Rapid proportioning and mixing method, system and equipment for SF6 / N2 mixed gas in GIS (Geographic Information System) equipment and storage medium

Abstract

The invention relates to the technical field of gas insulation of power equipment, in particular to a method, a system and equipment for quickly proportioning and mixing SF6 / N2 mixed gas in GIS (Gas Insulated Switchgear) equipment and a storage medium. GIS equipment geometric parameters are obtained, a pipeline model is constructed, and the effective volume of the equipment is derived based on a correction state equation introducing a compression factor Z; establishing a kinetic model of an SF6 / N2 diffusion rule, and simulating gas flowing, diffusion and mixing processes through a Standard k-epsilon turbulence model and a component transport model; performing real-time concentration detection on the mixed gas by using an infrared spectroscopy, and establishing a relation model of light intensity attenuation and gas concentration based on a Lambert-Beer law; and performing dynamic gas distribution control according to a detection result, and adjusting the flow of each gas branch through a mass flow controller to realize a target mixing ratio. Through multi-level technology integration, the technical problems of inaccurate volume calculation, non-uniform gas distribution and obvious detection hysteresis in a traditional mixing method are solved, and + / -0.5% mixing precision control and rapid mixing within 5 minutes are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of gas insulation of power equipment, and in particular to a method, system, equipment and storage medium for quickly proportioning and mixing SF6 / N2 mixed gas in GIS equipment. Background Art

[0002] With the rapid development of the power industry and improvements in technological equipment, SF6 gas has been widely used in GIS (gas-insulated switchgear) due to its excellent insulation properties and arc-extinguishing capabilities. At room temperature and pressure, SF6 gas is colorless, odorless, non-toxic, and non-flammable, making it an ideal insulating medium. Consequently, a large number of sulfur hexafluoride circuit breakers and fully enclosed combination electrical appliances are being put into construction and operation.

[0003] However, SF6 gas also has significant shortcomings in its application: First, it is sensitive to the uniformity of the electric field and only shows its advantages in uniform or slightly non-uniform electric fields. Second, SF6 gas emitted into the atmosphere is difficult to degrade and persists for a long time, which has a cumulative effect on global warming. In addition, SF6 gas is relatively expensive, significantly increasing operating costs. Due to these problems, the use of a mixture of SF6 and N2 to replace pure SF6 as a high-voltage insulating gas medium has become an important development direction.

[0004] Current SF6 / N2 mixed gas preparation technology faces the following major technical challenges: uneven gas distribution during the mixing process, affecting the stability of insulation performance; low mixing efficiency, unable to meet the needs of industrial production; a lack of precise mixing ratio control methods, making it difficult to achieve the ideal mixing ratio; and significant lag in existing detection methods, making real-time monitoring and dynamic adjustment impossible. These technical limitations have severely restricted the widespread application of SF6 / N2 mixed gas in GIS equipment. Summary of the Invention

[0005] In view of the problems existing in the prior art, the present invention is proposed.

[0006] Therefore, the problem to be solved by the present invention is how to solve the technical problems such as uneven mixing, low efficiency, inaccurate proportion control, and lack of real-time monitoring in the preparation process of SF6 / N2 mixed gas in the prior art, develop a rapid mixing technology suitable for non-vacuum conditions, improve the mixing efficiency and accuracy, and realize intelligent control and real-time monitoring of the mixing process.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, an embodiment of the present invention provides a method for quickly proportioning and mixing SF6 / N2 mixed gas in a GIS device, comprising obtaining geometric parameters of the GIS device and constructing a pipeline model, and deriving the effective volume of the GIS device based on a state equation;

[0009] A kinetic model of SF6 / N2 diffusion law was established, and the gas flow, diffusion and mixing processes were simulated using the Standard k-ε model and component transport model.

[0010] Use infrared spectroscopy to detect the concentration of mixed gases in real time and obtain mixing ratio data;

[0011] Dynamic gas distribution control is performed based on the test results, and the flow rate of each gas branch is adjusted by the mass flow controller to achieve the target mixing ratio.

[0012] As a preferred solution of the method for quickly proportioning and mixing SF6 / N2 mixed gas in the GIS equipment of the present invention, the effective volume of the GIS equipment is derived based on the state equation, including:

[0013] According to the actual gas behavior, the compression factor Z is introduced to deduce the effective volume of irregular typical equipment or models, and the modified state equation is established:

[0014] PV=nRTZ

[0015] Where: P is pressure, V is volume, n is the amount of substance, R is the gas constant, and T is temperature;

[0016] Set the initial pressure of the GIS chamber to be tested to P1, and use a standard container with a known volume V2 for vacuum treatment;

[0017] Connect the two containers through a pipe and open the valve, and record the pressure P2 after pressure balance;

[0018] The effective volume of the GIS air chamber is calculated based on the pressure balance principle.

[0019] As a preferred solution of the method for quickly proportioning and mixing SF6 / N2 mixed gas in the GIS equipment of the present invention, the kinetic model for establishing the diffusion law of SF6 / N2 includes:

[0020] The Standard k-ε turbulence model is used to numerically simulate the SF6 and N2 charging process;

[0021] The component transport model is used to simulate the diffusion process of N2 in the container;

[0022] Combine the continuity equation, momentum equation and energy equation to establish a numerical calculation model of gas dynamic changes;

[0023] Set the corresponding boundary conditions and initial conditions to solve the gas flow and mixing process.

[0024] As a preferred solution for the rapid proportioning and mixing method of SF6 / N2 mixed gas in the GIS equipment described in the present invention, the turbulent kinetic energy k and dissipation rate ε of the Standard k-ε model are calculated by solving the turbulent kinetic energy generation term, buoyancy generation term and compressible turbulent fluctuation expansion term.

[0025] As a preferred solution of the method for quickly proportioning and mixing SF6 / N2 mixed gas in the GIS equipment of the present invention, the method for performing real-time concentration detection of the mixed gas by infrared spectroscopy includes:

[0026] The infrared light source emits infrared light of a specific wavelength range to pass through the gas being measured;

[0027] The measured gas selectively absorbs infrared light, causing light intensity attenuation;

[0028] A relationship model between light intensity attenuation and gas concentration was established based on the Lambert-Beer law;

[0029] The concentration ratio of each component in the mixed gas is calculated through the light intensity attenuation data.

[0030] As a preferred solution of the method for quickly proportioning and mixing SF6 / N2 mixed gas in GIS equipment of the present invention, the dynamic gas distribution control based on the detection results includes:

[0031] comparing the actual mixing ratio obtained by detection with the target mixing ratio;

[0032] Calculate the type and flow of gas that needs to be supplemented;

[0033] The gas flow of each branch is precisely controlled by mass flow controllers;

[0034] A buffer tank is set between the mass flow controller and the boost component, and the buffer tank pressure is controlled by PID regulation method.

[0035] As a preferred solution of the method for quickly proportioning and mixing SF6 / N2 mixed gas in the GIS equipment of the present invention, the calculation of the type and flow rate of gas to be supplemented includes:

[0036] When the mixed gas concentration is lower than the target concentration, SF6 gas is added;

[0037] When the mixed gas concentration is higher than the target concentration, N2 gas is added;

[0038] The gas supply flow rate is calculated according to the formula: gas supply flow rate = mixed gas flow rate × target concentration - actual concentration;

[0039] After being fully mixed in the buffer tank, the compressor boosts the pressure and outputs it to the GIS equipment.

[0040] In a second aspect, an embodiment of the present invention provides a system for rapidly proportioning and mixing SF6 / N2 mixed gas in a GIS device, which includes a volume calculation module for obtaining geometric parameters of the GIS device and constructing a pipeline model, and deriving the effective volume of the GIS device based on a state equation;

[0041] Kinetic modeling module, used to establish a kinetic model of SF6 / N2 diffusion law, and simulate gas flow, diffusion and mixing processes through the Standard k-ε model and component transport model;

[0042] Spectral detection module, used to detect the concentration of mixed gas in real time using infrared spectroscopy to obtain mixing ratio data;

[0043] The dynamic gas distribution control module is used to perform dynamic gas distribution control according to the detection results, and adjust the flow of each gas branch through the mass flow controller to achieve the target mixing ratio.

[0044] In a third aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the method for rapid proportioning and mixing of SF6 / N2 mixed gas in the GIS equipment as described in the first aspect of the present invention are implemented.

[0045] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the method for rapidly proportioning and mixing SF6 / N2 mixed gas in GIS equipment as described in the first aspect of the present invention are implemented.

[0046] The beneficial effects of the present invention are as follows: the present invention introduces the state equation modified by the compression factor Z to derive the effective volume of the GIS equipment, breaking through the limitations of the traditional ideal gas model, realizing the accurate description of the real gas behavior of the SF6 body under high pressure conditions, solving the fundamental problem of the deviation of the mixing ratio caused by the volume calculation error, and significantly improving the volume measurement accuracy from the 5% to 10% error of the traditional method to within 1%; by establishing a dynamic simulation system that couples the Standard k-ε turbulence model with the component transport model, the density gradient mixing problem caused by the significant difference in the molecular weight of SF6 and N2 is overcome, and the accurate prediction and control of the heavy gas deposition and light gas floating phenomenon is realized, effectively eliminating the stratification phenomenon and local concentration unevenness problem in the traditional mixing process; by adopting the real-time concentration detection technology based on the Lambert-Beer law of infrared spectroscopy, the SF6 molecules at 948cm -1The characteristic absorption peak at the N2 and the infrared transparency of N2 molecules enable online monitoring with millisecond-level response, fundamentally overcoming the significant lag and inability to adjust in real time of traditional detection methods. A multi-level dynamic gas distribution control system integrating PID control, neural network prediction, and fuzzy logic optimization, combined with a precise flow regulation mechanism of mass flow controllers and buffer tanks, achieves ±0.5% mixing accuracy and a rapid response within 30 seconds, significantly outperforming traditional batch mixing methods in terms of efficiency, accuracy, and automation. The overall technical solution forms a complete closed-loop system encompassing precise volume calculation, mixing process modeling, real-time concentration monitoring, and dynamic ratio control. This system not only reduces mixing time from several hours to less than 5 minutes, achieving continuous operational stability exceeding 720 hours, but also achieves rapid and uniform mixing without vacuuming. This provides a breakthrough technical solution for the industrialized, precise preparation of insulating gas for GIS equipment. Furthermore, by precisely controlling SF6 usage, environmental emissions are reduced, meeting the requirements of green manufacturing and sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only 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.

[0048] Figure 1 This is a flow chart of the method for quickly proportioning and mixing SF6 / N2 mixed gas in GIS equipment;

[0049] Figure 2 This is a computer equipment diagram for the rapid proportioning and mixing method of SF6 / N2 mixed gas in GIS equipment;

[0050] Figure 3 Schematic diagram of the gas chamber effective volume measurement model for the SF6 / N2 mixed gas rapid ratio mixing method in GIS equipment;

[0051] Figure 4 Schematic diagram of the diffusion measurement and evaluation experimental device for the rapid mixing method of SF6 / N2 mixed gas in GIS equipment;

[0052] Figure 5 This is a schematic diagram of the spectroscopic detection principle of the SF6 / N2 mixed gas rapid mixing method in GIS equipment;

[0053] Figure 6 Schematic diagram of the dynamic gas distribution principle of the SF6 / N2 mixed gas rapid mixing method in GIS equipment. DETAILED DESCRIPTION

[0054] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0055] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0056] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it constitute a separate or selective embodiment that is mutually exclusive with other embodiments.

[0057] Example 1

[0058] Reference Figure 1-Figure 2 , which is the first embodiment of the present invention, provides a method for quickly proportioning and mixing SF6 / N2 mixed gas in GIS equipment, comprising:

[0059] S100: Obtain the geometric parameters of GIS equipment and build pipeline models, derive based on the state equation

[0060] The effective volume of GIS equipment;

[0061] S200: Establish a kinetic model for SF6 / N2 diffusion, and simulate gas flow, diffusion, and mixing processes using the Standard k-ε model and component transport model;

[0062] S300: Use infrared spectroscopy to detect the concentration of mixed gases in real time and obtain mixing ratio data;

[0063] S400: Dynamic gas distribution control is performed based on the test results, and the flow rate of each gas branch is adjusted through the mass flow controller to achieve the target mixing ratio.

[0064] The application of SF6 / N2 mixed gas in GIS equipment faces many technical challenges. In the S100 stage, traditional volume calculation methods often use the ideal gas model, ignoring the actual gas behavior of SF6 gas under high pressure conditions, resulting in large errors in volume calculation, which in turn affects the precise control of the subsequent mixing ratio. In actual engineering, GIS equipment has a complex structure and a large number of irregular geometric shapes inside, making it difficult for traditional geometric calculation methods to accurately obtain the effective volume. In the S200 stage, existing mixed gas flow simulations lack accurate modeling of the different physical properties of SF6 and N2. The coupled application of the Standard k-ε model and the component transport model is still immature in this field, resulting in stratification and local concentration unevenness during the gas mixing process. In the S300 stage, traditional gas concentration detection methods have problems such as slow response speed and insufficient accuracy, which cannot meet the needs of real-time dynamic monitoring. Especially in the rapid proportioning process, detection delays can lead to the accumulation of mixing ratio deviations.

[0065] Claim 1 of the present invention constitutes a complete technical solution through four core steps, which can effectively solve the technical problem of rapid proportioning and mixing of SF6 / N2 mixed gas in GIS equipment. First, by obtaining the geometric parameters of the GIS equipment and constructing a pipeline model, the effective volume is derived based on the modified state equation, which solves the problem of insufficient accuracy of the traditional ideal gas model and provides reliable basic data for subsequent precise proportioning. Secondly, by establishing a kinetic model of the SF6 / N2 diffusion law and adopting the coupled simulation of the Standard k-ε model and the component transport model, the gas flow, diffusion and mixing processes are accurately predicted, ensuring the uniformity and stability of the mixed gas. Thirdly, infrared spectroscopy is used to realize real-time concentration detection of the mixed gas, and an accurate concentration-spectrum relationship model is established through the Lambert-Beer law, realizing fast and accurate online monitoring. Finally, dynamic gas distribution control is carried out according to the detection results, and the target mixing ratio is accurately controlled and adjusted in real time through the mass flow controller and PID adjustment system. These four steps form a closed-loop control system, which not only improves the mixing efficiency and accuracy, but also realizes the intelligence and automation of the entire process.

[0066] The "Standard k-ε model" mentioned in the document is a turbulence model widely used in computational fluid dynamics, where k represents turbulent kinetic energy and ε represents the turbulent dissipation rate. This model describes turbulent flow characteristics by solving two transport equations and is applicable to most flow problems in engineering. "GIS" stands for Gas Insulated Switchgear, a critical device in power systems. "PID" control, short for Proportional-Integral-Derivative control, is the most commonly used control algorithm in industrial control.

[0067] Example 2

[0068] Reference Figure 2-Figure 6 , which is the second embodiment of the present invention.

[0069] In the embodiment of the present application, the effective volume of the GIS equipment is derived based on the state equation in step S100, including the following steps A1-A2:

[0070] A1: The effective volume of GIS equipment is derived based on the equation of state, including:

[0071] According to the actual gas behavior, the compression factor Z is introduced to deduce the effective volume of irregular typical equipment or models, and the modified state equation is established:

[0072] PV=nRTZ

[0073] Where: P is pressure, V is volume, n is the amount of substance, R is the gas constant, and T is temperature;

[0074] Set the initial pressure of the GIS chamber to be tested to P1, and use a standard container with a known volume V2 for vacuum treatment;

[0075] Connect the two containers through a pipe and open the valve, and record the pressure P2 after pressure balance;

[0076] The effective volume of the GIS air chamber is calculated based on the pressure balance principle.

[0077] Specifically, in practical applications, SF6 gas deviates significantly from ideal gas behavior under high pressure, and the effects of intermolecular forces and molecular volume must be considered. The compressibility factor, Z, measures the deviation of a real gas from the ideal gas. Its calculation requires consideration of temperature, pressure, and the gas's critical parameters. For SF6 gas, its critical temperature is 45.58°C and its critical pressure is 3.76 MPa. These parameters directly impact the accuracy of the calculated compressibility factor.

[0078] For example, the compression factor Z can be calculated by the following relationship:

[0079] Z=1+B(T)P+C(T)P 2 +D(T)P 3

[0080] Among them, B(T), C(T), and D(T) are temperature-related virial coefficients. For SF6 gas, the second virial coefficient B(T) can be obtained by fitting experimental data:

[0081] B(T)=-156.7+0.45T-0.0012T 2

[0082] (Unit: cm 3 / mol, T is absolute temperature).

[0083] In engineering applications, when the pressure is lower than 1 MPa, usually only the second-order terms need to be considered to meet the accuracy requirements.

[0084] It should be noted that the introduction of the compressibility factor not only improves the accuracy of volume calculations but also provides a theoretical basis for subsequent mixing ratio control. Under different temperature and pressure conditions, the compressibility factor of SF6 gas varies from 0.85 to 0.98. If this deviation is not corrected, it will lead to an error of more than 5% in the final mixing ratio, seriously affecting the insulation performance of GIS equipment.

[0085] A2: Volume measurement experiment design and data processing

[0086] During volume measurement, the initial pressure of the GIS chamber to be measured is set at P1, and a standard container with a known volume, V2, is used for evacuation. The choice of the standard container is crucial; its volume should be of the same order of magnitude as the chamber to be measured to ensure sensitivity to pressure changes. Typically, V2 is chosen to be approximately 0.3-0.5 times the estimated GIS chamber volume, ensuring measurement accuracy while avoiding excessive pressure fluctuations.

[0087] The specific measurement steps include: first, thoroughly vacuum the standard container, and the vacuum degree should reach 10~ 3 Pa to eliminate the influence of residual gas on the measurement results; then monitor the initial pressure P1 of the GIS gas chamber through a high-precision pressure sensor, the accuracy of the pressure sensor should be no less than 0.1% FS; next open the connecting valve to allow the two containers to reach pressure balance, and record the pressure P2 after balance.

[0088] Based on the principle of pressure balance, the following relationship can be established:

[0089] P1V1Z1=P2(V1+V2)Z2

[0090] Among them, Z1 and Z2 are the compression factors in the initial state and equilibrium state respectively. Through mathematical transformation, the effective volume calculation formula of the GIS air chamber can be obtained:

[0091]

[0092] In an alternative embodiment, multiple measurements can be averaged to improve measurement accuracy. Each measurement should be taken at least 30 minutes apart to ensure system temperature stability. Temperature compensation is also necessary, as even small temperature changes can affect the gas equation of state.

[0093] It should be noted that the accuracy of this measurement method is primarily affected by the accuracy of the pressure sensor, temperature stability, and valve sealing. Under ideal conditions, the measurement accuracy of this method can reach ±1%, fully meeting the requirements of engineering applications.

[0094] In the embodiment of the present application, the kinetic model of SF6 / N2 diffusion law is established in step S200, including the following steps B1-B3:

[0095] B1: Establish a kinetic model of SF6 / N2 diffusion, including:

[0096] The Standard k-ε turbulence model is used to numerically simulate the SF6 and N2 charging process;

[0097] The component transport model is used to simulate the diffusion process of N2 in the container;

[0098] Combine the continuity equation, momentum equation and energy equation to establish a numerical calculation model of gas dynamic changes;

[0099] Set the corresponding boundary conditions and initial conditions to solve the gas flow and mixing process.

[0100] The Standard k-ε turbulence model is used to numerically simulate the SF6 and N2 charging process. This model is based on the Reynolds-averaged Navier-Stokes equations (RANS) and describes the turbulent characteristics by solving the transport equations for the turbulent kinetic energy k and the turbulent dissipation rate ε. For the SF6 / N2 mixed gas system, the turbulent kinetic energy equation is:

[0101]

[0102] Where ρ is the density, kg / m 3 ; G k represents the turbulent kinetic energy generated by the mean velocity gradient, G β represents the turbulent kinetic energy generated by buoyancy, Y Mrepresents the contribution of wave expansion to the total dissipation rate in compressible turbulence; x i and x j They represent the i-th and j-th directions in the spatial coordinate system, respectively. In the three-dimensional rectangular coordinate system, i and j can be 1, 2, and 3, corresponding to the x, y, and z directions; is the partial differential symbol, indicating the partial derivative of a variable; μ is the dynamic viscosity coefficient, in Pa·s, which describes the viscous resistance between molecules in the fluid; ρk and ρ ε are the turbulent Prandtl numbers k and ε, respectively, ρk=1.0, ρ ε =1.3;S k , ε is a custom source term.

[0103] Specifically, the turbulent kinetic energy produces the term G k It can be expressed as:

[0104]

[0105] where μ t is the turbulent viscosity, u i is the velocity component in the i-th direction. In three-dimensional space, u1, u2, and u3 correspond to the velocity components in the x, y, and z directions, respectively. Through the relationship:

[0106]

[0107] Calculated, C μ It is an empirical constant, and the standard value is 0.09. Buoyancy generation term:

[0108]

[0109] Where β is the thermal expansion coefficient, g i is the gravity component, Pr t is the turbulent Prandtl number.

[0110] For SF6 / N2 gas mixtures, the buoyancy effect is not negligible due to the significant difference in molecular weight between the two gases (SF6 146g / mol, N2 28g / mol). During vertical mixing, the buoyancy caused by the density difference affects the mixing effect, causing the heavier SF6 gas to settle at the bottom of the container, while the lighter N2 gas diffuses upward.

[0111] It should be noted that the model constants of the Standard k-ε model need to be adjusted according to the specific gas properties. For the SF6 / N2 mixed gas system, the recommended model constants are: ρk=1.0, ρ ε =1.3, these parameters have been verified through experiments to be able to better predict the flow characteristics during the mixing process.

[0112] B2: The turbulent kinetic energy k and dissipation rate ε of the Standard k-ε model are calculated by solving the turbulent kinetic energy generation term, buoyancy generation term, and compressible turbulent wave expansion term.

[0113] The component transport model is used to simulate the diffusion process of N2 in the container. The component transport equation describes the transfer process of each component in the flow field. For the dilute component (such as N2), the transport equation is:

[0114]

[0115] Among them, x j To represent the jth direction in the spatial coordinate system, in the three-dimensional rectangular coordinate system, j can be 1, 2, or 3, corresponding to the x, y, and z directions; u j is the velocity component in the jth direction, which is consistent with the above u i Same meaning, j is the spatial direction index; Y i is the mass fraction of the component, D i , m is the molecular diffusion coefficient, D t is the turbulent diffusion coefficient, R i is the chemical reaction source term, S i Defines source items for users.

[0116] Specifically, the molecular diffusion coefficients of SF6 and N2 can be calculated using the Fuller equation:

[0117]

[0118] Where T is temperature (K), P is pressure (atm), M i and M j is the molecular mass, ∑V is the molecular diffusion volume. For the SF6-N2 system, the molecular diffusion coefficient at room temperature and pressure is about 0.087 cm 2 / s.

[0119] Turbulent diffusion coefficient:

[0120] Among them Sc t is the turbulent Schmidt number, which is usually 0.7-0.9 for gas mixing. In high Reynolds number turbulence, turbulent diffusion is usually much greater than molecular diffusion and is the dominant mass transfer mechanism.

[0121] In an optional embodiment, the effects of the concentration diffusion effect caused by the temperature gradient and the thermal diffusion effect caused by the concentration gradient on multi-component mass transfer can be considered. The temperature gradient diffusion effect describes the mass transfer phenomenon that occurs in the presence of a temperature gradient, even in the absence of a concentration gradient; the concentration gradient thermal diffusion effect describes the additional heat transfer that may be caused by the concentration gradient. For SF6 / N2 mixed gases, due to the large difference in molecular weight (SF6 molecular weight 146g / mol, N2 molecular weight 28g / mol), these cross-effects may have a certain impact on the mass transfer process in the presence of a significant temperature gradient.

[0122] It should be noted that in most engineering applications, due to the dominance of turbulent mass transfer, the impact of these cross-diffusion effects is relatively small and can usually be ignored. However, in some special conditions, such as large temperature differences or low flow rates, it may be necessary to consider these effects to improve the prediction accuracy of the model.

[0123] B3: Coupled solution methods and numerical stability analysis

[0124] Combining the continuity equation, momentum equation and energy equation, a numerical calculation model of gas dynamic changes is established. Continuity equation:

[0125]

[0126] Describes the conservation of mass and the momentum equation:

[0127]

[0128] Describes the conservation of momentum, the energy equation:

[0129]

[0130] Describes the conservation of energy.

[0131] The specific numerical solution uses the finite volume method, the spatial discretization uses the second-order upwind scheme, and the time marching uses the implicit Euler scheme. To ensure numerical stability, the time step needs to meet the CFL condition:

[0132]

[0133] Where Δx, Δy, and Δz are the grid sizes, and u, v, and w are the velocity components.

[0134] In the solution process, the SIMPLE algorithm is used to deal with the pressure-velocity coupling problem. The algorithm iteratively solves the problem in a prediction-correction manner until the variables converge. The convergence criterion is usually set as a residual less than 10 -5 .

[0135] For example, for a typical GIS air chamber (2m × 1m × 1m), a structured grid with approximately 500,000 cells is used for discretization. On a modern high-performance computer, the computation time for a single case is approximately 2–4 hours. To improve computational efficiency, parallel computing techniques can be used to decompose the computational domain onto multiple processors for parallel solution.

[0136] It should be noted that the accuracy of numerical simulations must be ensured through both grid-independence verification and experimental validation. Grid-independence verification requires calculations on grids of varying densities to ensure that key parameters (such as mixing time and concentration distribution) vary by less than 5%. Experimental validation is achieved by comparing the results with visualization experiments or concentration measurements.

[0137] In the embodiment of the present application, the real-time concentration detection of the mixed gas using infrared spectroscopy in step S300 includes the following steps C1-C2:

[0138] C1: Use infrared spectroscopy to detect the concentration of mixed gases in real time, including:

[0139] The infrared light source emits infrared light of a specific wavelength range to pass through the gas being measured;

[0140] The measured gas selectively absorbs infrared light, causing light intensity attenuation;

[0141] A relationship model between light intensity attenuation and gas concentration was established based on the Lambert-Beer law;

[0142] The concentration ratio of each component in the mixed gas is calculated through the light intensity attenuation data.

[0143] The infrared light source emits infrared light of a specific wavelength range through the gas being measured, and the quantitative detection of gas concentration is achieved based on the molecular vibration absorption theory. The SF6 molecule has a symmetrical octahedral structure, containing 6 identical SF bonds, and its characteristic absorption peak is located at 948cm -1 The absorption peak is near 10.55 μm, corresponding to the ν3 vibration mode (F2u, infrared active) of the SF6 molecule. Since the N2 molecule has a symmetrical structure and no dipole moment change, it has no obvious absorption peak in the infrared region, which facilitates the selective detection of SF6.

[0144] The specific optical system design includes: the infrared light source uses a broadband infrared LED or a blackbody radiation source with an emission wavelength range of 8-12μm, covering the main absorption peak of SF6; the optical filter uses a narrowband filter with a central wavelength of 10.55μm, a half-maximum full width of approximately 0.5μm, and a transmittance greater than 80%; the gas sample cell length is designed to be 10-50cm, and the cell wall is gold-plated with high reflectivity to reduce light loss; the infrared detector uses a pyroelectric detector or an MCT (mercury cadmium telluride) detector with a response time of less than 1ms and a detection accuracy of ppm level.

[0145] The measured gas selectively absorbs infrared light, resulting in light intensity attenuation. The absorption intensity is related to the gas concentration, optical path length, and absorption cross-sectional area. -1 The absorption cross-sectional area at -6 cm 2 , which enables effective detection even at lower concentrations.

[0146] It should be noted that the advantages of infrared spectroscopy include fast response, good selectivity, and the absence of sample preprocessing, making it particularly suitable for online real-time monitoring. However, this method places high demands on the stability of optical components, requiring regular calibration and maintenance.

[0147] C2: Application of Lambert-Beer Law and Concentration Calculation Model

[0148] The relationship model between light intensity attenuation and gas concentration is established based on the Lambert-Beer law. The Lambert-Beer law is expressed as:

[0149] I=I0×exp(-αcl)

[0150] I=I0×exp(-αcl),

[0151] Where I is the transmitted light intensity, I0 is the incident light intensity, α is the molar absorptivity, c is the gas concentration, and l is the optical path length. By logarithmic transformation, a linear relationship can be obtained:

[0152]

[0153] Absorbance

[0154] For SF6 gas, at 948cm -1 The molar absorption coefficient α is about 2.3×10 3 L / (mol·cm). In actual measurement, considering the influence of temperature and pressure on the absorption coefficient, correction is required:

[0155]

[0156] Where α0 is the absorption coefficient under standard conditions, P0 and T0 are standard pressure and temperature.

[0157] The concentration ratio of each component in the mixed gas is calculated by calculating the light intensity attenuation data. In actual measurement, due to the presence of various interference factors, it is necessary to use a multi-wavelength detection method to improve accuracy. The main absorption peak of SF6 (948cm -1 ) as the measurement wavelength, and select a reference wavelength (such as 980cm -1 , where SF6 absorption is very weak) is used to compensate for the effects of light source fluctuations and optical component contamination.

[0158] The concentration calculation formula is:

[0159]

[0160] Where k is the correction factor, which is determined by calibration with standard gas. The volume fraction of SF6 in the mixed gas is:

[0161] Volume fraction of N2:

[0162] For example, for a 20% SF6 / N2 gas mixture with a volume fraction, the absorbance at a 10cm optical pathlength is approximately 0.46, corresponding to a transmittance of approximately 63%. Detection accuracy is primarily affected by detector noise, light source stability, and environmental interference, and can achieve a relative error of ±1% under optimized conditions.

[0163] It should be noted that to improve detection stability and accuracy, the system needs to be equipped with temperature and pressure sensors to monitor environmental conditions in real time and perform corresponding correction calculations. It is also recommended to calibrate using standard gas every 24 hours to ensure long-term stability.

[0164] In the embodiment of the present application, the real-time concentration detection of the mixed gas is performed using infrared spectroscopy in step S400, which includes the following steps D1-D2:

[0165] D1: Dynamic gas distribution control based on test results, including:

[0166] comparing the actual mixing ratio obtained by detection with the target mixing ratio;

[0167] Calculate the type and flow of gas that needs to be supplemented;

[0168] The gas flow of each branch is precisely controlled by mass flow controllers;

[0169] A buffer tank is set between the mass flow controller and the boost component, and the buffer tank pressure is controlled by PID regulation method.

[0170] The deviation feedback control system is established by comparing the actual mixing ratio obtained by detection with the target mixing ratio. The control system adopts PID (Proportional-Integral-Differential) algorithm, and the controller output is:

[0171]

[0172] in, is the concentration deviation, is the target concentration, is the actual detection concentration, K p , K i , K d are proportional, integral, and differential gains respectively.

[0173] Specific parameter adjustment strategy: proportional gain K p It mainly affects the response speed and steady-state error of the system. Increasing K p It can improve the response speed but may cause system oscillation. The typical value is 0.5-2.0; integral gain K i Used to eliminate steady-state errors, but too large K i It will cause system instability, the typical value is 0.1-0.5; differential gain K d It can improve the dynamic characteristics of the system and reduce overshoot, but it is sensitive to noise, with a typical value of 0.01-0.1.

[0174] The predictive control algorithm is used to calculate the type and flow of gas that needs to be replenished. When a concentration deviation is detected, the system first determines the direction of the deviation: This indicates that the SF6 concentration is low and SF6 gas needs to be supplemented; if This indicates that the SF6 concentration is too high and needs to be diluted with additional N2 gas.

[0175] Mass flow controllers precisely control the gas flow in each branch. Based on the principle of a thermal mass flowmeter, a mass flow controller (MFC) measures the mass flow of gas using a heating element and a temperature sensor. Due to their different molecular weights and thermal conductivities, SF6 and N2 require separate calibration. MFC control accuracy typically reaches ±1% of full scale, with a response time of approximately 1 to 3 seconds.

[0176] A buffer tank is placed between the mass flow controller and the booster component, and the buffer tank pressure is controlled using PID regulation. The buffer tank's function is to smooth out flow fluctuations and ensure stable pressure in downstream equipment. The buffer tank's volume is typically designed to be 5% to 10% of the system's hourly flow rate, and it houses a pressure sensor and safety valve. The pressure control loop also uses a PID algorithm, with the target pressure set at 1.1-1.2 times the system's operating pressure.

[0177] It should be noted that the response characteristics of the dynamic gas distribution control system directly affect mixing accuracy and stability. System design requires consideration of the time constants of each link, including detection delay (approximately 1 to 2 seconds), controller calculation time (approximately 0.1 seconds), flow controller response time (approximately 1 to 3 seconds), and mixing time (approximately 10 to 30 seconds). The total control loop time is approximately 12 to 35 seconds.

[0178] D2: Calculate the type and flow of gas that needs to be replenished, including:

[0179] When the mixed gas concentration is lower than the target concentration, SF6 gas is added;

[0180] When the mixed gas concentration is higher than the target concentration, N2 gas is added;

[0181] The gas supply flow rate is calculated according to the formula: gas supply flow rate = mixed gas flow rate × target concentration - actual concentration;

[0182] After being fully mixed in the buffer tank, the compressor boosts the pressure and outputs it to the GIS equipment.

[0183] The calculation of the type and flow of gas to be supplemented is based on the mass balance principle. Assume that the total flow of the current mixed gas is Q t , the actual SF6 volume fraction is The target SF6 volume fraction is The required air flow rate is:

[0184]

[0185] in, is the volume fraction of the supplementary gas (SF6 is 100%, N2 is 0%).

[0186] When the mixed gas concentration is lower than the target concentration Replenish SF6 gas. The calculation formula for the gas replenishment flow rate is:

[0187]

[0188] For example, if the current total flow rate is 100 NL / min, the actual SF6 concentration is 18%, and the target concentration is 20%, the SF6 flow rate to be supplemented is:

[0189]

[0190] When the mixed gas concentration is higher than the target concentration Supplement N2 gas for dilution. The calculation formula for the gas flow rate is:

[0191]

[0192] Continuing with the above example, if the actual SF6 concentration is 22%, the N2 flow rate required to be supplemented is:

[0193]

[0194] After thorough mixing in a buffer tank, the gas is pressurized and delivered to the GIS equipment by a compressor. A static mixer is designed within the buffer tank, using a blade or spiral structure to promote thorough mixing of the gas. The evaluation metric for mixing effectiveness is mixing uniformity, defined as: η = 1 - (σ / σmax), where σ is the standard deviation of concentration and σmax is the standard deviation under fully separated conditions. A good mixing design should achieve η > 0.95.

[0195] To further improve mixing performance, a neural network predictive model can be used to optimize control parameters. The neural network inputs include current concentration deviation, historical concentration trends, and flow rate change rates, and the outputs are optimized PID parameters. The network architecture uses a three-layer feedforward neural network with 10 to 20 hidden layer neurons and a ReLU activation function. Training data is derived from experimental data under various operating conditions, encompassing various concentration ranges, flow rate variations, and environmental conditions.

[0196] For example, the input vector of the neural network is:

[0197] x=[e(t),e(t-1),e(t-2),Δe(t),Q t ,T,P]

[0198] Where e(t) is the current concentration deviation, Δe(t) is the deviation change rate, and T and P are the ambient temperature and pressure. The output vector is:

[0199] y=[K p , K i , K d ]

[0200] That is, the optimized PID parameters. The network training uses the back propagation algorithm, the learning rate is set to 0.001, and the number of training rounds is 1000-2000 rounds.

[0201] It should be noted that the introduction of the neural network model significantly improves the control system's adaptability, especially under conditions of large fluctuations in operating conditions. Compared with traditional fixed-parameter PID control, adaptive neural network PID control can improve concentration control accuracy from ±2% to ±0.5% and shorten system response time by approximately 30%.

[0202] In an alternative embodiment, a fuzzy logic controller can be used to perform secondary optimization of the neural network output. The fuzzy controller takes the PID parameters output by the neural network as input and, combined with the current system state information, outputs the final control parameters. The fuzzy rule base incorporates the operator's empirical knowledge, such as "When the concentration deviation is large and the rate of change is rapid, the proportional gain should be appropriately increased and the integral time should be reduced." This hybrid control strategy combines the learning capabilities of a neural network with the robustness of fuzzy control.

[0203] For example, the input variables of the fuzzy controller include the concentration deviation |e(t)|, the deviation change rate |Δe(t)|, and the system stability index, and the output variable is the PID parameter correction coefficient. The fuzzy set is defined as follows: the deviation size is divided into five levels {very small, small, medium, large, very large}, and the corresponding membership function uses a triangular or trapezoidal function. Typical fuzzy rules are: IF |e(t)|is large AND |Δe(t)|is large THEN K p The correction coefficient is large.

[0204] In summary, this embodiment achieves precise control of the SF6 / N2 mixed gas ratio by establishing a complete dynamic gas distribution control system. The system combines traditional PID control, neural network prediction, and fuzzy logic optimization, achieving excellent control accuracy and meeting the stringent mixed gas quality requirements of GIS equipment.

[0205] In another optional embodiment, the control system is equipped with fault diagnosis and fault-tolerant control capabilities to address unexpected system disturbances or equipment failures. The fault diagnosis module, based on principal component analysis (PCA), identifies abnormal conditions by monitoring the statistical characteristics of key process variables. When a fault is detected, the system automatically switches to safe mode, halting gas replenishment operations and issuing an alarm.

[0206] It should be noted that the entire dynamic gas distribution control system was designed with safety and reliability in mind. All key equipment is redundant, and the control system features self-diagnosis and self-recovery capabilities. Under normal operating conditions, the system can control SF6 concentration within ±0.5% of the target value with a response time of less than 30 seconds, meeting the stringent requirements of industrial applications.

[0207] This invention constructs a complete technical solution for the rapid proportioning of SF6 / N2 mixed gas through four key steps. In terms of volume calculation, the introduction of a compressibility factor-corrected equation of state significantly improves volume measurement accuracy, reducing the measurement error from 5% to 10% with traditional methods to less than 1%. In terms of dynamic modeling, coupled simulation of the Standard k-ε turbulence model and a component transport model accurately predicts the mixing process, providing theoretical guidance for optimizing mixing time and improving mixing uniformity.

[0208] In terms of detection technology, infrared spectroscopy enables real-time online monitoring of SF6 concentration, with an accuracy of ±1% and a response time of less than 2 seconds, meeting the requirements for rapid proportioning control. In terms of control systems, a multi-level control architecture integrating PID control, neural network prediction, and fuzzy logic optimization achieves high-precision, fast-response dynamic gas distribution control.

[0209] The system's overall performance indicators are as follows: mixing accuracy of ±0.5%, mixing time of less than 5 minutes, system response time of less than 30 seconds, and continuous operation stability of more than 720 hours. Compared with traditional batch mixing methods, the continuous dynamic mixing technology of this invention has significantly improved efficiency, precision, and automation.

[0210] In order to further optimize system performance, improvements are recommended in the following aspects: First, consider introducing multi-sensor fusion technology, combining multiple detection methods such as infrared spectroscopy, gas chromatography and mass spectrometry, to improve the accuracy and reliability of detection; second, in terms of control algorithms, explore advanced control strategies based on model predictive control (MPC) to optimize control decisions by predicting future states; finally, in terms of system integration, develop a virtual debugging platform based on digital twin technology to reduce actual debugging time and cost.

[0211] It should be noted that the technical solution of this invention is not only applicable to SF6 / N2 mixed gas systems but can also be extended to the mixing control of other multi-component gases. By adjusting the detection wavelength, revising the calculation model, and optimizing the control parameters, this technology can be applied to other gas mixing systems such as CO2 / N2 and Ar / N2, showing good versatility and broad prospects for promotion.

[0212] In engineering applications, the technical solution of this invention has been validated on the production lines of multiple GIS equipment manufacturers. Practical application results show that the use of this invention's rapid mixing technology significantly improves the insulation performance consistency of GIS equipment, reduces the defective product rate from 3% to below 0.5%, and increases production efficiency by approximately 40%. These application results fully demonstrate the practicality and advanced nature of the technical solution of this invention.

[0213] Furthermore, this invention has significant environmental implications. By precisely controlling the amount of SF6 used, it reduces overuse and waste gas emissions, meeting current requirements for green manufacturing and sustainable development. With increasingly stringent environmental regulations and the development of alternative gas technologies, the precise mixing control technology provided by this invention will become a key technology in the manufacture of gas-insulated equipment.

[0214] In summary, the present invention solves the technical problem of rapid, precise and stable mixing of SF6 / N2 mixed gas in GIS equipment through systematic technological innovation, providing important support for technological progress and industrial upgrading in related industries.

[0215] Example 3

[0216] The above is a schematic diagram of a method for rapidly proportioning and mixing an SF6 / N2 mixed gas in a GIS device. It should be noted that the technical solution of the system for rapidly proportioning and mixing an SF6 / N2 mixed gas in a GIS device and the technical solution of the method for rapidly proportioning and mixing an SF6 / N2 mixed gas in a GIS device are based on the same concept. For details not described in detail in the technical solution of the system for rapidly proportioning and mixing an SF6 / N2 mixed gas in a GIS device in this embodiment, please refer to the description of the technical solution of the method for rapidly proportioning and mixing an SF6 / N2 mixed gas in a GIS device.

[0217] This embodiment also provides a system for rapidly proportioning and mixing SF6 / N2 mixed gas in GIS equipment, comprising:

[0218] Volume calculation module, used to obtain the geometric parameters of GIS equipment and build pipeline models, and derive the effective volume of GIS equipment based on the state equation;

[0219] Kinetic modeling module, used to establish a kinetic model of SF6 / N2 diffusion law, and simulate gas flow, diffusion and mixing processes through the Standard k-ε model and component transport model;

[0220] Spectral detection module, used to detect the concentration of mixed gas in real time using infrared spectroscopy to obtain mixing ratio data;

[0221] The dynamic gas distribution control module is used to perform dynamic gas distribution control according to the detection results, and adjust the flow of each gas branch through the mass flow controller to achieve the target mixing ratio.

[0222] This embodiment also provides an electronic device suitable for the rapid proportioning and mixing of SF6 / N2 mixed gas in GIS equipment, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the method for rapid proportioning and mixing of SF6 / N2 mixed gas in GIS equipment as proposed in the above embodiment.

[0223] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for quickly proportioning and mixing SF6 / N2 mixed gas in GIS equipment as proposed in the above embodiment is implemented.

[0224] The storage medium proposed in this embodiment and the method for realizing rapid proportioning and mixing of SF6 / N2 mixed gas in GIS equipment proposed in the above embodiment belong to the same inventive concept. For technical details not fully described in this embodiment, please refer to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0225] Through the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented with the help of software and necessary general hardware, and of course can also be implemented by hardware. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0226] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for quickly mixing SF6 / N2 mixed gas in GIS equipment, characterized by: The method comprises obtaining geometric parameters of the GIS equipment and constructing a pipeline model, and deriving the effective volume of the GIS equipment based on a state equation; A kinetic model of SF6 / N2 diffusion law was established, and the gas flow, diffusion and mixing processes were simulated using the Standard k-ε model and component transport model. Use infrared spectroscopy to detect the concentration of mixed gases in real time and obtain mixing ratio data; Dynamic gas distribution control is performed based on the test results, and the flow rate of each gas branch is adjusted by the mass flow controller to achieve the target mixing ratio.

2. The method for rapidly mixing SF6 / N2 mixed gas in GIS equipment according to claim 1, characterized in that: The derivation of the effective volume of the GIS equipment based on the state equation includes: According to the actual gas behavior, the compression factor Z is introduced to deduce the effective volume of irregular typical equipment or models, and the modified state equation is established: PV=nRTZ Where: P is pressure, V is volume, n is the amount of substance, R is the gas constant, and T is temperature; Set the initial pressure of the GIS chamber to be tested to P1, and use a standard container with a known volume V2 for vacuum treatment; Connect the two containers through a pipe and open the valve, and record the pressure P2 after pressure balance; The effective volume of the GIS air chamber is calculated based on the pressure balance principle.

3. The method for rapidly mixing SF6 / N2 mixed gas in GIS equipment according to claim 2, characterized in that: The kinetic model for establishing the SF6 / N2 diffusion law includes: The Standard k-ε turbulence model is used to numerically simulate the SF6 and N2 charging process; The component transport model is used to simulate the diffusion process of N2 in the container; Combine the continuity equation, momentum equation and energy equation to establish a numerical calculation model of gas dynamic changes; Set the corresponding boundary conditions and initial conditions to solve the gas flow and mixing process.

4. The method for rapidly mixing SF6 / N2 mixed gas in GIS equipment according to claim 3, characterized in that: The turbulent kinetic energy k and dissipation rate ε of the Standard k-ε model are calculated by solving the turbulent kinetic energy generation term, the buoyancy generation term, and the compressible turbulent wave expansion term.

5. The method for rapidly mixing SF6 / N2 mixed gas in GIS equipment according to claim 4, characterized in that: The method of using infrared spectroscopy to detect the concentration of mixed gas in real time includes: The infrared light source emits infrared light of a specific wavelength range to pass through the gas being measured; The measured gas selectively absorbs infrared light, causing light intensity attenuation; A relationship model between light intensity attenuation and gas concentration was established based on the Lambert-Beer law; The concentration ratio of each component in the mixed gas is calculated through the light intensity attenuation data.

6. The method for rapidly mixing SF6 / N2 mixed gas in GIS equipment according to claim 5, characterized in that: The dynamic gas distribution control according to the detection result includes: The actual mixing ratio obtained from the test is compared with the target mixing ratio; the type and flow rate of the gas that needs to be supplemented are calculated; the gas flow rate of each branch is accurately controlled by a mass flow controller; a buffer tank is set between the mass flow controller and the boost component, and the buffer tank pressure is controlled by the PID adjustment method.

7. The method for rapidly mixing SF6 / N2 mixed gas in GIS equipment according to claim 6, characterized in that: The calculation requires the type and flow of gas to be supplemented. include: When the mixed gas concentration is lower than the target concentration, SF6 gas is added; when the mixed gas concentration is higher than the target concentration, N2 gas is added; the gas supply flow rate is calculated according to the formula: gas supply flow rate = mixed gas flow rate × target concentration - actual concentration; After being fully mixed in the buffer tank, the compressor boosts the pressure and outputs it to the GIS equipment.

8. A system for rapidly proportioning and mixing SF6 / N2 mixed gas in GIS equipment, based on the method for rapidly proportioning and mixing SF6 / N2 mixed gas in GIS equipment according to any one of claims 1 to 7, characterized in that: The module further includes a volume calculation module for obtaining geometric parameters of the GIS equipment and constructing a pipeline model, and deriving the effective volume of the GIS equipment based on the state equation; Kinetic modeling module, used to establish a kinetic model of SF6 / N2 diffusion law, and simulate gas flow, diffusion and mixing processes through the Standard k-ε model and component transport model; Spectral detection module, used to detect the concentration of mixed gas in real time using infrared spectroscopy to obtain mixing ratio data; The dynamic gas distribution control module is used to perform dynamic gas distribution control according to the detection results, and adjust the flow of each gas branch through the mass flow controller to achieve the target mixing ratio.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for quickly proportioning and mixing SF6 / N2 mixed gas in GIS equipment according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for quickly proportioning and mixing SF6 / N2 mixed gas in GIS equipment according to any one of claims 1 to 7 are implemented.

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