SF6 gas anti-liquefaction prediction method, device, equipment and medium

Abstract

The invention relates to the technical field of new energy power station equipment maintenance, and discloses an SF6 gas anti-liquefaction prediction method and device, equipment and a medium, and the method comprises the steps: obtaining data corresponding to a plurality of factors affecting the SF6 gas liquefaction in target equipment; calculating liquefaction condition parameters of SF6 gas liquefaction caused by various factors according to the data corresponding to various factors; and combining the liquefaction condition parameters corresponding to various factors with the gas pressure data to obtain a probability coefficient of SF6 gas liquefaction. The SF6 gas liquefaction early warning system can carry out early warning on SF6 gas liquefaction, so that targeted measures can be taken in time, and safe and stable operation of new energy power station equipment is guaranteed.

Description

A method, apparatus, equipment and medium for predicting SF6 gas liquefaction. Technical Field

[0001] This invention relates to the field of new energy power plant equipment maintenance technology, specifically to a method, device, equipment, and medium for predicting SF6 gas liquefaction. Background Technology

[0002] In new energy power plants, SF6 gas possesses excellent insulation and arc-quenching properties, thus it is used as an arc-quenching and insulating medium in high-voltage switchgear. However, SF6 gas is quite sensitive to temperature changes and is prone to liquefaction in low-temperature environments, leading to a decline in insulation performance. Traditional temperature monitoring equipment can only monitor ambient temperature and cannot directly reflect changes in the state of SF6 gas itself, making it difficult to accurately predict the risk of liquefaction. Summary of the Invention

[0003] This invention provides a method, apparatus, equipment, and medium for predicting SF6 gas liquefaction, in order to solve the problem that traditional temperature monitoring equipment is difficult to accurately predict liquefaction risks.

[0004] In a first aspect, the present invention provides a method for predicting the liquefaction of SF6 gas, comprising: acquiring data corresponding to various factors affecting the liquefaction of SF6 gas in a target device; calculating liquefaction condition parameters for SF6 gas liquefaction caused by various factors based on the data corresponding to each factor; and combining the liquefaction condition parameters corresponding to each factor with the gas pressure data to obtain the probability coefficient of SF6 gas liquefaction.

[0005] This embodiment provides an SF6 gas liquefaction prediction method. By comprehensively considering various factors affecting SF6 gas liquefaction, and quantifying and analyzing the data of each factor, the liquefaction probability coefficient of SF6 gas can be accurately calculated, thereby improving the accuracy of early warning of liquefaction risks.

[0006] In one optional implementation, the factors affecting SF6 gas liquefaction include ambient temperature, and the corresponding data for ambient temperature include ambient temperature data. Based on the data corresponding to each factor, liquefaction condition parameters for SF6 gas liquefaction caused by each factor are calculated, including: obtaining the ambient temperature at the target time, and the average ambient temperature and standard deviation of the ambient temperature within the time period to which the target time belongs; calculating the standardized difference of the ambient temperature at the target time within a preset time period based on the ambient temperature at the target time, the average ambient temperature, and the standard deviation of the ambient temperature; and normalizing the standardized difference using a pre-established error function to obtain the liquefaction condition parameters for SF6 gas liquefaction caused by ambient temperature.

[0007] This embodiment provides an SF6 gas liquefaction prediction method. By using function calculation, the data corresponding to the environmental temperature factor of SF6 gas liquefaction is quantified into liquefaction condition parameters that can reflect the influence of environmental temperature factor on liquefaction probability, providing data support for subsequent calculation of the probability coefficient of SF6 gas liquefaction.

[0008] In one optional implementation, the factors affecting SF6 gas liquefaction include gas pressure factors, and the corresponding data for gas pressure factors include gas pressure data. Based on the data corresponding to each factor, liquefaction condition parameters leading to SF6 gas liquefaction are calculated, including: acquiring gas pressure data at the target time, as well as the long-term average value, fluctuation range, and basic standard deviation of gas pressure for the time period to which the target time belongs, and the operating characteristics of the target equipment; constructing the expected pressure value of SF6 gas based on the long-term average pressure value, fluctuation range, and the operating characteristics of the target equipment; adjusting the basic standard deviation using the long-term average value and the gas pressure value at the target time to obtain the pressure standard deviation at the target time; calculating the standardized deviation between the gas pressure value at the target time and the expected pressure value based on the expected pressure value, the pressure standard deviation, and the gas pressure value at the target time; and using a pre-established Gaussian function to calculate the standardized deviation and the pressure standard deviation to obtain the liquefaction condition parameters of SF6 gas liquefaction caused by gas pressure factors.

[0009] This embodiment provides a method for predicting the liquefaction of SF6 gas. By using function calculation, the data corresponding to the gas pressure factors of SF6 gas liquefaction are quantified into liquefaction condition parameters that can reflect the influence of gas pressure factors on the liquefaction probability, providing data support for subsequent calculation of the probability coefficient of SF6 gas liquefaction.

[0010] In one optional implementation, the factors affecting SF6 gas liquefaction include gas purity factors, and the data corresponding to the gas purity factors include gas purity data. Based on the data corresponding to each type of factor, the liquefaction condition parameters that cause SF6 gas liquefaction are calculated for each type of factor, including: obtaining the gas purity data at the target time; and determining the liquefaction condition parameters that cause SF6 gas liquefaction based on the range to which the gas purity data belongs.

[0011] This embodiment provides a method for predicting the liquefaction of SF6 gas. By calculating the data corresponding to the gas pressure factor of SF6 gas liquefaction through function calculation, it determines whether the gas purity is within the effective range. The judgment result is used as the liquefaction condition parameter of the gas purity factor on the liquefaction probability, providing data support for the subsequent calculation of the probability coefficient of SF6 gas liquefaction.

[0012] In one optional implementation, the factors affecting SF6 gas liquefaction include time factors. Based on the data corresponding to each factor, liquefaction condition parameters for SF6 gas liquefaction caused by each factor are calculated, including: determining the time period of the target time and the average time of the time period; and calculating the liquefaction condition parameters for SF6 gas liquefaction caused by time factors based on the dispersion of the target time relative to the average time.

[0013] This embodiment provides an SF6 gas liquefaction prediction method. The method uses a normalization function to calculate the average time and dispersion of the collected data, quantifies the time factor of SF6 gas liquefaction, and obtains the liquefaction condition parameters of SF6 gas liquefaction caused by the time factor, providing data support for the subsequent calculation of the probability coefficient of SF6 gas liquefaction.

[0014] In one optional implementation, the factors affecting SF6 gas liquefaction include low-temperature weather factors, and the data corresponding to low-temperature weather factors includes weather temperature data. Based on the data corresponding to each type of factor, liquefaction condition parameters for SF6 gas liquefaction caused by each type of factor are calculated, including: determining the weather temperature data at the target time; if the weather temperature data is less than the low-temperature threshold, calculating the liquefaction condition parameters for SF6 gas liquefaction caused by low-temperature weather factors based on the difference between the weather temperature data and the low-temperature threshold.

[0015] This embodiment provides a method for predicting SF6 gas liquefaction. By combining real-time weather temperature, the lower limit of the normal operating temperature of the equipment, and related adjustment parameters, the method quantifies the impact of low-temperature weather on the liquefaction probability and obtains the liquefaction condition parameters of SF6 gas caused by low-temperature weather factors, providing data support for subsequent calculation of the probability coefficient of SF6 gas liquefaction.

[0016] In one alternative implementation, various factors affecting SF6 gas liquefaction in the target equipment include ambient temperature, gas pressure, gas purity, time, and low-temperature weather.

[0017] By combining the liquefaction condition parameters corresponding to various factors and the data corresponding to each factor, the probability coefficient of SF6 gas liquefaction is obtained. This includes: determining the first parameter based on the liquefaction condition parameters corresponding to environmental temperature, gas pressure, gas purity, time, and low temperature weather at different times within a preset time period, as well as the gas pressure and critical pressure value of SF6 gas; determining the second parameter based on the liquefaction condition parameters corresponding to environmental temperature, gas pressure, gas purity, and time at different times within a preset time period; and determining the probability coefficient of SF6 gas liquefaction based on the quotient of the first and second parameters.

[0018] This embodiment provides a method for predicting the liquefaction of SF6 gas. Based on data such as ambient temperature, gas pressure, gas purity, time, and low-temperature weather, a liquefaction probability coefficient is calculated comprehensively. By considering and calculating multiple factors, a quantified SF6 gas liquefaction risk is achieved, enabling the prediction of liquefaction. Accurate prediction of gas liquefaction risks.

[0019] Secondly, the present invention provides an SF6 gas liquefaction prediction device, comprising: a data acquisition module for acquiring data corresponding to various factors affecting SF6 gas liquefaction in a target device; a data analysis module for calculating liquefaction condition parameters for each factor based on the data corresponding to each factor; and a probability calculation module for combining the liquefaction condition parameters corresponding to each factor with the data corresponding to each factor to obtain the probability coefficient of SF6 gas liquefaction.

[0020] Thirdly, the present invention provides an electronic device, comprising: 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 computer instructions to perform an SF6 gas liquefaction prediction method as described in the first aspect or any corresponding embodiment thereof.

[0021] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute an SF6 gas liquefaction prediction method according to the first aspect or any corresponding embodiment described above.

[0022] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute an SF6 gas anti-liquefaction prediction method according to the first aspect or any corresponding embodiment described above. Attached Figure Description

[0023] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0024] Figure 1 is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 is a schematic diagram of a first process of an SF6 gas liquefaction prediction method according to an embodiment of the present invention; Figure 3 is a schematic diagram of a second process of an SF6 gas liquefaction prediction method according to an embodiment of the present invention; Figure 4 is a schematic diagram of a third process of an SF6 gas liquefaction prediction method according to an embodiment of the present invention; Figure 5 is a schematic diagram of a fourth process of an SF6 gas liquefaction prediction method according to an embodiment of the present invention; Figure 6 is a schematic diagram of a fifth process of an SF6 gas liquefaction prediction method according to an embodiment of the present invention; Figure 7 is a schematic diagram of a sixth process of an SF6 gas liquefaction prediction method according to an embodiment of the present invention; Figure 8 is a schematic diagram of a seventh process of an SF6 gas liquefaction prediction method according to an embodiment of the present invention; Figure 9 is a structural block diagram of an SF6 gas liquefaction prediction device according to an embodiment of the present invention; Figure 10 is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0027] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0028] As an optional application scenario of this invention, as shown in FIG1, the terminal device 110 is equipped with application 101, and the user 130 can interact with application 101 through the terminal device 110 and / or the access device of the terminal device 110.

[0029] For example, application 101 can be any application that provides question-and-answer related services. For instance, application 101 can be a question-and-answer interactive application, such as a text-to-text application or an image-to-text application. In the application scenario shown in Figure 1, if application 101 is active, the terminal device 110 can display the interface 102 of application 101. Interface 102 can include various types of pages that application 101 can provide, such as interactive pages, settings pages, and query pages.

[0030] In some embodiments, terminal device 110 is communicatively connected to server 120 to provide services to application 101. Terminal device 110 may be a mobile terminal, fixed terminal, or portable terminal, including but not limited to mobile phones, desktop computers, laptop computers, multimedia tablets, e-book devices, gaming devices, or any combination thereof, including accessories and peripherals of these devices or any combination thereof. In some embodiments, terminal device 110 may also support any type of interface, and server 120 may be various types of computing systems or servers capable of providing computing power, including but not limited to mainframes, edge computing nodes, and computing devices in cloud environments.

[0031] It should be noted that Figure 1 is merely an example of an application scenario and does not limit the scope of protection of this invention.

[0032] The embodiments of the present invention will now be described with reference to the accompanying drawings. It should be understood that the pages shown in the drawings are merely examples, and various page designs are possible in practice. The various graphic elements on the page may have different arrangements and different visual representations; one or more elements may be omitted or replaced, and one or more other elements may also be present, without any limitation in the embodiments of the present invention. Furthermore, the embodiments described below primarily pertain to terminal device 110. It should be understood that the actions described relative to terminal device 110 can be performed by application 101 on terminal device 110, or can be performed by application 101 in conjunction with its server (e.g., server 120).

[0033] For example, embodiments of the present invention provide a method for predicting the liquefaction of SF6 gas, which calculates the liquefaction probability of SF6 gas to achieve the effect of accurately predicting the liquefaction risk.

[0034] According to an embodiment of the present invention, an embodiment of an SF6 gas anti-liquefaction prediction method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0035] This embodiment provides an SF6 gas liquefaction prediction method, which can be used in mobile terminals such as mobile phones and tablets. Figure 2 is a flowchart of an SF6 gas liquefaction prediction method according to an embodiment of the present invention. As shown in Figure 2, the process includes the following steps: Step S201, obtaining data corresponding to various factors affecting SF6 gas liquefaction in the target device.

[0036] In this step, the various factors affecting SF6 gas liquefaction are used to describe the external factors that may influence SF6 gas and cause it to liquefy. The data corresponding to each of the various factors affecting SF6 gas liquefaction in the target equipment refers to the data obtained by collecting data from each of the above factors.

[0037] As an example, various factors affecting SF6 gas liquefaction in target equipment include ambient temperature, gas pressure, gas purity, time, and low-temperature weather. The corresponding data for each of these factors include ambient temperature, gas pressure, gas purity, time, and low-temperature weather data.

[0038] Step S202: Calculate the liquefaction condition parameters for SF6 gas liquefaction based on the data corresponding to each factor.

[0039] The liquefaction condition parameters refer to the quantitative data on the impact of each type of data on the liquefaction probability, obtained by using the corresponding calculation methods for each data point based on the data of various factors related to SF6 gas liquefaction.

[0040] As an example, liquefaction condition parameters for ambient temperature can be obtained by calculating ambient temperature data using a normalization function; liquefaction condition parameters for gas pressure can be obtained by calculating gas pressure data using a Gaussian function; liquefaction condition parameters for gas purity can be obtained by calculating gas purity data using a rectangular function; liquefaction condition parameters for time can be obtained by calculating time-related data using a normalization function; and liquefaction condition parameters for low-temperature weather can be obtained by calculating low-temperature weather data using an exponential function.

[0041] Step S203: Combine the liquefaction condition parameters and gas pressure data corresponding to various factors to obtain the probability coefficient of SF6 gas liquefaction.

[0042] Gas pressure data includes the critical pressure value for SF6 gas liquefaction. The probability of liquefaction changes significantly as the gas pressure approaches this value. The SF6 gas liquefaction probability coefficient integrates liquefaction condition parameters from various factors, quantifying the probability of SF6 gas liquefaction and serving as a core indicator for assessing gas liquefaction risk. For example, the SF6 gas liquefaction probability coefficient can be 0.2, 0.4, 0.6, etc., without limitation.

[0043] This embodiment provides an SF6 gas liquefaction prediction method. By comprehensively considering various factors affecting SF6 gas liquefaction, and quantifying and analyzing the data of each factor, the liquefaction probability coefficient of SF6 gas can be accurately calculated, thereby improving the accuracy of early warning of liquefaction risks.

[0044] This embodiment provides a method for predicting SF6 gas liquefaction. Figure 3 is a flowchart of an SF6 gas liquefaction prediction method according to an embodiment of the present invention. As shown in Figure 3, the process includes the following steps: Step S301, obtaining data corresponding to various factors affecting SF6 gas liquefaction in the target equipment. For details, please refer to step S201 of the embodiment shown in Figure 2, which will not be repeated here.

[0045] Step S302: Calculate the liquefaction condition parameters for SF6 gas liquefaction based on the data corresponding to each factor.

[0046] Specifically, the factors for gas liquefaction include ambient temperature, and the data corresponding to the ambient temperature factor includes ambient temperature data. The above step S302 includes: step S3021, obtaining the ambient temperature at the target time, as well as the average ambient temperature and the standard deviation of the ambient temperature in the time period to which the target time belongs.

[0047] Ambient temperature is one of the key factors affecting the liquefaction of SF6 gas. The average and standard deviation of ambient temperature are calculated using ambient temperature. The average ambient temperature serves as a benchmark for assessing ambient temperature variation, while the standard deviation measures the dispersion of ambient temperature changes.

[0048] As an example, with Raw ambient temperature data are collected at minute intervals. To eliminate the influence of various noise interferences on the ambient temperature data and obtain data that more accurately reflects the actual temperature change trend, after obtaining the raw ambient temperature data, a moving average filtering method can be used to preprocess the raw ambient temperature data, and the average ambient temperature and standard deviation of the time period to which the target time belongs can be calculated based on the preprocessed ambient temperature data.

[0049] For example, the raw ambient temperature data is filtered using a moving average using the following formula:

[0050] The input is the raw ambient temperature data. , This represents the number of raw ambient temperature data collected within the time period to which the target time belongs. For example, where This indicates that the average value is calculated using data from the target time and three adjacent time points before and after it. Ambient temperature after filtering at all times This process effectively removes noise interference, resulting in a smoother and more accurate reflection of ambient temperature changes. .

[0051] For example, at a certain moment If the original temperature data fluctuates greatly, this filtering process can yield a value that is closer to the actual ambient temperature, providing reliable data for subsequent calculations.

[0052] Calculate using the following formula. Average ambient temperature after filtering within the time period :

[0053] in In order to be in The total number of data collections within the time period. A benchmark value used to assess changes in ambient temperature.

[0054] The standard deviation, which measures the dispersion of changes in ambient temperature, is calculated using the following formula. :

[0055] This step involves inputting the ambient temperature. and The output yields the standard deviation. .

[0056] This process eliminates various noise interferences that may affect ambient temperature data, resulting in data that more accurately reflects the actual temperature change trend.

[0057] Step S3022: Calculate the standardized difference of the ambient temperature at the target time within a preset time period based on the ambient temperature at the target time, the average ambient temperature, and the standard deviation of the ambient temperature.

[0058] Standardized differences construct a dimensionless intermediate variable related to time, which is used to normalize the time factor.

[0059] As an example, the following formula is used to calculate... Standardized difference between the filtered ambient temperature and the average ambient temperature at any given time. :

[0060] This process, as an intermediate step in deriving liquefaction condition parameters, reflects the degree of anomaly in the measured ambient temperature. For example, during seasons with significant temperature variations, The value will be relatively large. The fluctuations will also be more pronounced.

[0061] Step S3023: Normalize the standardized differences using a pre-established error function to obtain the liquefaction condition parameters for SF6 gas liquefaction caused by ambient temperature factors.

[0062] Normalization of the time factor ensures that the calculations fall on a uniform scale, making all data comparable. The liquefaction condition parameters for SF6 gas liquefaction, calculated using normalized ambient temperature data and standardized variance data, can quantify the impact of ambient temperature on SF6 gas liquefaction.

[0063] As an example, the liquefaction condition parameters for SF6 gas liquefaction caused by ambient temperature are calculated using the following normalization function formula:

[0064] For example, The fluctuations are more pronounced, which will lead to The change reflects the increased influence of ambient temperature on the probability of liquefaction.

[0065] Given the complex fluctuations in ambient temperature, this step processes the ambient temperature and time data using a normalization function. The error function compares these fluctuations with the average temperature, reflecting their impact on liquefaction probability in a standardized way. This avoids the problem that simple temperature numerical comparisons cannot accurately reflect the influence on liquefaction, thus precisely quantifying the impact of ambient temperature changes on liquefaction. The influence of gas liquefaction probability.

[0066] Step S303 involves combining the liquefaction condition parameters and gas pressure data corresponding to various factors to obtain the probability coefficient of SF6 gas liquefaction. For details, please refer to step S203 of the embodiment shown in Figure 2, which will not be repeated here.

[0067] This embodiment provides an SF6 gas liquefaction prediction method. By using function calculation, the data corresponding to the environmental temperature factor of SF6 gas liquefaction is quantified into liquefaction condition parameters that can reflect the influence of environmental temperature factor on liquefaction probability, providing data support for subsequent calculation of the probability coefficient of SF6 gas liquefaction.

[0068] This embodiment provides a method for predicting SF6 gas liquefaction. Figure 4 is a flowchart of an SF6 gas liquefaction prediction method according to an embodiment of the present invention. As shown in Figure 4, the process includes the following steps: Step S301, obtaining data corresponding to various factors affecting SF6 gas liquefaction in the target equipment. For details, please refer to step S201 of the embodiment shown in Figure 2, which will not be repeated here.

[0069] Step S402: Calculate the liquefaction condition parameters for SF6 gas liquefaction based on the data corresponding to each factor.

[0070] Specifically, the factors affecting SF6 gas liquefaction include gas pressure factors, and the data corresponding to the gas pressure factors include gas pressure data. The above step S402 includes: step S4021, obtaining gas pressure data at the target time, as well as the long-term average value, fluctuation range, basic standard deviation of gas pressure in the time period to which the target time belongs, and the operating characteristics of the target equipment.

[0071] Gas pressure is a crucial factor in SF6 gas liquefaction. Directly measured raw gas pressure data is used as the gas pressure data for the target time. The long-term average gas pressure is derived from historical measurement data. The fluctuation range refers to the range of fluctuation in the raw gas pressure data caused by equipment operating characteristics and environmental factors. The baseline pressure standard deviation is a fundamental parameter for measuring the dispersion of pressure changes and is used in calculating the adjusted pressure standard deviation. The operating characteristics of the target equipment include information such as the angular frequency and initial phase related to the equipment's operating cycle. The angular frequency reflects the impact of the equipment's periodicity on pressure, and the initial phase is used as a trigonometric function in the pressure expectation calculation. Together with the angular frequency, these factors adjust the pressure expectation to better reflect actual pressure changes.

[0072] As an example, the long-term average gas pressure can be 0.6 MPa, the fluctuation range can be 0.05 MPa, the standard deviation of the base pressure can be 0.01 MPa, and the angular frequency can be... ,in seconds, the initial phase can be .

[0073] Obtain the gas pressure data at the target time, as well as the long-term average value, fluctuation range, basic standard deviation of the gas pressure in the time period to which the target time belongs, and the operating characteristics of the target equipment, to provide a data foundation for subsequent formula calculations.

[0074] Step S4022: Construct the expected pressure value of SF6 gas based on the long-term pressure average value, fluctuation range value and the operating characteristics of the target equipment.

[0075] The pressure expectation value integrates multiple factors to reflect the concentrated trend of gas pressure in actual operation, and serves as a reference value for measuring pressure changes.

[0076] As an example, the expected stress value can be calculated using the following formula.

[0077] First, a median filtering algorithm is used to remove sudden outliers from the original SF6 gas pressure data:

[0078] here The input is the raw pressure data, where k represents the number of moments within the time period to which the target time belongs. For example, if... This indicates that the median is calculated using data from the current time and one time before and after it. SF6 gas pressure after filtering at all times When sudden outliers appear in the pressure data, median filtering can effectively remove these anomalies, resulting in an output that better represents the actual pressure situation. .

[0079] Based on the influence of operating characteristics and environmental factors on gas pressure, the expected pressure value is calculated using the long-term average value of gas pressure, pressure fluctuation amplitude, angular frequency, and initial phase through the following formula:

[0080] in This represents the long-term average pressure of SF6 gas. To account for pressure fluctuations caused by equipment operating characteristics and environmental factors, The angular frequency related to the equipment's operating cycle. This is the initial phase.

[0081] This process uses a median filtering algorithm to remove sudden outliers from the original pressure data, resulting in original pressure data with smaller errors. The calculated expected pressure value provides the data basis for subsequent formula calculations.

[0082] Step S4023: Adjust the baseline standard deviation using the long-term average value and the gas pressure value at the target time to obtain the pressure standard deviation at the target time.

[0083] Pressure standard deviation is used to reflect the degree of dispersion of gas pressure changes in actual operation.

[0084] As an example, the pressure standard deviation is calculated using the following method based on the long-term average gas pressure and filtered SF6 gas pressure data:

[0085] in, This represents the long-term average pressure of SF6 gas. for The SF6 gas pressure after filtering at any time. The baseline standard deviation of SF6 gas pressure. This is an adjustment factor related to the pressure deviation. For example, the basic standard deviation can be set to 0.01 MPa, and the adjustment factor related to the pressure deviation can be set to 2.

[0086] The pressure standard deviation calculated through this process at the target time can more comprehensively describe the pressure changes, and can be used to analyze the effect of gas pressure on the liquefaction probability, providing a data basis for subsequent steps.

[0087] Step S4024: Calculate the standardized deviation between the gas pressure value at the target time and the pressure expectation value based on the expected pressure value, the pressure standard deviation, and the gas pressure value at the target time.

[0088] Standardized bias is used to highlight the effect of the difference between pressure changes and expectations on the probability of liquefaction.

[0089] As an example, the standardized deviation can be calculated using the following formula:

[0090] in, Is Time after filtering The intermediate variable is the standardized deviation of gas pressure from the adjusted pressure expectation.

[0091] The standardized deviation measures the standardized deviation between the filtered SF6 gas pressure and the adjusted pressure expectation during data acquisition, providing data support for subsequent Gaussian function calculations of liquefaction condition parameters that cause SF6 gas liquefaction due to gas pressure.

[0092] Step S4025: Calculate the standardized deviation and pressure standard deviation using a pre-established Gaussian function to obtain the liquefaction condition parameters for SF6 gas liquefaction caused by gas pressure factors.

[0093] The liquefaction condition parameters for SF6 gas liquefaction caused by gas pressure factors quantitatively describe the influence of the distribution characteristics of gas pressure changes on the liquefaction probability.

[0094] As an example, the liquefaction condition parameters for SF6 gas liquefaction caused by gas pressure factors are calculated using the following Gaussian function:

[0095] The effect of gas pressure on liquefaction probability is not a simple linear relationship. The Gaussian function can characterize the distribution of the effect of pressure on liquefaction probability under different values, more accurately reflect the complex role of pressure in liquefaction probability, and solve the problem that simple numerical values ​​alone cannot fully describe the effect of pressure.

[0096] Step S403 combines the liquefaction condition parameters and gas pressure data corresponding to various factors to obtain the probability coefficient of SF6 gas liquefaction. For details, please refer to step S203 of the embodiment shown in Figure 2, which will not be repeated here.

[0097] This embodiment provides a method for predicting the liquefaction of SF6 gas. By using function calculation, the data corresponding to the gas pressure factors of SF6 gas liquefaction are quantified into liquefaction condition parameters that can reflect the influence of gas pressure factors on the liquefaction probability, providing data support for subsequent calculation of the probability coefficient of SF6 gas liquefaction.

[0098] This embodiment provides a method for predicting SF6 gas liquefaction. Figure 5 is a flowchart of an SF6 gas liquefaction prediction method according to an embodiment of the present invention. As shown in Figure 5, the process includes the following steps: Step S501, obtaining data corresponding to various factors affecting SF6 gas liquefaction in the target equipment. For details, please refer to step S201 of the embodiment shown in Figure 2, which will not be repeated here.

[0099] Step S502: Calculate the liquefaction condition parameters for SF6 gas liquefaction based on the data corresponding to each factor.

[0100] Specifically, the factors affecting SF6 gas liquefaction include gas purity factors, and the data corresponding to the gas purity factors include gas purity data. The above step S502 includes: step S5021, obtaining gas purity data at the target time.

[0101] Gas purity is a factor affecting the liquefaction probability of SF6 gas. Directly measured gas purity data is used as the gas purity data at the target time.

[0102] Step S5022: Determine the liquefaction condition parameters that cause SF6 gas liquefaction based on the range of gas purity data.

[0103] As an example, a rectangular function can be used to limit the effective range of gas purity:

[0104] in

[0105] In this method, This refers to the purity of SF6 gas detected at the data time. This refers to the basis of new energy power plants The actual requirements for gas purity are determined by The lower limit of gas purity, This refers to the basis of new energy power plants The actual requirements for gas purity are determined by Upper limit of gas purity, and Both are used together in the rectangular function to determine whether the gas purity is within the valid range.

[0106] Using a piecewise function form, when the gas purity When within the limit range, the value is taken as follows: This indicates that the purity data is validly used in the liquefaction probability calculation; otherwise, the value is [value missing]. Exclude invalid data.

[0107] For example, based on gas purity Is it in and Within a certain range, its contribution to the liquefaction probability calculation is determined. If the gas purity is below the lower limit, This means that the gas purity is abnormal at this moment, which has a significant impact on the probability of liquefaction, and timely measures need to be taken.

[0108] In this process, only those that meet the actual requirements are selected. Incorporating gas purity data into the liquefaction probability calculation avoids inaccurate calculations due to interference from abnormal gas purity data, thus improving the reliability of the calculation results.

[0109] Step S503 involves combining the liquefaction condition parameters and gas pressure data corresponding to various factors to obtain the probability coefficient of SF6 gas liquefaction. For details, please refer to step S203 of the embodiment shown in Figure 2, which will not be repeated here.

[0110] This embodiment provides a method for predicting the liquefaction of SF6 gas. By calculating the data corresponding to the gas pressure factor of SF6 gas liquefaction through function calculation, it determines whether the gas purity is within the effective range. The judgment result is used as the liquefaction condition parameter of the gas purity factor on the liquefaction probability, providing data support for the subsequent calculation of the probability coefficient of SF6 gas liquefaction.

[0111] This embodiment provides a method for predicting SF6 gas liquefaction. Figure 6 is a flowchart of an SF6 gas liquefaction prediction method according to an embodiment of the present invention. As shown in Figure 6, the process includes the following steps: Step S601, obtaining data corresponding to various factors affecting SF6 gas liquefaction in the target equipment. For details, please refer to step S201 of the embodiment shown in Figure 2, which will not be repeated here.

[0112] Step S602: Calculate the liquefaction condition parameters for SF6 gas liquefaction based on the data corresponding to each factor.

[0113] Specifically, factors affecting SF6 gas liquefaction include time factors. Step S602 above includes: step S6021, determining the time period of the target time and the average time of the time period.

[0114] Time is also a factor in SF6 gas liquefaction. The average time is calculated based on the start and end times of data acquisition.

[0115] As an example, the formula is used:

[0116] To calculate the average time, where The start time of data collection. This is the end time of data collection. for The average duration of a time period.

[0117] The average time calculated in this process is used in conjunction with the dispersion calculated in subsequent steps to determine the liquefaction condition parameters of SF6 gas liquefaction affected by the time factor.

[0118] Step S6022: Calculate the liquefaction condition parameters for SF6 gas liquefaction caused by the time factor based on the dispersion of the target time relative to the average time.

[0119] The dispersion of average time is a value that can be adjusted according to time, representing a measure of the dispersion of time.

[0120] As an example, the dispersion of the mean time can be calculated using the following formula. :

[0121] As an example, the liquefaction condition parameters for SF6 gas liquefaction due to the time factor are calculated using the following formula:

[0122] in, , A dimensionless intermediate variable related to time was constructed to normalize the time factor. Parameters for adjusting the degree of time normalization. For example, parameters for adjusting the degree of time normalization. The value can be 5.

[0123] Liquefaction condition parameters for SF6 gas liquefaction caused by time factor. When, a dimensionless intermediate variable related to time is used. As input, the time factor is normalized by utilizing the properties of the exponential function, so that the time factor has a uniform scale and weight in the entire liquefaction probability calculation.

[0124] Because the time factor needs to be considered in the liquefaction probability calculation in conjunction with other factors of the same magnitude and scale, the normalization function transforms the time factor into... The values ​​between these factors resolve the issue of inconsistent dimensions between time and other factors, which prevents direct comprehensive calculation and ensures the rationality and comparability of each factor in the calculation.

[0125] Step S603 combines the liquefaction condition parameters and gas pressure data corresponding to various factors to obtain the probability coefficient of SF6 gas liquefaction. For details, please refer to step S203 of the embodiment shown in Figure 2, which will not be repeated here.

[0126] This embodiment provides an SF6 gas liquefaction prediction method. The method uses a normalization function to calculate the average time and dispersion of the collected data, quantifies the time factor of SF6 gas liquefaction, and obtains the liquefaction condition parameters of SF6 gas liquefaction caused by the time factor, providing data support for the subsequent calculation of the probability coefficient of SF6 gas liquefaction.

[0127] This embodiment provides a method for predicting SF6 gas liquefaction. Figure 7 is a flowchart of an SF6 gas liquefaction prediction method according to an embodiment of the present invention. As shown in Figure 7, the process includes the following steps: Step S701, obtaining data corresponding to various factors affecting SF6 gas liquefaction in the target equipment. For details, please refer to step S201 of the embodiment shown in Figure 2, which will not be repeated here.

[0128] Step S702: Calculate the liquefaction condition parameters for SF6 gas liquefaction based on the data corresponding to each factor.

[0129] Specifically, the factors affecting SF6 gas liquefaction include low temperature weather factors, and the data corresponding to the low temperature weather factors include weather temperature data. The above step S702 includes: step S7021, determining the weather temperature data at the target time.

[0130] Weather temperature is a factor to consider when assessing the impact of low temperatures on The key factor affecting the probability of gas liquefaction is the use of real-time weather temperature data to reflect the current weather temperature conditions.

[0131] Step S7021: If the weather temperature data is less than the low temperature threshold, calculate the liquefaction condition parameters for SF6 gas liquefaction caused by low temperature weather factors based on the difference between the weather temperature data and the low temperature threshold.

[0132] The low temperature threshold is the lower limit of the ambient temperature for the normal operation of new energy power plant equipment. The low temperature threshold can be adjusted according to the characteristics of the equipment.

[0133] As an example, the liquefaction condition parameters for SF6 gas liquefaction caused by low-temperature weather factors can be calculated using the following formula:

[0134] in,

[0135] in, This indicates the lower limit of the ambient temperature for normal operation of new energy power plant equipment. These are temperature adjustment parameters related to the impact of low temperatures, used to adjust the sensitivity to the effects of low temperatures. This refers to the coefficient related to the impact of low-temperature weather. This is for real-time weather temperature data at the time of collection. For example, the lower limit of the ambient temperature for normal operation of new energy power plant equipment. It can be Temperature adjustment parameters related to the impact of low temperatures It can be The coefficient related to the impact of low temperature weather It can be 3.

[0136] Based on real-time weather temperature The lower limit of the ambient temperature for normal operation of the equipment The comparison results are expressed using different expressions. When At that time, it was considered that the impact of low temperature weather was relatively small, and the value was taken as [value missing]. ;when At that time, through the exponential function Combine with adjusting parameters and To quantify the impact of low-temperature weather on the probability of liquefaction.

[0137] The impact of low-temperature weather is related to the difference between the real-time weather temperature and the lower limit of the equipment's normal operating temperature. This function method, through piecewise and exponential functions, can reasonably quantify the impact of low-temperature weather on the probability of liquefaction based on actual temperature conditions, solving the problem that traditional methods cannot accurately assess the impact of low-temperature weather.

[0138] Step S703 involves combining the liquefaction condition parameters and gas pressure data corresponding to various factors to obtain the probability coefficient of SF6 gas liquefaction. For details, please refer to step S203 of the embodiment shown in Figure 2, which will not be repeated here.

[0139] This embodiment provides a method for predicting SF6 gas liquefaction. By combining real-time weather temperature, the lower limit of the normal operating temperature of the equipment, and related adjustment parameters, the method quantifies the impact of low-temperature weather on the liquefaction probability and obtains the liquefaction condition parameters of SF6 gas caused by low-temperature weather factors, providing data support for subsequent calculation of the probability coefficient of SF6 gas liquefaction.

[0140] This embodiment provides a method for predicting SF6 gas liquefaction. Figure 8 is a flowchart of an SF6 gas liquefaction prediction method according to an embodiment of the present invention. As shown in Figure 8, the process includes the following steps: Step S801, obtaining data corresponding to various factors affecting SF6 gas liquefaction in the target equipment. For details, please refer to step S201 of the embodiment shown in Figure 2, which will not be repeated here.

[0141] Step S802: Calculate the liquefaction condition parameters for SF6 gas liquefaction based on the data corresponding to each factor. For details, please refer to step S202 of the embodiment shown in Figure 2, which will not be repeated here.

[0142] Step S803: Combine the liquefaction condition parameters and gas pressure data corresponding to various factors to obtain the probability coefficient of SF6 gas liquefaction.

[0143] Various factors affecting SF6 gas liquefaction in target equipment include ambient temperature, gas pressure, gas purity, time, and low-temperature weather. By combining the liquefaction condition parameters corresponding to each factor and the data corresponding to each factor, the probability coefficient of SF6 gas liquefaction is obtained.

[0144] Specifically, step S803 includes: step S8031, determining the first parameter based on the liquefaction condition parameters corresponding to the ambient temperature, gas pressure, gas purity, time and low temperature weather factors at different times within a preset time period, as well as the gas pressure of SSF6 gas and the critical pressure value of SF6 gas.

[0145] The first parameter is used to synthesize the impact of all the factors calculated in the above steps on the liquefaction probability.

[0146] As an example, the first parameter can be calculated using the following formula. :

[0147] in, This is the function value reflecting the influence of ambient temperature on the liquefaction probability after processing with the error function. To reflect through Gaussian function The function value of the effect of gas pressure distribution on the liquefaction probability. To reflect through rectangular functions The functional value of the effect of gas purity on liquefaction probability. This is the function value reflecting the effect of time on the liquefaction probability after being processed by the normalization function. This is the critical pressure value for SF6 gas. After median filtering Gas pressure data, To consider the function value of the impact of low temperature weather on the probability of liquefaction, This is a coefficient related to SF6 gas pressure. Based on the independent variable... (This is) The sign of the pressure is determined by three possible values, clarifying the relative direction of the pressure and the critical pressure. For example, the critical pressure value of SF6 gas... It can be 0.55 MPa, a coefficient related to SF6 gas pressure. It can be 10.

[0148] When considering the impact of pressure on liquefaction probability, the relative magnitude of pressure and critical pressure affects the liquefaction probability differently. The sign function can clearly determine this relationship, providing directional guidance for subsequent calculations of the pressure's influence on liquefaction probability and resolving the problem of accurately distinguishing the impact of different pressure states relative to the critical pressure on the liquefaction probability. This process integrates the effects of all factors on the liquefaction probability, including ambient temperature, gas pressure, gas purity, time, and low-temperature weather, comprehensively reflecting the contribution of various factors to the liquefaction probability under their combined influence.

[0149] Step S8032: Determine the second parameter based on the liquefaction condition parameters corresponding to the ambient temperature, gas pressure, gas purity and time factors at different times within the preset time period.

[0150] The second parameter includes the influence of other fundamental factors besides the relationship between pressure and critical pressure and the impact of low-temperature weather. The denominator in the formula for calculating the liquefaction probability coefficient includes the influence of other basic factors besides the relationship between pressure and critical pressure and the impact of low temperature weather. It is used to divide the denominator by the numerator to obtain the liquefaction probability coefficient, so as to balance the influence of various factors and accurately quantify the liquefaction probability.

[0151] As an example, the second parameter can be calculated using the following formula. :

[0152] in, This is the function value reflecting the influence of ambient temperature on the liquefaction probability after processing with the error function. To reflect through Gaussian function The function value of the effect of gas pressure distribution on the liquefaction probability. To reflect through rectangular functions The functional value of the effect of gas purity on liquefaction probability. This is the function value reflecting the influence of time on the liquefaction probability after being processed by the normalization function.

[0153] Step S8033: Determine the probability coefficient of SF6 gas liquefaction based on the quotient of the first parameter and the second parameter.

[0154] The probability coefficient of SF6 gas liquefaction is used as a core indicator to assess the risk of gas liquefaction, in order to quantify... The possibility of gas liquefaction.

[0155] The probability coefficient for SF6 gas liquefaction is determined using the quotient of the first and second parameters using the following method:

[0156] Where L is the liquefaction probability coefficient, used for subsequent calculations based on... The value is used to assess the liquefaction risk of SF6 gas.

[0157] As an example, when This indicates that the probability of SF6 gas liquefaction is low. Looking at the various parts of the formula, regarding ambient temperature, the ambient temperature is relatively stable, and its fluctuations are controlled within a small range. The absolute value is small, therefore The value is also relatively small, indicating that changes in ambient temperature have little impact on the probability of liquefaction; regarding gas pressure, Close , making The value is small. It is also at a low level, meaning that changes in gas pressure have a limited impact on the probability of liquefaction; regarding gas purity, the gas purity... In and between, It participates in the calculation normally, but its contribution to the liquefaction probability is not significant; regarding time, after normalization, the time factor... The relatively stable values ​​indicate that the time factor did not significantly affect the liquefaction probability; regarding low-temperature weather, among the factors related to low-temperature weather, if ,but It has no additional effect on the liquefaction probability; if However, due to the combined effects of other factors, the overall improvement in the liquefaction probability is still not significant. This indicates that the liquefaction probability of SF6 gas is low.

[0158] when This indicates a certain risk of liquefaction. Looking at the various parts of the formula, regarding ambient temperature, there may have been relatively large fluctuations in the ambient temperature, leading to… The absolute value increases. The value increases accordingly, thus amplifying the impact on the liquefaction probability; regarding gas pressure, there may also be deviations from expectations, leading to... Increase As the value increases, the impact of gas pressure on the liquefaction probability becomes more significant; regarding gas purity, although it remains within the acceptable range, it may be approaching the boundary value, making its potential impact on the liquefaction probability a concern; in terms of time, the time factor may change over time due to equipment aging or changes in operating conditions. The value has changed, which has a certain effect on the probability of liquefaction; regarding low temperature weather, if , The probability of liquefaction increases exponentially, and in conjunction with other factors, rises to this risk range. This indicates a certain risk of SF6 gas liquefaction.

[0159] when At this time, it indicates a high risk of liquefaction. Looking at the various parts of the formula, regarding ambient temperature, there are significant fluctuations. A significant increase in the value has a major impact on the probability of liquefaction; regarding gas pressure, the gas pressure may deviate considerably from the normal range. The value has increased significantly, greatly increasing the possibility of liquefaction; regarding gas purity, the gas purity may be substandard. or , Although not directly involved in the current calculations, this reflects the potential threat that gas purity issues pose to equipment safety. Regarding time, the prolonged operation of the equipment may accumulate numerous factors affecting liquefaction, making... The value is relatively large; regarding low temperature weather, if the low temperature weather is in a low temperature state ( ), The value increases sharply through an exponential function, and in conjunction with other adverse factors, significantly increases the probability of liquefaction. Under these circumstances, it indicates a high risk of SF6 gas liquefaction.

[0160] This embodiment provides a method for predicting the liquefaction of SF6 gas. Based on data such as ambient temperature, gas pressure, gas purity, time, and low-temperature weather, a liquefaction probability coefficient is calculated comprehensively. By considering and calculating multiple factors, a quantified SF6 gas liquefaction risk is achieved, enabling the prediction of liquefaction. Accurate prediction of gas liquefaction risks.

[0161] This embodiment also provides an SF6 gas liquefaction prediction device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0162] This embodiment provides an SF6 gas liquefaction prediction device, as shown in Figure 9, including: a data acquisition module 901, used to acquire data corresponding to various factors affecting SF6 gas liquefaction in the target equipment.

[0163] The data analysis module 902 is used to calculate the liquefaction condition parameters that cause SF6 gas liquefaction based on the data corresponding to various factors.

[0164] The probability calculation module 903 is used to combine the liquefaction condition parameters corresponding to various factors and the data corresponding to each factor to obtain the probability coefficient of SF6 gas liquefaction.

[0165] The SF6 gas liquefaction prediction device provided in this embodiment of the invention can execute the SF6 gas anti-liquefaction prediction method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0166] Figure 10 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0167] Referring specifically to FIG10, a schematic diagram of a structure suitable for implementing an electronic device according to an embodiment of the present invention is shown below. The electronic device may include a processor (e.g., a central processing unit, a graphics processor, etc.) 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a memory 1008 into a random access memory (RAM) 1003. The RAM 1003 also stores various programs and data required for the operation of the electronic device. The processor 1001, ROM 1002, and RAM 1003 are interconnected via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0168] Typically, the following devices can be connected to the I / O interface 1005: input devices 1006 including, for example, a touchscreen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 1007 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; memory 1008 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication devices 1009 allow the electronic device to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 10 shows an electronic device with various devices, it should be understood that it is not required to implement or possess all the devices shown, and more or fewer devices may be implemented alternatively.

[0169] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 1009, or installed from a memory 1008, or installed from a ROM 1002. When the computer program is executed by the processor 1001, it performs the functions defined in the SF6 gas anti-liquefaction prediction method of an embodiment of the present invention.

[0170] The electronic device shown in Figure 10 is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0171] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, it implements the SF6 gas liquefaction prediction method shown in the above embodiments.

[0172] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0173] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for predicting SF6 gas liquefaction, characterized in that, The method includes: acquiring data corresponding to various factors affecting SF6 gas liquefaction in the target equipment; calculating liquefaction condition parameters for SF6 gas liquefaction based on the data corresponding to each factor; and combining the liquefaction condition parameters corresponding to each factor with the gas pressure data to obtain the probability coefficient of SF6 gas liquefaction.

2. The method according to claim 1, characterized in that, Factors affecting SF6 gas liquefaction include ambient temperature. The data corresponding to this ambient temperature factor includes ambient temperature data. The calculation of liquefaction condition parameters for SF6 gas liquefaction based on the data for each factor includes: obtaining the ambient temperature at a target time, as well as the average ambient temperature and standard deviation of the time period to which the target time belongs; calculating the standardized difference of the ambient temperature at the target time within a preset time period based on the ambient temperature at the target time, the average ambient temperature, and the standard deviation of the ambient temperature; and normalizing the standardized difference using a pre-established error function to obtain the liquefaction condition parameters for SF6 gas liquefaction caused by the ambient temperature factor.

3. The method according to claim 1, characterized in that, Factors affecting SF6 gas liquefaction include gas pressure factors. The data corresponding to these gas pressure factors includes gas pressure data. The calculation of liquefaction condition parameters for SF6 gas liquefaction based on the data for each factor includes: acquiring gas pressure data at a target time, as well as the long-term average, fluctuation range, and basic standard deviation of gas pressure over the time period to which the target time belongs, and the operating characteristics of the target equipment; constructing an expected pressure value for SF6 gas based on the long-term average pressure value, fluctuation range, and the operating characteristics of the target equipment over a preset time period; adjusting the basic standard deviation using the long-term average value and the gas pressure value at the target time to obtain the pressure standard deviation at the target time; calculating the standardized deviation between the gas pressure value at the target time and the expected pressure value based on the expected pressure value, the pressure standard deviation, and the gas pressure value at the target time; and using a pre-established Gaussian function to calculate the standardized deviation and the pressure standard deviation to obtain the liquefaction condition parameters for SF6 gas liquefaction caused by the gas pressure factors.

4. The method according to claim 1, characterized in that, Factors affecting SF6 gas liquefaction include gas purity, and the data corresponding to the gas purity factor includes gas purity data. The step of calculating the liquefaction condition parameters for SF6 gas liquefaction caused by each factor based on the data corresponding to each factor includes: obtaining gas purity data at the target time; and determining the liquefaction condition parameters for SF6 gas liquefaction caused by the gas purity factor based on the range to which the gas purity data belongs.

5. The method according to claim 1, characterized in that, Factors affecting SF6 gas liquefaction include time factors. The step of calculating liquefaction condition parameters for SF6 gas liquefaction based on the data corresponding to each factor includes: determining the time period to which the target time belongs and the average time of the time period; and calculating the liquefaction condition parameters for SF6 gas liquefaction caused by the time factors based on the dispersion of the target time relative to the average time.

6. The method according to claim 1, characterized in that, Factors affecting SF6 gas liquefaction include low-temperature weather factors. The data corresponding to these low-temperature weather factors includes weather temperature data. The calculation of liquefaction condition parameters for SF6 gas liquefaction based on the data corresponding to each factor includes: determining the weather temperature data at the target time; if the weather temperature data is less than a low-temperature threshold, calculating the liquefaction condition parameters for SF6 gas liquefaction caused by the low-temperature weather factors based on the difference between the weather temperature data and the low-temperature threshold.

7. The method according to claim 1, characterized in that, Multiple factors affecting SF6 gas liquefaction in the target equipment include ambient temperature, gas pressure, gas purity, time, and low-temperature weather. The method involves combining the liquefaction condition parameters corresponding to each factor with the corresponding data to obtain the probability coefficient of SF6 gas liquefaction. This includes: determining a first parameter based on the liquefaction condition parameters corresponding to ambient temperature, gas pressure, gas purity, time, and low-temperature weather at different times within a preset time period, as well as the gas pressure and critical pressure value of SF6 gas; determining a second parameter based on the liquefaction condition parameters corresponding to ambient temperature, gas pressure, gas purity, and time at different times within a preset time period; and determining the probability coefficient of SF6 gas liquefaction based on the quotient of the first parameter and the second parameter.

8. An SF6 gas anti-liquefaction prediction device, characterized in that, The device includes: a data acquisition module for acquiring data corresponding to various factors affecting SF6 gas liquefaction in the target equipment; a data analysis module for calculating liquefaction condition parameters for SF6 gas liquefaction based on the data corresponding to each factor; and a probability calculation module for combining the liquefaction condition parameters corresponding to each factor with the data corresponding to each factor to obtain the probability coefficient of SF6 gas liquefaction.

9. A computer device, characterized in that, include: The system includes a memory and a processor, which are interconnected and the memory stores computer instructions. The processor executes the computer instructions to perform the SF6 gas liquefaction prevention early warning method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the SF6 gas liquefaction prevention early warning method according to any one of claims 1 to 7.

11. A computer program product, characterized in that, It includes computer instructions, which are used to cause a computer to execute the SF6 gas liquefaction prevention and early warning method according to any one of claims 1 to 7.

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