A vacuum sealing leakage rate prediction method, device, equipment and medium

Abstract

The application discloses a kind of vacuum sealing leakage rate prediction method, device, equipment and medium, the method includes: according to the processing mode of flange sealing surface, the three-dimensional microtopography model of flange sealing surface is constructed;Based on three-dimensional microtopography model, the leakage microchannel between sealing contact interface under different contact states is established and the channel characteristics are analyzed, the flow characteristics of leakage medium in the leakage microchannel of different contact states are determined;According to working environment parameters, the physical properties and flow characteristics of leakage medium, the first leakage rate prediction model characterized by micro feature parameters is constructed;The mapping relationship between macroscopic design parameters and micro feature parameters is constructed by characteristic multiscale coupling, the mapping relationship is substituted into the first leakage rate prediction model to obtain the second leakage rate prediction model driven by macroscopic design parameters, to carry out vacuum sealing leakage rate prediction.The application has 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:

[0006] 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;

[0007] Constructing a three-dimensional microscopic morphology model of the flange sealing surface according to the processing method;

[0008] establish a leakage micro-channel between the sealing contact interfaces under different contact states based on the three-dimensional micro-topography model and analyze the channel characteristics to determine the flow characteristics of the leakage medium in the leakage micro-channel corresponding to different contact states;

[0009] construct a first leakage rate prediction model characterized by micro-feature parameters according to the working environment parameters, the physical properties of the leakage medium, and the flow characteristics;

[0010] based on the sealing design parameters and the three-dimensional micro-topography model, a mapping relationship between macro-design parameters and micro-feature parameters is constructed through feature multi-scale coupling;

[0011] substitute the mapping relationship into the first leakage rate prediction model to obtain a second leakage rate prediction model driven by macro-design parameters for vacuum sealing leakage rate prediction.

[0012] As an improvement of the above scheme, the three-dimensional micro-topography model of the flange sealing surface constructed according to the processing mode comprises:

[0013] determine the surface topography height distribution of the corresponding flange sealing surface according to different processing modes;

[0014] According to the surface topography height distribution corresponding to the processing mode, if the height of the surface topography is uniformly distributed in the x-axis direction and the y-axis direction, a three-dimensional isotropic rough surface profile is constructed to obtain the three-dimensional micro-topography model corresponding to the processing mode; if the height of the surface topography is not uniformly distributed in the x-axis direction and the y-axis direction, a three-dimensional anisotropic rough surface profile is constructed to obtain the three-dimensional micro-topography model corresponding to the processing mode.

[0015] As an improvement of the above scheme, the three-dimensional micro-topography model, the leakage micro-channel between the sealing contact interfaces under different contact states is established based on the three-dimensional micro-topography model and the channel characteristics are analyzed, comprising:

[0016] the contact between the sealing ring and the flange sealing surface is equivalent to the contact between the rigid plane and the three-dimensional micro-topography model, forming a contact domain; wherein the uncontacted space in the contact domain constitutes a leakage micro-channel;

[0017] Based on the first distance under different contact states obtained based on the contact domain, combined with the roughness of the flange sealing surface in the sealing design parameters, the volume ratio of the uncontacted space in the contact domain under different contact states is determined; the first distance is the distance between the rigid plane and the height average plane of the three-dimensional rough surface profile;

[0018] Based on the three-dimensional micro-topography model, the first distance, and the roughness, the minimum leakage micro-channel diameter and the maximum leakage micro-channel diameter in the contact domain under different contact states are calculated respectively;

[0019] determining a fractal dimension of the non-contact space in the contact domain according to the volume proportion of the non-contact space, the minimum leakage micro-channel diameter and the maximum leakage micro-channel diameter;

[0020] equivalent the non-contact space in the contact domain to a curved capillary bundle, and determining a length of a single capillary according to a diameter of a leakage micro-channel corresponding to the capillary, a sealing contact surface width in the sealing design parameter, the volume proportion of the non-contact space and the fractal dimension.

[0021] As an improvement of the above scheme, the determining of the flow characteristics of the leakage medium in the leakage micro-channel corresponding to different contact states comprises:

[0022] for each leakage micro-channel, calculating a Knudsen number corresponding to the leakage micro-channel according to the diameter of the leakage micro-channel and the working environment parameter and the physical property of the leakage medium;

[0023] if the Knudsen number is less than or equal to a preset first threshold value, determining that the flow characteristics of the leakage medium in the corresponding leakage micro-channel is continuous flow;

[0024] if the Knudsen number is greater than the first threshold value and less than or equal to a preset second threshold value, determining that the flow characteristics of the leakage medium in the corresponding leakage micro-channel is slip flow;

[0025] if the Knudsen number is greater than the second threshold value and less than or equal to a preset third threshold value, determining that the flow characteristics of the leakage medium in the corresponding leakage micro-channel is transition flow;

[0026] if the Knudsen number is greater than the third threshold value, determining that the flow characteristics of the leakage medium in the corresponding leakage micro-channel is molecular flow; wherein the first threshold value is less than the second threshold value, and the second threshold value is less than the third threshold value.

[0027] As an improvement of the above scheme, the constructing of the first leakage rate prediction model represented by micro-characteristic parameters according to the working environment parameter, the physical property of the leakage medium and the flow characteristics comprises:

[0028] constructing a leakage rate prediction model of a single leakage micro-channel in which the flow characteristics is continuous flow, slip flow, transition flow or molecular flow respectively according to the working environment parameter, the physical property of the leakage medium, the flow characteristics and the length of the capillary.

[0029] According to the integral operation of the leakage rate prediction model of the single leakage micro-channel, a first leakage rate prediction model characterized by micro-parameters is determined, wherein the micro-parameters include but are not limited to a fractal dimension, a characteristic scale parameter, and a volume ratio of the first distance to the non-contact space in the contact domain.

[0030] As an improvement of the above scheme, the mapping relationship between the macroscopic design parameters and the micro-parameters is constructed by coupling the characteristics of multiple scales based on the sealing design parameters and the three-dimensional micro-topography model, comprising:

[0031] The structural function method is used to analyze the rough profile of the preset sample block of different processing methods, to establish a first mapping relationship between different processing methods, different roughness and the fractal dimension of the three-dimensional rough surface topography, and a second mapping relationship between different processing methods, different roughness and the characteristic scale parameter of the three-dimensional rough surface topography.

[0032] Based on the three-dimensional micro-topography model, the first mapping relationship and the second mapping relationship, a finite element contact simulation model is constructed for the three-dimensional rough surface profile under different scales and simulated, and then the simulation results are analyzed based on the response surface method and a third mapping relationship between the first distance and the macroscopic design parameters is constructed; the macroscopic design parameters include but are not limited to the processing method of the flange sealing surface, the roughness, the apparent contact area, the material properties and the sealing pre-tightening force.

[0033] As an improvement of the above scheme, based on the three-dimensional micro-topography model, the first mapping relationship and the second mapping relationship, a finite element contact simulation model is constructed for the three-dimensional rough surface profile under different scales and simulated, and then the simulation results are analyzed based on the response surface method and a third mapping relationship between the first distance and the macroscopic design parameters is constructed, comprising:

[0034] Based on the three-dimensional micro-topography model, the first mapping relationship and the second mapping relationship, a finite element contact simulation model is constructed for the three-dimensional rough surface profile under different scales and simulated, and then the simulation results are analyzed based on the response surface method and a third mapping relationship between the first distance and the macroscopic design parameters is constructed, comprising:

[0035] Based on the finite element contact simulation model, different sealing pre-tightening forces are applied on the rigid plane to simulate and obtain simulation results, wherein the simulation results include the first distance.

[0036] According to the simulation results, a 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 pre-tightening force.

[0037] The application further provides a vacuum sealing leakage rate prediction device, comprising:

[0038] A data acquisition module is configured to acquire working environment parameters of a sealing structure, sealing design parameters, and physical properties of a leakage medium, wherein the sealing design parameters include a processing mode of a flange sealing surface;

[0039] A contact surface reconstruction module is configured to construct a three-dimensional micro-topography model of the flange sealing surface according to the processing mode;

[0040] A characteristic analysis module is configured to establish leakage micro-channels between sealing contact interfaces in different contact states based on the three-dimensional micro-topography model, analyze channel characteristics, and determine flow characteristics of the leakage medium in the leakage micro-channels corresponding to different contact states;

[0041] A model construction module is configured to construct a first leakage rate prediction model characterized by micro-feature parameters according to the working environment parameters, the physical properties of the leakage medium, and the flow characteristics;

[0042] A parameter mapping module is configured to construct a mapping relationship between macro-design parameters and micro-feature parameters through feature multi-scale coupling based on the sealing design parameters and the three-dimensional micro-topography model;

[0043] A leakage rate prediction module 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 sealing leakage rate prediction.

[0044] The application further provides a computer device comprising a processor and a memory, wherein the memory stores a computer program, and the computer program is configured to be executed by the processor, and the processor implements the vacuum sealing leakage rate prediction method according to any one of the above-mentioned embodiments when executing the computer program.

[0045] The application further provides a computer readable storage medium storing a computer program, wherein the computer program controls a device where the computer readable storage medium is located to execute the vacuum sealing leakage rate prediction method according to any one of the above-mentioned embodiments when the computer program is running.

[0046] Compared with the prior art, the vacuum sealing leakage rate prediction method, device, equipment and medium provided by the application have the following advantages:

[0047] The three-dimensional micro-morphology model of the flange sealing surface is constructed according to a processing mode, the micro-morphology of the sealing contact interface is accurately reconstructed, and the prediction accuracy is improved; the leakage micro-channels between the sealing contact interfaces in different contact states are established based on the three-dimensional micro-morphology model, and the channel characteristics are analyzed, the flow characteristics of the leakage medium in the leakage micro-channels corresponding to different contact states are determined, and then the first leakage rate prediction model represented by the micro-characteristic parameters is constructed, which can comprehensively consider the evolution law of the leakage micro-channel geometric structure in different contact states, and reasonably divide the flow characteristic type based on the relationship between the micro-channel size characteristics and the gas flow scale, so as to realize the fine modeling of the leakage behavior in the full flow field range, and significantly improve the accuracy and application range of the sealing leakage rate prediction; based on the sealing design parameters and the three-dimensional micro-morphology model, the multi-scale coupling relationship between the macroscopic design parameters and the micro-characteristic parameters is established by combining the finite element contact simulation, so as to form the second leakage rate prediction model driven by the macroscopic design parameters, for the vacuum sealing leakage rate prediction. The present application can solve the problems of insufficient interface morphology modeling accuracy, fuzzy micro-channel flow mechanism division, decoupling of the leakage rate calculation model and the engineering design parameters in the prior art, has high precision, strong adaptability and good engineering practicability, and is especially suitable for fields such as nuclear power equipment, aerospace and other fields with extremely high sealing reliability requirements, and has wide application prospect. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 is a flow diagram of a vacuum sealing leakage rate prediction method provided by an embodiment of the present application;

[0049] Figure 2 is a finite element simulation model schematic diagram of the contact between the rigid plane and the three-dimensional rough surface morphology provided by an embodiment of the present application;

[0050] Figure 3 is a three-dimensional rough surface profile schematic diagram provided by an embodiment of the present application;

[0051] Figure 4 is an application example flow chart of a vacuum sealing leakage rate prediction method provided by an embodiment of the present application;

[0052] Figure 5 is a structure schematic diagram of a vacuum sealing leakage rate prediction device provided by an embodiment of the present application;

[0053] Figure 6 is a structure schematic diagram of a computer device provided by an embodiment of the present application;

[0054] Among them, the reference signs are as follows:

[0055] 1, rigid plane; 2, three-dimensional rough profile surface; 3, contact surface; 4, non-contact space; 5, contact domain. DETAILED DESCRIPTION

[0056] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0057] Please refer to Figure 1 , Figure 1 is a flowchart of a vacuum sealing leakage rate prediction method provided by an embodiment of the present application. The vacuum sealing leakage rate prediction method comprises:

[0058] S1: obtaining working environment parameters of a sealing structure, sealing design parameters, and physical properties of a leakage medium, wherein the sealing design parameters comprise a processing mode of a flange sealing surface;

[0059] S2: constructing a three-dimensional micro-topography model of the flange sealing surface according to the processing mode;

[0060] S3: based on the three-dimensional micro-topography model, establishing leakage micro-channels between sealing contact interfaces in different contact states and analyzing channel characteristics, to determine flow characteristics of the leakage medium in the leakage micro-channels corresponding to different contact states;

[0061] S4: constructing a first leakage rate prediction model characterized by micro-feature parameters according to the working environment parameters, the physical properties of the leakage medium, and the flow characteristics;

[0062] S5: based on the sealing design parameters and the three-dimensional micro-topography model, constructing a mapping relationship between macro-design parameters and micro-feature parameters through feature multi-scale coupling;

[0063] S6: substituting 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 sealing leakage rate prediction.

[0064] Specifically, the working environment parameters of the sealing structure, the physical properties of the leakage medium, and the sealing design parameters at the macro level are obtained according to actual working conditions. The working environment parameters of the sealing structure include types of sealing media, pressure difference and average pressure , etc.; the physical properties of the leakage medium include molecular weight , viscosity , and temperature , etc.; the sealing design parameters include the processing mode of the flange sealing surface and roughness , sealing structure size, and sealing material properties seal contact force seal contact surface width etc. Exemplarily, the processing methods include turning, grinding, polishing, lapping, etc., and different processing methods will result in different micro topographies of the flange surface.

[0065] First, in step S2, the three-dimensional micro topography model of the seal contact surface is accurately reconstructed, and in step S3, the characteristics of the leakage microchannels between the seal 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 according to the leakage microchannel characteristics; then in step S4, a leakage rate calculation model based on micro feature parameter representation is established according to the flow characteristics of the medium in the leakage microchannels, i.e. the first leakage rate prediction model; then in step S5, based on multi-scale coupling analysis, the mapping relationship between the micro feature parameters and the macro seal design parameters is constructed, so as to establish the second leakage rate prediction model driven by the macro design parameters in step S6, realizing the prediction of the vacuum seal leakage rate and the quantitative evaluation of the sealing performance.

[0066] As one of the optional embodiments, the three-dimensional micro topography model of the flange sealing surface is constructed according to the processing method, comprising:

[0067] determining the surface topography height distribution of the corresponding flange sealing surface according to different processing methods;

[0068] According to the surface topography height distribution corresponding to the processing method, if the height of the surface topography is uniformly distributed in the x-axis direction and the y-axis direction, a three-dimensional isotropic rough surface profile is constructed to obtain the three-dimensional micro topography model corresponding to the processing method; if the height of the surface topography is not uniformly distributed in the x-axis direction and the y-axis direction, a three-dimensional anisotropic rough surface profile is constructed to obtain the three-dimensional micro topography model corresponding to the processing method.

[0069] Specifically, the control equation of the three-dimensional micro topography model constructed in step S2 is determined by judging whether the processing method of the flange sealing surface has directionless property. If the processing method adopted results in that the height of the micro topography of the flange surface in the x-axis direction and the y-axis direction obeys the same Gaussian distribution, a three-dimensional isotropic rough surface profile is constructed, and the three-dimensional isotropic fractal function of the corresponding three-dimensional micro topography model is:

[0070]

[0071] wherein, is the rough topography height of the flange surface, represents 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 .

[0072] 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:

[0073]

[0074] 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 .

[0075] 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:

[0076] 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;

[0077] 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;

[0078] 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;

[0079] 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;

[0080] 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.

[0081] 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.

[0082] 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:

[0083]

[0084] in, is the volume fraction of the uncontacted space in the contact domain.

[0085] 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:

[0086]

[0087]

[0088] wherein, is the minimum leakage micro-channel diameter, is the maximum leakage micro-channel diameter, and are the fractal dimension and characteristic scale parameter of the surface, respectively, is the spatial frequency density parameter, is the maximum order number corresponding to the spatial frequency, is the roughness, is the first distance between the rigid plane and the average plane of the three-dimensional rough surface topography.

[0089] Further, based on the volume ratio of the non-contact space calculated above , the minimum leakage micro-channel diameter and the maximum leakage micro-channel diameter , the fractal dimension of the non-contact space in the contact domain formed between the rigid plane and the three-dimensional rough surface is derived as:

[0090]

[0091] wherein, is the fractal dimension of the non-contact space.

[0092] Further, the non-contact space in the contact domain formed between the rigid plane and the three-dimensional rough surface is equivalent to a bundle of curved capillaries, wherein the curved fractal dimension of the capillary is:

[0093]

[0094] wherein, is the sealing contact surface width.

[0095] The length of a single capillary is:

[0096]

[0097] wherein, is the diameter of the leakage micro-channel, is the sealing contact surface width, is the curved fractal dimension of the capillary.

[0098] As one of the optional embodiments, the determination of the flow characteristics of the leakage medium in the leakage micro-channel corresponding to different contact states includes:

[0099] 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;

[0100] 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;

[0101] 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;

[0102] 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;

[0103] 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.

[0104] 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:

[0105]

[0106] 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.

[0107] 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:

[0108] 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 ;

[0109] when When the diameter satisfies The flow characteristic in the leakage microchannel is slip flow; for The corresponding leakage microchannel diameter when ;

[0110] When the diameter satisfies the flow characteristics in the leakage micro-channel is transitional flow; is the corresponding leakage micro-channel diameter;

[0111] When the diameter satisfies the flow characteristics in the leakage micro-channel is molecular flow.

[0112] Further, in step S4, leakage rate prediction models based on continuous flow, slip flow, transitional flow, and molecular flow are respectively constructed, thereby realizing fine modeling of leakage behavior in the full flow range and significantly improving the accuracy and scope of sealing leakage rate prediction.

[0113] As one of the optional embodiments, the first leakage rate prediction model characterized by micro-characteristic parameters is constructed according to the working environment parameters, the physical properties of the leakage medium, and the flow characteristics, comprising:

[0114] According to the working environment parameters, the physical properties of the leakage medium, the flow characteristics, and the length of the capillary, leakage rate prediction models of single leakage micro-channels with flow characteristics in continuous flow, slip flow, transitional flow, and molecular flow are respectively constructed;

[0115] According to the integral operation of the leakage rate prediction model of the single leakage micro-channel, the first leakage rate prediction model characterized by micro-characteristic parameters is determined; the micro-characteristic parameters include but are not limited to fractal dimension, characteristic scale parameter, the first distance, and the volume ratio of the non-contact space in the contact domain.

[0116] Specifically, based on the division of the flow characteristics of the leakage micro-channel in step S3, the leakage rate models of single leakage micro-channels with flow characteristics in continuous flow, slip flow, transitional flow, and molecular flow are established.

[0117] The control equation of the leakage rate prediction model of the single leakage micro-channel with flow characteristics in continuous flow is as follows:

[0118]

[0119] wherein, is the pressure difference between the two ends of the sealing interface; is the viscosity coefficient of the leakage gas; is the diameter of the leakage micro-channel; is the length of the capillary.

[0120] The control equation of the leakage rate prediction model of the single leakage micro-channel with flow characteristics in slip flow is as follows:​ As follows:

[0121]

[0122] wherein, Kn is Knudsen number.

[0123] Control equation of the leakage rate prediction model of a single leakage microchannel with flow characteristics in transition flow As follows:

[0124]

[0125] wherein, P is the average pressure of the sealing interface; T is the temperature of the leakage gas; M is the molecular weight of the leakage gas; R is the gas universal constant.

[0126] Control equation of the leakage rate prediction model of a single leakage microchannel with flow characteristics in molecular flow As follows:

[0127]

[0128] wherein, ΔP is the pressure difference between the two ends of the sealing interface; D is the diameter of the leakage microchannel; L is the length of the capillary tube; T is the temperature of the leakage gas; M is the molecular weight of the leakage gas; R is the gas universal constant.

[0129] Further, based on the above leakage rate prediction model of a single leakage microchannel, a total leakage rate prediction model characterized by micro-features parameters, i.e. the first leakage rate prediction model , is solved, and the formula is as follows:

[0130] When , there is:

[0131]

[0132] When , there is:

[0133]

[0134] When , there is:

[0135]

[0136] When , there is:

[0137]

[0138] wherein, is the number of leaky microchannels with diameters in the range of and . .

[0139] As one of the optional embodiments, the mapping relationship between the macroscopic design parameters and the microscopic feature parameters is constructed by feature multi-scale coupling based on the sealing design parameters and the three-dimensional microscopic morphology model, comprising:

[0140] The structural function method is used to analyze the rough profile of the preset sample block of different processing methods, to establish a first mapping relationship between different processing methods, different roughness and the fractal dimension of the three-dimensional rough surface morphology, and a second mapping relationship between different processing methods, different roughness and the characteristic scale parameter of the three-dimensional rough surface morphology;

[0141] Based on the three-dimensional microscopic morphology model, the first mapping relationship and the second mapping relationship, a finite element contact simulation model is constructed for the three-dimensional rough surface profile under different scales and simulated, and then the simulation results are analyzed based on the response surface method and a third mapping relationship between the first distance and the macroscopic design parameters is constructed; the macroscopic design parameters include but are not limited to the processing method of the flange sealing surface, the roughness, the apparent contact area, the material properties and the sealing pre-tightening force.

[0142] As one of the optional embodiments, based on the three-dimensional microscopic morphology model, the first mapping relationship and the second mapping relationship, a finite element contact simulation model is constructed for the three-dimensional rough surface profile under different scales and simulated, and then the simulation results are analyzed based on the response surface method and a third mapping relationship between the first distance and the macroscopic design parameters is constructed, comprising:

[0143] Based on the three-dimensional microscopic 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 the three-dimensional rough surface profile under different processing methods, different roughness, different apparent contact area and different material properties;

[0144] Based on the finite element contact simulation model, different sealing pre-tightening forces are applied on the rigid plane to simulate and obtain simulation results, and the simulation results include the first distance;

[0145] According to the simulation results, a multivariate nonlinear regression data fitting in response surface method is adopted to construct a third mapping relationship between the first distance and the processing mode, the roughness, the apparent contact area, the material property, and the sealing pre-tightening force.

[0146] Specifically, in step S5, roughness test blocks obtained by different processing modes are manufactured, and roughness profile lines of the roughness test blocks are extracted by an instrument. Further, the roughness profile lines of the test blocks are analyzed based on a structure function method, a first mapping relationship between different processing modes, different roughnesses, and a fractal dimension of a three-dimensional rough surface morphology, and a second mapping relationship between different processing modes, different roughnesses, and a characteristic scale parameter of the three-dimensional rough surface morphology are established, and the formulas are as follows:

[0147]

[0148]

[0149] wherein, is the fractal dimension of the three-dimensional rough surface morphology, is a mapping function corresponding thereto; is the characteristic scale parameter of the three-dimensional rough surface morphology, is a mapping function corresponding thereto; is the roughness, is the processing mode.

[0150] Further, based on the three-dimensional micro-morphology model in 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 modes and different roughnesses is constructed. Specifically, the mapping relationship between the explicit roughness, the fractal dimension, and the fractal characteristic scale parameter of the micro three-dimensional rough surface is substituted into the three-dimensional micro-morphology model in step S2, and a three-dimensional rough surface profile with different processing modes, different roughnesses, and different apparent contact areas is reconstructed. Exemplarily, as shown in FIG. 2, a three-dimensional rough surface profile with a grinding processing and a roughness of 0.8 um is constructed. Figure 3

[0151] Further, a finite element contact simulation model of the three-dimensional rough surface profile with different processing modes and different roughnesses is established, and then a response surface method test design test point is analyzed to construct a third mapping relationship. Specifically, for the three-dimensional rough surface profile with different processing modes , different roughnesses , different sealing apparent contact areas , and different material properties ​A finite element contact simulation model is established between each three-dimensional rough surface and the rigid plane, and different compression loads are applied to 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 three-dimensional rough surface profile height average plane. Processing method of three-dimensional rough surface contour , roughness , apparent contact area , material properties , sealing preload The third mapping relationship is as follows:

[0152]

[0153] in, is a function of the third mapping relationship.

[0154] 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:

[0155]

[0156] 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.

[0157] 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 ;

[0158] Identify the physical properties of the leaking medium, including molecular weight , viscosity and temperature ;

[0159] 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 ;

[0160] The above design parameters are input into the second leakage rate prediction model constructed by the present invention. Calculate the overall leakage rate;

[0161] If the calculated overall leakage rate meets the preset sealing leakage rate requirement, the design of the sealing structure is completed;

[0162] 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.

[0163] 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.

[0164] Correspondingly, the application also provides a vacuum sealing leakage rate prediction device capable of realizing all processes of the vacuum sealing leakage rate prediction method in the above embodiments.

[0165] Please refer to Figure 5 , Figure 5 is a structural schematic diagram of a vacuum sealing leakage rate prediction device provided by an embodiment of the application. The vacuum sealing leakage rate prediction device comprises:

[0166] A data acquisition module 501 is configured to acquire working environment parameters of a sealing structure, sealing design parameters, and physical properties of a leakage medium, wherein the sealing design parameters comprise a processing mode of a flange sealing surface.

[0167] A contact surface reconstruction module 502 is configured to construct a three-dimensional micro-topography model of the flange sealing surface according to the processing mode.

[0168] A characteristic analysis module 503 is configured to establish leakage micro-channels between sealing contact interfaces in different contact states based on the three-dimensional micro-topography model, analyze channel characteristics, and determine flow characteristics of the leakage medium in the leakage micro-channels corresponding to different contact states.

[0169] A model construction module 504 is configured to construct a first leakage rate prediction model characterized by micro-feature parameters according to the working environment parameters, the physical properties of the leakage medium, and the flow characteristics.

[0170] A parameter mapping module 505 is configured to construct a mapping relationship between macro-design parameters and micro-feature parameters through feature multi-scale coupling based on the sealing design parameters and the three-dimensional micro-topography model.

[0171] A 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 sealing leakage rate prediction.

[0172] Preferably, the construction of the three-dimensional micro-topography model of the flange sealing surface according to the processing mode comprises:

[0173] determining a surface topography height distribution of the flange sealing surface corresponding to different processing modes;

[0174] according to the surface topography height distribution corresponding to the processing mode, if the height of the surface topography is uniformly distributed in the x-axis direction and the y-axis direction, constructing an isotropic three-dimensional rough surface profile to obtain the three-dimensional micro-topography model corresponding to the processing mode, or if the height of the surface topography is not uniformly distributed in the x-axis direction and the y-axis direction, constructing an anisotropic three-dimensional rough surface profile to obtain the three-dimensional micro-topography model corresponding to the processing mode.

[0175] Preferably, the step of establishing the leakage microchannels between the sealing contact interfaces under different contact states based on the three-dimensional micro-topography model and analyzing the channel characteristics comprises:

[0176] equivalent the contact between the sealing ring and the flange sealing surface to the contact between a rigid plane and the three-dimensional micro-topography model to form a contact domain; wherein the uncontacted space in the contact domain constitutes the leakage microchannels;

[0177] based on the contact domain, obtaining a first distance under different contact states, and combining the roughness of the flange sealing surface in the sealing design parameters to determine the volume ratio of the uncontacted space in the contact domain under different contact states; the first distance is the distance between the rigid plane and the height average plane of the three-dimensional rough surface profile;

[0178] based on the three-dimensional micro-topography 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;

[0179] determining the fractal dimension of the uncontacted space in the contact domain according to the volume ratio of the uncontacted space, the minimum leakage microchannel diameter and the maximum leakage microchannel diameter;

[0180] equivalent the uncontacted space in the contact domain to a curved capillary bundle, and according to the diameter of the corresponding leakage microchannel of the capillary, the sealing contact surface width in the sealing design parameters, the volume ratio of the uncontacted space and the fractal dimension, determine the length of a single capillary.

[0181] Preferably, the step of determining the flow characteristics of the leakage medium in the leakage microchannel corresponding to different contact states comprises:

[0182] for each leakage microchannel, according to the diameter of the leakage microchannel and the working environment parameters and the physical properties of the leakage medium, calculate the Knudsen number corresponding to the leakage microchannel;

[0183] if the Knudsen number is less than or equal to a preset first threshold, it is determined that the flow characteristics of the leakage medium in the corresponding leakage microchannel is continuous flow;

[0184] if the Knudsen number is greater than the first threshold and less than or equal to a preset second threshold, it is determined that the flow characteristics of the leakage medium in the corresponding leakage microchannel is slip flow;

[0185] if the Knudsen number is greater than the second threshold and less than or equal to a preset third threshold, it is determined that the flow characteristics of the leakage medium in the corresponding leakage microchannel is transition flow;

[0186] If the Knudsen number is greater than the third threshold value, it is determined that the flow characteristic of the leaked medium in the corresponding leakage micro-channel is molecular flow; wherein the first threshold value is less than the second threshold value, and the second threshold value is less than the third threshold value.

[0187] Preferably, the first leakage rate prediction model characterized by micro-feature parameters is constructed according to the working environment parameters, the physical properties of the leaked medium, and the flow characteristic, including:

[0188] According to the working environment parameters, the physical properties of the leaked medium, the flow characteristic, and the length of the capillary, the leakage rate prediction model of a single leakage micro-channel is constructed respectively when the flow characteristic is in continuous flow, slip flow, transition flow, and molecular flow;

[0189] According to the integral operation of the leakage rate prediction model of the single leakage micro-channel, the first leakage rate prediction model characterized by micro-feature parameters is determined; the micro-feature parameters include but are not limited to fractal dimension, characteristic scale parameter, the first distance, and the volume proportion of the non-contact space in the contact domain.

[0190] Preferably, the mapping relationship between the macro-design parameters and the micro-feature parameters is constructed by feature multi-scale coupling based on the sealing design parameters and the three-dimensional micro-topography model, including:

[0191] The structural function method is used to analyze the rough profile of the preset sample block of different processing methods, to establish a first mapping relationship between different processing methods, different roughness, and the fractal dimension of the three-dimensional rough surface topography, and a second mapping relationship between different processing methods, different roughness, and the characteristic scale parameter of the three-dimensional rough surface topography;

[0192] Based on the three-dimensional micro-topography 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 profile under different scales, and then the third mapping relationship between the first distance and the macro-design parameters is constructed based on the response surface method to analyze the simulation results; the macro-design parameters include but are not limited to the processing method of the flange sealing surface, the roughness, the apparent contact area, the material properties, and the sealing pre-tightening force.

[0193] Preferably, based on the three-dimensional micro-topography 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 profile under different scales, and then the third mapping relationship between the first distance and the macro-design parameters is constructed based on the response surface method to analyze the simulation results, including:

[0194] Based on the three-dimensional micro-topography model, the first mapping relationship and the second mapping relationship, a finite element contact simulation model between a three-dimensional rough surface profile and a rigid plane is established for different processing methods, different roughnesses, different apparent contact areas and different material properties of the three-dimensional rough surface profile;

[0195] Based on the finite element contact simulation model, a simulation result is obtained by simulating and applying different sealing pre-tightening forces on the rigid plane, and the simulation result includes the first distance;

[0196] According to the simulation result, a third mapping relationship between the first distance and the processing method, the roughness, the apparent contact area, the material property and the sealing pre-tightening force is constructed by using multivariate nonlinear regression data fitting in the response surface method.

[0197] In specific implementation, the working principle, control process and technical effect of the vacuum sealing leakage rate prediction device provided by the embodiment of the present application are the same as the vacuum sealing leakage rate prediction method in the above embodiment, and will not be described here.

[0198] Referring to Figure 6 , Figure 6 is a structural block diagram of a computer device provided by an embodiment of the present application, which includes a processor 601, a memory 602, and a computer program stored in the memory 602 and executable on the processor 601. The processor 601 implements the steps in the above-mentioned vacuum sealing leakage rate prediction method embodiment when executing the computer program. Alternatively, the processor 601 implements the functions of each module / unit in the above-mentioned device embodiment when executing the computer program.

[0199] For example, the computer program can be divided into one or more modules / units, which are stored in the memory 602 and executed by the processor 601 to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the computer device.

[0200] The computer device can include, but is not limited to, the processor 601 and the memory 602. Those skilled in the art can understand that the schematic diagram is only an example of the computer device and does not limit the computer device, which can include more or fewer components than the diagram, or combine certain components or different components, for example, the computer device can also include an input / output device, a network access device, a bus, etc.

[0201] 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.

[0202] 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.

[0203] 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.

[0204] 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.

[0205] The application provides a vacuum sealing leakage rate prediction method, device, equipment and medium, which has the beneficial effects that: by constructing a three-dimensional micro-morphology model of a flange sealing surface according to a processing mode, the micro-morphology of a sealing contact interface is accurately reconstructed, and the prediction accuracy is improved; based on the three-dimensional micro-morphology model, the leakage micro-channels between the sealing contact interfaces in different contact states are established and the channel characteristics are analyzed, the flow characteristics of the leakage medium in the leakage micro-channels corresponding to different contact states are determined, and then a first leakage rate prediction model represented by micro-characteristic parameters is constructed, which can comprehensively consider the evolution law of the leakage micro-channel geometric structure in different contact states, and reasonably divide the flow characteristic type based on the relationship between the micro-channel size characteristics and the gas flow scale, so as to realize the fine modeling of the leakage behavior in the full flow range, and significantly improve the accuracy and application range of the sealing leakage rate prediction; based on the sealing design parameters and the three-dimensional micro-morphology model, combined with the finite element contact simulation, the multi-scale coupling relationship between the macro design parameters and the micro characteristic parameters is established, so as to form a second leakage rate prediction model driven by the macro design parameters, for vacuum sealing leakage rate prediction. The application can solve the problems of insufficient interface morphology modeling accuracy, fuzzy micro-channel flow mechanism division, decoupling of the leakage rate calculation model and the engineering design parameters in the prior art, has high precision, strong adaptability and good engineering practicability, and is especially suitable for fields such as nuclear power equipment, aerospace and other fields with extremely high sealing reliability requirements, and has a wide application prospect.

[0206] The above is the preferred embodiment of the application, and it should be pointed out that for ordinary skilled persons in the technical field, several improvements and refinements can be made without departing from the principles of the application, and these improvements and refinements are also considered to be within the protection scope of the application.

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; Substituting the mapping relationship into the first leakage rate prediction model to obtain a second leakage rate prediction model driven by the macro design parameters to predict the vacuum seal leakage rate; Wherein, based on the three-dimensional micromorphology model, establishing leakage microchannels between sealed contact interfaces under different contact states and analyzing channel characteristics include: 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; Wherein, 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.

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 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.

4. The vacuum seal leakage rate prediction method according to claim 1, 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.

5. The vacuum seal leakage rate prediction method according to claim 4, 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.

6. A vacuum seal leakage rate prediction device, characterized in that: include: A data acquisition module, 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, 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; a leakage rate prediction module, 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 predict the vacuum seal leakage rate; Wherein, based on the three-dimensional micromorphology model, establishing leakage microchannels between sealed contact interfaces under different contact states and analyzing channel characteristics include: 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; Wherein, 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.

7. 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 5 is implemented.

8. 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 5 is implemented.

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