickly identify and issue an alarm signal. This allows maintenance personnel to take timely measures before the problem escalates, such as equipment repair and leak detection and repair, effectively avoiding electrical equipment failures caused by undetected gas leaks, ensuring the safe and stable operation of electrical equipment, reducing the probability of equipment damage and power outages, and improving the reliability of the power system.

[0152] Real-time continuous monitoring and dynamic feedback: An automated continuous monitoring system enables real-time, continuous monitoring of SF6 gas pressure. This not only reflects dynamic pressure changes in real time, allowing maintenance personnel to understand equipment operating status at any time, but also promptly detects sudden faults. This real-time and dynamic nature allows maintenance personnel to proactively plan maintenance and respond to changes based on pressure trends, shifting from reactive to proactive maintenance, improving efficiency and reducing costs. Simultaneously, the data from real-time continuous monitoring provides rich foundational data for equipment condition assessment and lifespan prediction, helping to further optimize equipment maintenance strategies and extend equipment lifespan.

[0153] This embodiment also provides an SF6 gas pressure early warning device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0154] This embodiment provides an SF6 gas pressure early warning device, such as... Figure 3 As shown, it includes: The first calculation module 301 is used to perform environmental compensation on the measured pressure data of SF6 gas using the ambient temperature data of the surrounding environment for the target electrical equipment, and obtain the compensated pressure data.

[0155] The second calculation module 302 is used to calculate the corrected pressure change rate based on the compensation pressure data at multiple times.

[0156] Module 303 is used to build a dataset based on the target electrical equipment's operating status data, ambient temperature data, compensation pressure data, and correction pressure change rate.

[0157] The analysis module 304 is used to perform feature matching between the current time dataset and the historical time dataset when the current time compensation pressure data does not meet the pressure standard and / or the current time correction pressure change rate does not meet the change rate standard. It determines the target dataset that meets the matching range from the historical time dataset and uses the historical time SF6 gas leakage status corresponding to the target dataset as the current time SF6 gas leakage status.

[0158] The early warning module 305 is used to issue early warnings based on the current SF6 gas leakage status.

[0159] In some alternative implementations, the first computing module 301 includes: Construct a submodule for building the SF6 gas temperature-pressure correction function.

[0160] The compensation submodule is used to input ambient temperature data and measured pressure data into the SF6 gas temperature-pressure correction function to obtain compensated pressure data.

[0161] In some alternative implementations, the construction submodule includes: The first building unit is used to calculate the comprehensive correction value of the measured pressure data by the ambient temperature data and the measured pressure data under multiple time point factors.

[0162] The second building unit is used to correct the measured pressure data using the comprehensive correction value and to perform integral calculation within a preset time window to obtain the average corrected pressure data.

[0163] The third building block is used to calculate the temperature compensation factor based on the impact of periodic changes in ambient temperature data on measured pressure data and the degree of difference between measured pressure data and pressure standard values.

[0164] Multiplying the average corrected pressure data by the temperature compensation factor yields the SF6 gas temperature-pressure correction function.

[0165] In some alternative implementations, the first building unit includes: The first calculation subunit is used to construct an exponential function for multiple time point factors and use the exponential function to adjust the factor weight coefficients of the corresponding time point factors to obtain the first data item.

[0166] The second calculation subunit is used to normalize the measured pressure data based on the error function to obtain the second data item.

[0167] The third calculation subunit is used to map the ambient temperature data based on the Sigmoid function to obtain the third data item.

[0168] The fourth calculation subunit is used to multiply the first, second, and third data items and sum them according to multiple time point factors to obtain the fourth data item.

[0169] The fifth calculation subunit is used to sum the first data items corresponding to multiple time point factors to obtain the fifth data item.

[0170] The sixth calculation subunit is used to calculate the ratio of the fourth data item to the fifth data item to obtain the comprehensive correction value.

[0171] In some alternative implementations, the second building unit includes: The seventh calculation subunit is used to add the measured pressure data to the comprehensive correction value and perform integration calculation within a preset time window to obtain the average corrected pressure data.

[0172] In some alternative implementations, the third building block includes: The eighth calculation subunit is used to normalize the ambient temperature data within a preset temperature data range to obtain the sixth data item.

[0173] The ninth calculation subunit is used to calculate the impact of periodic changes in ambient temperature data on the measured pressure data, resulting in the seventh data item.

[0174] The tenth calculation subunit is used to calculate the difference between the measured pressure data and the pressure standard value, resulting in the eighth data item.

[0175] The eleventh calculation subunit is used to multiply the sixth, seventh, and eighth data items and perform integral calculations within a preset temperature data range to obtain the ninth data item.

[0176] The twelfth calculation subunit is used to multiply the seventh and eighth data items and perform integral calculations within a preset temperature data range to obtain the tenth data item.

[0177] The thirteenth calculation subunit is used to calculate the ratio of the ninth and tenth data items to obtain the temperature compensation factor.

[0178] In some alternative implementations, the analysis module 304 includes: The first analysis submodule includes: acquiring a first pressure threshold and a second pressure threshold; if the compensation pressure data at the current moment is less than the first pressure threshold or greater than the second pressure threshold, then the compensation pressure data at the current moment does not meet the pressure standard; acquiring a first rate of change threshold; if the rate of change of the corrected pressure at the current moment is greater than the first rate of change threshold, then the rate of change of the corrected pressure at the current moment does not meet the rate of change standard.

[0179] The second analysis submodule is used to calculate the temperature matching range, pressure matching range, and rate of change matching range based on the current ambient temperature data, compensated pressure data, and corrected pressure change rate, as well as the corresponding temperature tolerance value, pressure tolerance value, and rate of change tolerance value; according to the temperature matching range, pressure matching range, and rate of change matching range, feature matching is performed on the historical dataset to obtain at least one target dataset; the historical SF6 gas leakage status corresponding to the target dataset is obtained, and the historical SF6 gas leakage status with the largest proportion is obtained as the current SF6 gas leakage status.

[0180] In some alternative implementations, the warning module 305 includes: The early warning submodule is used to issue an early warning when the SF6 gas leakage status is a leakage fault at the current moment.

[0181] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0182] In this embodiment, the SF6 gas pressure early warning device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0183] This invention also provides a computer device having the above-described features. Figure 3 The SF6 gas pressure early warning device shown is shown.

[0184] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 4 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 4 Take a processor 10 as an example.

[0185] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0186] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0187] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0188] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0189] The computer device also includes an input device 30 and an output device 40. The processor 10, memory 20, input device 30, and output device 40 can be connected via a bus or other means. Figure 4 Taking the example of a connection between China and Israel via a bus.

[0190] Input device 30 can receive input numerical or character information, and generate key signal inputs related to user settings and function control of the computer device, such as a touchscreen, keypad, mouse, trackpad, touchpad, joystick, one or more mouse buttons, trackball, joystick, etc. Output device 40 may include display devices, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibration motors). The aforementioned display devices include, but are not limited to, liquid crystal displays, light-emitting diodes, displays, and plasma displays. In some alternative embodiments, the display device may be a touchscreen.

[0191] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0192] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0193] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for early warning of SF6 gas pressure, characterized in that, The method includes: For the target electrical equipment, environmental compensation is performed on the measured pressure data of SF6 gas using the ambient temperature data of the surrounding environment to obtain compensated pressure data. The corrected pressure change rate is calculated based on the compensated pressure data at multiple times. A dataset is constructed based on the operating status data of the target electrical equipment, the ambient temperature data, the compensation pressure data, and the correction pressure change rate; If the compensation pressure data at the current moment does not meet the pressure standard and / or the rate of change of the correction pressure at the current moment does not meet the rate of change standard, feature matching is performed based on the dataset at the current moment and the dataset at the historical moment. A target dataset that meets the matching range is determined from the dataset at the historical moment, and the SF6 gas leakage status at the historical moment corresponding to the target dataset is used as the SF6 gas leakage status at the current moment. An early warning is issued based on the current SF6 gas leakage status. The method of using ambient temperature data to perform environmental compensation on the measured pressure data of SF6 gas to obtain compensated pressure data includes: Construct the SF6 gas temperature-pressure correction function; The ambient temperature data and the measured pressure data are input into the SF6 gas temperature-pressure correction function to obtain the compensated pressure data; The construction of the SF6 gas temperature-pressure correction function includes: Calculate the combined correction value of the ambient temperature data and the measured pressure data for the measured pressure data under multiple time point factors; The measured pressure data is corrected using the comprehensive correction value, and the average corrected pressure data is obtained by integral calculation within a preset time window. Based on the influence of the periodic changes in the ambient temperature data on the measured pressure data and the degree of difference between the measured pressure data and the pressure standard value, a temperature compensation factor is calculated. Multiplying the average corrected pressure data by the temperature compensation factor yields the SF6 gas temperature-pressure correction function; The comprehensive correction value for the measured pressure data based on the ambient temperature data and the measured pressure data under multiple time point factors includes: Construct an exponential function for multiple time point factors, and use the exponential function to adjust the factor weight coefficients of the corresponding time point factors to obtain the first data item; The measured pressure data is normalized based on the error function to obtain the second data item; The environmental temperature data is mapped using the Sigmoid function to obtain the third data item. Multiply the first data item, the second data item, and the third data item together, and sum them according to multiple time point factors to obtain the fourth data item; Summing the first data items corresponding to multiple time point factors yields the fifth data item; Calculate the ratio of the fourth data item to the fifth data item to obtain the comprehensive correction value; The step of correcting the measured pressure data using the comprehensive correction value and performing integration calculation within a preset time window to obtain the average corrected pressure data includes: The measured pressure data is added to the comprehensive correction value, and the integral is calculated within a preset time window to obtain the average corrected pressure data. The calculation of the temperature compensation factor based on the influence of the periodic changes in the ambient temperature data on the measured pressure data and the degree of difference between the measured pressure data and the pressure standard value includes: Within a preset temperature data range, the ambient temperature data is normalized to obtain the sixth data item; The influence of the periodic changes in the ambient temperature data on the measured pressure data is calculated to obtain the seventh data item; The difference between the measured pressure data and the pressure standard value is calculated to obtain the eighth data item; Multiply the sixth, seventh, and eighth data items together and integrate them within the preset temperature data range to obtain the ninth data item. Multiply the seventh and eighth data items and perform integration within the preset temperature data range to obtain the tenth data item; The ratio of the ninth data item to the tenth data item is calculated to obtain the temperature compensation factor.

2. The SF6 gas pressure early warning method according to claim 1, characterized in that, The method includes: Obtain the first pressure threshold and the second pressure threshold; If the compensation pressure data at the current moment is less than the first pressure threshold or greater than the second pressure threshold, then the compensation pressure data at the current moment does not meet the pressure standard. Obtain the first rate of change threshold; If the rate of change of the corrected pressure at the current moment is greater than the first rate of change threshold, then the rate of change of the corrected pressure at the current moment does not meet the rate of change standard.

3. The SF6 gas pressure early warning method according to any one of claims 1-2, characterized in that, The process of performing feature matching between the current-time dataset and historical-time datasets, determining a target dataset that meets the matching range from the historical-time dataset, and using the historical-time SF6 gas leakage status corresponding to the target dataset as the current-time SF6 gas leakage status includes: Based on the current ambient temperature data, the compensation pressure data, and the correction pressure change rate, as well as the corresponding temperature tolerance value, pressure tolerance value, and change rate tolerance value, calculate the temperature matching range, pressure matching range, and change rate matching range. Based on the temperature matching range, the pressure matching range, and the rate of change matching range, feature matching is performed in the dataset at historical time points to obtain at least one target dataset; Obtain the historical SF6 gas leakage status corresponding to the target dataset, and obtain the historical SF6 gas leakage status with the largest proportion as the current SF6 gas leakage status. The early warning based on the current SF6 gas leakage status includes: An early warning will be issued when the current SF6 gas leakage status is a leakage fault.

4. An SF6 gas pressure early warning device, characterized in that, The device includes: The first calculation module is used to perform environmental compensation on the measured pressure data of SF6 gas using the ambient temperature data of the surrounding environment for the target electrical equipment, and obtain the compensated pressure data. The second calculation module is used to calculate the corrected pressure change rate based on the compensated pressure data at multiple times. The construction module is used to construct a dataset based on the operating status data of the target electrical equipment, the ambient temperature data, the compensation pressure data, and the correction pressure change rate; The analysis module is used to perform feature matching between the current time dataset and the historical time dataset when the current time compensation pressure data does not meet the pressure standard and / or the current time correction pressure change rate does not meet the change rate standard, and to determine the target dataset that meets the matching range from the historical time dataset, and to take the historical time SF6 gas leakage status corresponding to the target dataset as the current time SF6 gas leakage status. The early warning module is used to issue an early warning based on the current SF6 gas leakage status. The method of using ambient temperature data to perform environmental compensation on the measured pressure data of SF6 gas to obtain compensated pressure data includes: Construct the SF6 gas temperature-pressure correction function; The ambient temperature data and the measured pressure data are input into the SF6 gas temperature-pressure correction function to obtain the compensated pressure data; The construction of the SF6 gas temperature-pressure correction function includes: Calculate the combined correction value of the ambient temperature data and the measured pressure data for the measured pressure data under multiple time point factors; The measured pressure data is corrected using the comprehensive correction value, and the average corrected pressure data is obtained by integral calculation within a preset time window. Based on the influence of the periodic changes in the ambient temperature data on the measured pressure data and the degree of difference between the measured pressure data and the pressure standard value, a temperature compensation factor is calculated. Multiplying the average corrected pressure data by the temperature compensation factor yields the SF6 gas temperature-pressure correction function; The comprehensive correction value for the measured pressure data based on the ambient temperature data and the measured pressure data under multiple time point factors includes: Construct an exponential function for multiple time point factors, and use the exponential function to adjust the factor weight coefficients of the corresponding time point factors to obtain the first data item; The measured pressure data is normalized based on the error function to obtain the second data item; The environmental temperature data is mapped using the Sigmoid function to obtain the third data item. Multiply the first data item, the second data item, and the third data item together, and sum them according to multiple time point factors to obtain the fourth data item; Summing the first data items corresponding to multiple time point factors yields the fifth data item; Calculate the ratio of the fourth data item to the fifth data item to obtain the comprehensive correction value; The step of correcting the measured pressure data using the comprehensive correction value and performing integration calculation within a preset time window to obtain the average corrected pressure data includes: The measured pressure data is added to the comprehensive correction value, and the integral is calculated within a preset time window to obtain the average corrected pressure data. The calculation of the temperature compensation factor based on the influence of the periodic changes in the ambient temperature data on the measured pressure data and the degree of difference between the measured pressure data and the pressure standard value includes: Within a preset temperature data range, the ambient temperature data is normalized to obtain the sixth data item; The influence of the periodic changes in the ambient temperature data on the measured pressure data is calculated to obtain the seventh data item; The difference between the measured pressure data and the pressure standard value is calculated to obtain the eighth data item; Multiply the sixth, seventh, and eighth data items together and integrate them within the preset temperature data range to obtain the ninth data item. Multiply the seventh and eighth data items and perform integration within the preset temperature data range to obtain the tenth data item; The ratio of the ninth data item to the tenth data item is calculated to obtain the temperature compensation factor.

5. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the SF6 gas pressure early warning method according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the SF6 gas pressure early warning method according to any one of claims 1 to 3.

7. A computer program product, characterized in that, It includes computer instructions for causing a computer to execute the SF6 gas pressure early warning method according to any one of claims 1 to 3.

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