Thin film vacuum gauge optimization method and device, electronic equipment and storage medium

Abstract

The invention provides a thin film vacuum gauge optimization method and device, electronic equipment and a storage medium, and relates to the technical field of vacuum gauge structure optimization. The method comprises the steps of obtaining multiple pieces of capacitance data and multiple pieces of pressure data under different structure parameters through simulation, calculating sensitivities and linearity corresponding to the different structure parameters, obtaining optimal structure parameters according to the sensitivities and the linearity, and finally outputting a corresponding simulation model according to the optimal structure parameters to obtain a final model. Therefore, the optimal balance between the sensitivity and the linearity of the selected final model is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of vacuum gauge structure optimization, and in particular to a thin film vacuum gauge optimization method, device, electronic equipment and storage medium. Background Art

[0002] At present, in order to improve the performance of thin film vacuum gauges, improvements in structural design mainly rely on experimental methods. However, this method has shortcomings, such as high experimental cost, long cycle, and difficulty in fully covering all possible working conditions. Therefore, the introduction of simulation improvement methods has become a trend. By combining theoretical analysis with simulation simulation, various factors affecting the performance of thin film vacuum gauges, such as film materials, electrode structures, and sizes, can be studied more deeply, so as to propose more effective improvement plans. Simulation methods can not only reduce experimental costs and shorten R&D cycles, but also improve the accuracy and reliability of designs. However, when evaluating the performance of thin film vacuum gauges, the linearity and sensitivity of the capacitance-pressure curve are two key indicators. Among them, linearity reflects the linear relationship between the output signal of the vacuum gauge and the true pressure value. Good linearity means higher accuracy and reliability of the measurement results; while sensitivity describes the response ability of the vacuum gauge to small pressure changes. High-sensitivity vacuum gauges can capture more subtle pressure fluctuations and provide more accurate measurement data. However, the two performances check and balance each other. Improving sensitivity often means reducing linearity. Therefore, it is necessary to study a thin film vacuum gauge optimization method that can balance linearity and sensitivity.

[0003] There is currently no effective technical solution to the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a thin film vacuum gauge optimization method, device, electronic device and storage medium, the purpose of which is to find a set of optimal structural parameters so that the vacuum gauge achieves an optimal balance between sensitivity and linearity.

[0005] In a first aspect, the present invention provides a thin film vacuum gauge optimization method, comprising the steps of: S1. construct multiple simulation models of the thin film vacuum gauge based on COMSOL Multiphysics, and perform simulation tests on the multiple simulation models, wherein the multiple simulation models correspond to different structural parameters respectively; S2. Acquire multiple capacitance data and multiple pressure data under various structural parameters obtained from simulation experiments; S3. Obtaining corresponding sensitivity according to the plurality of capacitance data and the plurality of pressure data under each structural parameter; S4. Obtaining corresponding linearity according to the plurality of capacitance data and the plurality of pressure data under each structural parameter; S5. Obtain the optimal structural parameters according to each of the sensitivities and each of the linearities; S6. Output the corresponding simulation model according to the optimal structural parameters to obtain the final model.

[0006] Through the above settings, a set of optimal structural parameters is found, so that the vacuum gauge achieves the best balance between sensitivity and linearity.

[0007] Further, step S3 includes: According to the multiple capacitance data and multiple pressure data under each structural parameter; calculate the sensitivity using the following formula: ; Where, = ; In the formula, is the sensitivity corresponding to the th structural parameter; is the maximum pressure value among all the pressure data under the th structural parameter; is the minimum pressure value among all the pressure data under the th structural parameter; is the normalization constant, is the maximum capacitance value among all the capacitance data under the th structural parameter; is the minimum capacitance value among all the capacitance data under the th structural parameter, is the maximum pressure value among all the pressure data under the preset structural parameter; is the minimum pressure value among all the pressure data under the preset structural parameter; is the maximum capacitance value among all the capacitance data under the preset structural parameter; is the minimum capacitance value among all the capacitance data under the preset structural parameter.

[0008] Through the above settings, the capacitance data and pressure data obtained by simulation can be converted into quantifiable sensitivity indicators, providing a clear numerical basis for the optimization of subsequent steps and ensuring the effectiveness and reliability of the optimization process.

[0009] Further, step S4 includes: According to the multiple capacitance data and multiple pressure data under each structural parameter, calculate the linearity using the following formula: ; Where, = ; Wherein, is the linearity corresponding to the th structural parameter; is the total number of data points corresponding to each structural parameter. The abscissa of each data point corresponds to one of the pressure data, and the ordinate of each data point corresponds to one of the capacitance data; is the maximum pressure value among all the pressure data under the th structural parameter; is the th pressure data of the th data point under the th structural parameter; is the minimum pressure value among all the pressure data under the th structural parameter; is the maximum capacitance value among all the capacitance data under the th structural parameter; is the minimum capacitance value among all the capacitance data under the th structural parameter; is the th capacitance data of the th data point under the th structural parameter; is the maximum pressure value among all the pressure data under the preset structural parameter; is the minimum pressure value among all the pressure data under the preset structural parameter; is the maximum capacitance value corresponding to all the capacitance data under the preset structural parameter;

[0010] Through the above settings, the linearity values under different structural parameters are unified to a comparable scale, so as to facilitate optimization more conveniently.

[0011] Further, step S5 includes: Performing weighted calculation according to each of the sensitivities and each of the linearities and obtaining a minimum comprehensive value; Obtaining the corresponding optimal structural parameter according to the minimum comprehensive value.

[0012] Further, the step of performing weighted calculation according to each of the sensitivities and each of the linearities and obtaining a minimum comprehensive value includes: According to each of the sensitivities and each of the linearities, the following weighted formula is used to calculate the comprehensive value: ; In the formula, is the comprehensive value corresponding to the th structural parameter, is the weight coefficient; is the weight coefficient; is the sensitivity corresponding to the th structural parameter; is the linearity corresponding to the th structural parameter; Compare each of the comprehensive values to obtain the minimum comprehensive value.

[0013] Furthermore, step S1 includes: S11. Based on COMSOL Multiphysics, set up the initial model; S12. Perform parametric modeling according to the initial model to obtain a plurality of the simulation models for simulation tests.

[0014] Furthermore, the specific steps of step S12 include: S121. Set the material properties; S122. Determine the physical field configuration; S123. Configure the steady-state solver and perform the simulation test; S124. Add structural parameter scanning and preset the structural parameters to be scanned and the structural parameter scanning range of variation; S125. Perform structural parameter scanning and export all capacitance data and all pressure data corresponding to each structural parameter.

[0015] In a second aspect, the present invention provides a thin-film vacuum gauge optimization device, including: A modeling module, configured to build a plurality of simulation models of the thin-film vacuum gauge based on COMSOL Multiphysics and perform simulation tests on the plurality of simulation models, where the plurality of simulation models respectively correspond to different structural parameters; A first acquisition module, configured to acquire a plurality of capacitance data and a plurality of pressure data under each different structural parameter obtained from the simulation test; A second acquisition module, configured to acquire the corresponding sensitivities according to the plurality of capacitance data and the plurality of pressure data under each structural parameter; A third acquisition module, configured to acquire the corresponding linearities according to the plurality of capacitance data and the plurality of pressure data under each structural parameter; A fourth acquisition module, configured to acquire the optimal structural parameters according to each of the sensitivities and each of the linearities; An output module, configured to output the corresponding simulation model according to the optimal structural parameters to obtain a final model.

[0016] The thin-film vacuum gauge optimization device provided by the present invention effectively solves the problem of low efficiency of manual operation, shortens the optimization cycle, and improves the optimization efficiency and accuracy.

[0017] Through the collaborative work among various modules, the problem of low efficiency of manual operation is effectively solved, the optimization cycle is shortened, and the optimization efficiency and accuracy are improved.

[0018] In a third aspect, the present invention provides an electronic device, including a processor and a memory, where the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the thin-film vacuum gauge optimization method provided in the first aspect above are run.

[0019] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps in the thin-film vacuum gauge optimization method provided in the first aspect above are run.

[0020] As can be seen from the above, for the thin-film vacuum gauge optimization method, device, electronic device, and storage medium provided by the present invention, multiple capacitance data and multiple pressure data under different structural parameters are obtained through simulation, the sensitivity and linearity corresponding to different structural parameters are calculated, the optimal structural parameters are obtained through optimization according to each sensitivity and each linearity, and finally the corresponding simulation model is output according to the optimal structural parameters to obtain a final model, so as to ensure that the selected final model achieves the best balance between sensitivity and linearity.

[0021] Other features and advantages of the present invention will be described in the subsequent description, and part of them will become obvious from the description, or be understood by implementing the embodiments of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the structures specifically pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a schematic flowchart of the thin-film vacuum gauge optimization method in an embodiment of the present invention.

[0023] Figure 2 It is a schematic structural diagram of the thin-film vacuum gauge optimization device in an embodiment of the present invention.

[0024] Figure 3 It is a schematic structural diagram of the electronic device provided in an embodiment of the present invention.

[0025] Figure 4Schematic diagram of capacitance and pressure data obtained under different structural parameters provided by the embodiments of the present invention.

[0026] Figure 5 Schematic structural diagram of a thin-film vacuum gauge in the prior art.

[0027] Label description: 11, fixed electrode plate; 12, sensing diaphragm; 21, modeling module; 22, first acquisition module; 23, second acquisition module; 24, third acquisition module; 25, fourth acquisition module; 26, output module; 13, electronic device; 1301, processor; 1302, memory; 1303, communication bus. Detailed implementation manners

[0028] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The components of the embodiments of the present invention described and illustrated herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0029] It should be noted that: similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used for differential description and cannot be understood as indicating or implying relative importance.

[0030] In a first aspect, the present invention provides a method for optimizing a thin-film vacuum gauge, including the steps of: S1. Based on COMSOL Multiphysics, construct multiple simulation models of the thin-film vacuum gauge and conduct simulation tests on the multiple simulation models, where the multiple simulation models respectively correspond to different structural parameters; S2. Obtain multiple capacitance data and multiple pressure data under each structural parameter obtained from the simulation tests; S3. Obtain the corresponding sensitivity according to the multiple capacitance data and multiple pressure data under each structural parameter; S4. Obtain the corresponding linearity according to the multiple capacitance data and multiple pressure data under each structural parameter; S5. Obtain the optimal structural parameters according to each sensitivity and each linearity; S6. Output the corresponding simulation model according to the optimal structural parameters to obtain the final model.

[0031] This technical solution provides an optimization method for a thin-film vacuum gauge, aiming to solve the problem that it is difficult to balance the linearity and sensitivity of the thin-film vacuum gauge. This method first establishes multiple simulation models of thin-film vacuum gauges with different structural parameters through COMSOL Multiphysics software, and conducts simulation tests to simulate the performance of the vacuum gauge under different structural parameters. Then, capacitance data and pressure data are obtained from the simulation tests, and based on these data, the sensitivity and linearity corresponding to each structural parameter are calculated. Sensitivity reflects the sensitivity of the vacuum gauge to pressure changes, and linearity reflects the linear relationship between the output signal of the vacuum gauge and pressure. Next, optimization is carried out according to the calculated sensitivity and linearity, with the aim of finding a set of optimal structural parameters to achieve the best balance between the sensitivity and linearity of the vacuum gauge. Finally, the simulation model corresponding to the optimal structural parameters is output as the final design solution.

[0032] This technical solution uses simulation means to replace the traditional experimental method, reducing the experimental cost and cycle, and being able to achieve a good balance between sensitivity and linearity.

[0033] Among them, the structural parameters can be the thickness of the sensing diaphragm or the plate spacing (i.e., the distance between the sensing diaphragm and the fixed electrode), etc.

[0034] In practical applications, taking the plate spacing (i.e., Figure 5 shown) of the thin-film vacuum gauge of the existing technology (such as Figure 5 the straight-line distance between the sensing diaphragm 12 and the fixed plate 11 in the structure) h as an example, the change range of the parameter (plate spacing h) is set according to the actual working range of the designed thin-film vacuum gauge. Through this solution, capacitance-pressure relationship diagrams under different structural parameters (i.e., different plate spacings, for example, h1 = 3mm, h2 = 3.2mm, h3 = 3.6mm, h4 = 3.8mm, h5 = 4mm) are obtained through simulation, as shown in Figure 4 shown. Then, the capacitance data and pressure data corresponding to each h are subjected to the relevant calculations below, and the linearity and sensitivity corresponding to each structural parameter (such as h) can be obtained. Furthermore, the optimal structural parameters can be obtained based on the linearity and sensitivity. The above is only an example taking the plate spacing as an example. In practical applications, other key structural parameters of the thin-film vacuum gauge can be used for simulation, such as the thickness of the sensing diaphragm 12, but not limited to this.

[0035] In some embodiments, step S3 includes: According to multiple capacitance data and multiple pressure data under each structural parameter; the following formula is used to calculate the sensitivity; ; Among them, = ; In the formula, is the sensitivity corresponding to the th structural parameter; is the maximum pressure value among all pressure data under the th structural parameter; is the minimum pressure value among all pressure data under the th structural parameter; is the normalization constant, is the maximum capacitance value among all capacitance data under the th structural parameter; is the minimum capacitance value among all capacitance data under the th structural parameter, is the maximum pressure value among all pressure data under the preset structural parameter; is the minimum pressure value among all pressure data under the preset structural parameter; is the maximum capacitance value among all capacitance data under the preset structural parameter; is the minimum capacitance value among all capacitance data under the preset structural parameter.

[0036] Specifically, by normalizing the current pressure change rate and capacitance change rate with the corresponding values (common benchmark) of the preset structural parameter, the sensitivity values of different structural parameters can be compared under the common benchmark, ensuring the effectiveness and reliability of the optimization process. Therefore, according to the sensitivity calculation formula provided in this application, the simulated capacitance data and pressure data can be converted into quantifiable sensitivity indicators, providing a clear numerical basis for subsequent optimization and ensuring the effectiveness and reliability of the optimization process.

[0037] In some embodiments, step S4 includes: Calculating the linearity according to the multiple capacitance data and multiple pressure data under each structural parameter by using the following formula; ; Wherein, = ; In the formula, is the linearity corresponding to the th structural parameter; is the total number of data points corresponding to each structural parameter, the abscissa of each data point corresponds to a pressure data, and the ordinate of each data point corresponds to a capacitance data; is the maximum pressure value among all pressure data under the th structural parameter; is the th under the The pressure data of the data points; is the minimum pressure value among all the pressure data under the th structural parameter; is the maximum capacitance value among all the capacitance data under the th structural parameter; is the minimum capacitance value among all the capacitance data under the th structural parameter; is the capacitance data of the th data point under the th structural parameter; is the normalization constant; is the maximum pressure value among all the pressure data under the preset structural parameter; is the minimum pressure value among all the pressure data under the preset structural parameter; is the maximum capacitance value among all the capacitance data under the preset structural parameter; is the minimum capacitance value among all the capacitance data under the preset structural parameter, is the pressure data of the th data point under the preset structural parameter, is the capacitance data of the th data point under the preset structural parameter.

[0038] Specifically, by adopting this formula, the linearity of the thin-film vacuum gauge under different structural parameters can be quantitatively evaluated, making the calculation of linearity have a unified standard and avoiding the evaluation deviation caused by different calculation methods. In addition, a normalization constant is introduced in the formula, and this normalization constant is calculated based on the pressure and capacitance data under the preset structural parameter (the preset structural parameter is obtained from the empirical initial model, and the empirical initial model is a basic design model of the thin-film vacuum gauge established based on historical experimental data, industry standards or preliminary simulation verification, and its core purpose is to provide a scientific and reasonable initial value for the optimization of structural parameters). In order to unify the linearity values under different structural parameters to a comparable scale, thus making it more convenient to optimize, and further improving the operability of the thin-film vacuum gauge optimization method and the reliability of the results.

[0039] In some embodiments, step S5 includes: Performing weighted calculation based on each sensitivity and each linearity and obtaining the minimum comprehensive value; Obtaining the corresponding optimal structural parameter according to the minimum comprehensive value.

[0040] Specifically, by weighted calculation, sensitivity and linearity are comprehensively considered, and taking the minimum comprehensive value as the optimization goal, it is possible to effectively optimize according to sensitivity and linearity to obtain the optimal structural parameter and achieve the balance between sensitivity and linearity.

[0041] In some embodiments, the step of performing weighted calculation according to each sensitivity and each linearity and obtaining the minimum comprehensive value includes: According to each sensitivity and each linearity, calculate the comprehensive value using the following weighted formula: ; In the formula, is the comprehensive value corresponding to the th structural parameter, is the weight coefficient; is the weight coefficient; is the sensitivity corresponding to the th structural parameter; is the linearity corresponding to the th structural parameter; Compare each comprehensive value to obtain the minimum comprehensive value.

[0042] Specifically, first, weight coefficients are set for sensitivity and linearity respectively. These two weight coefficients can be adjusted according to the degree of emphasis on sensitivity and linearity in actual applications, which reflects the flexibility of the design. Then, a comprehensive value is calculated through the weighted formula. This comprehensive value reflects the overall performance of the structural parameter under the current weight allocation. By comparing the comprehensive values corresponding to different structural parameters and selecting the structural parameter corresponding to the minimum comprehensive value as the optimal structural parameter. This method transforms the multi-objective optimization problem into a single-objective optimization problem, making the optimization process clearer and more operable. By adjusting the weight coefficients, a trade-off can be made between sensitivity and linearity, so as to obtain the optimal thin-film vacuum gauge structural parameters that meet specific application requirements.

[0043] In some embodiments, step S1 includes: S11. Based on COMSOL Multiphysics, set the initial model; S12. Perform parametric modeling according to the initial model to obtain multiple simulation models for simulation tests.

[0044] Specifically, first, a basic initial model is established. This initial model serves as the basis for subsequent parametric modeling. On the basis of the initial model, using parametric modeling technology, by adjusting the model parameters, multiple simulation models with different structural parameters are quickly generated in batches for subsequent simulation tests. This method makes the construction process of the simulation model more systematic and efficient, facilitating parameter scanning and optimization design, and improving the efficiency and feasibility of simulation optimization.

[0045] In some embodiments, the specific steps of step S12 include: S121. Set the material properties; S122. Determine the physical field configuration; S123. Configure the steady-state solver and conduct simulation tests; S124. Add structural parameter scanning and preset the structural parameters to be scanned and the variation range of the structural parameter scanning; S125. Conduct structural parameter scanning and export all capacitance data and all pressure data corresponding to each structural parameter.

[0046] Through the above settings, the parametric modeling steps are made more operable, and the efficiency of the thin-film vacuum gauge optimization method is improved.

[0047] Among them, COMSOL Multiphysics is a simulation software of the prior art, and the specific simulation process and method will not be elaborated here.

[0048] In a second aspect, the present invention provides a thin-film vacuum gauge optimization device, including: A modeling module 21, configured to build multiple simulation models of the thin-film vacuum gauge based on COMSOL Multiphysics and conduct simulation tests on the multiple simulation models, where the multiple simulation models respectively correspond to different structural parameters; A first acquisition module 22, configured to acquire multiple capacitance data and multiple pressure data under various different structural parameters obtained from the simulation tests; A second acquisition module 23, configured to obtain the corresponding sensitivity according to the multiple capacitance data and multiple pressure data under each structural parameter; A third acquisition module 24, configured to obtain the corresponding linearity according to the multiple capacitance data and multiple pressure data under each structural parameter; A fourth acquisition module 25, configured to obtain the optimal structural parameters according to each sensitivity and each linearity; An output module 26, configured to output the corresponding simulation model according to the optimal structural parameters to obtain the final model.

[0049] The thin-film vacuum gauge optimization device provided by the present invention can find a set of optimal structural parameters, so that the vacuum gauge achieves the best balance between sensitivity and linearity, effectively solves the problem of low efficiency of manual operation, shortens the optimization cycle, and improves the optimization efficiency and accuracy.

[0050] This technical solution provides an optimization method for a thin-film vacuum gauge, aiming to solve the problem that it is difficult to balance the linearity and sensitivity of the thin-film vacuum gauge. This method first establishes multiple simulation models of thin-film vacuum gauges with different structural parameters through COMSOL Multiphysics software, and conducts simulation tests to simulate the performance of the vacuum gauge under different structural parameters. Then, capacitance data and pressure data are obtained from the simulation tests, and based on these data, the sensitivity and linearity corresponding to each structural parameter are calculated. Sensitivity reflects the sensitivity of the vacuum gauge to pressure changes, and linearity reflects the linear relationship between the output signal of the vacuum gauge and pressure. Next, optimization is carried out according to the calculated sensitivity and linearity, with the aim of finding a set of optimal structural parameters to achieve the best balance between the sensitivity and linearity of the vacuum gauge. Finally, the simulation model corresponding to the optimal structural parameters is output as the final design solution.

[0051] This technical solution uses simulation means to replace the traditional experimental method, reducing the experimental cost and cycle, and being able to achieve a good balance between sensitivity and linearity.

[0052] Among them, the structural parameters can be the thickness of the diaphragm or the distance between the diaphragm and the fixed electrode, etc.

[0053] In practical applications, taking the plate spacing (i.e., Figure 5 the straight-line distance between the sensing diaphragm 12 and the fixed plate 11 in the Figure 5 structure) h of the thin-film vacuum gauge of the existing technology (as shown) as an example, the change range of the parameter (plate spacing h) is set according to the actual working range of the designed thin-film vacuum gauge. Through this solution, capacitance-pressure relationship diagrams under different structural parameters (i.e., different plate spacings, for example, h1 = 3mm, h2 = 3.2mm, h3 = 3.6mm, h4 = 3.8mm, h5 = 4mm) are obtained through simulation, as shown in Figure 4 . Then, the capacitance data and pressure data corresponding to each h are subjected to the relevant calculations below, and the linearity and sensitivity corresponding to each structural parameter (such as h) can be obtained. Furthermore, the optimal structural parameters can be obtained based on the linearity and sensitivity. The above is only an example taking the plate spacing. In practical applications, other key structural parameters of the thin-film vacuum gauge can be used for simulation, such as the thickness of the sensing diaphragm 12, but not limited to this.

[0054] In some embodiments, when the second acquisition module 23 executes to obtain the corresponding sensitivity according to the multiple capacitance data and multiple pressure data under each structural parameter, it specifically executes: According to the multiple capacitance data and multiple pressure data under each structural parameter; the following formula is used to calculate the sensitivity; ; Among them, = ; In the formula, is the sensitivity corresponding to the th structural parameter; is the maximum pressure value among all the pressure data under the th structural parameter; is the minimum pressure value among all the pressure data under the th structural parameter; is the normalization constant, is the maximum capacitance value among all the capacitance data under the th structural parameter; is the minimum capacitance value among all the capacitance data under the th structural parameter, is the maximum pressure value among all the pressure data under the preset structural parameter; is the minimum pressure value among all the pressure data under the preset structural parameter; is the maximum capacitance value among all the capacitance data under the preset structural parameter; is the minimum capacitance value among all the capacitance data under the preset structural parameter.

[0055] Specifically, by normalizing the current pressure change rate and capacitance change rate with the corresponding values (common benchmark) of the preset structural parameters, the sensitivity values of different structural parameters can be compared under the common benchmark, ensuring the effectiveness and reliability of the optimization process. Therefore, according to the sensitivity calculation formula provided in this application, the simulated capacitance data and pressure data can be converted into quantifiable sensitivity indicators, providing a clear numerical basis for subsequent optimization and ensuring the effectiveness and reliability of the optimization process.

[0056] In some embodiments, when the third acquisition module 24 executes to obtain the corresponding linearity according to multiple capacitance data and multiple pressure data under each structural parameter, it specifically executes: According to multiple capacitance data and multiple pressure data under each structural parameter, calculate the linearity using the following formula; ; Wherein, = ; In the formula, is the linearity corresponding to the th structural parameter; is the total number of data points corresponding to each structural parameter. The abscissa of each data point corresponds to a pressure data, and the ordinate of each data point corresponds to a capacitance data; is the The maximum pressure value among all pressure data under a structural parameter; is the pressure data of the th data point under a structural parameter; is the minimum pressure value among all pressure data under a structural parameter; is the maximum capacitance value among all capacitance data under a structural parameter; is the minimum capacitance value among all capacitance data under a structural parameter; is the pressure data of the th data point under a structural parameter; is the normalization constant; is the maximum pressure value among all pressure data under the preset structural parameter; is the minimum pressure value among all pressure data under the preset structural parameter; is the maximum capacitance value among all capacitance data under the preset structural parameter; is the minimum capacitance value among all capacitance data under the preset structural parameter, is the pressure data of the th data point under the preset structural parameter, is the capacitance data of the

[0057] Specifically, by adopting this formula, the linearity of the thin-film vacuum gauge under different structural parameters can be quantitatively evaluated, making the calculation of linearity have a unified standard and avoiding evaluation deviations caused by different calculation methods. In addition, a normalization constant is introduced in the formula. This normalization constant is calculated based on the pressure and capacitance data under the preset structural parameter (the preset structural parameter is obtained from the empirical initial model, and the empirical initial model is a basic design model of the thin-film vacuum gauge established based on historical experimental data, industry standards, or preliminary simulation verification. Its core purpose is to provide a scientific and reasonable initial value for the optimization of structural parameters). In order to unify the linearity values under different structural parameters to a comparable scale, so as to facilitate optimization more conveniently, and thus improve the operability of the thin-film vacuum gauge optimization method and the reliability of the results.

[0058] In some embodiments, when the fourth acquisition module 25 executes to obtain the optimal structural parameter according to each sensitivity and each linearity, it specifically executes: Perform weighted calculation according to each sensitivity and each linearity and obtain the minimum comprehensive value; Obtain the corresponding optimal structural parameter according to the minimum comprehensive value.

[0059] Specifically, by weighted calculation, comprehensively considering sensitivity and linearity, and taking the minimum comprehensive value as the optimization goal, it is possible to effectively optimize according to sensitivity and linearity to obtain the optimal structural parameters and achieve a balance between sensitivity and linearity.

[0060] In some embodiments, when the fourth acquisition module 25 performs weighted calculation based on each sensitivity and each linearity and obtains the minimum comprehensive value, it specifically performs: According to each sensitivity and each linearity, calculate the comprehensive value using the following weighted formula: ; In the formula, is the comprehensive value corresponding to the th structural parameter, is the weight coefficient; is the weight coefficient; is the th sensitivity corresponding to the structural parameter; is the th linearity corresponding to the structural parameter; Compare each comprehensive value to obtain the minimum comprehensive value.

[0061] Specifically, first, weight coefficients are set for sensitivity and linearity respectively. These two weight coefficients can be adjusted according to the degree of emphasis on sensitivity and linearity in actual applications, which reflects the flexibility of the design. Then, a comprehensive value is calculated through the weighted formula. This comprehensive value reflects the overall performance of the structural parameters under the current weight allocation. By comparing the comprehensive values corresponding to different structural parameters and selecting the structural parameter corresponding to the minimum comprehensive value as the optimal structural parameter. This method transforms the multi-objective optimization problem into a single-objective optimization problem, making the optimization process clearer and more operable. By adjusting the weight coefficients, a trade-off can be made between sensitivity and linearity, so as to obtain the optimal thin-film vacuum gauge structural parameters that meet specific application requirements.

[0062] In some embodiments, when the modeling module 21 constructs multiple simulation models of the thin-film vacuum gauge based on COMSOL Multiphysics and conducts simulation tests on the multiple simulation models, and the multiple simulation models respectively correspond to different structural parameters, it specifically performs: S11. Based on COMSOL Multiphysics, set the initial model; S12. Perform parametric modeling based on the initial model to obtain multiple simulation models for simulation tests.

[0063] Specifically, first, a basic initial model is established, which serves as the basis for subsequent parametric modeling. Based on the initial model, parametric modeling technology is used to quickly generate multiple simulation models with different structural parameters in batches for subsequent simulation tests through adjusting model parameters. This method makes the construction process of simulation models more systematic and efficient, facilitating parameter scanning and optimal design, and improving the efficiency and feasibility of simulation optimization.

[0064] In some embodiments, when the modeling module 21 performs parametric modeling based on the initial model to obtain multiple simulation models for simulation tests, it specifically performs: S121. Set material properties; S122. Determine the physical field configuration; S123. Configure the steady-state solver and conduct simulation tests; S124. Add structural parameter scanning and preset the structural parameters to be scanned and the variation range of structural parameter scanning; S125. Conduct structural parameter scanning and export all capacitance data and all pressure data corresponding to each structural parameter.

[0065] Through the above settings, the parametric modeling steps are made more operable, improving the efficiency of the thin-film vacuum gauge optimization method.

[0066] Among them, COMSOL Multiphysics is a simulation software of the prior art, and the specific simulation process and method will not be elaborated here.

[0067] Please refer to Figure 3 , Figure 3A structural schematic diagram of an electronic device provided by an embodiment of the present invention. The present invention provides an electronic device 13, including: a processor 1301 and a memory 1302. The processor 1301 and the memory 1302 are interconnected and communicate with each other through a communication bus 1303 and / or other forms of connection mechanisms (not marked). The memory 1302 stores computer-readable instructions executable by the processor 1301. When the electronic device runs, the processor 1301 executes the computer-readable instructions to execute the thin-film vacuum gauge optimization method in any optional implementation manner of the above embodiment to achieve the following functions: constructing a plurality of simulation models of the thin-film vacuum gauge based on COMSOL Multiphysics, and performing simulation tests on the plurality of simulation models, where the plurality of simulation models respectively correspond to different structural parameters; obtaining a plurality of capacitance data and a plurality of pressure data under each structural parameter obtained from the simulation tests; obtaining the corresponding sensitivity according to the plurality of capacitance data and the plurality of pressure data under each structural parameter; obtaining the corresponding linearity according to the plurality of capacitance data and the plurality of pressure data under each structural parameter; obtaining the optimal structural parameter according to each sensitivity and each linearity; and outputting the corresponding simulation model according to the optimal structural parameter to obtain the final model.

[0068] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it executes the thin-film vacuum gauge optimization method in any optional implementation manner of the above embodiment to achieve the following functions: constructing a plurality of simulation models of the thin-film vacuum gauge based on COMSOL Multiphysics, and performing simulation tests on the plurality of simulation models, where the plurality of simulation models respectively correspond to different structural parameters; obtaining a plurality of capacitance data and a plurality of pressure data under each structural parameter obtained from the simulation tests; obtaining the corresponding sensitivity according to the plurality of capacitance data and the plurality of pressure data under each structural parameter; obtaining the corresponding linearity according to the plurality of capacitance data and the plurality of pressure data under each structural parameter; obtaining the optimal structural parameter according to each sensitivity and each linearity; and outputting the corresponding simulation model according to the optimal structural parameter to obtain the final model.

[0069] Among them, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM for short), electrically erasable programmable read-only memory (EEPROM for short), erasable programmable read-only memory (EPROM for short), programmable read-only memory (PROM for short), read-only memory (ROM for short), magnetic memory, flash memory, magnetic disk or optical disc.

[0070] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For another example, 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 displayed or discussed couplings or direct couplings or communication connections between each other can be through some communication interfaces. The indirect couplings or communication connections of devices or units can be electrical, mechanical or other forms.

[0071] In addition, the units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0072] Furthermore, in each embodiment of the present invention, the functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0073] In this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0074] The above are only embodiments of the present invention and are not intended to limit the protection scope of the present invention. For those skilled in the art, the present invention may have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An optimization method for a thin-film vacuum gauge, characterized in that, Including steps: S1. Based on COMSOL Multiphysics, construct multiple simulation models of a thin-film vacuum gauge, and conduct simulation tests on the multiple simulation models, where the multiple simulation models respectively correspond to different structural parameters; S2. Obtain multiple capacitance data and multiple pressure data under each structural parameter obtained from the simulation tests; S3. Obtain the corresponding sensitivity according to the multiple capacitance data and the multiple pressure data under each structural parameter; S4. Obtain the corresponding linearity according to the multiple capacitance data and the multiple pressure data under each structural parameter; S5. Obtain the optimal structural parameter according to each sensitivity and each linearity; S6. Output the corresponding simulation model according to the optimal structural parameter to obtain the final model.

2. The thin-film vacuum gauge optimization method according to claim 1, characterized in that Step S3 includes: According to the multiple capacitance data and the multiple pressure data under each structural parameter; calculate the sensitivity using the following formula; ； Among them, = ; Wherein, is the sensitivity corresponding to the th structural parameter; is the maximum pressure value among all the said pressure data under the th structural parameter; is the minimum pressure value among all the said pressure data under the th structural parameter; is the normalization constant, is the maximum capacitance value among all the said capacitance data under the th structural parameter; is the minimum capacitance value among all the said capacitance data under the th structural parameter, is the maximum pressure value among all the pressure data under the preset structural parameter; is the minimum pressure value among all the pressure data under the preset structural parameter; is the maximum capacitance value among all the capacitance data under the preset structural parameter; is the minimum capacitance value among all the capacitance data under the preset structural parameter.

3. The method for optimizing a thin-film vacuum gauge according to claim 1, wherein Step S4 includes: According to the multiple capacitance data and the multiple pressure data under each structural parameter, calculate the linearity using the following formula; ； Among them, = ; In the formula, is the linearity corresponding to the th structural parameter; is the total number of data points corresponding to each structural parameter. The abscissa of each data point corresponds to one of the said pressure data, and the ordinate of each data point corresponds to one of the said capacitance data; is the maximum pressure value among all the said pressure data under the th structural parameter; is the pressure data of the th data point under the th structural parameter; is the minimum pressure value among all the said pressure data under the th structural parameter; is the maximum capacitance value among all the said capacitance data under the th structural parameter; is the minimum capacitance value among all the said capacitance data under the th structural parameter; is the capacitance data of the th data point under the th structural parameter; is the normalization constant; is the maximum pressure value among all the pressure data under the preset structural parameter; is the minimum pressure value among all the pressure data under the preset structural parameter; is the maximum capacitance value corresponding to all the capacitance data under the preset structural parameter; is the minimum capacitance value among all the capacitance data under the preset structural parameter, is the pressure data of the th data point under the preset structural parameter, is the capacitance data of the th data point under the preset structural parameter.

4. The method for optimizing a thin-film vacuum gauge according to claim 1, characterized in that, Step S5 includes: Conduct weighted calculation according to each sensitivity and each linearity and obtain the minimum comprehensive value; Obtain the corresponding optimal structural parameter according to the minimum comprehensive value.

5. The thin-film vacuum gauge optimization method according to claim 4, characterized in that The step of conducting weighted calculation according to each sensitivity and each linearity and obtaining the minimum comprehensive value includes: According to each sensitivity and each linearity, calculate the comprehensive value using the following weighted formula: ； In the formula, is the comprehensive value corresponding to the th structural parameter, is the weight coefficient; is the weight coefficient; is the sensitivity corresponding to the th structural parameter; is the linearity corresponding to the th structural parameter; Compare each comprehensive value to obtain the minimum comprehensive value.

6. The method for optimizing a thin-film vacuum gauge according to claim 1, wherein Step S1 includes: S11. Based on COMSOL Multiphysics, set the initial model; S12. Conduct parametric modeling according to the initial model to obtain the multiple simulation models for simulation tests.

7. The method for optimizing a thin-film vacuum gauge according to claim 6, wherein The specific steps of step S12 include: S121. Set the material properties; S122. Determine the physical field configuration; S123. Configure the steady-state solver and conduct simulation tests; S124. Add structural parameter scanning and preset the structural parameters to be scanned and the structural parameter scanning range of variation; S125. Conduct structural parameter scanning and export all capacitance data and all pressure data corresponding to each structural parameter.

8. An optimized device for a thin-film vacuum gauge, characterized in that, Including: A modeling module, used to construct multiple simulation models of a thin-film vacuum gauge based on COMSOL Multiphysics, and conduct simulation tests on the multiple simulation models, where the multiple simulation models respectively correspond to different structural parameters; A first acquisition module, used to obtain multiple capacitance data and multiple pressure data under each different structural parameter obtained from the simulation tests; A second acquisition module, used to obtain the corresponding sensitivity according to the multiple capacitance data and the multiple pressure data under each structural parameter; A third acquisition module, used to obtain the corresponding linearity according to the multiple capacitance data and the multiple pressure data under each structural parameter; A fourth acquisition module, used to obtain the optimal structural parameter according to each sensitivity and each linearity; An output module, used to output the corresponding simulation model according to the optimal structural parameter to obtain the final model.

9. An electronic device, characterized in that, It includes a processor and a memory, and the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the thin-film vacuum gauge optimization method according to any one of claims 1-7 are run.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps in the thin-film vacuum gauge optimization method according to any one of claims 1-7 are run.

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