SF6 gas pressure early warning method, device, equipment, storage medium and program product

Abstract

The invention relates to the technical field of leakage detection, and discloses an SF6 gas pressure early warning method, device and equipment, a storage medium and a program product.The SF6 gas pressure early warning method comprises the steps that for target electrical equipment, environment temperature data of the environment where the target electrical equipment is located is used for conducting environment compensation on measured pressure data of SF6 gas, and compensation pressure data is obtained; calculating a corrected pressure change rate based on the compensated pressure data at the plurality of moments; if the compensation pressure data at the current moment does not meet the pressure standard and / or the correction pressure change rate at the current moment does not meet the change rate standard, feature matching is carried out based on the data set at the current moment and the data set at the historical moment, and a target data set meeting the matching range is determined from the data set at the historical moment, taking the SF6 gas leakage condition at the historical moment corresponding to the target data set as the SF6 gas leakage condition at the current moment; and performing early warning based on the SF6 gas leakage condition at the current moment. According to the invention, the accuracy of SF6 gas early warning can be improved.

Description

Technical Field

[0001] The present invention relates to the field of leakage detection technology, and in particular to an SF6 gas pressure early warning method, device, equipment, storage medium and program product. Background Art

[0002] With the widespread use of power systems, substations, as core hubs for power transmission and distribution, have a direct impact on the overall stability of the power system. SF6 (sulfur hexafluoride) gas, a component of high-voltage equipment, is widely used in substation circuit breakers, disconnectors, and other equipment due to its excellent insulation and arc-extinguishing properties. However, fluctuations in SF6 gas pressure directly affect the operating state of the equipment. In particular, SF6 leakage can degrade the insulation performance of equipment and, in severe cases, cause electrical accidents.

[0003] Currently, SF6 gas pressure monitoring primarily relies on online sensor monitoring systems, density relays, manual pressure gauges, and gas analyzers. However, these methods have limitations and cannot meet the requirements of modern electrical equipment for accurate, real-time, and reliable SF6 gas pressure monitoring. Summary of the Invention

[0004] In view of this, the present invention provides an SF6 gas pressure early warning method, device, equipment, 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, using the ambient temperature data of the environment in which it is located to perform environmental compensation on the measured pressure data of SF6 gas to obtain compensated pressure data; calculating the corrected pressure change rate based on the compensated pressure data at multiple moments; constructing a data set based on the operating status data, ambient temperature data, compensated pressure data and corrected pressure change rate of the target electrical device; 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, performing feature matching between the data set at the current moment and the data set at the historical moment, determining a target data set that meets the matching range from the data set at the historical moment, and using the SF6 gas leakage status at the historical moment corresponding to the target data set as the SF6 gas leakage status at the current moment; and issuing an early warning based on the SF6 gas leakage status at the current moment.

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

[0007] In an optional embodiment, environmental compensation is performed on the measured pressure data of the SF6 gas using the ambient temperature data of the environment to obtain compensated pressure data, including: constructing an SF6 gas temperature-pressure correction function; 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, and the measurement accuracy is greatly improved.

[0009] In an optional embodiment, constructing an SF6 gas temperature-pressure correction function includes: calculating a comprehensive correction value of ambient temperature data and measured pressure data on measured pressure data under multiple time point factors; correcting the measured pressure data using the comprehensive correction value, and performing an integral calculation within a preset time window to obtain average corrected pressure data; calculating a temperature compensation factor based on the impact of periodic changes in ambient temperature data on the measured pressure data and the difference between the measured pressure data and a 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 an optional embodiment, calculating the comprehensive correction value of the ambient temperature data and the measured pressure data for the measured pressure data under multiple time point factors includes: constructing an exponential function of the multiple time point factors, and using the exponential function to adjust the factor weight coefficient of the corresponding time point factor to obtain a first data item; normalizing the measured pressure data based on the error function to obtain a second data item; performing data mapping on the ambient temperature data based on the Sigmoid function to obtain a third data item; multiplying the first data item, the second data item, and the third data item, and summing them according to the multiple time point factors to obtain a fourth data item; summing the first data items corresponding to the multiple time point factors to obtain a fifth data item; calculating the ratio of the fourth data item to the fifth data item to obtain a comprehensive correction value; correcting the measured pressure data using the comprehensive correction value, and performing an integral 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 an integral calculation is performed within a preset time window to obtain average corrected pressure data; based on the influence of the periodic change of the ambient temperature data on the measured pressure data and the difference between the measured pressure data and the pressure standard value, a temperature compensation factor is calculated, including: normalizing the ambient temperature data within the preset temperature data range to obtain a sixth data item; calculating the influence of the periodic change of the ambient temperature data on the measured pressure data to obtain a seventh data item; calculating the difference between the measured pressure data and the pressure standard value to obtain an eighth data item; multiplying the sixth data item, the seventh data item and the eighth data item, and performing an integral calculation within the preset temperature data range to obtain a ninth data item; multiplying the seventh data item and the eighth data item, and performing an integral calculation within the preset temperature data range to obtain a tenth data item; calculating the ratio of the ninth data item to the tenth data item to obtain the temperature compensation factor.

[0011] This implementation fully considers the inherent relationship between SF6 gas pressure and temperature, compensating for temperature variations by establishing a precise mathematical model. By thoroughly studying the physical properties of SF6 gas and analyzing how gas pressure varies under different temperature conditions, a temperature-pressure correction function was constructed based on extensive experimental data and theoretical analysis. This function dynamically corrects SF6 gas pressure measurements based on the real-time monitored ambient temperature, effectively eliminating measurement errors caused by ambient temperature fluctuations and preventing false alarms.

[0012] In an optional embodiment, the SF6 gas pressure warning method includes: obtaining 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, the compensated pressure data at the current moment does not meet the pressure standard; obtaining a first change rate threshold; if the corrected pressure change rate at the current moment is greater than the first change rate threshold, the corrected pressure change rate at the current moment does not meet the change rate standard.

[0013] In an optional embodiment, feature matching is performed between a data set at a current moment and a data set at a historical moment, a target data set that meets a matching range is determined from the data set at the historical moment, and the SF6 gas leakage status at the historical moment corresponding to the target data set is used as the SF6 gas leakage status at the current moment, including: calculating a temperature matching range, a pressure matching range, and a change rate matching range based on the ambient temperature data, compensated pressure data, and corrected pressure change rate at the current moment, and corresponding temperature tolerance values, pressure tolerance values, and change rate tolerance values; performing feature matching in the data sets at the historical moments according to the temperature matching range, pressure matching range, and change rate matching range to obtain at least one set of target data sets; obtaining the SF6 gas leakage status at the historical moment corresponding to the target data set, and obtaining the SF6 gas leakage status at the historical moment with the largest number proportion as the SF6 gas leakage status at the current moment; and issuing an early warning based on the SF6 gas leakage status at the current moment, including: issuing an early warning when the SF6 gas leakage status at the current moment is a leakage fault.

[0014] In this implementation, when the detected rate of pressure change exceeds a threshold and the temperature-compensated pressure value deviates from the normal range, the system combines historical equipment operating data to determine whether a true pressure anomaly exists. If so, an alarm is promptly issued. This approach more accurately determines the true state of SF6 gas pressure, effectively avoiding false or missed alarms caused by relying solely on fixed thresholds.

[0015] In a second aspect, the present invention provides an SF6 gas pressure warning device, which includes: a first calculation module, which is used to perform environmental compensation on the measured pressure data of SF6 gas for the target electrical equipment using the ambient temperature data of the environment in which it is located to obtain compensated pressure data; a second calculation module, which is used to calculate the corrected pressure change rate based on the compensated pressure data at multiple moments; a construction module, which is used to construct a data set based on the operating status data, ambient temperature data, compensated pressure data and corrected pressure change rate of the target electrical equipment; an analysis module, which is used to perform feature matching based on the data set at the current moment and the data set at the historical moment 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, determine the target data set that meets the matching range from the data set at the historical moment, and use the SF6 gas leakage status at the historical moment corresponding to the target data set as the SF6 gas leakage status at the current moment; and an early warning module, which is used to issue an early warning based on the SF6 gas leakage status at the current moment.

[0016] In a third aspect, 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 thereby execute the SF6 gas pressure warning method of the first aspect or any corresponding embodiment thereof.

[0017] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the SF6 gas pressure warning method of the first aspect or any corresponding embodiment thereof.

[0018] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, which are used to enable a computer to execute the SF6 gas pressure early warning method of the above-mentioned first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 This is a flow chart of a SF6 gas pressure early warning method according to an embodiment of the present invention;

[0021] Figure 2 is a flow chart of another SF6 gas pressure early warning method according to an embodiment of the present invention;

[0022] Figure 3 is a structural block diagram of an SF6 gas pressure early warning device according to an embodiment of the present invention;

[0023] Figure 4 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0025] In the field of SF6 gas pressure detection, the main methods used are sensor online monitoring systems, density relays or manual pressure gauge monitoring technologies, and gas analyzer detection to monitor changes in SF6 gas pressure.

[0026] Among them, online sensor monitoring: Although this method can achieve a certain degree of real-time monitoring, the equipment cost is high, the installation process requires professional technicians to carry out complex wiring and debugging, and subsequent maintenance is also relatively cumbersome. More importantly, this method is extremely sensitive to changes in ambient temperature and humidity. The pressure of SF6 gas is closely related to temperature. Fluctuations in ambient temperature will cause corresponding changes in SF6 gas pressure, thereby affecting measurement accuracy. For example, in an outdoor substation environment with large temperature fluctuations, the measurement error can reach 5%-10% for every 10°C temperature fluctuation. This greatly reduces the reliability of the measurement results and easily leads to false alarms.

[0027] Density relays: Due to their measurement principle, they are significantly affected by ambient temperature. Under extreme temperature conditions, such as extreme heat or freezing temperatures, the internal structural characteristics of the density relay can change, significantly increasing measurement errors. Furthermore, density relays only monitor the density of SF6 gas and cannot accurately and promptly reflect pressure fluctuations caused by gas leaks. When a slow leak occurs in SF6 equipment, the density relay cannot react quickly due to the relatively slow change in density. This can lead to problems not being addressed promptly and potentially escalating, potentially causing electrical equipment failures or even accidents.

[0028] Manual pressure gauge measurement: This method relies entirely on manual operation and cannot continuously monitor SF6 gas pressure in real time. Operators must regularly visit the site to read the pressure gauge readings, which can hinder the timely detection of dynamic pressure changes and sudden faults. Furthermore, test results rely heavily on the operator's skills and commitment. If operators fail to read accurately or fail to conduct tests on time, potential problems may go unnoticed, posing a risk to the safe operation of electrical equipment.

[0029] Gas analyzer testing: This method is relatively complex and requires specialized personnel following specific procedures. The testing cycle is long, with sample collection and analysis results potentially taking several minutes or even longer, and it does not provide a real-time view of gas pressure. Furthermore, gas analyzers are expensive to maintain, requiring regular calibration and component replacement, which increases operating costs.

[0030] In summary, the existing SF6 gas pressure detection method has many deficiencies in terms of accuracy, timeliness, reliability and cost, and cannot meet the needs of modern electrical equipment for accurate, real-time and reliable detection of SF6 gas pressure. Therefore, this application proposes an SF6 gas pressure early warning method, designs an automated continuous detection system, and uses high-precision pressure sensors and temperature sensors to collect SF6 gas pressure and ambient temperature data in real time. The sensor transmits the collected data to the data processing unit in real time, and the data processing unit performs real-time analysis and processing according to the above-mentioned temperature compensation mechanism and pressure change judgment method. At the same time, the pressure data is dynamically monitored using a data analysis algorithm, which can not only reflect the dynamic changes of pressure in real time, but also capture sudden faults in a timely manner. For example, by performing real-time differential analysis on the pressure data, the pressure change rate can be accurately calculated. Once an abnormal pressure change is found, the system responds quickly to achieve all-round, real-time and dynamic monitoring of SF6 gas pressure.

[0031] 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 of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0032] In this embodiment, a SF6 gas pressure early warning method is provided. Figure 1 is a flow chart of a SF6 gas pressure warning method according to an embodiment of the present invention. It should be noted that if there are substantially the same results, this embodiment is not based on Figure 1 The process sequence shown is limited. Figure 1 As shown, the process includes the following steps:

[0033] Step S101 : For a target electrical device, environmental compensation is performed on the measured pressure data of SF6 gas using the ambient temperature data of the environment in which the target electrical device is located, to obtain compensated pressure data.

[0034] This application uses a pressure sensor to collect and measure pressure data, and a temperature sensor to collect ambient temperature data.

[0035] Specifically, pressure sensors are installed at key locations of SF6 electrical equipment to collect the measured pressure data P of SF6 gas at different times u in real time. measured (u), in MPa. Time u, measured in minutes, provides the pressure data foundation for subsequent data processing. The pressure sensor should be highly sensitive and stable, capable of accurately measuring minute pressure changes, with a measurement accuracy of ±0.01 MPa.

[0036] 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 have the characteristics of fast response speed and high precision, which can meet the needs of real-time and accurate measurement of SF6 gas pressure.

[0037] Specifically, a temperature sensor is installed near the pressure sensor to synchronously collect ambient temperature data T(u) at the corresponding time u, in degrees Celsius. This ambient temperature data reflects the impact of environmental factors on the SF6 gas pressure. The temperature sensor must have a wide temperature measurement range and high measurement accuracy.

[0038] In a specific implementation, the temperature sensor is a thermocouple temperature sensor. The measurement range of the thermocouple temperature sensor can reach -200℃-1300℃, and the accuracy can reach ±0.5℃. It can adapt to various complex ambient temperature conditions and provide accurate temperature data for subsequent temperature compensation.

[0039] The pressure sensor and the temperature sensor transmit the collected data to the SF6 gas pressure early warning device via wired or wireless means, and the data is processed by the data processing unit of the SF6 gas pressure early warning device.

[0040] Specifically, for sensors that are close to the data processing unit, shielded twisted pair cables can be used for wired transmission 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.

[0041] Furthermore, the ambient temperature data of the environment is used to perform ambient temperature compensation on the measured pressure data of the SF6 gas to obtain compensated pressure data.

[0042] In one implementation, a temperature-pressure correction function is pre-established to perform ambient temperature compensation on the measured pressure data. Assume that the temperature-pressure correction function is P corr =P measured +k×(T-T0). Among them, P corr is the compensated pressure data after temperature compensation, P measured is the pressure data measured by the pressure sensor, T is the ambient temperature data measured by the temperature sensor, T0 is the standard temperature, and k is the correction coefficient obtained by fitting the experimental data. measured Substitute T into the function and calculate P corr .

[0043] Step S102 : calculating a corrected pressure change rate based on the compensated pressure data at multiple moments.

[0044] Specifically, the data processing unit in the SF6 gas pressure early warning device records the compensated pressure data obtained by temperature compensation in real time, performs differential calculation on multiple consecutive compensated pressure data, and obtains the corrected pressure change rate: ΔP / Δt.

[0045] Step S103 : constructing a data set based on the operating status data, ambient temperature data, compensated pressure data, and corrected pressure change rate of the target electrical device.

[0046] The data sets include the current time data set and the historical time data set. Each data set corresponds to the operating status data, ambient temperature data, compensated pressure data and corrected pressure change rate at a certain time.

[0047] In step S104, 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, and a target data set that meets the matching range is determined from the data set at the historical moment, and the SF6 gas leakage status at the historical moment corresponding to the target data set is used as the SF6 gas leakage status at the current moment.

[0048] The pressure standard and the rate of change standard are set in advance based on the historical operating data and safety standards of the target electrical equipment.

[0049] In one implementation, the SF6 gas leakage status of the target electrical equipment at historical moments and the corresponding pressure data and pressure change rate data are obtained. The pressure standard and pressure change rate standard for the target electrical equipment are determined based on the pressure data and pressure change rate data when the SF6 gas leakage fault occurs and when the SF6 gas leakage fault does not occur, and the established safety standards.

[0050] It is understandable that when there is a SF6 gas leakage fault, the corresponding pressure data does not meet the pressure standard, or the pressure change rate data does not meet the change rate standard. When there is no SF6 gas leakage fault, the corresponding pressure data and pressure change rate data meet the pressure standard and change rate standard.

[0051] It is understandable that for different target electrical devices, under different temperature environments, the pressure standard and the pressure change rate standard are different. In one implementation, the pressure standard and the pressure change rate standard are determined separately for different ambient temperature data ranges.

[0052] If the current compensated pressure data does not meet the pressure standard and / or the current corrected pressure change rate does not meet the change rate standard, the target electrical equipment may have an SF6 gas leakage failure risk, and further analysis of the data of the target electrical equipment at the current moment is required.

[0053] For example, under normal circumstances, the pressure standard range is [P min ,P max ], when P corr <P min or P corr >P max , and ΔP / Δt exceeds the set change rate standard, the data processing unit determines that there may be a pressure abnormality.

[0054] Furthermore, when a possible abnormal pressure situation is detected, the data processing unit compares and analyzes the data set at the current moment with the data set at the historical moment to eliminate misjudgments caused by instantaneous interference or other non-fault factors.

[0055] In one implementation, if the data set at a historical moment shows that a similar short-term pressure change has occurred under certain specific conditions but is not a fault condition, 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.

[0056] In one implementation, feature matching is performed on the data in the data set at the current moment and the data in the data set at the historical moment. The higher the feature matching degree, the closer the data in the data set at the current moment and the data in the data set at the historical moment are, and the more similar the SF6 gas states of the electrical equipment at the current moment and the electrical equipment at the historical moment are.

[0057] At least one data set at a historical moment with a high matching degree is screened out as a target data set, and the SF6 gas leakage status at the historical moment corresponding to the target data set is used as the SF6 gas leakage status at the current moment.

[0058] The SF6 gas leakage status at a historical moment includes whether an early warning has occurred and whether an actual SF6 gas leakage fault has occurred. If an early warning and a gas leakage fault occurred at the target moment corresponding to the target dataset, it indicates that the SF6 gas leakage is abnormal at the current moment. If no early warning and no gas leakage fault occurred at the target moment corresponding to the target dataset, it indicates that the SF6 gas is normal at the current moment.

[0059] Step S105: issuing an early warning based on the current SF6 gas leakage status.

[0060] When it is determined that the SF6 gas pressure at the current moment is abnormal, the early warning module is triggered to issue an early warning.

[0061] Among them, the early warning method can use various methods such as sound and light alarm, SMS alarm, remote signal transmission, etc. to warn relevant personnel.

[0062] In one feasible method, an audible and visual alarm is set at the electrical equipment site to emit bright flashes and loud alarm sounds to attract the attention of on-site personnel; at the same time, a text message containing detailed information about the abnormal situation, such as pressure value, temperature value, pressure change rate, etc., is sent to the equipment maintenance personnel through the SMS platform so that the maintenance personnel can take timely measures; in addition, the alarm signal can also be remotely transmitted to the monitoring center, and an alarm prompt window will pop up on the monitoring system interface, displaying the location of the abnormal equipment, the type of abnormality and other information, which is convenient for monitoring personnel to carry out unified scheduling and management.

[0063] The SF6 gas pressure early warning method provided in this embodiment improves the accuracy of pressure detection by compensating SF6 gas pressure data with temperature data, thereby avoiding misjudgments of leaks due to measurement errors. Furthermore, by comprehensively considering the temperature, pressure change rate, and the degree of match between the temperature-compensated pressure value and historical data, combined with historical equipment operation data, the method can determine whether a true pressure anomaly exists. This improves the accuracy, reliability, and timeliness of SF6 gas pressure detection, ensuring the safe and stable operation of electrical equipment.

[0064] In this embodiment, a SF6 gas pressure early warning method is provided. Figure 2 is a flow chart of another SF6 gas pressure warning method according to an embodiment of the present invention. It should be noted that if there are substantially the same results, this embodiment is not based on Figure 2 The process sequence shown is limited. Figure 2 As shown, the process includes the following steps:

[0065] Step S201 : For a target electrical device, environmental compensation is performed on the measured pressure data of SF6 gas using the ambient temperature data of the environment in which the target electrical device is located, to obtain compensated pressure data.

[0066] Specifically, the above step S201 includes:

[0067] Step S2011: constructing an SF6 gas temperature-pressure correction function.

[0068] In one implementation, a comprehensive correction value for the measured pressure data based on ambient temperature data and measured pressure data at multiple time points is calculated. The measured pressure data is corrected using this comprehensive correction value and integrated over a preset time window to obtain average corrected pressure data. A temperature compensation factor is calculated based on the impact of periodic changes in ambient temperature data on the measured pressure data and the difference between the measured pressure data and the standard pressure value. The average corrected pressure data is multiplied by the temperature compensation factor to obtain the SF6 gas temperature-pressure correction function.

[0069] Specifically, the expression formula of the SF6 gas temperature-pressure correction function is:

[0070]

[0071] Among them, the left side of the formula P final It is the final SF6 gas pressure value after temperature compensation and comprehensive processing, which is used to accurately determine the actual pressure state of SF6 gas.

[0072] Among them, the first term on the right side of the formula It is the mean corrected pressure data.

[0073] The average corrected pressure data is calculated based on complex summation. In the time window [t-Δt, t], multiple time-related temperature factors and pressure factors are summed. Each factor is represented by a weight coefficient ω i , exponential function Error function And the Sigmoid function The exponential function adjusts the weights of various factors based on time correlation, the error function normalizes and extracts features from the pressure values, and the sigmoid function maps the temperature values to an appropriate range to reflect the nonlinear relationship between temperature and pressure. This complex combination comprehensively considers the impact of multiple factors on the pressure measurement and generates a comprehensive correction value. The pressure measurement, after undergoing complex summation and correction, is then integrated within the time window [t-Δt, t] and divided by the time window length Δt to obtain an averaged corrected pressure value. This smoothes pressure data fluctuations and reflects the overall pressure trend within the time period.

[0074] Specifically, the process of constructing the mean corrected pressure data includes:

[0075] 1. Weight adjustment based on time correlation: Construct an exponential function of multiple time point factors, and use the exponential function to adjust the factor weight coefficient of the corresponding time point factor to obtain the first data item

[0076] Specifically, within the time window [t-Δt, t], a complex summation function is introduced to comprehensively consider the impact of multiple related factors (i.e., factors at multiple time points) on the pressure value. Here, t is the current moment, measured in minutes, used to determine the time base for data processing. Δt is the length of the time window set for pressure data processing, set to 10 minutes based on actual testing requirements, limiting the time range of pressure data involved in the calculation. u is the integral variable, measured in minutes, used to traverse each moment within the time window [t-Δt, t].

[0077] For each relevant factor, the exponential function To adjust its weight, t iis the i-th relevant time point in the second data item, in minutes, used to determine the time correlation of the influence of various factors on the pressure value. Its value is determined according to historical data and equipment operating characteristics; i To control the parameters of the exponential function shape, it determines the weight distribution of the influence of each time point on the pressure value. i The value range is, for example, 1 to 5. Based on this, the factor weight corresponding to the time point closer to the current time t is higher, highlighting the importance of recent data in judging the current stress state.

[0078] 2. Pressure feature extraction and normalization: Normalize the measured pressure data based on the error function to obtain the second data item

[0079] Among them, P measured (u) is the SF6 gas pressure value measured by the pressure sensor at time u, that is, the measured pressure data, in MPa, with a measurement accuracy of up to ±0.01 MPa.

[0080] Specifically, the error function of the second data item is combined Normalize and extract features of pressure measurement values. P is the mean of historical pressure data, σ P is the standard deviation of the historical pressure data. In one possible implementation, μ P Assuming 0.6MPa, σ P The error function can map the pressure measurement value to a specific range and extract the key features in the pressure data, which is convenient for subsequent comprehensive analysis with other factors.

[0081] Among them, for the error function:

[0082] The error function is a special function that maps the input value to the (-1,1) interval through the integral form. In the present invention, the pressure measurement value P measured (u) minus the mean μ p and divided by As the input of the error function, it is used to normalize the pressure measurements to a specific range, highlighting the deviation characteristics of the pressure data from the mean.

[0083] SF6 gas pressure measurements fluctuate, with inconsistent magnitudes and distributions across different values, making direct comprehensive analysis difficult. The error function normalizes pressure measurements to a comparable range, facilitating consideration of other factors. This solves the problem of extracting and standardizing pressure data features, enabling subsequent calculations to more accurately reflect pressure fluctuations.

[0084] 3. Nonlinear mapping of temperature influence: Based on the Sigmoid function, the ambient temperature data is mapped to obtain the third data item

[0085] Where T(u) is the ambient temperature value measured by the temperature sensor at time u, in °C, with a measurement accuracy of ±0.5 °C.

[0086] Specifically, the third data item uses the Sigmoid function Temperature values are mapped to the (0,1) interval to highlight the nonlinear nature of temperature's impact on pressure. θ1 is the temperature threshold, and θ2 is the temperature scaling factor. In one possible implementation, θ1 is set to 25°C and θ2 is set to 10°C. The impact of different temperature ranges on pressure is not linear, and the Sigmoid function effectively captures this nonlinearity, allowing the temperature factor to be more accurately reflected in pressure calculations.

[0087] 4. Calculation of comprehensive correction value: Multiply the first data item, the second data item and the third data item, and sum them according to multiple time point factors to obtain the fourth data item Sum the first data items corresponding to multiple time point factors to obtain the fifth data item

[0088] Specifically, each relevant factor is also multiplied by the weight coefficient ω i , with a value ranging from 0.1 to 1, is obtained through a machine learning algorithm trained on historical data and is used to adjust the importance of each factor on the pressure value. These factors are combined and summed for i from 1 to n to obtain a comprehensive correction value, which comprehensively reflects the impact of multiple factors on the pressure measurement within the time window. In one possible implementation, n is set to 15, which comprehensively considers the impact of multiple relevant factors on the pressure value.

[0089] Among them, for the Sigmoid function:

[0090] The Sigmoid function maps real numbers to the interval (0, 1), and its shape exhibits nonlinear changes. In this paper, the temperature value T(u) is used as the input of the Sigmoid function after being calculated with the threshold θ1 and the scaling factor θ2. Its nonlinear mapping properties are utilized to highlight the nonlinear relationship between temperature and pressure.

[0091] The effect of temperature on SF6 gas pressure is not a simple linear relationship, and traditional linear processing methods cannot accurately describe this complex relationship. The Sigmoid function can capture the nonlinear characteristics of temperature effects, making the temperature factor more realistic in pressure calculations and solving the problem of nonlinear modeling of the effect of temperature on pressure.

[0092] 5. Integral calculation: Calculate the ratio of the fourth data item and 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.

[0093] Specifically, the pressure measurement, after complex summation correction, is integrated within the time window [t-Δt, t]. This integration smoothes fluctuations in the pressure data and reflects the overall pressure trend within that time period. The integrated result is then divided by the time window length Δt to obtain an average corrected pressure value, which provides a relatively stable pressure data foundation for subsequent temperature compensation.

[0094] Among them, the second term on the right side of the formula is the temperature compensation factor.

[0095] Among them, for the temperature compensation factor, in the temperature range [T min ,T max ], the temperature-related function is integrated. First, Normalize the temperature and then compare as well as Multiply. Simulate the effect of periodic temperature changes on pressure, The temperature compensation is then further adjusted in conjunction with the pressure value. The integral result is divided by the integral of the same function to obtain a temperature-dependent correction factor, which is used to temperature compensate the average corrected pressure value obtained previously.

[0096] Specifically, the construction process of the temperature compensation factor includes:

[0097] 1. Temperature normalization: Normalize the ambient temperature data within the preset temperature data range to obtain the sixth data item

[0098] Among them, T min and T max are the lower limit and upper limit of temperature data processing respectively. In a possible implementation, according to the actual temperature measurement range, T min =-30℃, T max =60℃. For [T min ,T max ] is the average temperature within the range, which is calculated by taking the arithmetic mean of the temperature values within the range.

[0099] Specifically, in the temperature range [T min ,T max ], through The temperature is normalized, and the normalized temperature value can reflect the impact of temperature changes on pressure on a unified scale.

[0100] 2. Temperature periodic adjustment: Calculate the effect of periodic changes in ambient temperature data on measured pressure data to obtain the seventh data item

[0101] Among them, T cycle The temperature change period is set to 24 hours in a possible implementation, which is 1440 minutes in minutes. The function simulates the effect of periodic temperature changes on pressure.

[0102] 3. Pressure correlation adjustment: Calculate the difference between the measured pressure data and the pressure standard value to obtain the eighth data item

[0103] Among them, P threshold is the pressure threshold, P scale is the scaling factor. In one possible implementation, P threshold Set to 0.5MPa, P scale Set to 0.1MPa.

[0104] Specifically, ReLU(x)=max(0,x), and the eighth data item is used to highlight the degree of deviation between the pressure value and the pressure threshold, and only affects the result when the pressure value exceeds the threshold, thereby further adjusting the temperature compensation in combination with the pressure value.

[0105] Among them, for the ReLU function:

[0106] The ReLU function has a unilateral inhibition characteristic. When the input is greater than 0, the output is the input value, otherwise it is 0. In the present invention, the pressure measurement value is compared with the threshold value P. threshold The deviation is scaled by the factor P scale After processing, it is used as the input of the ReLU function, which uses 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.

[0107] When calculating temperature compensation, it's important to consider the effect of abnormal pressure on temperature compensation. The ReLU function effectively highlights the impact of abnormal pressure and prevents it from interfering with temperature compensation when pressure is normal. This solves the problem of making targeted adjustments to temperature compensation based on abnormal pressure.

[0108] 4. Integral calculation: Multiply the sixth data item, the seventh data item, and the eighth data item, and perform integral calculation within the preset temperature data range to obtain the ninth data item; multiply the seventh data item and the eighth data item, and perform integral calculation within the preset temperature data range to obtain the tenth data item.

[0109] Specifically, the normalized temperature value and as well as Multiply the above product results in the temperature range [T min ,T max ] to get the ninth data item. as well as Multiply the above product results in the temperature range [T min ,T max ] and integrate to obtain the tenth data item.

[0110] 5. Calculation of temperature compensation factor: Calculate the ratio of the ninth data item to the tenth data item to obtain the temperature compensation factor.

[0111] This correction factor comprehensively considers the temperature variation range, periodicity and correlation with the pressure value, and is used to perform temperature compensation on the average corrected pressure value obtained previously.

[0112] Furthermore, for the right side of the formula, the average corrected pressure value obtained by integration is multiplied by the temperature compensation factor to obtain the final P final , that is, the SF6 gas temperature-pressure correction function constructed in this application takes into account the SF6 gas pressure value after temperature compensation and the combined influence of multiple factors, which is used to accurately judge the actual pressure state of SF6 gas.

[0113] The SF6 gas temperature-pressure correction function of this application comprehensively considers the impact of various factors on SF6 gas pressure measurement, obtains real-time data of pressure and temperature through data acquisition, and processes these data using complex mathematical functions. In the time dimension, data is selected through the time window and integrated to smooth pressure fluctuations and reflect trends; in terms of influencing factors, the temperature, pressure characteristics and time correlation of each factor are comprehensively considered. Through different functions, pressure and temperature data are normalized, feature extracted, nonlinearly mapped and other operations are performed, and finally the pressure value P after temperature compensation and comprehensive processing is obtained. final .

[0114] Specifically, they conducted in-depth research on the physical properties of SF6 gas, analyzing how gas pressure changes under different temperature conditions. Based on extensive experimental data and theoretical analysis, they constructed a temperature-pressure correction function. This function dynamically corrects SF6 gas pressure measurements based on the real-time ambient temperature, effectively eliminating measurement errors caused by ambient temperature fluctuations and preventing false alarms. For example, by experimentally obtaining data on the deviation between the actual and measured SF6 gas pressures at different temperatures, they used mathematical methods such as regression analysis to fit a correction function. This improved measurement accuracy to within ±2% in environments with large temperature fluctuations.

[0115] Traditional SF6 gas pressure detection methods fail to fully account for the impact of ambient temperature changes and various complex factors on pressure measurement, resulting in large measurement errors and an inability to accurately determine gas pressure status. This formula addresses the measurement errors caused by temperature changes by comprehensively considering temperature compensation and the combined influence of multiple factors, improving detection accuracy and enabling more precise determination of SF6 gas pressure anomalies, ensuring the safe and stable operation of electrical equipment.

[0116] Step S2012: input the ambient temperature data and the measured pressure data into the SF6 gas temperature-pressure correction function to obtain compensated pressure data.

[0117] Step S202 : Calculating a corrected pressure change rate based on the compensated pressure data at multiple moments.

[0118] Specifically, the data processing unit in the SF6 gas pressure early warning device records the compensated pressure data obtained by temperature compensation in real time, performs differential calculation on multiple consecutive compensated pressure data, and obtains the corrected pressure change rate: ΔP / Δt.

[0119] Step S203 : constructing a data set based on the operating status data, ambient temperature data, compensated pressure data, and corrected pressure change rate of the target electrical device.

[0120] The data sets include the current time data set and the historical time data set. Each data set corresponds to the operating status data, ambient temperature data, compensated pressure data and corrected pressure change rate at a certain time.

[0121] In step S204, 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 rate standard, feature matching is performed based on the data set at the current moment and the data set at the historical moment, and a target data set that meets the matching range is determined from the data set at the historical moment, and the SF6 gas leakage status at the historical moment corresponding to the target data set is used as the SF6 gas leakage status at the current moment.

[0122] Specifically, the above step S204 includes:

[0123] Step S2041 , calculating whether the current compensated pressure data meets the pressure standard, and calculating whether the current corrected pressure change rate meets the change rate standard.

[0124] In one implementation, a first pressure threshold and a second pressure threshold are obtained; if the compensated pressure data at the current moment is less than the first pressure threshold or greater than the second pressure threshold, the compensated pressure data at the current moment does not meet the pressure standard; a first change rate threshold is obtained; if the corrected pressure change rate at the current moment is greater than the first change rate threshold, the corrected pressure change rate at the current moment does not meet the change rate standard.

[0125] If the current compensated pressure data does not meet the pressure standard and / or the current corrected pressure change rate does not meet the change rate standard, step S2042 is executed.

[0126] Step S2042 , based on the current ambient temperature data, compensated pressure data and corrected pressure change rate, and 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.

[0127] For each ambient temperature data, compensated pressure data and corrected pressure change rate, a tolerance value, ie, a detection error tolerance range, is determined respectively.

[0128] For the authorized abnormal situation to be detected at the current moment, the ambient temperature data, compensated pressure data, and the current operating status of the corrected pressure change rate device are extracted from the current data set. The matching range at the current moment is calculated according to the detection error tolerance range.

[0129] For example, the pressure tolerance is ±0.05 MPa, the temperature tolerance is ±5°C, and the rate of change tolerance is ±0.01 MPa / min. The detected ambient temperature data at the current moment is 30°C, the compensated pressure data is 0.55 MPa, and the corrected pressure change rate is 0.02 MPa / min. The calculated temperature matching range is 25°C-35°C, 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.

[0130] Step S2043 : performing feature matching in the data sets at historical moments according to the temperature matching range, the pressure matching range, and the change rate matching range to obtain at least one set of target data sets.

[0131] Specifically, the historical data stored by the data processing unit encompasses multiple dimensions, such as ambient temperature data, compensated pressure data, corrected pressure change rate, and information about whether an alarm has occurred. Historical data is categorized based on different equipment operating states, such as normal operation, load changes, and equipment startup or shutdown phases. For example, all relevant data from the equipment startup phase can be organized into one subset, while data from the normal operation phase can be organized into another. This categorization helps to more accurately identify historical scenarios similar to the current situation during subsequent comparative analysis.

[0132] Search the historical data for data records with pressure, temperature, and rate of change values within the temperature matching range, pressure matching range, and rate of change matching range to obtain at least one matching data set. Ensure that the device operating state corresponding to the selected historical data is the same or similar to the current device operating state.

[0133] For example, we searched for historical data with temperature values between 25°C and 35°C, pressure values between 0.50 MPa and 0.60 MPa, and rate of change values between 0.01 MPa / min and 0.03 MPa / min, ensuring that the equipment operating status corresponding to the data was normal. After screening, we obtained 10 data sets of historical moments that matched these characteristics.

[0134] Step S2044 , obtaining the SF6 gas leakage status at the historical moment corresponding to the target data set, and obtaining the SF6 gas leakage status at the historical moment with the largest number proportion as the SF6 gas leakage status at the current moment.

[0135] After selecting data sets from historical moments with similar key characteristics, a comprehensive analysis of this historical data is performed. The data sets are checked to see whether an alarm occurred at the moment corresponding to the data set, as well as the actual operation of the subsequent equipment, such as whether a fault occurred and the type of fault. The SF6 gas leakage status at that moment is used as the current SF6 gas leakage status.

[0136] In one implementation, the SF6 gas leakage status at the historical moment with the largest number ratio is obtained as the SF6 gas leakage status at the current moment.

[0137] Understandably, if the filtered historical data sets show that alarms have occurred under similar pressure, temperature, and pressure change rate conditions, and that the equipment has subsequently been confirmed to have a leak, then the current occurrence of a similar situation is more likely to be a true failure. Conversely, if the historical data shows no alarms and normal equipment operation under similar circumstances, the current pressure change is likely due to factors other than a fault.

[0138] For example, a detailed review of data records from 10 historical moments revealed that eight of these records triggered alarms, and subsequent testing confirmed an SF6 gas leak in the equipment. The other two records, despite 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 instances, indicating that the pressure change is accompanied by an alarm and may indicate a gas leak. Therefore, it is highly likely that the current pressure change is a true fault. In other words, an SF6 gas leak is currently occurring.

[0139] This application abandons the traditional method of using fixed thresholds as a judgment indicator and establishes a new pressure change judgment method that takes temperature compensation into account. Instead of relying solely on a single pressure value to determine whether to issue an alarm, this method comprehensively considers multiple factors, including the pressure change rate, the temperature-compensated pressure value, and historical equipment operating data. Specifically, different pressure change rate thresholds are set based on the 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 uses the equipment's historical operating data to determine whether it is a true pressure anomaly. If it is determined to be an anomaly, an alarm signal is promptly issued. 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 specific type of SF6 electrical equipment, the pressure change rate is typically 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 determines that an abnormality such as a gas leak may exist.

[0140] Step S205: issuing an early warning based on the current SF6 gas leakage status.

[0141] The data processing unit can further determine whether to trigger the alarm module based on this judgment result, and issue an early warning when the SF6 gas leakage condition is a leakage fault at the current moment to remind relevant personnel to deal with possible equipment failures in a timely manner.

[0142] This application can effectively improve the accuracy of judging whether the pressure change is a real fault, reduce the occurrence of misjudgment, and ensure the stable operation of SF6 electrical equipment.

[0143] In the actual SF6 electrical equipment monitoring scenario, we must first ensure that the high-precision pressure sensor and temperature sensor are working properly and collect the pressure value P in real time. measured(u) and temperature T(u). 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 every minute to ensure timely and continuous data, providing basic input for subsequent calculations.

[0144] This application establishes a temperature-pressure correction function based on the physical properties of SF6 gas and a large amount of experimental data to achieve accurate compensation for temperature changes, which is the key to improving measurement accuracy. The innovative pressure alarm method that comprehensively considers the pressure change rate, the pressure value after temperature compensation, and the historical data of equipment operation is the core of accurately judging pressure anomalies and reducing the false alarm rate. By using high-precision pressure sensors and temperature sensors, and through reasonable data acquisition, transmission and processing processes, real-time continuous monitoring and dynamic analysis of SF6 gas pressure can be achieved. This application can solve the technical problems existing in the existing SF6 gas pressure detection method, such as measurement errors and false alarms caused by temperature influence, and the inability to accurately judge pressure anomalies and realize continuous dynamic monitoring, thereby improving the accuracy, reliability and timeliness of SF6 gas pressure detection and ensuring the safe and stable operation of electrical equipment.

[0145] The method of the present application is applied to different operating scenarios, including normal operating scenarios, temperature fluctuation scenarios, and leakage scenarios.

[0146] 1. Normal operation scenario.

[0147] Formula application: When the equipment is operating normally, the real-time collected P measured (u) and T(u) are substituted into the formula for calculation. P , σ P ,θ1,θ2,P threshold 、P scale etc., are set based on the historical operating data and design standards of the equipment. For example, μ P and σ P The result is obtained by statistical analysis of the pressure data during long-term stable operation of the equipment; θ1 and θ2 are determined by combining the common temperature range of the equipment operating environment and experimental data on the effect of temperature on pressure. At this time, the complex summation function and integral function in the formula are calculated step by step to obtain P final .

[0148] Value range and threshold judgment: During normal operation, P final The value range of should fall within the normal pressure range preset by the equipment (for example [0.55MPa, 0.65MPa]). finalWithin this range, it indicates that the equipment is operating normally and the SF6 gas pressure is stable. This is because the formula fully considers temperature compensation and the impact of various factors on pressure. Under normal circumstances, the calculation result should be consistent with the stable operation state of the equipment.

[0149] 2. Temperature fluctuation scenario.

[0150] Formula application: When the ambient temperature fluctuates, the change in temperature value T(u) will directly affect many parts of the formula. For example, during high temperature periods in summer or low temperature periods in winter, T(u) may exceed the normal operating temperature range of the equipment. In this case, the temperature-related functions in the formula, such as As the temperature rises or falls, the output values of these functions change, which in turn affects P final The calculation results of .

[0151] Value range and threshold judgment: Due to temperature fluctuations, P final The value range of may vary. However, after the temperature compensation mechanism of the formula, as long as the temperature fluctuation is within the tolerance range of the equipment, P final Still should try to maintain in normal pressure range. final If the pressure exceeds the normal range, it may not be due to abnormal equipment pressure, but rather to excessive temperature changes leading to under- or over-compensation. In this case, the operation and maintenance personnel can further check the accuracy of the temperature sensor based on the calculation results and temperature changes, or adjust the temperature-related parameters in the formula (such as θ1, θ2, etc.) to ensure the accuracy of temperature compensation.

[0152] 3. There is a leakage scenario.

[0153] Formula application: When there is potential SF6 gas leakage in the equipment, the pressure value P measured (u) will gradually decrease. The complex summation function in the formula will take into account the time correlation of pressure changes (through t i and σ i and other parameters), and the effect of pressure changes on temperature compensation (via As the pressure decreases, the output of these functions will change accordingly, ultimately affecting P final Calculation.

[0154] Value range and threshold judgment: If P final Continuously decreasing and falling below the lower limit of the normal pressure range, combined with the prominent effect of the ReLU function on the deviation between pressure and threshold, indicates that there may be gas leakage. finalThe change in the value range of reflects the abnormal decrease in pressure. Based on this result, the operation and maintenance personnel can timely detect and repair the equipment to prevent the leakage from further expanding. At the same time, by analyzing the effects of various factors in the formula on P final The contribution of the change can roughly determine the severity of the leakage and the possible cause.

[0155] Furthermore, in actual operation, the operating status and environmental conditions of the equipment will change over time, requiring the model data to be updated and the parameters to be optimized.

[0156] Data update: Regularly update the relevant data in the formula, such as the mean μ of historical pressure data p and standard deviation σ p At regular intervals, such as one month, statistical analysis is performed on the newly collected pressure data and μ is recalculated. p and σ p , to adapt to the slow changes in equipment performance. At the same time, temperature-related parameters such as T min 、T max Etc., and should also be adjusted according to seasonal changes or changes in the equipment operating environment.

[0157] Parameter optimization: As the equipment runs longer and data accumulates, other parameters in the formula can be optimized. For example, by analyzing a large amount of operating data, the weight coefficient ω can be optimized using a machine learning algorithm. i Optimize it to make it more accurately reflect the influence of various factors on the pressure value. In addition, if it is found that the formula calculation result deviates from the actual equipment status, θ1, θ2, P threshold 、P scale The threshold parameters are fine-tuned to improve the adaptability and accuracy of the formula to the actual situation.

[0158] Through the application and analysis of the above formulas in different actual situations, operation and 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.

[0159] The SF6 gas pressure detection method and device considering temperature compensation proposed in the present invention have the following significant beneficial effects compared with the existing technology:

[0160] Improved Detection Accuracy: By establishing a precise temperature-pressure correction function to compensate for temperature variations, the influence of ambient temperature on SF6 gas pressure measurements is effectively eliminated, significantly improving measurement accuracy. Compared to traditional detection methods, which can experience errors of 5%-10% due to temperature fluctuations, this invention can control measurement accuracy to within ±2%, significantly improving the accuracy of detection results and providing reliable data support for the safe operation of electrical equipment. This means that the actual SF6 gas pressure state can be more accurately determined, avoiding misjudgments of equipment operating conditions due to measurement errors.

[0161] Reduced false alarm rates: This innovative pressure alarm method no longer relies solely on fixed thresholds. Instead, it comprehensively considers multiple factors, including the rate of pressure change, temperature-compensated pressure values, and historical equipment operating data. This approach more accurately identifies true pressure anomalies and effectively avoids false alarms caused by environmental fluctuations or other interference. According to actual testing, compared with traditional threshold-based alarm methods, the false alarm rate can be reduced by 70%-80%, reducing the unnecessary workload placed on operations and maintenance personnel by false alarms while also improving the credibility of the alarm system.

[0162] Early fault warning: The system can keenly detect pressure changes during the initial stages of SF6 gas leakage. When an initial leak occurs, through real-time monitoring and analysis of the pressure change rate and temperature-compensated pressure value, the system can quickly identify and issue an alarm. This allows operations and maintenance personnel to take timely measures, such as equipment maintenance and leak detection and repair, before the problem escalates. This effectively avoids electrical equipment failures caused by undetected gas leaks, ensures the safe and stable operation of electrical equipment, reduces the probability of equipment damage and power outages, and improves the reliability of the power system.

[0163] Real-time, continuous monitoring and dynamic feedback: Utilizing an automated continuous detection system, the 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 the equipment's operating status at all times, but also promptly detects unexpected failures. This real-time and dynamic nature allows maintenance personnel to proactively plan and implement maintenance based on pressure trends, shifting from reactive maintenance to proactive maintenance, improving efficiency and reducing costs. Furthermore, the real-time, continuous monitoring data provides a wealth of fundamental data for equipment status assessment and lifespan prediction, helping to further optimize maintenance strategies and extend equipment lifespan.

[0164] This embodiment also provides an SF6 gas pressure warning device for implementing the above-mentioned embodiments and preferred embodiments. Details already described will not be repeated here. As used below, the term "module" may refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented using software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0165] This embodiment provides an SF6 gas pressure warning device, such as Figure 3 Shown, including:

[0166] The first calculation module 301 is used to perform environmental compensation on the measured pressure data of SF6 gas for the target electrical equipment using the ambient temperature data of the environment in which the equipment is located, so as to obtain compensated pressure data.

[0167] The second calculation module 302 is configured to calculate a corrected pressure change rate based on the compensated pressure data at multiple moments.

[0168] The construction module 303 is used to construct a data set based on the operating status data, ambient temperature data, compensated pressure data and corrected pressure change rate of the target electrical device.

[0169] The analysis module 304 is configured to perform feature matching based on the dataset at the current moment and the dataset at the historical moment 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, determine a target dataset that meets the matching range from the dataset at the historical moment, and use the SF6 gas leakage status at the historical moment corresponding to the target dataset as the SF6 gas leakage status at the current moment.

[0170] The early warning module 305 is used to issue an early warning based on the current SF6 gas leakage status.

[0171] In some optional implementations, the first calculation module 301 includes:

[0172] Construct a submodule for constructing the SF6 gas temperature-pressure correction function.

[0173] The compensation submodule is used to input the ambient temperature data and the measured pressure data into the SF6 gas temperature-pressure correction function to obtain the compensated pressure data.

[0174] In some optional embodiments, the building block includes:

[0175] The first construction unit is used to calculate the comprehensive correction value of the ambient temperature data and the measured pressure data to the measured pressure data under multiple time point factors.

[0176] The second construction unit is used to correct the measured pressure data using the comprehensive correction value, and perform integral calculation within a preset time window to obtain average corrected pressure data.

[0177] The third construction unit is configured to calculate a temperature compensation factor based on the influence of the periodic change of the ambient temperature data on the measured pressure data and the difference between the measured pressure data and the pressure standard value.

[0178] Multiply the average corrected pressure data by the temperature compensation factor to obtain the SF6 gas temperature-pressure correction function.

[0179] In some optional embodiments, the first building block includes:

[0180] The first calculation subunit is used to construct an exponential function of multiple time point factors, and use the exponential function to adjust the factor weight coefficients of the factors corresponding to the time point factors to obtain a first data item.

[0181] The second calculation subunit is configured to perform normalization processing on the measured pressure data based on the error function to obtain a second data item.

[0182] The third calculation subunit is used to perform data mapping on the ambient temperature data based on the Sigmoid function to obtain a third data item.

[0183] The fourth calculation subunit is used to multiply the first data item, the second data item and the third data item, and sum them according to multiple time point factors to obtain a fourth data item.

[0184] The fifth calculation subunit is configured to sum the first data items corresponding to the multiple time point factors to obtain a fifth data item.

[0185] The sixth calculation subunit is used to calculate the ratio of the fourth data item to the fifth data item to obtain a comprehensive correction value.

[0186] In some optional embodiments, the second building block includes:

[0187] The seventh calculation subunit is used to add the measured pressure data and the comprehensive correction value, and perform integration calculation within a preset time window to obtain average corrected pressure data.

[0188] In some optional embodiments, the third building block includes:

[0189] The eighth calculation subunit is configured to perform normalization processing on the ambient temperature data within a preset temperature data range to obtain a sixth data item.

[0190] The ninth calculation subunit is configured to calculate the influence of the periodic change of the ambient temperature data on the measured pressure data to obtain a seventh data item.

[0191] The tenth calculation subunit is used to calculate the difference between the measured pressure data and the pressure standard value to obtain an eighth data item.

[0192] The eleventh calculation subunit is configured to multiply the sixth data item, the seventh data item, and the eighth data item, and perform integration calculation within a preset temperature data range to obtain a ninth data item.

[0193] The twelfth calculation subunit is configured to multiply the seventh data item and the eighth data item, and perform integration calculation within a preset temperature data range to obtain a tenth data item.

[0194] The thirteenth calculation subunit is used to calculate the ratio of the ninth data item and the tenth data item to obtain a temperature compensation factor.

[0195] In some optional implementations, the analysis module 304 includes:

[0196] The first analysis submodule includes: obtaining 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, the compensated pressure data at the current moment does not meet the pressure standard; obtaining a first change rate threshold; if the corrected pressure change rate at the current moment is greater than the first change rate threshold, the corrected pressure change rate at the current moment does not meet the change rate standard.

[0197] The second analysis submodule is used to calculate the temperature matching range, pressure matching range, and change rate matching range based on the current ambient temperature data, compensated pressure data, and corrected pressure change rate, and the corresponding temperature tolerance value, pressure tolerance value, and change rate tolerance value; perform feature matching in the data sets at historical moments according to the temperature matching range, pressure matching range, and change rate matching range to obtain at least one set of target data sets; obtain the SF6 gas leakage status at the historical moments corresponding to the target data sets, and obtain the SF6 gas leakage status at the historical moment with the largest number proportion as the SF6 gas leakage status at the current moment.

[0198] In some optional implementations, the early warning module 305 includes:

[0199] The early warning submodule is used to issue an early warning when the SF6 gas leakage condition is a leakage fault at the current moment.

[0200] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0201] The SF6 gas pressure warning device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0202] The embodiment of the present invention also provides a computer device having the above Figure 3 The SF6 gas pressure warning device shown.

[0203] See also Figure 4 , Figure 4 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 4 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of a GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 4 A processor 10 is taken as an example.

[0204] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0205] The memory 20 stores instructions that can be executed by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0206] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0207] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0208] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 4 The bus connection is taken as an example.

[0209] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touch pad, an indicator stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor). The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display, and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0210] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0211] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0212] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A SF6 gas pressure early warning method, characterized in that: The method comprises: For the target electrical equipment, the measured pressure data of SF6 gas is environmentally compensated using the ambient temperature data of the environment in which it is located to obtain compensated pressure data; Calculating a corrected pressure change rate based on the compensated pressure data at a plurality of moments; constructing a data set based on the operating status data of the target electrical device, the ambient temperature data, the compensated pressure data, and the corrected pressure change rate; 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 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 SF6 gas leakage status at the current moment.

2. The SF6 gas pressure early warning method according to claim 1, characterized in that: The method of performing environmental compensation on the measured pressure data of the SF6 gas using the ambient temperature data of the environment to obtain the compensated pressure data includes: Construct 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.

3. The SF6 gas pressure early warning method according to claim 2, characterized in that: The constructing of the SF6 gas temperature-pressure correction function includes: Calculating a comprehensive correction value of the ambient temperature data and the 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 an integral calculation within a preset time window to obtain average corrected pressure data; Calculating a temperature compensation factor based on the effect of the periodic change of the ambient temperature data on the measured pressure data and the difference between the measured pressure data and a pressure standard value; The average corrected pressure data is multiplied by the temperature compensation factor to obtain the SF6 gas temperature-pressure correction function.

4. The SF6 gas pressure early warning method according to claim 3, characterized in that: The calculation of the comprehensive correction value of the ambient temperature data and the measured pressure data to the measured pressure data under the multiple time point factors includes: Constructing an exponential function of multiple time point factors, and using the exponential function to adjust the factor weight coefficients of the factors corresponding to the time point factors to obtain a first data item; performing normalization processing on the measured pressure data based on an error function to obtain a second data item; Performing data mapping on the ambient temperature data based on a Sigmoid function to obtain a third data item; Multiplying the first data item, the second data item, and the third data item, and summing them according to multiple time point factors to obtain a fourth data item; Summing the first data items corresponding to the multiple time point factors to obtain a fifth data item; calculating a ratio of the fourth data item to the fifth data item to obtain the comprehensive correction value; The method of correcting the measured pressure data by using the comprehensive correction value and performing integral calculation within a preset time window to obtain average corrected pressure data includes: Adding the measured pressure data to the comprehensive correction value and performing an integration calculation within a preset time window to obtain average corrected pressure data; The calculating of the temperature compensation factor based on the influence of the periodic change of the ambient temperature data on the measured pressure data and the difference between the measured pressure data and the pressure standard value includes: Normalizing the ambient temperature data within a preset temperature data range to obtain a sixth data item; calculating the influence of the periodic change of the ambient temperature data on the measured pressure data to obtain a seventh data item; Calculating the difference between the measured pressure data and the pressure standard value to obtain an eighth data item; multiplying the sixth data item, the seventh data item, and the eighth data item, and performing integration calculation within the preset temperature data range to obtain a ninth data item; Multiplying the seventh data item and the eighth data item, and performing integration calculation within the preset temperature data range to obtain a tenth data item; The ratio of the ninth data item to the tenth data item is calculated to obtain the temperature compensation factor.

5. The SF6 gas pressure early warning method according to claim 1, characterized in that: The method comprises: Obtaining 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, the compensated pressure data at the current moment does not meet the pressure standard; Obtaining a first change rate threshold; If the corrected pressure change rate at the current moment is greater than the first change rate threshold, the corrected pressure change rate at the current moment does not meet the change rate standard.

6. The SF6 gas pressure early warning method according to any one of claims 1 to 5, characterized in that: The 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, including: Calculating a temperature matching range, a pressure matching range, and a change rate matching range based on the ambient temperature data, the compensated pressure data, and the corrected pressure change rate at the current moment, and the corresponding temperature tolerance value, pressure tolerance value, and change rate tolerance value; Perform feature matching in data sets at historical moments according to the temperature matching range, the pressure matching range, and the change rate matching range to obtain at least one set of target data sets; Obtaining the SF6 gas leakage status at the historical moment corresponding to the target data set, and obtaining the SF6 gas leakage status at the historical moment with the largest number proportion as the SF6 gas leakage status at the current moment; The issuing of an early warning based on the current SF6 gas leakage condition includes: When the SF6 gas leakage condition at the current moment is a leakage fault, an early warning is issued.

7. An SF6 gas pressure warning device, characterized in that: The device comprises: The first calculation module is used to perform environmental compensation on the measured pressure data of SF6 gas for the target electrical equipment using the ambient temperature data of the environment in which the equipment is located, thereby obtaining compensated pressure data; a second calculation module, configured to calculate a corrected pressure change rate based on the compensated pressure data at a plurality of moments; a construction module, configured to construct a data set based on the operating status data of the target electrical device, the ambient temperature data, the compensated pressure data, and the corrected pressure change rate; an analysis module configured to, 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, perform feature matching based on the dataset at the current moment and the dataset at the historical moment, determine a target dataset that meets the matching range from the dataset at the historical moment, and use the SF6 gas leakage status at the historical moment corresponding to the target dataset as the SF6 gas leakage status at the current moment; The early warning module is used to issue an early warning based on the SF6 gas leakage status at the current moment.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the SF6 gas pressure early warning method according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the SF6 gas pressure early warning method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises computer instructions, wherein the computer instructions are used to enable a computer to execute the SF6 gas pressure early warning method according to any one of claims 1 to 6.

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