Gas mixing cabinet operation parameter correction system and method based on big data

Abstract

The present invention relates to the field of data analysis technology, and in particular to a system and method for correcting operating parameters of a gas mixing cabinet based on big data, comprising: importing physical characteristic data and gas type data into a mixed gas flow state change analysis model to analyze the flow state change of the mixed gas in the gas mixing cabinet; importing operating parameter data and gas type data into a gas mixing state change analysis model for the gas mixing cabinet to analyze the gas mixing state change in the gas mixing cabinet; evaluating the mixing uniformity of the mixed gas according to the mixed gas flow state change analysis results and the gas mixing state change analysis results; and correcting the operating parameters of the gas mixing cabinet according to the mixed gas mixing uniformity evaluation results, which can reduce material waste and defective product rate caused by uneven mixing, reduce production costs, and improve the production efficiency of welding shielding gas.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a system and method for correcting operating parameters of a gas mixing cabinet based on big data. Background Art

[0002] In the current industrial manufacturing field, welding technology is a key connection process, and its quality is directly related to the structural strength and service life of the product. The mixing ratio of the shielding gas during welding is an indispensable link to ensure the quality of welding. With the continuous advancement of science and technology, gas mixing cabinets, as important equipment for achieving precise gas mixing, have been widely used in various welding scenarios. However, in the actual operation of the gas mixing cabinet, it is affected by many factors, including fluctuations in gas purity, errors in the mixing ratio, insufficient mixing uniformity, and unstable pressure and flow control. These factors may lead to poor gas protection during welding, which in turn affects the quality of the welded joint, such as the generation of pores, cracks, or welding deformation. Therefore, how to ensure the stability and accuracy of the operating parameters of the gas mixing cabinet has become a hot spot and difficulty in the current research in the welding field.

[0003] Especially in large-scale, high-intensity welding operations, the welding process has more stringent requirements for shielding gas. Traditional manual adjustment and empirical operation can no longer meet the needs of modern industry for high-quality welding. In addition, the complexity and variability of the welding environment, such as changes in temperature, humidity, air pressure and other factors, will also affect the operating parameters of the mixing cabinet. If these deviations are not corrected in time, it may lead to inconsistent gas protection effects during welding, which in turn affects the quality and consistency of the welded joints.

[0004] When using a gas mixing cabinet to mix welding shielding gas, the prior art usually only focuses on the influence of gas mixing ratio and pressure flow control on the final gas quality, and improves welding quality by optimizing these parameters. However, although this approach is effective to a certain extent, it ignores the profound influence of the gas flow state in the gas mixing cabinet on the mixing effect. In fact, the flow state of the mixed gas, especially the laminar flow and turbulent flow phenomena, has a significant impact on the mixing uniformity and efficiency of the welding shielding gas. In the gas mixing cabinet, the flow state of the gas is affected by many factors such as gas flow rate, mixing chamber design, and gas viscosity. In the laminar state, the gas flows in an orderly layer, and the mixing between each layer is limited, which may lead to uneven mixing of the shielding gas, thereby affecting the welding quality. In the turbulent state, the gas flows in a turbulent state, forming vortices, which promotes full mixing between gases and improves mixing uniformity. However, turbulence may also bring higher pressure losses and increase energy consumption.

[0005] Therefore, it is not enough for the existing technology to simply optimize the mixing ratio and pressure flow control. It is necessary to comprehensively consider the influence of gas flow state and gas mixing state to improve the uniformity of gas mixing inside the mixing chamber of the gas mixing cabinet, thereby improving the mixing effect of welding shielding gas and welding quality. Summary of the invention

[0006] In order to overcome the defects and shortcomings of the prior art, the present invention provides a gas mixing cabinet operation parameter correction system and method based on big data, which comprehensively analyzes the flow state changes of the mixed gas and the gas mixing state changes, and evaluates the mixing uniformity of the mixed gas according to the comprehensive analysis results; thereby correcting the operation parameters of the gas mixing cabinet. It can reduce material waste and defective product rate caused by uneven mixing, reduce production costs, and improve the production efficiency of welding shielding gas.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] One of the purposes of the present invention is to provide a method for correcting operating parameters of a gas mixing cabinet based on big data, comprising the following steps:

[0009] S1. Obtaining the physical characteristic data and operating parameter data of the gas mixing cabinet, and simultaneously obtaining the gas type data input into the gas mixing cabinet;

[0010] S2. Importing the physical characteristic data and gas type data into the mixed gas flow pattern change analysis model to analyze the flow pattern change of the mixed gas in the gas mixing cabinet;

[0011] S3, importing the operating parameter data and gas type data into the gas mixing cabinet gas mixing state change analysis model, and analyzing the gas mixing state change in the gas mixing cabinet;

[0012] S4. Evaluate the mixing uniformity of the mixed gas according to the analysis results of the flow pattern change of the mixed gas and the analysis results of the gas mixing state change;

[0013] S5. Correct the operating parameters of the gas mixing cabinet based on the mixed gas uniformity assessment results.

[0014] In one implementation of the present invention, step S2 includes the following specific steps:

[0015] S21, extracting the physical characteristic data of the gas mixing cabinet and the gas type data input into the gas mixing cabinet;

[0016] S22, importing the physical characteristic data and gas type data into the flow pattern variation coefficient calculation formula to calculate the flow pattern variation coefficient of the mixed gas; the flow pattern variation coefficient calculation formula is:

[0017] ;

[0018] In the formula, LT represents the flow change coefficient of the mixed gas, Indicates the wall roughness of the mixing cabinet input pipeline in the physical characteristic data, n indicates the number of gas types, Indicates the mixing ratio of the i-th gas in the gas type data, It represents the density of the i-th gas in the gas type data, vi represents the input speed of the i-th gas in the gas type data when it is input into the gas mixing cabinet, di represents the inner diameter of the input pipeline of the i-th gas in the physical characteristic data, ui represents the gas viscosity of the i-th gas in the gas type data, and i is any one of 1 to n.

[0019] In one implementation of the present invention, step S3 includes the following specific contents:

[0020] S31, extracting the operating parameter data of the gas mixing cabinet and the gas type data input into the gas mixing cabinet;

[0021] S32, substituting the operating parameter data and the gas type data into the gas mixing state variation coefficient calculation formula to calculate the gas mixing state variation coefficient in the gas mixing cabinet; the gas mixing state variation coefficient calculation formula is:

[0022] ;

[0023] Wherein, HZ represents the coefficient of change of the gas mixing state in the mixing cabinet, P and T represent the preset pressure and preset temperature of the mixing cabinet in the operating parameter data, respectively, Po and To represent the average pressure and average temperature of the mixing cabinet in the cavity state in the operating parameter data, respectively, V represents the volume of the mixing cavity in the mixing cabinet, Qi represents the input volume of the i-th gas in the gas type data, Ci represents the concentration of the i-th gas in the gas type data, and fi represents the volume fraction of the i-th gas in the gas type data.

[0024] In one implementation of the present invention, step S4 includes the following specific steps:

[0025] S41, obtaining the calculated flow state variation coefficient of the mixed gas and the gas mixing state variation coefficient in the gas mixing cabinet;

[0026] S42, substituting the flow pattern variation coefficient of the mixed gas and the gas mixing state variation coefficient in the gas mixing cabinet into the mixing uniformity coefficient calculation formula to calculate the mixing uniformity coefficient of the mixed gas; the mixing uniformity coefficient calculation formula is:

[0027] ;

[0028] Where HJ represents the mixing uniformity of the mixed gas, a1 and a2 represent the gas flow pattern influence ratio and the mixing state influence ratio.

[0029] In one implementation of the present invention, step S5 includes the following specific steps:

[0030] S51, obtaining the calculated mixing uniformity coefficient of the mixed gas;

[0031] S52, preset a mixing uniformity threshold, and when the mixing uniformity coefficient of the mixed gas is less than the mixing uniformity threshold, issue a gas mixing cabinet operation parameter correction warning to the operator.

[0032] One of the purposes of the present invention is to provide a gas mixing cabinet operation parameter correction system based on big data, comprising:

[0033] A data acquisition module is used to acquire the physical characteristic data and operating parameter data of the gas mixing cabinet, and also acquire the gas type data input into the gas mixing cabinet;

[0034] The flow pattern change analysis module is used to import the physical characteristic data and gas type data into the mixed gas flow pattern change analysis model to analyze the flow pattern change of the mixed gas in the gas mixing cabinet;

[0035] A mixing state change analysis module is used to import the operating parameter data and gas type data into the gas mixing state change analysis model of the gas mixing cabinet to analyze the gas mixing state change in the gas mixing cabinet;

[0036] A mixing uniformity evaluation module is used to evaluate the mixing uniformity of the mixed gas based on the flow pattern change analysis results of the mixed gas and the gas mixing state change analysis results;

[0037] An operating parameter correction module is used to correct the operating parameters of the gas mixing cabinet according to the mixed gas uniformity evaluation result;

[0038] A control module is used to control the operation of the data acquisition module, the flow state change analysis module, the mixing state change analysis module, the mixing uniformity evaluation module, and the operation parameter correction module.

[0039] One of the objects of the present invention is to provide an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a mixing cabinet operating parameter correction method based on big data by calling the computer program stored in the memory.

[0040] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0041] The present invention imports physical characteristic data and gas type data into the mixed gas flow state change analysis model to analyze the flow state change of the mixed gas in the gas mixing cabinet; imports operating parameter data and gas type data into the gas mixing state change analysis model of the gas mixing cabinet to analyze the gas mixing state change in the gas mixing cabinet; evaluates the mixing uniformity of the mixed gas according to the mixed gas flow state change analysis results and the gas mixing state change analysis results; and corrects the operating parameters of the gas mixing cabinet according to the mixed gas mixing uniformity evaluation results. The present invention can reduce material waste and defective product rate caused by uneven mixing, reduce production costs, and improve the production efficiency of welding shielding gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0043] Figure 1 It is a schematic diagram of the overall process of the gas mixing cabinet operation parameter correction method based on big data of the present invention;

[0044] Figure 2 It is a structural schematic diagram of the gas mixing cabinet operation parameter correction system based on big data of the present invention;

[0045] Figure 3 It is a flow chart of the preparation of mixed gas in the gas mixing cabinet operation parameter correction method based on big data of the present invention. DETAILED DESCRIPTION

[0046] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0047] Example 1

[0048] like Figure 1 As shown, this embodiment provides a method for correcting operating parameters of a gas mixing cabinet based on big data, which specifically includes the following steps:

[0049] S1. Obtaining the physical characteristic data and operating parameter data of the gas mixing cabinet, and simultaneously obtaining the gas type data input into the gas mixing cabinet;

[0050] S2. Importing the physical characteristic data and gas type data into the mixed gas flow pattern change analysis model to analyze the flow pattern change of the mixed gas in the gas mixing cabinet;

[0051] S3, importing the operating parameter data and gas type data into the gas mixing cabinet gas mixing state change analysis model, and analyzing the gas mixing state change in the gas mixing cabinet;

[0052] S4. Evaluate the mixing uniformity of the mixed gas according to the analysis results of the flow pattern change of the mixed gas and the analysis results of the gas mixing state change;

[0053] S5. Correct the operating parameters of the gas mixing cabinet based on the mixed gas uniformity assessment results.

[0054] like Figure 3 As shown, the preparation flow chart of the mixed gas in the gas mixing cabinet operation parameter correction method based on big data provided in this embodiment; in this embodiment, Figure 3 The gas group to be mixed is composed of gases of different components. When the gas to be mixed is sent into the gas mixing cabinet for uniform mixing in this embodiment, it is necessary to conduct a comprehensive analysis of the changes in gas flow state and gas mixing state, and evaluate the gas mixing uniformity in the gas mixing cavity in the gas mixing cabinet based on the comprehensive analysis results, so as to ensure that the gas can be fully mixed and achieve the required uniformity. Finally, the mixed gas whose mixing uniformity evaluation result is greater than or equal to the mixing uniformity threshold is sent to the gas storage tank for storage. The gas storage tank in this embodiment is a container that can accommodate and maintain a stable gas pressure, which can ensure that the mixed gas can be stably supplied when needed. When the mixing uniformity evaluation result is less than the mixing uniformity threshold, the operating parameters of the gas mixing cabinet are corrected to ensure that the gas can be fully mixed and achieve the required uniformity.

[0055] In this embodiment, step S2 calculates the flow variation coefficient of the mixed gas by combining the physical characteristic data of the mixing cabinet with the gas type data input into the mixing cabinet. It can help analyze the mixing uniformity of the mixed gas and optimize the working performance of the mixing cabinet. Step S2 of this embodiment comprehensively considers the physical structure and gas characteristics of the mixing cabinet to ensure the comprehensiveness and accuracy of the calculation results. Specifically, the wall roughness reflects the friction resistance of the internal pipeline of the mixing cabinet, which directly affects the flow state of the gas; and the inner diameter of the input pipeline determines the channel size of the gas flow, affecting the flow rate and mixing effect. The density and viscosity in the gas type data are key parameters for describing the physical properties of the gas. The density affects the inertial force of the gas, while the viscosity affects the internal friction of the gas. The two together determine the flow characteristics of the gas. The input speed and mixing ratio directly reflect the flow behavior and mixing degree of the gas in the mixing cabinet, and are important indicators for evaluating the mixing uniformity of the mixed gas after this embodiment. Step S2 provides a specific formula for calculating the flow pattern variation coefficient, which can reflect the flow stability, mixing efficiency and possible flow unevenness of the gas inside the mixing cabinet by comprehensively considering the physical characteristics of the mixing cabinet and the gas properties. For example, when the flow pattern variation coefficient is small, it may indicate that the gas flow is unstable or the mixing is uneven, and the physical parameters of the mixing cabinet or the gas input conditions need to be adjusted; when the flow pattern variation coefficient is large, it indicates that the gas flow is stable and the mixing is uniform, which can meet the actual application requirements. In this embodiment, step S2 includes the following specific steps:

[0056] S21, extracting the physical characteristic data of the gas mixing cabinet and the gas type data input into the gas mixing cabinet;

[0057] S22, importing the physical characteristic data and gas type data into the flow pattern variation coefficient calculation formula to calculate the flow pattern variation coefficient of the mixed gas; the flow pattern variation coefficient calculation formula is:

[0058] ;

[0059] In the formula, LT represents the flow change coefficient of the mixed gas, Indicates the wall roughness of the input pipeline of the mixing cabinet in the physical characteristic data, n indicates the number of gas types, Indicates the mixing ratio of the i-th gas in the gas type data, It represents the density of the i-th gas in the gas type data, vi represents the input speed of the i-th gas in the gas type data when it is input into the gas mixing cabinet, di represents the inner diameter of the input pipeline of the i-th gas in the physical characteristic data, ui represents the gas viscosity of the i-th gas in the gas type data, and i is any one of 1 to n.

[0060] In this embodiment, step S3 calculates the coefficient of variation of the gas mixing state in the gas mixing cabinet by extracting the operating parameter data of the gas mixing cabinet and the gas type data input into the gas mixing cabinet. It can help analyze the mixing uniformity of the mixed gas and provide a scientific basis for optimizing the operating performance of the gas mixing cabinet. In step S3, the operating parameters and gas characteristics of the gas mixing cabinet are comprehensively considered to ensure the comprehensiveness and accuracy of the calculation results. The preset pressure and temperature in the operating parameters determine the mixing state of the gas in the gas mixing cabinet, which directly affects the flow and mixing process of the gas. The average pressure and average temperature in the cavity state reflect the environmental conditions of the gas mixing cabinet and are the benchmark parameters for evaluating the gas mixing effect. The input volume, concentration and volume fraction in the gas type data describe the input characteristics and mixing ratio of the gas, and are key indicators for evaluating the mixing uniformity. In this embodiment, step S3 can quantitatively analyze the mixing state of the gas in the gas mixing cabinet by calculating the coefficient of variation of the gas mixing state. The gas mixing state variation coefficient combines the operating parameters and gas characteristics, and can reflect the mixing efficiency of the gas in the gas mixing cabinet. In this embodiment, step S3 includes the following specific contents:

[0061] S31, extracting the operating parameter data of the gas mixing cabinet and the gas type data input into the gas mixing cabinet;

[0062] S32, substituting the operating parameter data and the gas type data into the gas mixing state variation coefficient calculation formula to calculate the gas mixing state variation coefficient in the gas mixing cabinet; the gas mixing state variation coefficient calculation formula is:

[0063] ;

[0064] Wherein, HZ represents the coefficient of change of the gas mixing state in the mixing cabinet, P and T represent the preset pressure and preset temperature of the mixing cabinet in the operating parameter data, respectively, Po and To represent the average pressure and average temperature of the mixing cabinet in the cavity state in the operating parameter data, respectively, V represents the volume of the mixing cavity in the mixing cabinet, Qi represents the input volume of the i-th gas in the gas type data, Ci represents the concentration of the i-th gas in the gas type data, and fi represents the volume fraction of the i-th gas in the gas type data.

[0065] In this embodiment, step S4 comprehensively considers two key factors: the flow state change and the mixing state change of the gas, ensuring the comprehensiveness and accuracy of the evaluation results. The flow state change coefficient reflects the flow state and stability of the gas in the mixing cabinet, that is, the change in the physical properties of the gas during the input and mixing process. The mixing state change coefficient reflects the mixing effect of the gas in the mixing cabinet, that is, the mixing uniformity of the gas under different input conditions and operating parameters. By taking these two coefficients into consideration, the mixing uniformity of the mixed gas can be evaluated more comprehensively. Step S4 can quantitatively analyze the overall mixing effect of the mixed gas by calculating the mixing uniformity coefficient, thereby optimizing the operating parameters of the mixing cabinet to improve the mixing uniformity and improve the working efficiency and reliability of the mixing cabinet; in this embodiment, step S4 includes the following specific steps:

[0066] S41, obtaining the calculated flow state variation coefficient of the mixed gas and the gas mixing state variation coefficient in the gas mixing cabinet;

[0067] S42, substituting the flow pattern variation coefficient of the mixed gas and the gas mixing state variation coefficient in the gas mixing cabinet into the mixing uniformity coefficient calculation formula to calculate the mixing uniformity coefficient of the mixed gas; the mixing uniformity coefficient calculation formula is:

[0068] ;

[0069] Where HJ represents the mixing uniformity of the mixed gas, a1 and a2 represent the gas flow pattern influence ratio and the mixing state influence ratio.

[0070] In this embodiment, step S5 includes the following specific steps:

[0071] S51, obtaining the calculated mixing uniformity coefficient of the mixed gas;

[0072] S52, preset a mixing uniformity threshold, when the mixing uniformity coefficient of the mixed gas is less than the mixing uniformity threshold, issue a warning to the operator to correct the operating parameters of the mixing cabinet. Among them, the gas flow pattern influence ratio coefficient, the mixing state influence ratio coefficient and the mixing uniformity threshold are obtained by: obtaining 2000 sets of physical characteristic data, operating parameter data and gas type data input into the mixing cabinet; substituting the physical characteristic data, operating parameter data and gas type data input into the mixing cabinet into the mixing uniformity coefficient calculation formula to calculate the mixing uniformity coefficient of 2000 sets of mixed gases; obtaining the corresponding mixing uniformity judgment results of 2000 sets of mixed gases, importing the mixing uniformity coefficient and the mixing uniformity judgment results into the fitting software, and outputting the corresponding gas flow pattern influence ratio coefficient, the mixing state influence ratio coefficient and the mixing uniformity threshold value that meet the highest mixing uniformity judgment accuracy.

[0073] Example 2

[0074] like Figure 2 As shown, this embodiment provides a gas mixing cabinet operation parameter correction system based on big data, including:

[0075] A data acquisition module is used to acquire the physical characteristic data and operating parameter data of the gas mixing cabinet, and also acquire the gas type data input into the gas mixing cabinet;

[0076] The flow pattern change analysis module is used to import the physical characteristic data and gas type data into the mixed gas flow pattern change analysis model to analyze the flow pattern change of the mixed gas in the gas mixing cabinet;

[0077] A mixing state change analysis module is used to import the operating parameter data and gas type data into the gas mixing state change analysis model of the gas mixing cabinet to analyze the gas mixing state change in the gas mixing cabinet;

[0078] A mixing uniformity evaluation module is used to evaluate the mixing uniformity of the mixed gas based on the flow pattern change analysis results of the mixed gas and the gas mixing state change analysis results;

[0079] An operating parameter correction module is used to correct the operating parameters of the gas mixing cabinet according to the mixed gas uniformity evaluation result;

[0080] The control module is used to control the operation of the data acquisition module, the flow state change analysis module, the mixing state change analysis module, the mixing uniformity evaluation module, and the operation parameter correction module.

[0081] The above-mentioned parameters and steps for each unit module to realize the corresponding functions in the big data-based gas mixing cabinet operating parameter correction system of the present invention can refer to the parameters and steps in the embodiment of the big data-based gas mixing cabinet operating parameter correction method above, and will not be repeated here.

[0082] Example 3

[0083] An electronic device according to an embodiment of the present invention comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a method for correcting the operating parameters of a gas mixing cabinet based on big data by calling the computer program stored in the memory. It should be noted that all computer programs of the method for correcting the operating parameters of a gas mixing cabinet based on big data are implemented in C language, wherein the data acquisition module, the flow state change analysis module, the mixing state change analysis module, the mixing uniformity evaluation module, the operating parameter correction module and the control module are all controlled by a remote server.

[0084] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0085] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0086] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks.

[0087] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for correcting the operating parameters of a mixing cabinet based on big data, characterized in that: The steps include: S1. Obtaining the physical characteristic data and operating parameter data of the gas mixing cabinet, and simultaneously obtaining the gas type data input into the gas mixing cabinet; S2. Importing the physical characteristic data and gas type data into the mixed gas flow pattern change analysis model to analyze the flow pattern change of the mixed gas in the gas mixing cabinet; S3, importing the operating parameter data and gas type data into the gas mixing cabinet gas mixing state change analysis model, and analyzing the gas mixing state change in the gas mixing cabinet; S4. Evaluate the mixing uniformity of the mixed gas according to the analysis results of the flow pattern change of the mixed gas and the analysis results of the gas mixing state change; S5. Correct the operating parameters of the gas mixing cabinet according to the mixed gas uniformity evaluation results; The step S2 comprises the following specific steps: S21, extracting the physical characteristic data of the gas mixing cabinet and the gas type data input into the gas mixing cabinet; S22, importing the physical characteristic data and gas type data into the flow pattern variation coefficient calculation formula to calculate the flow pattern variation coefficient of the mixed gas; the flow pattern variation coefficient calculation formula is: ； In the formula, LT represents the flow change coefficient of the mixed gas, Indicates the wall roughness of the mixing cabinet input pipeline in the physical characteristic data, n indicates the number of gas types, Indicates the mixing ratio of the i-th gas in the gas type data, It represents the density of the i-th gas in the gas type data, vi represents the input speed of the i-th gas in the gas type data when it is input into the gas mixing cabinet, di represents the inner diameter of the input pipeline of the i-th gas in the physical characteristic data, ui represents the gas viscosity of the i-th gas in the gas type data, and i is any one of 1 to n.

2. The method for correcting the operating parameters of a gas mixing cabinet based on big data according to claim 1 is characterized in that: The step S3 includes the following specific contents: S31, extracting the operating parameter data of the gas mixing cabinet and the gas type data input into the gas mixing cabinet; S32, substituting the operating parameter data and the gas type data into the gas mixing state variation coefficient calculation formula to calculate the gas mixing state variation coefficient in the gas mixing cabinet; the gas mixing state variation coefficient calculation formula is: ； Wherein, HZ represents the coefficient of change of the gas mixing state in the mixing cabinet, P and T represent the preset pressure and preset temperature of the mixing cabinet in the operating parameter data, respectively, Po and To represent the average pressure and average temperature of the mixing cabinet in the cavity state in the operating parameter data, respectively, V represents the volume of the mixing cavity in the mixing cabinet, Qi represents the input volume of the i-th gas in the gas type data, Ci represents the concentration of the i-th gas in the gas type data, and fi represents the volume fraction of the i-th gas in the gas type data.

3. The method for correcting the operating parameters of a gas mixing cabinet based on big data according to claim 2 is characterized in that: The step S4 comprises the following specific steps: S41, obtaining the calculated flow state variation coefficient of the mixed gas and the gas mixing state variation coefficient in the gas mixing cabinet; S42, substituting the flow pattern variation coefficient of the mixed gas and the gas mixing state variation coefficient in the gas mixing cabinet into the mixing uniformity coefficient calculation formula to calculate the mixing uniformity coefficient of the mixed gas; the mixing uniformity coefficient calculation formula is: ； Where HJ represents the mixing uniformity of the mixed gas, a1 and a2 represent the gas flow pattern influence ratio and the mixing state influence ratio.

4. The method for correcting the operating parameters of a gas mixing cabinet based on big data according to claim 3 is characterized in that: The step S5 comprises the following specific steps: S51, obtaining the calculated mixing uniformity coefficient of the mixed gas; S52, preset a mixing uniformity threshold, and when the mixing uniformity coefficient of the mixed gas is less than the mixing uniformity threshold, issue a gas mixing cabinet operation parameter correction warning to the operator.

5. A gas mixing cabinet operating parameter correction system based on big data, used to implement the gas mixing cabinet operating parameter correction method based on big data described in any one of claims 1 to 4, characterized in that: The system comprises: A data acquisition module is used to acquire the physical characteristic data and operating parameter data of the gas mixing cabinet, and also acquire the gas type data input into the gas mixing cabinet; The flow pattern change analysis module is used to import the physical characteristic data and gas type data into the mixed gas flow pattern change analysis model to analyze the flow pattern change of the mixed gas in the gas mixing cabinet; A mixing state change analysis module is used to import the operating parameter data and gas type data into the gas mixing state change analysis model of the gas mixing cabinet to analyze the gas mixing state change in the gas mixing cabinet; A mixing uniformity evaluation module is used to evaluate the mixing uniformity of the mixed gas based on the flow pattern change analysis results of the mixed gas and the gas mixing state change analysis results; An operating parameter correction module is used to correct the operating parameters of the gas mixing cabinet according to the mixed gas uniformity evaluation result; A control module is used to control the operation of the data acquisition module, the flow state change analysis module, the mixing state change analysis module, the mixing uniformity evaluation module, and the operation parameter correction module.

6. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes the big data-based gas mixing cabinet operating parameter correction method as described in any one of claims 1 to 4 by calling the computer program stored in the memory.

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