Vacuum seal leakage rate prediction method, device, equipment and medium

Abstract

The invention discloses a vacuum sealing leakage rate prediction method and device, equipment and a medium. The method comprises the following steps: constructing a three-dimensional microstructure model of a flange sealing surface according to a processing mode of the flange sealing surface; based on the three-dimensional microstructure model, establishing leakage micro-channels between the sealed contact interfaces in different contact states, analyzing channel characteristics, and determining flow characteristics of leakage media in the leakage micro-channels in different contact states; constructing a first leakage rate prediction model represented by the microscopic characteristic parameters according to the working environment parameters and the physical attributes and flow characteristics of the leakage medium; and constructing a mapping relation between the macroscopic design parameters and the microscopic characteristic parameters through characteristic multi-scale coupling, and substituting the mapping relation into the first leakage rate prediction model to obtain a second leakage rate prediction model driven by the macroscopic design parameters so as to predict the vacuum sealing leakage rate. The method has the advantages of high precision, strong adaptability and good engineering practicability.

Description

Technical Field

[0001] The present invention relates to the field of seal detection technology, and in particular to a vacuum seal leakage rate prediction method, device, equipment and medium. Background Art

[0002] Sealing technology is a crucial means of ensuring the safe and stable operation of various industrial devices and is widely used in aerospace, petrochemicals, energy equipment, vacuum systems, and other fields. In practical engineering applications, leakage in sealing structures can lead to dielectric loss, system failure, and even safety incidents. Therefore, reliable evaluation of sealing performance and accurate prediction of leakage rates remain core concerns in this field.

[0003] Existing sealing leakage rate prediction methods usually rely on simplified microchannel leakage models, empirical regression models and experimental methods, and have the following shortcomings: the sealing leakage microchannel is over-simplified into flat narrow slits, isosceles triangle slits and trapezoidal slits, etc., which makes it difficult to accurately describe the three-dimensional roughness characteristics of the real contact surface, especially the complex geometric morphology such as non-contact areas and groove structures at the microscale. Due to the lack of joint modeling of the micromorphology and contact state of the sealing interface, the existing models cannot effectively construct the spatial geometric characteristics of the leakage path under the contact state, resulting in large deviations in leakage rate prediction and lack of engineering applicability. The medium in the leakage microchannel may exist in multiple flow states at the same time, but most models only use a single flow form for modeling, which cannot fully cover the flow behavior under different channel scales and pressure conditions. There is a lack of multi-scale coupling mapping relationship between the micro-contact characteristics and the macro-design parameters, making it difficult to realize a quantitative sealing leakage rate prediction model for the engineering design link with macro-design parameters as input. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a vacuum seal leakage rate prediction method, device, equipment and medium, which combines the interface micromorphology characteristics, leakage channel flow mechanism and macro-microscale mapping relationship, and can achieve high-precision and highly adaptable seal leakage rate prediction, providing a quantitative evaluation method for the engineering design and optimization of sealing structures.

[0005] The present invention provides a vacuum seal leakage rate prediction method, comprising: Obtaining working environment parameters of the sealing structure, sealing design parameters, and physical properties of the leaking medium, wherein the sealing design parameters include the processing method of the flange sealing surface; Constructing a three-dimensional microscopic morphology model of the flange sealing surface according to the processing method; Based on the three-dimensional micromorphology model, establishing leakage microchannels between the sealed contact interfaces under different contact states and analyzing channel characteristics, and determining flow characteristics of the leakage medium in the leakage microchannels corresponding to the different contact states; Constructing a first leakage rate prediction model characterized by microscopic characteristic parameters according to the working environment parameters, the physical properties of the leakage medium, and the flow characteristics; Based on the sealing design parameters and the three-dimensional microscopic morphology model, a mapping relationship between macroscopic design parameters and microscopic characteristic parameters is constructed through characteristic multi-scale coupling; The mapping relationship is substituted into the first leakage rate prediction model to obtain a second leakage rate prediction model driven by macro-design parameters to perform vacuum seal leakage rate prediction.

[0006] As an improvement to the above solution, the three-dimensional microscopic morphology model of the flange sealing surface is constructed according to the processing method, including: Determine the surface topography height distribution of the corresponding flange sealing surface according to different processing methods; According to the surface morphology height distribution corresponding to the processing method, if the height of the surface morphology is uniformly distributed in the x-axis direction and the y-axis direction, an isotropic three-dimensional rough surface profile is constructed to obtain a three-dimensional microscopic morphology model corresponding to the processing method; if the height of the surface morphology is inconsistently distributed in the x-axis direction and the y-axis direction, an anisotropic three-dimensional rough surface profile is constructed to obtain a three-dimensional microscopic morphology model corresponding to the processing method.

[0007] As an improvement to the above solution, the method of establishing leakage microchannels between sealed contact interfaces under different contact states and analyzing channel characteristics based on the three-dimensional micromorphology model includes: The contact between the sealing ring and the flange sealing surface is equivalent to the contact between a rigid plane and the three-dimensional micro-morphology model to form a contact domain; wherein the uncontacted space in the contact domain constitutes a leakage microchannel; Obtaining a first distance under different contact states based on the contact domain, and determining the volume ratio of the uncontacted space in the contact domain under different contact states in combination with the roughness of the flange sealing surface in the sealing design parameters; the first distance being the distance between the rigid plane and the height average plane of the three-dimensional rough surface profile; Based on the three-dimensional micromorphology model, the first distance and the roughness, respectively calculating the minimum leakage microchannel diameter and the maximum leakage microchannel diameter in the contact domain under different contact states; determining the fractal dimension of the uncontacted space in the contact domain according to the volume proportion of the uncontacted space, the minimum leakage microchannel diameter, and the maximum leakage microchannel diameter; The uncontacted space in the contact domain is equivalent to a curved capillary bundle, and the length of a single capillary is determined based on the diameter of the leakage microchannel corresponding to the capillary, the sealing contact surface width in the sealing design parameters, the volume ratio of the uncontacted space, and the fractal dimension.

[0008] As an improvement to the above solution, the determining of the flow characteristics of the leaking medium in the leaking microchannel corresponding to different contact states includes: For each leakage microchannel, calculating the Knudsen number corresponding to the leakage microchannel according to the diameter of the leakage microchannel, the working environment parameters, and the physical properties of the leakage medium; If the Knudsen number is less than or equal to a preset first threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is a continuous flow; If the Knudsen number is greater than the first threshold and less than or equal to a preset second threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is slip flow; If the Knudsen number is greater than the second threshold and less than or equal to a preset third threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is a transition flow; If the Knudsen number is greater than the third threshold, the flow characteristic of the leakage medium in the corresponding leakage microchannel is determined to be molecular flow; wherein the first threshold is less than the second threshold, and the second threshold is less than the third threshold.

[0009] As an improvement to the above solution, the first leakage rate prediction model characterized by microscopic characteristic parameters is constructed based on the working environment parameters, the physical properties of the leakage medium, and the flow characteristics, including: According to the working environment parameters, the physical properties of the leakage medium, the flow characteristics and the length of the capillary, a leakage rate prediction model for a single leakage microchannel with flow characteristics in continuous flow, slip flow, transition flow and molecular flow is constructed respectively; According to the integral operation of the leakage rate prediction model of the single leakage microchannel, a first leakage rate prediction model characterized by microscopic characteristic parameters is determined; the microscopic characteristic parameters include but are not limited to fractal dimension, characteristic scale parameter, and the volume ratio of the first distance to the uncontact space in the contact domain.

[0010] As an improvement to the above solution, the mapping relationship between macro design parameters and micro feature parameters is constructed based on the sealing design parameters and the three-dimensional micro morphology model through feature multi-scale coupling, including: The structure function method is used to analyze the rough contours of the samples with different preset processing methods. The first mapping relationship between different processing methods, different roughness and the fractal dimension of the three-dimensional rough surface morphology is established, as well as the second mapping relationship between different processing methods, different roughness and the characteristic scale parameters of the three-dimensional rough surface morphology. Based on the three-dimensional micromorphology model, the first mapping relationship and the second mapping relationship, a finite element contact simulation model is constructed and simulated for the three-dimensional rough surface profiles at different scales. Then, based on the response surface method, the simulation results are analyzed and a third mapping relationship between the first distance and the macro design parameters is constructed; the macro design parameters include but are not limited to the processing method, roughness, apparent contact area, material properties and sealing preload of the flange sealing surface.

[0011] As an improvement to the above solution, based on the three-dimensional micro-morphology model, the first mapping relationship, and the second mapping relationship, a finite element contact simulation model is constructed for three-dimensional rough surface profiles at different scales and simulation is performed, and then the simulation results are analyzed based on the response surface methodology to construct a third mapping relationship between the first distance and the macro design parameter, including: Based on the three-dimensional micro-morphology model, the first mapping relationship, and the second mapping relationship, a finite element contact simulation model is established between the three-dimensional rough surface profile and the rigid plane for three-dimensional rough surface profiles with different processing methods, different roughness, different apparent contact areas, and different material properties; Based on the finite element contact simulation model, simulation results are obtained by applying different sealing preload forces on a rigid plane, wherein the simulation results include the first distance; According to the simulation results, multivariate nonlinear regression data fitting in the response surface method is used to construct a third mapping relationship between the first distance and the processing method, the roughness, the apparent contact area, the material properties, and the sealing preload force.

[0012] The present invention also provides a vacuum seal leakage rate prediction device, comprising: A data acquisition module is used to obtain the working environment parameters of the sealing structure, the sealing design parameters, and the physical properties of the leaking medium. The sealing design parameters include the processing method of the flange sealing surface; A contact surface reconstruction module, used to construct a three-dimensional microscopic morphology model of the flange sealing surface according to the processing method; a characteristic analysis module for establishing, based on the three-dimensional microscopic morphology model, leakage microchannels between the sealed contact interfaces under different contact states and analyzing the channel characteristics, thereby determining the flow characteristics of the leakage medium in the leakage microchannels corresponding to the different contact states; A model building module, configured to build a first leakage rate prediction model characterized by microscopic characteristic parameters according to the working environment parameters, the physical properties of the leakage medium, and the flow characteristics; A parameter mapping module, configured to construct a mapping relationship between macroscopic design parameters and microscopic feature parameters through feature multi-scale coupling based on the sealing design parameters and the three-dimensional microscopic morphology model; The leakage rate prediction module is used to substitute the mapping relationship into the first leakage rate prediction model to obtain a second leakage rate prediction model driven by macro design parameters to predict the vacuum seal leakage rate.

[0013] The present invention also provides a computer device, comprising a processor and a memory, wherein a computer program is stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, the vacuum seal leakage rate prediction method described in any one of the above items is implemented.

[0014] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any of the above-mentioned vacuum seal leakage rate prediction methods.

[0015] Compared with the prior art, the vacuum seal leakage rate prediction method, device, equipment and medium provided by the present invention have the following beneficial effects: By constructing a three-dimensional micromorphology model of the flange sealing surface according to the processing method, the micromorphology of the sealing contact interface is accurately reconstructed, thereby achieving improved prediction accuracy; based on the three-dimensional micromorphology model, leakage microchannels between the sealing contact interfaces under different contact states are established and the channel characteristics are analyzed, the flow characteristics of the leakage medium in the leakage microchannels corresponding to different contact states are determined, and then a first leakage rate prediction model represented by micro-characteristic parameters is constructed. This model can comprehensively consider the evolution law of the geometric structure of the leakage microchannel under different contact states, and reasonably divide the flow characteristic types based on the relationship between the microchannel size characteristics and the gas flow scale, thereby achieving refined modeling of leakage behavior in the entire flow domain, significantly improving the accuracy and applicability of the sealing leakage rate prediction; based on the sealing design parameters and the three-dimensional micromorphology model, combined with finite element contact simulation, a multi-scale coupling relationship between the macro design parameters and the micro characteristic parameters is established, thereby forming a second leakage rate prediction model driven by the macro design parameters for vacuum sealing leakage rate prediction. The present invention can solve the problems in the existing technology such as insufficient accuracy of interface morphology modeling, fuzzy division of microscopic channel flow mechanism, and decoupling of leakage rate calculation model from engineering design parameters. It has high precision, strong adaptability and good engineering practicality, and is particularly suitable for fields such as nuclear energy equipment, aerospace, etc. that have extremely high requirements for sealing reliability, and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 1 is a flow chart of a method for predicting a vacuum seal leakage rate provided by an embodiment of the present invention; Figure 2Schematic diagram of a finite element simulation model of contact between a rigid plane and a three-dimensional rough surface topography provided by an embodiment of the present invention; Figure 3 This is a schematic diagram of a three-dimensional rough surface profile provided by an embodiment of the present invention; Figure 4 This is a flowchart of an application example of a vacuum seal leakage rate prediction method provided by an embodiment of the present invention; Figure 5 1 is a schematic structural diagram of a vacuum seal leakage rate prediction device provided by an embodiment of the present invention; Figure 6 is a structural diagram of a computer device provided by an embodiment of the present invention; The accompanying drawings are numerals as follows: 1. Rigid plane; 2. Three-dimensional rough contour surface; 3. Contact surface; 4. Uncontacted space; 5. Contact domain. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] See also Figure 1 , Figure 1 : is a flow chart of a vacuum seal leakage rate prediction method provided by an embodiment of the present invention. The vacuum seal leakage rate prediction method includes: S1: Obtaining working environment parameters of the sealing structure, sealing design parameters, and physical properties of the leaking medium, wherein the sealing design parameters include a processing method of the flange sealing surface; S2: constructing a three-dimensional microscopic morphology model of the flange sealing surface according to the processing method; S3: Based on the three-dimensional micromorphology model, establishing leakage microchannels between the sealed contact interfaces under different contact states and analyzing channel characteristics, and determining flow characteristics of the leakage medium in the leakage microchannels corresponding to the different contact states; S4: constructing a first leakage rate prediction model characterized by microscopic characteristic parameters according to the working environment parameters, the physical properties of the leakage medium, and the flow characteristics; S5: Based on the sealing design parameters and the three-dimensional micro-morphology model, constructing a mapping relationship between macro-design parameters and micro-feature parameters through feature multi-scale coupling; S6: Substitute the mapping relationship into the first leakage rate prediction model to obtain a second leakage rate prediction model driven by macro-design parameters to perform vacuum seal leakage rate prediction.

[0019] Specifically, according to the actual working conditions, the working environment parameters of the sealing structure, the physical properties of the leaking medium, and the sealing design parameters at the macro level are obtained. Among them, the working environment parameters of the sealing structure include the type of sealing medium, the pressure difference and average pressure etc.; physical properties of the leaking medium, including molecular weight , viscosity and temperature etc.; Sealing design parameters include the processing method of flange sealing surface and roughness , sealing structure dimensions, sealing material properties , sealing preload , Sealing contact surface width For example, the processing methods include turning, grinding, polishing, lapping, etc. Different processing methods will produce different microscopic morphologies on the flange surface.

[0020] First, in step S2, a three-dimensional microscopic morphology model of the sealing contact surface is accurately reconstructed. In step S3, the characteristics of the leakage microchannels between the sealing contact interfaces under different contact states are established, and the flow characteristics of the medium in the leakage microchannels with different geometric characteristics are determined based on the leakage microchannel characteristics. Then, in step S4, a leakage rate calculation model based on the characterization of microscopic characteristic parameters is established according to the flow characteristics of the medium in the leakage microchannel, that is, the first leakage rate prediction model. Then, in step S5, based on multi-scale coupling analysis, a mapping relationship between the microscopic characteristic parameters and the macroscopic sealing design parameters is constructed, and then in step S6, a second leakage rate prediction model driven by the macroscopic design parameters is established to realize the vacuum sealing leakage rate prediction and the quantitative evaluation of the sealing performance.

[0021] As one of the optional embodiments, constructing a three-dimensional microscopic morphology model of the flange sealing surface according to the processing method includes: Determine the surface topography height distribution of the corresponding flange sealing surface according to different processing methods; According to the surface morphology height distribution corresponding to the processing method, if the height of the surface morphology is uniformly distributed in the x-axis direction and the y-axis direction, an isotropic three-dimensional rough surface profile is constructed to obtain a three-dimensional microscopic morphology model corresponding to the processing method; if the height of the surface morphology is inconsistently distributed in the x-axis direction and the y-axis direction, an anisotropic three-dimensional rough surface profile is constructed to obtain a three-dimensional microscopic morphology model corresponding to the processing method.

[0022] Specifically, the governing equation of the three-dimensional micro-morphology model constructed in step S2 is determined by determining whether the processing method of the flange sealing surface is directional unbiased. If the processing method used results in the height of the flange surface micro-morphology formed in the x-axis and y-axis directions obeying the same Gaussian distribution, an isotropic three-dimensional rough surface profile is constructed, and the three-dimensional isotropic fractal function used in the corresponding three-dimensional micro-morphology model is: in, is the roughness height of the flange surface, Indicates the spatial coordinate position; is the sampling length; and are the fractal dimension and characteristic scale parameter of the isotropic surface, respectively; is the spatial frequency density parameter; is the total number of overlapping wrinkles on the rough surface, Indicates the rough surface overlapping folds; is the maximum spatial frequency ordinal number, Represents the spatial frequency ordinal number; For the Overlapping folds The random phase corresponding to the spatial frequency has a value range of .

[0023] If the processing method used results in inconsistent distribution of the height of the flange sealing surface in the x-axis and y-axis directions, an anisotropic three-dimensional rough surface profile is constructed, and the three-dimensional anisotropic fractal function used in the corresponding three-dimensional micromorphology model is: in, is the height of the rough topography of the flange surface; is the maximum spatial frequency ordinal number, Represents the spatial frequency ordinal number; and are the fractal dimension and characteristic scale parameter of the anisotropic three-dimensional rough surface profile in the x-axis direction, and are the fractal dimension and characteristic scale parameter of the anisotropic three-dimensional rough surface profile in the y-axis direction; is the spatial frequency density parameter; For the The random phase of the spatial frequency in the x-axis direction, For the The random phase of the spatial frequency in the y-axis direction has a value range of .

[0024] As one of the optional embodiments, establishing leakage microchannels between sealed contact interfaces under different contact states and analyzing channel characteristics based on the three-dimensional micromorphology model includes: The contact between the sealing ring and the flange sealing surface is equivalent to the contact between a rigid plane and the three-dimensional micro-morphology model to form a contact domain; wherein the uncontacted space in the contact domain constitutes a leakage microchannel; Obtaining a first distance under different contact states based on the contact domain, and determining the volume ratio of the uncontacted space in the contact domain under different contact states in combination with the roughness of the flange sealing surface in the sealing design parameters; the first distance being the distance between the rigid plane and the height average plane of the three-dimensional rough surface profile; Based on the three-dimensional micromorphology model, the first distance and the roughness, respectively calculating the minimum leakage microchannel diameter and the maximum leakage microchannel diameter in the contact domain under different contact states; determining the fractal dimension of the uncontacted space in the contact domain according to the volume proportion of the uncontacted space, the minimum leakage microchannel diameter, and the maximum leakage microchannel diameter; The uncontacted space in the contact domain is equivalent to a curved capillary bundle, and the length of a single capillary is determined based on the diameter of the leakage microchannel corresponding to the capillary, the sealing contact surface width in the sealing design parameters, the volume ratio of the uncontacted space, and the fractal dimension.

[0025] Specifically, see Figure 2 The contact between the sealing ring and the flange surface is equivalent to the contact between a rigid plane and the three-dimensional rough surface topography constructed in step S2, forming a corresponding contact domain. The gap region (i.e., uncontacted space) within the contact domain forms a potential fluid channel, namely, a leakage microchannel. To achieve more accurate leakage rate prediction, this example conducts a thorough analysis and quantification of the channel characteristics of the leakage microchannel.

[0026] Furthermore, when the rigid plane contacts the highest peak of the three-dimensional rough surface, it is in the initial contact state. The second distance between the highest peak of the three-dimensional rough surface and the height average plane of the three-dimensional rough surface is calculated to be ,in The first distance between the rigid plane and the three-dimensional rough surface height average plane under different contact states is Based on the first distance and the second distance, the volume ratio of the uncontacted space in the contact domain is calculated as follows: in, is the volume fraction of the uncontacted space in the contact domain.

[0027] Furthermore, the minimum leakage microchannel diameter and the maximum leakage microchannel diameter in the contact domain formed between the rigid plane and the three-dimensional rough surface under different contact states are calculated using the following formula: in, is the minimum leakage microchannel diameter, is the maximum leakage microchannel diameter, and are the fractal dimension and characteristic scale parameter of the surface, is the spatial frequency density parameter, is the maximum ordinal number corresponding to the spatial frequency, is the roughness, It is the first distance between the rigid plane and the height average plane of the three-dimensional rough surface morphology.

[0028] Furthermore, based on the volume ratio of the uncontacted space obtained by the above calculation , minimum leakage microchannel diameter and maximum leakage microchannel diameter , it is deduced that the fractal dimension of the uncontacted space in the contact domain formed between the rigid plane and the three-dimensional rough surface is: in, is the fractal dimension of the untouched space.

[0029] Furthermore, the uncontacted space in the contact domain formed between the rigid plane and the three-dimensional rough surface is equivalent to a curved capillary bundle, where the bending fractal dimension of the capillary is for: in, is the sealing contact surface width.

[0030] The length of a single capillary for: in, is the diameter of the leaking microchannel, is the sealing contact surface width, is the bending fractal dimension of the capillary.

[0031] As one of the optional embodiments, determining the flow characteristics of the leakage medium in the leakage microchannel corresponding to different contact states includes: For each leakage microchannel, calculating the Knudsen number corresponding to the leakage microchannel according to the diameter of the leakage microchannel, the working environment parameters, and the physical properties of the leakage medium; If the Knudsen number is less than or equal to a preset first threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is a continuous flow; If the Knudsen number is greater than the first threshold and less than or equal to a preset second threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is slip flow; If the Knudsen number is greater than the second threshold and less than or equal to a preset third threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is a transition flow; If the Knudsen number is greater than the third threshold, the flow characteristic of the leakage medium in the corresponding leakage microchannel is determined to be molecular flow; wherein the first threshold is less than the second threshold, and the second threshold is less than the third threshold.

[0032] Specifically, in step S3, the equation followed when determining the flow characteristics of the medium in the leaking microchannel in the contact domain is as follows: in, is the Knudsen number; is the collision diameter of the leaking gas molecules; is the Boltzmann constant; is the molecular temperature of the leaking gas; is the average pressure in the leaking microchannel.

[0033] Calculate the Knudsen number corresponding to each leaky microchannel , and further, according to the Knudsen number The size of determines the flow characteristics in the leaky microchannel: when When the diameter satisfies The flow characteristics in the leakage microchannel are continuous flow based on Navier-Stokes; for The corresponding leakage microchannel diameter when ; when When the diameter satisfies The flow characteristic in the leakage microchannel is slip flow; for The corresponding leakage microchannel diameter when ; when When the diameter satisfies The flow characteristics in the leakage microchannel are transitional flow; for The corresponding leakage microchannel diameter when ; when When the diameter satisfies The flow characteristics in the leakage microchannel are molecular flow.

[0034] Furthermore, in step S4, leakage rate prediction models based on continuous flow, slip flow, transition flow, and molecular flow are constructed respectively, thereby achieving refined modeling of leakage behavior in the entire flow domain, significantly improving the accuracy and applicability of sealing leakage rate prediction.

[0035] As one of the optional embodiments, constructing a first leakage rate prediction model characterized by microscopic characteristic parameters based on the working environment parameters, the physical properties of the leakage medium, and the flow characteristics includes: According to the working environment parameters, the physical properties of the leakage medium, the flow characteristics and the length of the capillary, a leakage rate prediction model for a single leakage microchannel with flow characteristics in continuous flow, slip flow, transition flow and molecular flow is constructed respectively; According to the integral operation of the leakage rate prediction model of the single leakage microchannel, a first leakage rate prediction model characterized by microscopic characteristic parameters is determined; the microscopic characteristic parameters include but are not limited to fractal dimension, characteristic scale parameter, and the volume ratio of the first distance to the uncontact space in the contact domain.

[0036] Specifically, based on the division of the medium flow characteristics in the leakage microchannel in step S3, a leakage rate model is established in which the flow characteristics of a single leakage microchannel are under continuous flow, slip flow, transition flow and molecular flow.

[0037] Governing equations of the leakage rate prediction model for a single leaky microchannel with continuous flow characteristics as follows: in, is the pressure difference at both ends of the sealing interface; is the viscosity coefficient of the leaking gas; is the diameter of the leaking microchannel; is the length of the capillary.

[0038] Governing equations of the leakage rate prediction model for a single leaky microchannel with slip flow characteristics as follows: in, is the Knudsen number.

[0039] Governing equations of the leakage rate prediction model for a single leaky microchannel with transitional flow characteristics as follows: in, is the average pressure of the sealing interface; is the temperature of the leaking gas; is the molecular weight of the leaked gas; is the universal gas constant.

[0040] Governing equations of the leakage rate prediction model for a single leaky microchannel with molecular flow characteristics as follows: in, is the pressure difference at both ends of the sealing interface; is the diameter of the leaking microchannel; is the length of the capillary; is the temperature of the leaking gas; is the molecular weight of the leaked gas; is the universal gas constant.

[0041] Furthermore, based on the leakage rate prediction model of the single leaking microchannel, the total leakage rate prediction model characterized by the microscopic characteristic parameters is solved, that is, the first leakage rate prediction model , the formula is as follows: when When: when When: when When: when When: in, The diameter is and The number of leaky microchannels, and .

[0042] As one of the optional embodiments, the mapping relationship between macro design parameters and micro feature parameters is constructed through feature multi-scale coupling based on the sealing design parameters and the three-dimensional micro-morphology model, including: The structure function method is used to analyze the rough contours of the samples with different preset processing methods. The first mapping relationship between different processing methods, different roughness and the fractal dimension of the three-dimensional rough surface morphology is established, as well as the second mapping relationship between different processing methods, different roughness and the characteristic scale parameters of the three-dimensional rough surface morphology. Based on the three-dimensional micromorphology model, the first mapping relationship and the second mapping relationship, a finite element contact simulation model is constructed and simulated for the three-dimensional rough surface profiles at different scales. Then, based on the response surface method, the simulation results are analyzed and a third mapping relationship between the first distance and the macro design parameters is constructed; the macro design parameters include but are not limited to the processing method, roughness, apparent contact area, material properties and sealing preload of the flange sealing surface.

[0043] As one of the optional embodiments, based on the three-dimensional micro-morphology model, the first mapping relationship, and the second mapping relationship, a finite element contact simulation model is constructed for three-dimensional rough surface profiles at different scales and simulation is performed, and then the simulation results are analyzed based on the response surface method to construct a third mapping relationship between the first distance and the macro design parameter, including: Based on the three-dimensional micro-morphology model, the first mapping relationship, and the second mapping relationship, a finite element contact simulation model is established between the three-dimensional rough surface profile and the rigid plane for three-dimensional rough surface profiles with different processing methods, different roughness, different apparent contact areas, and different material properties; Based on the finite element contact simulation model, simulation results are obtained by applying different sealing preload forces on a rigid plane, wherein the simulation results include the first distance; According to the simulation results, multivariate nonlinear regression data fitting in the response surface method is used to construct a third mapping relationship between the first distance and the processing method, the roughness, the apparent contact area, the material properties, and the sealing preload force.

[0044] Specifically, in step S5, roughness test specimens obtained by different processing methods are manufactured, and the roughness profiles of the roughness test specimens are extracted by an instrument. Furthermore, the roughness profiles of the specimens are analyzed based on the structure function method to establish a first mapping relationship between different processing methods, different roughness, and the fractal dimension of the three-dimensional rough surface morphology, as well as a second mapping relationship between different processing methods, different roughness, and the characteristic scale parameters of the three-dimensional rough surface morphology, using the following formula: in, is the fractal dimension of the three-dimensional rough surface morphology, Its corresponding mapping function; is the characteristic scale parameter of the three-dimensional rough surface morphology, Its corresponding mapping function; is the roughness, For the processing method.

[0045] Furthermore, based on the three-dimensional micro-morphology model of step S2, the first mapping relationship and the second mapping relationship, a three-dimensional rough surface profile with different apparent contact areas under different processing methods and different roughness is constructed. Specifically, the mapping relationship between the clear roughness and the fractal dimension and fractal characteristic scale parameter of the microscopic three-dimensional rough surface is substituted into the three-dimensional micro-morphology model of step S2 to reconstruct the three-dimensional rough surface profile with different processing methods, different roughness and different apparent contact areas. For example, Figure 3 As shown in the figure, a three-dimensional rough surface profile with a roughness of 0.8 μm was constructed by grinding.

[0046] Furthermore, a finite element contact simulation model is established for three-dimensional rough surface profiles with different processing methods and different roughness, and then the test points are designed based on the response surface method, and the test points are analyzed to construct the third mapping relationship. , different roughness , Different sealing surface contact areas and different material properties A finite element contact simulation model is established between each three-dimensional rough surface and the rigid plane by applying different compression loads on the rigid plane. (i.e. sealing preload) to simulate and obtain the simulation results, and extract the first distance between the rigid plane and the average plane of the three-dimensional rough surface profile height in the simulation results Furthermore, based on a large number of simulation analysis results, the multivariate nonlinear regression data fitting in the response surface method is used to construct the first distance between the rigid plane and the average plane of the three-dimensional rough surface profile height. Processing method of three-dimensional rough surface contour , roughness , apparent contact area , material properties , sealing preload The third mapping relationship is as follows: in, is a function of the third mapping relationship.

[0047] Furthermore, in step S6, the first leakage rate prediction model characterized by the microscopic characteristic parameters established in step S4 is used to predict the leakage rate of the first leakage rate. All microscopic characteristic parameters in the model are replaced by macroscopic variables, thus establishing a second leakage rate prediction model driven by macroscopic design parameters. , expressed as: in, is the material property, is the roughness, For processing methods, is the viscosity coefficient of the leaking gas, is the molecular weight of the leaked gas, is the temperature of the leaking gas, is the average pressure at the sealing interface, is the pressure difference across the sealing interface, is the apparent contact area, is the sealing preload, is the width of the sealing contact surface. The microscopic parameters are replaced by macroscopic sealing design parameters during the calculation process.

[0048] In a specific application example, Figure 4 As shown, first of all, according to the actual sealing conditions, the service environment and working conditions of the sealing structure are clarified, including the type of sealing medium, pressure difference and average pressure ; Identify the physical properties of the leaking medium, including molecular weight , viscosity and temperature ; Determine the macro-level sealing design parameters, including: 1) flange surface processing method of the sealing surface and roughness ; 2) Sealing structure dimensions; 3) Sealing material properties ;4) Sealing preload ;5) Sealing contact surface width ; The above design parameters are input into the second leakage rate prediction model constructed by the present invention. Calculate the overall leakage rate; If the calculated overall leakage rate meets the preset sealing leakage rate requirement, the design of the sealing structure is completed; If the calculated overall leakage rate does not meet the preset sealing leakage rate requirements, it is necessary to adjust the sealing design parameters at the macro level and re-calculate the second leakage rate prediction model constructed based on the present invention. Calculate the overall leakage rate until the leakage performance index is met, and complete the sealing structure design and overall leakage rate prediction.

[0049] Compared with the existing technology, the present invention can accurately reconstruct the microscopic morphology of the sealing contact interface, comprehensively consider the evolution law of the geometric structure of the leakage microchannel under different contact states, and based on the relationship between the microchannel size characteristics and the gas flow scale, reasonably divide the typical flow types such as continuous flow, slip flow, transition flow and molecular flow, thereby realizing the refined modeling of leakage behavior in the entire flow domain, significantly improving the accuracy and applicability of the sealing leakage rate prediction. The present invention further extracts the rough contour parameters through the structure function method, constructs the mapping relationship between the macro processing mode and the micro fractal characteristic parameters, and combines the finite element contact simulation to establish the multi-scale coupling relationship between the macro loading conditions and the micro contact state. On this basis, a prediction model driven by the macro design parameters and responded to the leakage rate is formed. This method effectively overcomes the problems of insufficient accuracy of interface morphology modeling, fuzzy division of micro channel flow mechanism, and decoupling of leakage rate calculation model from engineering design parameters in the existing technology. It has higher prediction accuracy and engineering practicality, and is particularly suitable for key fields such as nuclear energy and aerospace that have extremely high requirements for sealing reliability, and has broad application prospects.

[0050] Correspondingly, the present invention also provides a vacuum seal leakage rate prediction device, which can implement all the processes of the vacuum seal leakage rate prediction method in the above embodiment.

[0051] See also Figure 5 , Figure 5 : is a schematic diagram of the structure of a vacuum seal leakage rate prediction device provided by an embodiment of the present invention. The vacuum seal leakage rate prediction device includes: Data acquisition module 501, used to obtain working environment parameters of the sealing structure, sealing design parameters, and physical properties of the leaking medium, wherein the sealing design parameters include the processing method of the flange sealing surface; A contact surface reconstruction module 502 is used to construct a three-dimensional microscopic topography model of the flange sealing surface according to the processing method; a characteristic analysis module 503 for establishing leakage microchannels between sealed contact interfaces under different contact states based on the three-dimensional micromorphology model and analyzing channel characteristics to determine flow characteristics of the leakage medium in the leakage microchannels corresponding to the different contact states; A model building module 504 is configured to build a first leakage rate prediction model characterized by microscopic characteristic parameters according to the working environment parameters, the physical properties of the leakage medium, and the flow characteristics; A parameter mapping module 505 is configured to construct a mapping relationship between macroscopic design parameters and microscopic feature parameters through feature multi-scale coupling based on the sealing design parameters and the three-dimensional microscopic morphology model; The leakage rate prediction module 506 is configured to substitute the mapping relationship into the first leakage rate prediction model to obtain a second leakage rate prediction model driven by macro-design parameters, so as to perform vacuum seal leakage rate prediction.

[0052] Preferably, the three-dimensional microscopic morphology model of the flange sealing surface is constructed according to the processing method, including: Determine the surface topography height distribution of the corresponding flange sealing surface according to different processing methods; According to the surface morphology height distribution corresponding to the processing method, if the height of the surface morphology is uniformly distributed in the x-axis direction and the y-axis direction, an isotropic three-dimensional rough surface profile is constructed to obtain a three-dimensional microscopic morphology model corresponding to the processing method; if the height of the surface morphology is inconsistently distributed in the x-axis direction and the y-axis direction, an anisotropic three-dimensional rough surface profile is constructed to obtain a three-dimensional microscopic morphology model corresponding to the processing method.

[0053] Preferably, the step of establishing leakage microchannels between sealed contact interfaces under different contact states and analyzing channel characteristics based on the three-dimensional micromorphology model includes: The contact between the sealing ring and the flange sealing surface is equivalent to the contact between a rigid plane and the three-dimensional micro-morphology model to form a contact domain; wherein the uncontacted space in the contact domain constitutes a leakage microchannel; Obtaining a first distance under different contact states based on the contact domain, and determining the volume ratio of the uncontacted space in the contact domain under different contact states in combination with the roughness of the flange sealing surface in the sealing design parameters; the first distance being the distance between the rigid plane and the height average plane of the three-dimensional rough surface profile; Based on the three-dimensional micromorphology model, the first distance and the roughness, respectively calculating the minimum leakage microchannel diameter and the maximum leakage microchannel diameter in the contact domain under different contact states; determining the fractal dimension of the uncontacted space in the contact domain according to the volume proportion of the uncontacted space, the minimum leakage microchannel diameter, and the maximum leakage microchannel diameter; The uncontacted space in the contact domain is equivalent to a curved capillary bundle, and the length of a single capillary is determined based on the diameter of the leakage microchannel corresponding to the capillary, the sealing contact surface width in the sealing design parameters, the volume ratio of the uncontacted space, and the fractal dimension.

[0054] Preferably, the determining of the flow characteristics of the leakage medium in the leakage microchannel corresponding to different contact states includes: For each leakage microchannel, calculating the Knudsen number corresponding to the leakage microchannel according to the diameter of the leakage microchannel, the working environment parameters, and the physical properties of the leakage medium; If the Knudsen number is less than or equal to a preset first threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is a continuous flow; If the Knudsen number is greater than the first threshold and less than or equal to a preset second threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is slip flow; If the Knudsen number is greater than the second threshold and less than or equal to a preset third threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is a transition flow; If the Knudsen number is greater than the third threshold, the flow characteristic of the leakage medium in the corresponding leakage microchannel is determined to be molecular flow; wherein the first threshold is less than the second threshold, and the second threshold is less than the third threshold.

[0055] Preferably, the constructing of a first leakage rate prediction model characterized by microscopic characteristic parameters according to the working environment parameters, the physical properties of the leakage medium and the flow characteristics comprises: According to the working environment parameters, the physical properties of the leakage medium, the flow characteristics and the length of the capillary, a leakage rate prediction model for a single leakage microchannel with flow characteristics in continuous flow, slip flow, transition flow and molecular flow is constructed respectively; According to the integral operation of the leakage rate prediction model of the single leakage microchannel, a first leakage rate prediction model characterized by microscopic characteristic parameters is determined; the microscopic characteristic parameters include but are not limited to fractal dimension, characteristic scale parameter, and the volume ratio of the first distance to the uncontact space in the contact domain.

[0056] Preferably, the mapping relationship between macroscopic design parameters and microscopic characteristic parameters is constructed through characteristic multi-scale coupling based on the sealing design parameters and the three-dimensional microscopic morphology model, including: The structure function method is used to analyze the rough contours of the samples with different preset processing methods. The first mapping relationship between different processing methods, different roughness and the fractal dimension of the three-dimensional rough surface morphology is established, as well as the second mapping relationship between different processing methods, different roughness and the characteristic scale parameters of the three-dimensional rough surface morphology. Based on the three-dimensional micromorphology model, the first mapping relationship and the second mapping relationship, a finite element contact simulation model is constructed and simulated for the three-dimensional rough surface profiles at different scales. Then, based on the response surface method, the simulation results are analyzed and a third mapping relationship between the first distance and the macro design parameters is constructed; the macro design parameters include but are not limited to the processing method, roughness, apparent contact area, material properties and sealing preload of the flange sealing surface.

[0057] Preferably, based on the three-dimensional micro-morphology model, the first mapping relationship and the second mapping relationship, a finite element contact simulation model is constructed for three-dimensional rough surface profiles at different scales and simulation is performed, and then the simulation results are analyzed based on the response surface method to construct a third mapping relationship between the first distance and the macro design parameter, including: Based on the three-dimensional micro-morphology model, the first mapping relationship, and the second mapping relationship, a finite element contact simulation model is established between the three-dimensional rough surface profile and the rigid plane for three-dimensional rough surface profiles with different processing methods, different roughness, different apparent contact areas, and different material properties; Based on the finite element contact simulation model, simulation results are obtained by applying different sealing preload forces on a rigid plane, wherein the simulation results include the first distance; According to the simulation results, multivariate nonlinear regression data fitting in the response surface method is used to construct a third mapping relationship between the first distance and the processing method, the roughness, the apparent contact area, the material properties, and the sealing preload force.

[0058] In specific implementation, the working principle, control process and technical effects achieved by the vacuum seal leakage rate prediction device provided in the embodiment of the present invention are the same as those of the vacuum seal leakage rate prediction method in the above embodiment, and will not be repeated here.

[0059] See also Figure 6 , Figure 6 6 is a block diagram of a computer device provided in an embodiment of the present invention. The computer device includes: a processor 601, a memory 602, and a computer program stored in the memory 602 and executable on the processor 601. When the processor 601 executes the computer program, the steps of the aforementioned vacuum seal leakage rate prediction method embodiment are implemented. Alternatively, when the processor 601 executes the computer program, the functions of the modules / units in the aforementioned device embodiments are implemented.

[0060] For example, the computer program may be divided into one or more modules / units, which are stored in the memory 602 and executed by the processor 601 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program in the computer device.

[0061] The computer device may include, but is not limited to, a processor 601 and a memory 602. Those skilled in the art will appreciate that the schematic diagram is merely an example of a computer device and does not limit the computer device. The computer device may include more or fewer components than shown in the diagram, or may combine certain components or different components. For example, the computer device may also include input and output devices, network access devices, buses, and the like.

[0062] The processor 601 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor. The processor 601 is the control center of the computer device, connecting various parts of the entire computer device using various interfaces and lines.

[0063] The memory 602 can be used to store the computer programs and / or modules. The processor 601 implements the various functions of the computer device by running or executing the computer programs and / or modules stored in the memory 602 and accessing the data stored in the memory 602. The memory 602 may mainly include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function (such as a sound playback function, an image playback function, etc.); the data storage area may store data generated based on the use of the mobile phone (such as audio data, a phone book, etc.). In addition, the memory 602 may include high-speed random access memory and non-volatile memory, such as a hard disk, internal memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0064] If the module / unit integrated into the computer device is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention can also implement all or part of the process steps in the above-mentioned method embodiments by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by the processor 601, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, software distribution medium, etc.

[0065] An embodiment of the present invention further provides a computer-readable storage medium, which includes a stored computer program. When the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the vacuum seal leakage rate prediction method described in any of the above embodiments.

[0066] The present invention provides a vacuum seal leakage rate prediction method, device, equipment and medium, which have the following beneficial effects: by constructing a three-dimensional micromorphology model of the flange sealing surface according to the processing method, the micromorphology of the sealing contact interface is accurately reconstructed, thereby achieving improved prediction accuracy; based on the three-dimensional micromorphology model, leakage microchannels between the sealing contact interfaces under different contact states are established and the channel characteristics are analyzed, the flow characteristics of the leakage medium in the leakage microchannels corresponding to the different contact states are determined, and then a first leakage rate prediction model characterized by micro characteristic parameters is constructed, which can comprehensively consider the evolution law of the geometric structure of the leakage microchannel under different contact states, and reasonably divide the flow characteristic types based on the relationship between the microchannel size characteristics and the gas flow scale, thereby achieving refined modeling of leakage behavior in the entire flow domain, and significantly improving the accuracy and applicability of the sealing leakage rate prediction; based on the sealing design parameters and the three-dimensional micromorphology model, combined with finite element contact simulation, a multi-scale coupling relationship between the macro design parameters and the micro characteristic parameters is established, thereby forming a second leakage rate prediction model driven by the macro design parameters to predict the vacuum seal leakage rate. The present invention can solve the problems in the existing technology such as insufficient accuracy of interface morphology modeling, fuzzy division of microscopic channel flow mechanism, and decoupling of leakage rate calculation model from engineering design parameters. It has high precision, strong adaptability and good engineering practicality, and is particularly suitable for fields such as nuclear energy equipment, aerospace, etc. that have extremely high requirements for sealing reliability, and has broad application prospects.

[0067] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for predicting vacuum seal leakage rate, characterized in that: include: Obtaining working environment parameters of the sealing structure, sealing design parameters, and physical properties of the leaking medium, wherein the sealing design parameters include the processing method of the flange sealing surface; Constructing a three-dimensional microscopic morphology model of the flange sealing surface according to the processing method; Based on the three-dimensional micromorphology model, establishing leakage microchannels between the sealed contact interfaces under different contact states and analyzing channel characteristics, and determining flow characteristics of the leakage medium in the leakage microchannels corresponding to the different contact states; Constructing a first leakage rate prediction model characterized by microscopic characteristic parameters according to the working environment parameters, the physical properties of the leakage medium, and the flow characteristics; Based on the sealing design parameters and the three-dimensional microscopic morphology model, a mapping relationship between macroscopic design parameters and microscopic characteristic parameters is constructed through characteristic multi-scale coupling; The mapping relationship is substituted into the first leakage rate prediction model to obtain a second leakage rate prediction model driven by macro-design parameters to perform vacuum seal leakage rate prediction.

2. The vacuum seal leakage rate prediction method according to claim 1, wherein: The three-dimensional microscopic morphology model of the flange sealing surface is constructed according to the processing method, including: Determine the surface topography height distribution of the corresponding flange sealing surface according to different processing methods; According to the surface morphology height distribution corresponding to the processing method, if the height of the surface morphology is uniformly distributed in the x-axis direction and the y-axis direction, an isotropic three-dimensional rough surface profile is constructed to obtain a three-dimensional microscopic morphology model corresponding to the processing method; if the height of the surface morphology is inconsistently distributed in the x-axis direction and the y-axis direction, an anisotropic three-dimensional rough surface profile is constructed to obtain a three-dimensional microscopic morphology model corresponding to the processing method.

3. The vacuum seal leakage rate prediction method according to claim 1, wherein: The method of establishing leakage microchannels between sealed contact interfaces under different contact states based on the three-dimensional micromorphology model and analyzing channel characteristics includes: The contact between the sealing ring and the flange sealing surface is equivalent to the contact between a rigid plane and the three-dimensional micro-morphology model to form a contact domain; wherein the uncontacted space in the contact domain constitutes a leakage microchannel; Obtaining a first distance under different contact states based on the contact domain, and determining the volume ratio of the uncontacted space in the contact domain under different contact states in combination with the roughness of the flange sealing surface in the sealing design parameters; the first distance being the distance between the rigid plane and the height average plane of the three-dimensional rough surface profile; Calculating the minimum leakage microchannel diameter and the maximum leakage microchannel diameter in the contact domain under different contact states based on the three-dimensional microscopic topography model, the first distance, and the roughness; determining the fractal dimension of the uncontacted space in the contact domain according to the volume proportion of the uncontacted space, the minimum leakage microchannel diameter, and the maximum leakage microchannel diameter; The uncontacted space in the contact domain is equivalent to a curved capillary bundle, and the length of a single capillary is determined based on the diameter of the leakage microchannel corresponding to the capillary, the sealing contact surface width in the sealing design parameters, the volume ratio of the uncontacted space, and the fractal dimension.

4. The vacuum seal leakage rate prediction method according to claim 3, wherein: The determining of the flow characteristics of the leakage medium in the leakage microchannel corresponding to different contact states includes: For each leakage microchannel, calculating the Knudsen number corresponding to the leakage microchannel according to the diameter of the leakage microchannel, the working environment parameters, and the physical properties of the leakage medium; If the Knudsen number is less than or equal to a preset first threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is a continuous flow; If the Knudsen number is greater than the first threshold and less than or equal to a preset second threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is slip flow; If the Knudsen number is greater than the second threshold and less than or equal to a preset third threshold, determining that the flow characteristic of the leakage medium in the corresponding leakage microchannel is a transition flow; If the Knudsen number is greater than the third threshold, the flow characteristic of the leakage medium in the corresponding leakage microchannel is determined to be molecular flow; wherein the first threshold is less than the second threshold, and the second threshold is less than the third threshold.

5. The vacuum seal leakage rate prediction method according to claim 3 or 4, characterized in that: The step of constructing a first leakage rate prediction model characterized by microscopic characteristic parameters based on the working environment parameters, the physical properties of the leakage medium, and the flow characteristics includes: According to the working environment parameters, the physical properties of the leakage medium, the flow characteristics and the length of the capillary, a leakage rate prediction model for a single leakage microchannel with flow characteristics in continuous flow, slip flow, transition flow and molecular flow is constructed respectively; According to the integral operation of the leakage rate prediction model of the single leakage microchannel, a first leakage rate prediction model characterized by microscopic characteristic parameters is determined; the microscopic characteristic parameters include but are not limited to fractal dimension, characteristic scale parameter, and the volume ratio of the first distance to the uncontact space in the contact domain.

6. The vacuum seal leakage rate prediction method according to claim 3, wherein: The mapping relationship between macro design parameters and micro feature parameters is constructed based on the sealing design parameters and the three-dimensional micro morphology model through feature multi-scale coupling, including: The structure function method is used to analyze the rough contours of the samples with different preset processing methods. The first mapping relationship between different processing methods, different roughness and the fractal dimension of the three-dimensional rough surface morphology is established, as well as the second mapping relationship between different processing methods, different roughness and the characteristic scale parameters of the three-dimensional rough surface morphology. Based on the three-dimensional micromorphology model, the first mapping relationship and the second mapping relationship, a finite element contact simulation model is constructed and simulated for the three-dimensional rough surface profiles at different scales. Then, based on the response surface method, the simulation results are analyzed and a third mapping relationship between the first distance and the macro design parameters is constructed; the macro design parameters include but are not limited to the processing method, roughness, apparent contact area, material properties and sealing preload of the flange sealing surface.

7. The vacuum seal leakage rate prediction method according to claim 6, wherein: The method includes constructing a finite element contact simulation model for three-dimensional rough surface profiles at different scales based on the three-dimensional micromorphology model, the first mapping relationship, and the second mapping relationship, and then analyzing the simulation results based on the response surface method and constructing a third mapping relationship between the first distance and the macro design parameter, including: Based on the three-dimensional micro-morphology model, the first mapping relationship, and the second mapping relationship, a finite element contact simulation model is established between the three-dimensional rough surface profile and the rigid plane for three-dimensional rough surface profiles with different processing methods, different roughness, different apparent contact areas, and different material properties; Based on the finite element contact simulation model, simulation results are obtained by applying different sealing preload forces on a rigid plane, wherein the simulation results include the first distance; According to the simulation results, multivariate nonlinear regression data fitting in the response surface method is used to construct a third mapping relationship between the first distance and the processing method, the roughness, the apparent contact area, the material properties, and the sealing preload force.

8. A vacuum seal leakage rate prediction device, characterized in that: include: A data acquisition module is used to obtain the working environment parameters of the sealing structure, the sealing design parameters, and the physical properties of the leaking medium. The sealing design parameters include the processing method of the flange sealing surface; A contact surface reconstruction module, used to construct a three-dimensional microscopic morphology model of the flange sealing surface according to the processing method; a characteristic analysis module for establishing, based on the three-dimensional microscopic morphology model, leakage microchannels between the sealed contact interfaces under different contact states and analyzing the channel characteristics, thereby determining the flow characteristics of the leakage medium in the leakage microchannels corresponding to the different contact states; A model building module, configured to build a first leakage rate prediction model characterized by microscopic characteristic parameters according to the working environment parameters, the physical properties of the leakage medium, and the flow characteristics; A parameter mapping module, configured to construct a mapping relationship between macroscopic design parameters and microscopic feature parameters through feature multi-scale coupling based on the sealing design parameters and the three-dimensional microscopic morphology model; The leakage rate prediction module is used to substitute the mapping relationship into the first leakage rate prediction model to obtain a second leakage rate prediction model driven by macro design parameters to predict the vacuum seal leakage rate.

9. A computer device, characterized in that: The invention comprises a processor and a memory, wherein a computer program is stored in the memory and the computer program is configured to be executed by the processor, and when the processor executes the computer program, the vacuum seal leakage rate prediction method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein when the device where the computer-readable storage medium is located executes the computer program, the vacuum seal leakage rate prediction method according to any one of claims 1 to 7 is implemented.

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