Lip seal structure optimization method and device, medium and computer program product

Abstract

The invention relates to the technical field of sealing structures, and particularly provides a lip sealing structure optimization method and equipment, a medium and a computer program product. The lip seal structure optimization method comprises the following steps: defining texture parameters of a lip seal to be optimized; fluid-solid-heat multi-field coupling analysis is conducted on the texture parameters of the lip seal to be optimized, and sealing performance parameters are obtained; determining a plurality of to-be-optimized texture parameter intervals based on the texture parameters and the sealing performance parameters; and optimizing the plurality of to-be-optimized texture parameter intervals by adopting a genetic algorithm to obtain a target texture parameter combination. According to the method, the sealing performance parameters are obtained through fluid-solid-heat multi-field coupling analysis, parameter optimization is conducted in combination with the genetic algorithm, accurate optimization of the lip sealing texture is achieved, and the sealing performance of the lip sealing piece is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of sealing structures, and in particular to a lip seal structure optimization method, device, medium and computer program product. Background Art

[0002] Lip seal is a sealing device widely used in the interface between rotating shaft and stationary parts. Its main function is to prevent the leakage of liquid or gas. Lip seal is usually made of elastic material and designed with one or more inclined lip edges. The lip edge fits tightly to the surface of the rotating shaft and relies on contact pressure to achieve effective sealing.

[0003] In the application of textured rotating shaft lip seals, texturing refers to designing specific microstructure patterns on the rotating shaft surface or the sealing lip surface. These subtle surface structures enhance the overall performance of the seal by improving the physical properties of the surface. Therefore, it is particularly important to determine the impact of different shapes of lip texture designs on sealing performance through simulation analysis. Summary of the invention

[0004] In view of this, exemplary embodiments of the present disclosure provide a lip seal structure optimization method, device, medium and computer program product to solve the problems existing in the related art.

[0005] In one aspect of an exemplary embodiment of the present disclosure, a method for optimizing a lip seal structure is provided, the method comprising:

[0006] defining texture parameters of the lip seal to be optimized;

[0007] Performing fluid-solid-thermal multi-field coupling analysis on the texture parameters of the lip seal to be optimized to obtain sealing performance parameters;

[0008] Determining a plurality of texture parameter intervals to be optimized based on the texture parameter and the sealing performance parameter;

[0009] A genetic algorithm is used to optimize the multiple texture parameter intervals to be optimized to obtain a target texture parameter combination.

[0010] Another aspect of the exemplary embodiments of the present disclosure provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method described in the exemplary embodiments of the present disclosure.

[0011] According to another aspect of the exemplary embodiments of the present disclosure, a computer-readable storage medium is provided, on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the method described in the exemplary embodiments of the present disclosure is implemented.

[0012] According to another aspect of the exemplary embodiments of the present disclosure, a computer program product is provided, including a computer program / instruction. When the computer program / instruction is executed by a processor, the method described in the exemplary embodiments of the present disclosure is implemented.

[0013] As will be described in detail below, according to a lip seal structure optimization method of an embodiment of the present disclosure, the texture parameters of the lip seal to be optimized are defined; the texture parameters of the lip seal to be optimized are subjected to fluid-solid-thermal multi-field coupling analysis to obtain sealing performance parameters; multiple texture parameter intervals to be optimized are determined based on the texture parameters and the sealing performance parameters; a genetic algorithm is used to optimize the multiple texture parameter intervals to be optimized to obtain a target texture parameter combination. Therefore, the lip seal structure optimization method provided by the present disclosure obtains the sealing performance parameters through fluid-solid-thermal multi-field coupling analysis, and combines the genetic algorithm to perform parameter optimization, thereby achieving accurate optimization of the lip seal texture and improving the sealing performance of the lip seal. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The above and other purposes, features and advantages of the present disclosure will become more apparent by describing the embodiments of the present disclosure in more detail in conjunction with the accompanying drawings. The accompanying drawings are used to provide a further understanding of the embodiments of the present disclosure and constitute a part of the specification. Together with the embodiments of the present disclosure, they are used to explain the present disclosure and do not constitute a limitation of the present disclosure. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0015] Figure 1 A schematic diagram of a flow chart of a lip seal structure optimization method provided by an exemplary embodiment of the present disclosure;

[0016] Figure 2 A schematic diagram of a common texture definition of a rotating axis provided as an example in the present disclosure;

[0017] Figure 3 A radial view of a two-dimensional triangular texture provided as an example of the present disclosure;

[0018] Figure 4 A schematic diagram of a three-dimensional surface morphology of a triangular texture provided as an example in the present disclosure;

[0019] Figure 5 A schematic diagram of a Pareto front solution provided as an example in the present disclosure;

[0020] Figure 6 A schematic block diagram of functional modules of a lip seal structure optimization device provided as an example in the present disclosure;

[0021] Figure 7 A structural block diagram of an electronic device provided as an example in the present disclosure;

[0022] Figure 8A schematic diagram of a computer program product provided by an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0023] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0024] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0025] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0026] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0027] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0028] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0029] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0030] As an optional but non-limiting implementation, in response to receiving an active request from the user, the method of sending a prompt message to the user may be, for example, a pop-up window, in which the prompt message may be presented in text. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device. It is understandable that the above notification and the process of obtaining user authorization are only illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0031] Lip seal is a sealing device widely used in the interface between rotating shaft and stationary parts. Its main function is to prevent the leakage of liquid or gas. Lip seal is usually made of elastic material and designed with one or more inclined lip edges. The lip edge fits tightly to the surface of the rotating shaft and relies on contact pressure to achieve effective sealing.

[0032] In the application of textured rotary shaft lip seals, texturing refers to the design of specific microstructure patterns on the surface of the rotary shaft or the sealing lip. These subtle surface structures enhance the overall performance of the seal by improving the physical properties of the surface. Therefore, it is particularly important to determine the impact of different shapes of lip texture designs on sealing performance through simulation analysis.

[0033] Therefore, in order to solve the above problems, the exemplary embodiment of the present disclosure provides a lip seal structure optimization method, the specific steps include:

[0034] 1. Define multiple rotating axis textures. The textures of multiple rotating axes may include different shapes, sizes, and layouts. Different textures can be defined to adapt to different working environments and performance requirements.

[0035] 2. Fluid-solid-thermal multi-field coupling analysis of lip seals considering texture. In the design of rotating shaft lip seals, considering the existence of texture, fluid-solid-thermal coupling analysis is used to simulate the performance of lip seals under actual working conditions. This step calculates the sealing parameters through numerical solution to obtain a preliminary performance evaluation value.

[0036] 3. Uncertainty analysis of texture processing error. The Monte Carlo simulation method is used to perform uncertainty analysis on the texture processing error and its impact on sealing performance. Under the assumption that the texture shape has changed, the parameters of the previous step are reused for simulation to evaluate the impact of the error on the performance and obtain a possible performance fluctuation range.

[0037] 4. Design variable optimization based on genetic method. Finally, the design variables are optimized by genetic algorithm. According to the multiple performance intervals obtained in the previous step, an optimal interval is found, that is, the optimal combination of wear and pumping rate, and the corresponding optimal design variables are determined.

[0038] The entire optimization process covers three levels of loops:

[0039] The innermost loop is responsible for evaluating the seal performance for a single design state by calculating the seal parameters.

[0040] Monte Carlo simulation is applied to the middle layer cycle to evaluate the effect of texture shape change on performance and provide a range of performance fluctuations.

[0041] The outermost loop uses a genetic algorithm to find the optimal solution in multiple performance intervals to achieve the best sealing effect.

[0042] Through this hierarchical and interrelated optimization process, the design accuracy and reliability of the lip seal can be effectively improved while taking into account the complexity of actual processing errors and operating conditions.

[0043] For example, Figure 1 A schematic diagram of a process flow of a lip seal structure optimization method provided by an exemplary embodiment of the present disclosure is shown in FIG. Figure 1 As shown, the following steps may be specifically included:

[0044] Step S110: defining the texture parameters of the lip seal to be optimized.

[0045] When designing an uncertainty optimization method for textured rotating shaft lip seals based on genetic algorithms, it is first necessary to define the various types of textures that may be used on the rotating shaft. The texture is formed on the surface of the rotating shaft through a specific machining method to improve the fluid dynamics of the seal contact area and enhance the sealing performance.

[0046] Exemplarily, three common shapes of textures may include triangle, rectangle and ellipse. Figure 2 This is a schematic diagram of a common texture definition of a rotating axis provided by the present disclosure. Figure 2 As shown, Figure 2 (a) in the figure represents a triangular texture, where α tr represents the angle between the bottom edge and the circumference of the shaft, a trrepresents the length of the base, b tr Indicates the length of the left side, c tr Indicates the length of the right side, (h c ,l c ) represents the midpoint coordinate of the base side. Figure 2 (b) in the figure represents a rectangular texture, α re represents the angle between the bottom edge and the circumference of the rotating shaft, a re represents the lower base, b re represents the left side, c re represents the right side, d re represents the top edge, (h c ,l c ) represents the midpoint coordinate of the base side. Figure 2 (c) in the figure shows an elliptical texture, α el represents the angle between the focal line and the bottom edge, a el represents the semi-major axis, b el represents the semi-minor axis, (h c ,l c ) represents the coordinates of the midpoint of the ellipse.

[0047] For example, the triangular texture area can be expressed in a rectangular coordinate system as follows:

[0048]

[0049] Among them, (x tr1 ,y tr1 ) represents the coordinates of the intersection of the left side and the bottom side; (x tr2 ,y tr2 ) represents the coordinates of the intersection of the right side and the bottom side; (h c ,l c ) represents the coordinate of the midpoint of the length of the base; k tr represents the slope of the base; k tr1 represents the slope of the left side; k tr2 Represents the slope of the right side.

[0050] In practical applications, processing errors that can characterize size are often used to describe texture errors. In the above formula (1), the triangular texture is defined by the slope, so the size error needs to be converted into the slope error. The size parameter can be converted into the slope parameter by solving the following formulas (2) and (3) simultaneously:

[0051]

[0052] Among them, (x tr1 ,y tr1 ) represents the coordinates of the intersection of the left side and the bottom side; (x tr2 ,y tr2) represents the coordinates of the intersection of the right side and the bottom side; b tr Indicates the length of the left side; c tr Indicates the length of the right side; k tr1 represents the slope of the left side; k tr2 Represents the slope of the right side.

[0053] In this embodiment, the error of the length of the three sides of the triangle can be defined as: there is a processing error and the error is approximately represented by an interval variable. At the same time, the change of the angle between the base and the circumference is not considered. The error can be expressed as:

[0054] η t ~U(ε i ,ε j )(4)

[0055] Among them, η t Represents the processing error; ε i and ε j They respectively represent the corresponding upper and lower deviations in the tolerance, and the upper and lower deviations are determined by the processing method.

[0056] Based on the interval variable characteristics and formula (4), the length of the bottom side considering the machining error can be obtained as:

[0057] a′ t =a t +η t (5)

[0058] Among them, a' t Indicates the length of the bottom side considering the processing error; a t Indicates the length of the bottom side without considering the processing error; η t Indicates processing error.

[0059] Similarly, the lengths of other sides that take processing errors into consideration can be obtained. According to the lengths of the sides that take processing errors into consideration, the intersection points of different side lengths can be determined. Substitute the lengths of the sides that take processing errors into consideration and the intersection points into formulas (2) and (3), solve for the slope that takes processing errors into consideration, and obtain the expression of the triangular texture that takes processing errors into consideration in the rectangular coordinate system based on formula (1):

[0060]

[0061] Among them, k′ tr1 , k′ tr2 Respectively represent the slopes of the left and right sides after considering the processing error; (x′ tr1 ,y′ tr1 ), (x′ tr2 ,y′ tr2 ) respectively represent the intersection points of the left side, right side and bottom side after considering the processing error; (h c ,lc ) represents the coordinate of the midpoint of the length of the base; k tr Represents the slope of the base.

[0062] For example, the rectangular texture area can be expressed in a rectangular coordinate system as:

[0063]

[0064] Among them, (h c ,l c ) represents the coordinates of the midpoint of the base; (x re1 ,y re1 ) represents the coordinates of the intersection of the left side and the top side; (x re2 ,y re2 ) represents the coordinates of the intersection of the right side and the top side; (h re1 ,l re1 ) represents the coordinates of the midpoint of the top edge; k re represents the slope of the base; k re1 represents the slope of the left side; k re2 represents the slope of the right side; k re3 Represents the slope of the top edge.

[0065] In this embodiment, the error of the four sides of the rectangle can be defined as: there is a processing error and the error is approximately represented by an interval variable. At the same time, the change of the angle between the bottom side and the circumferential direction is not considered. The four sides obey the interval variables of the above formula (4). The four sides can be represented by the above formula (5). Based on this, the four sides can be represented by the point slope type to represent the rectangular texture area:

[0066]

[0067] Among them, (h c ,l c ) represents the coordinate of the midpoint of the base length; (x' re1 ,y' re1 ) represents the coordinates of the intersection of the left side and the top side after considering the processing error; (x' re2 ,y' re2 ) represents the coordinates of the intersection of the right side and the top side after considering the processing error; k re represents the slope of the base; k′ re1 Indicates the slope of the left side after considering the processing error; k′ re2 Indicates the slope of the right side after considering the processing error; k′ re3 represents the slope of the upper top edge after considering the processing error; (h1,l1) represents the midpoint coordinates of the upper top edge after considering the processing error.

[0068] For example, important parameters of an ellipse include: focal length, (semi) major axis, (semi) minor axis, and the angle between the line connecting the two foci and the circumferential direction of the rotation axis (x axis). Figure 2 As shown in (c), α el represents the angle between the focal line and the bottom edge, a el represents the semi-major axis, b el represents the semi-minor axis and (h c ,l c ) represents the definition of the midpoint coordinates of the ellipse as the elliptical texture parameters. If and only if the major axis is equal to the minor axis, the texture shape is circular.

[0069] For example, the elliptical texture region can be expressed in a rectangular coordinate system as:

[0070] A el (xh c ) 2 +B el (xh c )(yl c )+C el (yl c ) 2 ≤1 (9)

[0071] in, α represents the angle between the focal line and the bottom edge, a el represents the semi-major axis, b el represents the semi-minor axis; (h c ,l c ) represents the coordinates of the midpoint of the ellipse.

[0072] In this embodiment, the machining error of the ellipse can be defined as: el With semi-minor axis b el As the object of error definition, the texture is simplified and α is not considered in the error analysis. el The machining error is fixed while the center of the ellipse (h c ,l c ). The machining error obeys the interval variable of the above formula (4). The semi-major axis and semi-minor axis considering the machining error can be obtained from the characteristics of the interval variable and formula (5).

[0073] Based on this, the above formula (5), α el And the center point coordinates (h c ,l c ) into formula (9) to obtain the elliptical texture area considering the processing error:

[0074] A el (xh c ) 2 +B el(xh c )(yl c )+C el (yl c ) 2 ≤1 (10)

[0075] in, α represents the angle between the focal line and the bottom edge, a' el represents the semi-major axis after considering the machining error, b' el represents the semi-minor axis after considering the machining error; (h c ,l c ) represents the coordinates of the midpoint of the ellipse.

[0076] Step S120: performing fluid-solid-thermal multi-field coupling analysis on the texture parameters of the lip seal to be optimized to obtain sealing performance parameters.

[0077] For example, a hybrid elastohydrodynamic lubrication model may be used to perform fluid-solid-thermal multi-field coupling analysis of a textured lip seal to simulate the sealing performance of the lip seal under working conditions.

[0078] Specifically, the three-dimensional fractal theory is used to construct the three-dimensional microscopic surface morphology of the lip seal to be optimized;

[0079] The sealing performance parameters and temperature of the three-dimensional microscopic surface topography under preset working parameters are evaluated through a pre-constructed hybrid elastohydrodynamic lubrication model;

[0080] After the pressure and temperature iterations converge, the sealing performance parameters are output.

[0081] Among them, the hybrid elastohydrodynamic lubrication model is a model used to evaluate the sealing performance under lubrication conditions. It combines elastic deformation and fluid dynamics effects and can evaluate the sealing performance under preset working parameters.

[0082] Input basic working parameters, which may include: speed U, ambient temperature T0, viscosity η, ambient pressure P0, sealing pressure P s , shaft radius R, friction coefficient f, sealing ring elastic modulus E, oil density ρ, oil specific heat capacity c and wear coefficient K, etc.

[0083] Step S121: Calculate the fluid dynamic pressure oil film thickness.

[0084] The oil film thickness equation and the oil film pressure equation are jointly solved to determine the oil film pressure value.

[0085] Step S122: Solve the elastic deformation equation.

[0086] The elastic deformation of the lip is calculated and the oil film thickness is updated based on the deformation.

[0087] Step S123: Apply the point-by-point super-relaxation iteration method to define the convergence criterion of the oil film thickness. Determine whether the oil film thickness and pressure have reached convergence through iteration. If converged, calculate the relevant pumping rate, friction force and other parameters; if not converged, repeat steps S121 to S123 until the convergence condition is met.

[0088] Step S124: Input the initial temperature and calculate the friction and pumping rate through the hybrid elastohydrodynamic lubrication model. Calculate the new temperature value by combining the energy conservation and heat conduction equations. Update the viscosity using the viscosity-temperature equation and iterate the new viscosity back to the model to recalculate until the temperature distribution error is less than 0.01.

[0089] When the temperature distribution error is less than 0.01, the temperature field is judged to be converged, and the output parameters of the simulation results after iteration are output. When the temperature distribution error is not less than 0.01, the temperature field is judged to be not converged, and steps S121 to S124 are repeated until the result meets the convergence condition.

[0090] Output parameters may include: half-moon oil film pressure value, output viscosity, pumping rate, friction, tangential torque, average oil film thickness, temperature, average contact load, contact load ratio and wear rate, etc.

[0091] Specifically, the expressions of the above parameters are as follows:

[0092] For example, the microscopic surface of the lip seal can be represented by a WM (Weierstrass-Mandelbrot) fractal surface with a dimension of D:

[0093]

[0094] Among them, C n represents independent random numbers that follow a standard normal distribution; A n ,B n They represent independent random numbers that obey a uniform distribution on [0,2π]; λ represents a constant greater than 1; D represents the fractal dimension of the surface; and n is a natural sequence number.

[0095] The static oil film thickness represents the static pressure of the fluid when the shaft is stationary. In order to better simulate the sealing effect of different texture structures based on the influence of different texture structures on the static oil film thickness, the static oil film thickness when the rotating shaft is not working can be defined:

[0096]

[0097] Among them, h s represents the static oil film thickness; h0 represents the initial average oil film pressure; δ represents the texture depth; z represents the WM fractal surface with dimension D.

[0098] Furthermore, the Reynolds equation of cavitation can be used to characterize the effect of different texture size parameters on the sealing mechanism:

[0099]

[0100] in, Indicates the aspect ratio of the region; represents the dimensionless radial sliding velocity; X represents the dimensionless circumferential length; Y represents the dimensionless axial width; H represents the dimensionless initial oil film thickness; P represents the dimensionless oil film pressure.

[0101] as well as:

[0102]

[0103] The complete liquid film area refers to a continuous liquid film area formed on the solid surface, where the liquid thickness is sufficient to prevent direct contact between solid surfaces.

[0104] Furthermore, due to the load pressure and initial interference in the working conditions, the oil film is subjected to a certain oil film pressure during operation, and the oil film pressure further acts on the lip of the lip seal ring, resulting in a certain amount of elastic deformation. The elastic deformation equation can be expressed as:

[0105]

[0106] Where, E represents the elastic modulus; υ represents the Poisson's ratio; x k Indicates additional coordinates corresponding to x; y l represents the additional coordinate corresponding to y; p represents the oil film pressure value at that point.

[0107] Furthermore, friction and pumping rate may be selected as important sealing performance parameters.

[0108] Among them, by integrating the friction force on the lip surface of the lip seal ring, the tangential friction force can be obtained as:

[0109]

[0110] Among them, F f represents the tangential friction force; b represents the axial width of the area; l represents the length of the contact area; h represents the oil film thickness under the convergence condition obtained by solving the Reynolds equation; p represents the oil film pressure under the convergence condition obtained by solving the Reynolds equation; η represents the viscosity of the lubricating oil; U represents the rotation speed of the rotating shaft.

[0111] The pumping rate can be expressed as:

[0112]

[0113] Wherein, Q represents the pumping rate; l represents the length of the contact area; h represents the oil film thickness under the convergence condition obtained by solving the Reynolds equation; p represents the oil film pressure under the convergence condition obtained by solving the Reynolds equation; η represents the viscosity of the lubricating oil.

[0114] Furthermore, when evaluating the sealing performance of a lip seal, it is necessary to consider the heat generated by friction and the heat transferred or retained through different mechanisms (such as the pumping effect).

[0115] According to the principle of energy conservation, the heat generated by the friction between the lip seal lip and the rotating shaft is equal to the heat "taken away" by the lubricating oil through the "pumping" effect and the heat retained in the sealing area:

[0116] fpV=Qρc(T-T0)+α2πRL(T-T0) (18)

[0117] Among them, f represents the friction coefficient; p represents the oil film pressure; Q represents the pumping rate; ρ represents the density; c represents the specific heat capacity; T represents the actual temperature; T0 represents the ambient temperature, that is, the initial temperature value; α represents the heat exchange coefficient of the lubricating oil; R represents the shaft radius; and L represents the shaft length.

[0118] Since the viscosity of the lubricating oil changes with temperature, after obtaining the actual temperature, the viscosity of the lubricating oil needs to be updated and then brought back to the hybrid elastohydrodynamic lubrication model to iterate and obtain a new temperature distribution. The Reynolds viscosity-temperature equation can be used to describe the relationship between fluid viscosity and temperature:

[0119]

[0120] Where η0 represents the viscosity at T0; α T represents the unknown coefficient; T represents the actual temperature; T0 represents the ambient temperature, that is, the initial temperature value.

[0121] For example, the Archard wear formula can be used to calculate the wear amount of the lip:

[0122]

[0123] Among them, f represents the wear amount of the lip surface; K represents the parameter related to the probability of particle wear generated by the two rough peaks in contact with each other; N represents the pressure acting on the contact surface between the sealing lip and the rotating shaft; H represents the material hardness of the rotating shaft.

[0124] Based on this, the precise three-dimensional microscopic surface morphology of the lip is constructed by applying the three-dimensional fractal theory, and the fluid-solid-thermal multi-field coupling analysis of the lip working environment is carried out to accurately simulate the lip seal under working conditions.

[0125] Step S130: determining a plurality of texture parameter intervals to be optimized based on the texture parameters and the sealing performance parameters.

[0126] Since there will inevitably be certain processing errors in the actual production process of seals, these errors may cause the sealing performance to deviate from the theoretical model prediction. Therefore, in order to more accurately evaluate the impact of these uncertain factors on the texture sealing performance, step S130 will use the input parameters in step S120 as input to perform multiple simulation analyses to obtain the possible variation range of the sealing performance parameters, and then determine multiple texture parameter ranges to be optimized.

[0127] Specifically, multiple simulations are performed based on the input parameters in step S120. In each simulation, the dimensional processing error of the texture shape is assumed to be a random variable in the interval [0, 1]. This random variable represents the range of possible errors from the minimum to the maximum.

[0128] Each simulation uses the analysis method of step S120, taking the randomly generated texture size processing error value as one of the input parameters. In this way, the sealing performance under different error levels can be evaluated, including key performance indicators such as oil film thickness, pressure distribution, friction and temperature.

[0129] Through multiple simulations, the sealing performance parameters obtained from each simulation are collected and analyzed to determine the range of performance variation and corresponding statistical characteristics. This includes calculating the mean (midpoint) and standard deviation (interval radius) of the target variable.

[0130] The result of step S130 will be directly used in the subsequent optimization iteration process of step S140. Each optimization iteration will be based on the interval (midpoint and radius) of the target variable obtained from the Monte Carlo simulation to ensure that the optimization strategy can take into account the uncertainty introduced by the machining error.

[0131] Based on this, uncertainty analysis based on Monte Carlo simulation is a key step in understanding and predicting the behavior of lip seals in the presence of machining errors. By simulating different error conditions, the stability and reliability of the sealing performance can be more comprehensively predicted.

[0132] Step S140: using a genetic algorithm to optimize multiple texture parameter intervals to be optimized to obtain a target texture parameter combination.

[0133] Step S140 is a process of optimizing the design variables of the lip seal assembly by using a genetic algorithm (GA) to handle the uncertainty of the seal texture parameters and to find a Pareto front solution under given constraints.

[0134] Step S141: define interval variables, interval midpoints and interval radius.

[0135] First, based on the results of the Monte Carlo method (step S130), each interval of texture parameters to be optimized is defined. The midpoint of the interval represents the expected average performance index, while the radius of the interval reflects the potential impact of processing errors or other uncertain factors on the performance.

[0136] Exemplarily, interval variables can be represented by interval mathematics as:

[0137] A I =[A L ,A R ] (twenty one)

[0138] Among them, A I Represents interval A; A L represents the lower bound of interval A; A R Represents the upper bound of interval A.

[0139] The midpoint of the interval and the radius of the interval are often used as important parameters for investigating the interval, which can be expressed as:

[0140]

[0141] Among them, A c Indicates the midpoint of interval A.

[0142]

[0143] Among them, A w Represents the radius of interval A.

[0144] Step S142: Determine the constraints and thresholds for optimization.

[0145] For example, the constraints and thresholds of the size parameters during optimization can be expressed as:

[0146]

[0147] Among them, h t Indicates the texture depth; h max Indicates the maximum machining depth; α1 indicates the air side angle; α2 indicates the liquid side angle.

[0148] Step S143: solving the optimization interval and finding the target texture parameter combination.

[0149] By applying the Monte Carlo method in step S130 to analyze the uncertainty of the seal texture parameters, each set of machining error uncertainties will result in an interval for the target variable (wear amount, pumping rate). Under the constraints, the operating parameters such as the rotation speed, the parameters of the shaft and the seal itself (elastic modulus, friction coefficient, wear coefficient) and other sealing component parameters are guaranteed to remain unchanged. The optimal performance interval is found from the several texture parameter intervals to be optimized based on the machining error uncertainty, and the texture parameter combination corresponding to this set of optimal intervals is returned. Under the given operating parameters, the decision variables are selected as: α1, α2, h t and the corresponding texture size parameters (defined in step S110 ), the decision variable is the target texture parameter combination, which is the final output.

[0150] Since pumping rate and friction torque are both important sealing properties, and wear and friction torque are positively correlated with the increase of wear time, pumping rate and wear can be used as the target variables for optimization, and friction torque can be regarded as the constraint condition of sealing. Therefore, in order to ensure that the sealing component designed after considering the uncertainty factor of texture processing error can meet the torque requirements, the constraint condition should consider the worst case so that it does not exceed the established threshold:

[0151] T e R ≤T e D (25)

[0152] Among them, T e R Indicates the maximum torque, T e D Indicates the torque threshold.

[0153] In addition to the friction torque constraint, the constraints on the dimensional parameters should be considered. The constraint expressions are shown in the above formula (24).

[0154] Under the condition that the working condition parameters remain unchanged, only the seal texture processing error is considered and the wear values ​​f1,f2,…,f are obtained by multi-field coupling simulation using the n-th Monte Carlo method. n and pumping rates Q1, Q2, ..., Q n There must be a maximum and a minimum value. According to the midpoint and radius representation method of interval mathematics, the wear amount and pumping rate can be expressed as:

[0155] f=[f m ,f w ] (26)

[0156] Q=[Q m ,Q w ] (27)

[0157] Among them, f m Indicates the midpoint of the wear range; f w Indicates the radius of the wear range; Q m Indicates the midpoint of the pumping rate range; Q w Indicates the radius of the pumping rate interval.

[0158] After m optimization iterations, m intervals of wear and pumping rate can be obtained as shown in equations (26) and (27). In order to identify the solution set that satisfies both the minimization of wear and the maximization of pumping rate, the optimization objective function can be expressed as:

[0159]

[0160] Among them, f m Indicates the midpoint of the wear range; f w Indicates the radius of the wear range; Q m Indicates the midpoint of the pumping rate range; Q w Indicates the radius of the pumping rate interval; T e R Indicates the maximum torque, T e D Indicates the torque threshold; h t Indicates the texture depth; h max Indicates the maximum machining depth; α1 indicates the air side angle; α2 indicates the liquid side angle.

[0161] By solving the four-variable optimization problem of formula (28) through genetic algorithm (GA), the Pareto frontier solution can be obtained, and the hierarchical analysis method can be used to weigh and select the optimal solution among these frontier solutions. After obtaining the optimal solution, the multi-field coupling and wear model in step S120 can be simulated again to verify the correctness of the optimization theory.

[0162] Based on the above embodiments, in another embodiment provided by the present disclosure, an experimental embodiment taking a triangular texture as an example is also provided.

[0163] First, step S110 is executed to establish the inner region of the triangular texture based on the above formula (1).

[0164] For example, Figure 3 A radial view of a two-dimensional triangular texture provided by an exemplary embodiment of the present disclosure is shown in FIG. Figure 3 As shown, red indicates textured areas and green indicates non-textured areas.

[0165] Furthermore, based on the above formula (11), the schematic diagram of the three-dimensional surface morphology of the triangular texture is obtained: Figure 4 A schematic diagram of the three-dimensional surface morphology of a triangular texture provided as an example in the present disclosure.

[0166] In step S110, the input parameters are as shown in Table 1:

[0167] Table 1 Input parameters of step S110

[0168] Input Parameters Numeric Fractal dimension D 2.3 Angle between base and circumference (°) 10 Left slope 1 Right slope -1 Texture depth (μm) 4 <![CDATA[Initial oil film thickness h0 (μm)]]> 5

[0169] Then, step S120 is executed, and the input parameters are as shown in Table 2:

[0170] Table 2 Input parameters of step S120

[0171]

[0172]

[0173] Execute step S121: The fluid dynamic pressure oil film thickness can be obtained by the above formula (12), and the oil film thickness equation and the oil film pressure equation are combined to calculate the oil film pressure value.

[0174] Execute step S122: solve the elastic deformation equation to obtain the elastic deformation of the lip, and update the oil film thickness according to the elastic deformation.

[0175] Execute step S123: Apply the point-by-point super-relaxation iteration method, and the convergence standard of the oil film thickness is defined as:

[0176]

[0177] Among them, ER is 0.01.

[0178] The above formula (29) is used to determine whether the oil film thickness and pressure of this iteration converge. If converged, the pumping rate and friction force and other parameters related to the sealing and lubrication of the lip seal ring can be calculated by the oil film thickness and the oil film pressure. If not converged, steps S121-S123 are repeated until the result is satisfactory.

[0179] Execute step S124: The hybrid thermal elastohydrodynamic lubrication model of the lip seal mainly considers the effect of temperature on the viscosity of the lubricating oil. The initial temperature is input, and the corresponding friction force and pumping rate are calculated through the hybrid elastohydrodynamic lubrication model (step S123). The new temperature value is calculated by thermal analysis, and the new temperature value is substituted into the viscosity-temperature equation to obtain the new viscosity of the lubricating oil. It is then iterated back to the original hybrid elastohydrodynamic lubrication model and recalculated until the temperature distribution error is less than the limit value.

[0180] After inputting the initial temperature, the relevant parameters of lubrication and sealing are obtained through the hybrid elastohydrodynamic lubrication model. The temperature at that time is solved by the energy conservation and heat conduction equations, and then the viscosity is updated using the viscosity-temperature equation. The obtained viscosity is iterated back to the original hybrid elastohydrodynamic lubrication model for calculation until the temperature error is less than 0.01.

[0181] Exemplarily, the temperature field convergence criterion is:

[0182]

[0183] Wherein, T1 represents the temperature value calculated last time; T2 represents the temperature of the last input viscosity value.

[0184] If the temperature field converges, the corresponding parameters are output. If the temperature field does not converge, steps S121-S124 are repeated until the result meets the convergence condition. The output parameters are shown in Table 3:

[0185] Table 3 Output parameters of step S120

[0186] Output Parameters Parameter Value Half-moon oil film pressure value (MPa) 0.01108 Output viscosity(Pas) 0.02 Pumping rate (ml / h) 5.836 Friction force (N) 0.029 Tangential torque(Nm) 0.0483 Average oil film thickness (μm) 5.63 Temperature(℃) 20.05 Average contact load (MPa) 0.1024 Contact load ratio 1.025 Wear rate 0.2048

[0187] Then, execute step S130, set the number of samples to 100, and set the processing error interval variable to [0,1] (the expression of the processing error interval variable can be found in the above formula (4)). Step S130 combines the Monte Carlo simulation method to perform uncertainty analysis on the texture size processing error. It only needs to set the number of simulations (number of samples) based on steps S110 and S120, and regard step S120 as each simulation of step S130. Step S130 provides the interval midpoint and interval radius required for analysis and optimization for step S140. For each optimization iteration, the result will generate a corresponding target variable interval (midpoint and radius).

[0188] Then, step S140 is performed, and the design variables may include α1 (gas side angle), α2 (liquid side angle), texture processing depth and texture size, wherein the gas side angle, liquid side angle and texture processing depth are all given in the form of upper and lower limits. Thresholds and simulation conditions are set, and the Pareto front solution is obtained to determine the target texture parameter combination.

[0189] The texture parameter values ​​in step S140 are shown in Table 4:

[0190] Table 4 Texture parameter values ​​of step S140

[0191] Design variables Parameter Value Air side angle lower limit (℃) 30 Upper limit of air side angle (℃) 33 Liquid side angle lower limit (℃) 45 Liquid side angle lower limit (℃) 48 Lower limit of texture processing depth (μm) 2 Upper limit of texture processing depth (μm) 3 Left slope 1 Right slope -1

[0192] For example, Figure 5 A schematic diagram of a Pareto front solution provided as an example in the present disclosure is shown in FIG. Figure 5 As shown, the black dots represent the solutions obtained in each cycle, and ⊙ represents the frontier solutions.

[0193] The target texture parameter combination outputted in step S140 is shown in Table 5:

[0194] Table 5 Target texture parameter combinations

[0195] Design variables Numeric Processing depth (μm) 3.796 Texture size parameter 1 1.023 Texture size parameter 2 -0.8359 Air side angle(℃) 31.35 Liquid side angle (℃) 46.2

[0196] One or more technical solutions provided in the exemplary embodiments of the present disclosure first comprehensively define the lip seal texture, covering key parameters such as texture morphology and posture, and accurately describe the specific characteristics of the texture in a rectangular coordinate system. This detailed definition helps to ensure the accuracy and reliability of subsequent simulation and optimization processes, and provides a solid foundation for seal design.

[0197] Secondly, the three-dimensional fractal theory was applied to construct the three-dimensional microscopic surface morphology of the lip, and the fluid-solid-thermal multi-field coupling analysis of the lip working environment was performed to accurately simulate the performance of the lip seal under actual working conditions.

[0198] In addition, the genetic algorithm combined with the Monte Carlo statistical method was used to comprehensively optimize the macro and micro design parameters of the lip seal. In this way, not only can a single parameter be processed and optimized, but also the interaction between the design parameters and their impact on the sealing performance can be considered, thereby solving the Pareto front solution, providing an effective solution strategy for multi-objective optimization problems.

[0199] Therefore, the lip seal structure optimization method provided in the exemplary embodiment of the present disclosure can seek the optimal target texture parameter combination through Monte Carlo simulation and genetic algorithm, thereby ensuring that the rotating shaft lip seal can achieve the best sealing effect under actual working conditions.

[0200] The above mainly introduces the solutions provided by the exemplary embodiments of the present disclosure. It is understandable that in order to implement the above functions, the electronic device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present disclosure.

[0201] The exemplary embodiments of the present disclosure can divide the functional units of the electronic device according to the above method examples. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the exemplary embodiments of the present disclosure is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0202] In the case of dividing each functional module according to each function, an exemplary embodiment of the present disclosure provides a lip seal structure optimization device, which can be a server or a chip applied to a server. Figure 6 This is a schematic block diagram of the functional modules of a lip seal structure optimization device provided by the present disclosure. Figure 6 As shown, the lip seal structure optimization device 600 includes:

[0203] The data acquisition module 610 is used to define the texture parameters of the lip seal to be optimized.

[0204] The data processing module 620 is used to perform fluid-solid-thermal multi-field coupling analysis on the texture parameters of the lip seal to be optimized to obtain sealing performance parameters.

[0205] The data processing module 620 is further used to determine a plurality of texture parameter intervals to be optimized based on the texture parameters and the sealing performance parameters.

[0206] The data processing module 620 is further configured to use a genetic algorithm to optimize the multiple texture parameter intervals to be optimized to obtain a target texture parameter combination.

[0207] In another embodiment provided in the present disclosure, the data processing module 620 is also used to define the texture area of ​​the lip seal to be optimized based on a rectangular coordinate system; define a processing error interval; and determine the texture parameters of the lip seal to be optimized based on the texture area and the processing error interval.

[0208] In another embodiment provided by the present disclosure, the data processing module 620 is also used to construct the three-dimensional microscopic surface morphology of the lip seal to be optimized using three-dimensional fractal theory; evaluate the sealing performance parameters and temperature of the three-dimensional microscopic surface morphology under preset working parameters through a pre-constructed hybrid elastohydrodynamic lubrication model; and output the sealing performance parameters when the temperature meets the preset conditions.

[0209] In another embodiment provided by the present disclosure, the data processing module 620 further includes: the sealing performance parameters include tangential friction and pumping rate; the tangential friction is expressed as:

[0210]

[0211] Among them, F f represents the tangential friction force; b represents the axial width of the area; l represents the length of the contact area; h represents the oil film thickness under the convergence condition obtained by solving the Reynolds equation; p represents the oil film pressure under the convergence condition obtained by solving the Reynolds equation; η represents the viscosity of the lubricating oil; U represents the rotation speed of the rotating shaft;

[0212] The pumping rate is expressed as:

[0213]

[0214] Wherein, Q represents the pumping rate; l represents the length of the contact area; h represents the oil film thickness under the convergence condition obtained by solving the Reynolds equation; p represents the oil film pressure under the convergence condition obtained by solving the Reynolds equation; η represents the viscosity of the lubricating oil.

[0215] In another embodiment provided in the present disclosure, the data processing module 620 is also used to extract random variables multiple times in the processing error range and determine multiple texture parameters considering the processing error; simulate the multiple texture parameters considering the processing error in turn through Monte Carlo simulation to obtain corresponding sealing performance parameters considering the processing error; and determine multiple texture parameter intervals to be optimized based on the multiple sealing performance parameters considering the processing error.

[0216] In another embodiment provided by the present disclosure, the data processing module 620 is also used to define an optimization objective function; the genetic algorithm evaluates multiple texture parameter intervals to be optimized through the objective function to obtain corresponding frontier solutions; and the hierarchical analysis method is used to optimize the multiple frontier solutions to obtain the target texture parameter combination.

[0217] In another embodiment provided by the present disclosure, the data processing module 620 further includes: the objective function is expressed as:

[0218] min{f m ,f w ,-Q m ,-Q w}

[0219]

[0220] Among them, f m Indicates the midpoint of the wear range; f w Indicates the radius of the wear range; Q m Indicates the midpoint of the pumping rate range; Q w Indicates the radius of the pumping rate interval; T e R Indicates the maximum torque, T e D Indicates the torque threshold; h t Indicates the texture depth; h max Indicates the maximum machining depth; α1 indicates the air side angle; α2 indicates the liquid side angle.

[0221] The exemplary embodiment of the present disclosure also provides an electronic device, comprising: at least one processor; and a memory connected to the at least one processor in communication. The memory stores a computer program that can be executed by the at least one processor, and the computer program is used to cause the electronic device to perform the method according to the embodiment of the present disclosure when executed by the at least one processor.

[0222] The exemplary embodiments of the present disclosure also provide a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to perform the method according to the embodiments of the present disclosure.

[0223] Figure 7 The block diagram of the electronic device provided as an example of the present disclosure, the block diagram of the electronic device 700 that can be used as the server or client of the present disclosure will now be described, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples, and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0224] like Figure 7 As shown, the electronic device 700 includes a computing unit 701, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the electronic device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0225] A plurality of components in the electronic device 700 are connected to the I / O interface 705, including: an input unit 706, an output unit 707, a storage unit 708, and a communication unit 709. The input unit 706 may be any type of device capable of inputting information to the electronic device 700, and the input unit 706 may receive input digital or character information, and generate key signal inputs related to user settings and / or function control of the electronic device. The output unit 707 may be any type of device capable of presenting information, and may include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 708 may include but is not limited to a disk, an optical disk. The communication unit 709 allows the electronic device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and may include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0226] The computing unit 701 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 701 performs the various methods and processes described above. Each of the methods described above may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 700 via the ROM 702 and / or the communication unit 709.

[0227] Figure 8 This is a schematic diagram of an exemplary computer program product provided by the present disclosure. The exemplary embodiment of the present disclosure also provides a computer program product 800, including a computer program 801, wherein the computer program 801 is used to enable the computer to perform a method according to an embodiment of the present disclosure when executed by a processor of the computer.

[0228] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0229] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0230] As used in this disclosure, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0231] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0232] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0233] A computer system may include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship to each other.

[0234] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instruction is loaded and executed on a computer, the process or function described in the embodiment of the present disclosure is executed in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, a terminal, a user device or other programmable device. The computer program or instruction may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer program or instruction may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server, data center, etc. that integrates one or more available media. The available medium may be a magnetic medium, for example, a floppy disk, a hard disk, a tape; it may also be an optical medium, for example, a digital video disc (DVD); it may also be a semiconductor medium, for example, a solid state drive (SSD).

[0235] Although the present disclosure has been described in conjunction with specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present disclosure. Accordingly, this specification and the drawings are merely exemplary illustrations of the present disclosure as defined by the appended claims, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present disclosure. Obviously, those skilled in the art may make various modifications and variations to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is also intended to include these modifications and variations.

Claims

1. A method for optimizing a lip seal structure, characterized in that: The method comprises: defining texture parameters of the lip seal to be optimized; Performing fluid-solid-thermal multi-field coupling analysis on the texture parameters of the lip seal to be optimized to obtain sealing performance parameters; Determining a plurality of texture parameter intervals to be optimized based on the texture parameter and the sealing performance parameter; A genetic algorithm is used to optimize the multiple texture parameter intervals to be optimized to obtain a target texture parameter combination.

2. The method according to claim 1, characterized in that The texture parameters of the lip seal to be optimized are defined as follows: Defining a texture region of the lip seal to be optimized based on a rectangular coordinate system; Define the machining error range; The texture parameters of the lip seal to be optimized are determined based on the texture area and the processing error interval.

3. The method according to claim 1, characterized in that The fluid-solid-thermal multi-field coupling analysis is performed on the texture parameters of the lip seal to be optimized to obtain the sealing performance parameters, including: The three-dimensional microscopic surface morphology of the lip seal to be optimized is constructed using three-dimensional fractal theory; Evaluating the sealing performance parameters and temperature of the three-dimensional microscopic surface topography under preset working parameters through a pre-constructed hybrid elastohydrodynamic lubrication model; After the pressure and temperature iterations converge, the sealing performance parameters are output.

4. The method according to claim 3, characterized in that The sealing performance parameters include tangential friction and pumping rate; The tangential friction force is expressed as: Among them, F f represents the tangential friction force; b represents the axial width of the area; l represents the length of the contact area; h represents the oil film thickness under the convergence condition obtained by solving the Reynolds equation; p represents the oil film pressure under the convergence condition obtained by solving the Reynolds equation; η represents the viscosity of the lubricating oil; U represents the rotation speed of the rotating shaft; The pumping rate is expressed as: Wherein, Q represents the pumping rate; l represents the length of the contact area; h represents the oil film thickness under the convergence condition obtained by solving the Reynolds equation; p represents the oil film pressure under the convergence condition obtained by solving the Reynolds equation; η represents the viscosity of the lubricating oil.

5. The method according to claim 2, characterized in that: The determining a plurality of texture parameter intervals to be optimized based on the texture parameter and the sealing performance parameter comprises: extracting random variables multiple times in the machining error interval, and determining multiple texture parameters taking the machining error into consideration; Simulating multiple texture parameters taking into account processing errors in sequence through Monte Carlo simulation to obtain corresponding sealing performance parameters taking into account processing errors; Based on multiple sealing performance parameters taking into account processing errors, multiple texture parameter intervals to be optimized are determined.

6. The method according to claim 1, characterized in that The step of optimizing the plurality of texture parameter intervals to be optimized by using a genetic algorithm to obtain a target texture parameter combination includes: Define the objective function for optimization; The genetic algorithm evaluates multiple texture parameter intervals to be optimized through the objective function and obtains the corresponding frontier solution; The target texture parameter combination is obtained by optimizing multiple frontier solutions using the analytic hierarchy process.

7. The method according to claim 6, characterized in that The objective function is expressed as: min{f m ,f w ,-Q m ,-Q w } Among them, f m Indicates the midpoint of the wear range; f w Indicates the radius of the wear range; Q m Indicates the midpoint of the pumping rate range; Q w Indicates the radius of the pumping rate interval; T e R Indicates the maximum torque, T e D Indicates the torque threshold; h t Indicates the texture depth; h max Indicates the maximum machining depth; α1 indicates the air side angle; α2 indicates the liquid side angle.

8. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the method of claim 1.

9. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the method of claim 1 is implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the method of claim 1 is implemented.

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