Fatigue safety coefficient prediction method and device

Abstract

The invention provides a method and a device for predicting a fatigue safety coefficient. The method comprises the following steps: acquiring physical parameters, structural characteristic information, nonlinear factors and material fatigue attributes of a to-be-predicted mechanical system; based on the physical parameters, the structural characteristic information and the non-linear factors, constructing a non-dimensionalized non-linear multi-body dynamic model; simulating the non-dimensionalized nonlinear multi-body dynamic model through a harmonic balance method to obtain a system dynamic response; calculating stress-strain response data of a preset part in the to-be-predicted mechanical system based on the system dynamic response; and calculating a life prediction value of the preset part by using a preset life calculation expression in combination with the stress-strain response data and the material fatigue attribute. The nonlinear characteristics in the nonlinear multi-body dynamic model of the to-be-predicted mechanical system are accurately captured by using the harmonic balance method, the solving process is simplified, the calculation complexity and resource consumption are reduced, and the precision of fatigue life estimation is improved.

Description

Technical Field

[0001] This invention relates to the field of structural fatigue reliability technology, and in particular to a method and apparatus for predicting fatigue safety factor. Background Technology

[0002] Calculating fatigue life in nonlinear dynamics is an important topic in engineering, especially in complex systems where nonlinear characteristics have a significant impact on fatigue life. To address this challenge, current research mainly focuses on three directions: finite element simulation combined with fatigue damage models, direct solution of nonlinear dynamic equations, and estimation methods based on experimental data. The aim is to capture nonlinear dynamic characteristics and evaluate fatigue life through different technical approaches.

[0003] Finite element simulation combined with fatigue damage models offers high accuracy and can handle the nonlinear characteristics of complex systems, but it suffers from drawbacks such as high computational resource consumption, complex solution processes, and strong dependence on mesh generation. Directly solving nonlinear dynamic equations can capture nonlinear dynamic characteristics, but the solution is difficult, sensitive to initial / boundary conditions leading to unstable results, and nonlinear interactions in multibody systems exacerbate the solution complexity. Estimation methods based on experimental data directly reflect actual working conditions, but they are costly, have limited applicability, and are prone to estimation errors due to differences between experimental and actual working conditions. Furthermore, linear assumption methods are simple but have low accuracy, and while the algorithms are applicable to periodic systems, they suffer from truncation errors. Summary of the Invention

[0004] This invention provides a method and apparatus for predicting fatigue safety factor, which estimates the fatigue life of a multibody dynamic system by using the harmonic balance method, so as to quickly predict the fatigue failure process of the mechanical system.

[0005] In a first aspect, the present invention provides a method for predicting fatigue safety factors, comprising: Step S1: Obtain the physical parameters, structural characteristics, nonlinear factors, and material fatigue properties of the mechanical system to be predicted; Step S2: Based on the physical parameters, the structural characteristic information, and the nonlinear factors, construct a dimensionless nonlinear multibody dynamics model; Step S3: Simulate the dimensionless nonlinear multibody dynamics model using the harmonic balance method to obtain the system dynamic response; Step S4: Based on the system dynamic response, calculate the stress-strain response data of a preset part in the mechanical system to be predicted; Step S5: Using a preset life calculation expression, combined with the stress-strain response data and the material fatigue properties, calculate the predicted life value of the preset part.

[0006] Optionally, step S2 includes: Based on the physical parameters, the structural characteristic information, and the nonlinear factors, the nonlinear multibody dynamic differential equations of the mechanical system to be predicted are established using the Newton-Euler method or the Lagrange method. The nonlinear multibody dynamics differential equations are made dimensionless to obtain the dimensionless nonlinear multibody dynamics model.

[0007] Optionally, step S3 includes: The solution of the dimensionless nonlinear multibody dynamics model is assumed to be in harmonic form; Substituting the solution in the harmonic form into the dimensionless nonlinear multibody dynamics model, the differential equation is transformed into a system of nonlinear algebraic equations about the harmonic coefficients using the harmonic balance method. Solving the nonlinear algebraic equations yields the harmonic coefficients, which in turn provide the system's dynamic response.

[0008] Optionally, the structural characteristic information includes: geometric parameters and cross-sectional area; step S4 includes: Based on the system's dynamic response, determine the damping force and stiffness force; Based on the damping force, stiffness force, and geometric parameters of the preset location, and in conjunction with the cross-sectional area, the stress-strain response data of the preset location are calculated.

[0009] Optionally, the material fatigue properties include: material fatigue limit, effective stress concentration factor, size factor, surface condition factor, and mean stress reduction factor; the life calculation expression is: ; in, For fatigue life, The fatigue limit of the material. The effective stress concentration factor, This is a size factor. The surface state coefficient, For equivalent alternating stress, This is the average stress reduction factor. This is the equivalent average stress.

[0010] Optionally, after step S5, the method further includes: The mechanical system to be predicted is designed and optimized based on the predicted life value. If the fatigue life does not meet the preset target, the physical parameters and / or the structural characteristic information and / or the nonlinear factor system are adjusted, and steps S1 to S5 are repeated until the fatigue life meets the preset target.

[0011] Secondly, the present invention provides a device for predicting fatigue safety factors, comprising: The acquisition module is used to acquire the physical parameters, structural characteristics, nonlinear factors, and material fatigue properties of the mechanical system to be predicted. The model building module is used to construct a dimensionless nonlinear multibody dynamics model based on the physical parameters, the structural characteristic information, and the nonlinear factors. The simulation module is used to simulate the dimensionless nonlinear multibody dynamics model using the harmonic balance method to obtain the system dynamic response. The response data calculation module is used to calculate the stress-strain response data of a preset part in the mechanical system to be predicted based on the dynamic response of the system. The prediction module is used to calculate the predicted life value of the preset location by using a preset life calculation expression, combined with the stress-strain response data and the material fatigue properties.

[0012] Thirdly, the present invention provides an electronic device including a processor and a memory, the memory storing computer-readable instructions that, when executed by the processor, perform the steps of the method provided in the first aspect above.

[0013] Fourthly, the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the method provided in the first aspect above.

[0014] Fifthly, the present invention provides a computer program product comprising a computer program that, when executed by a processor, performs the steps of the method provided in the first aspect above.

[0015] As can be seen from the above technical solutions, the present invention has the following advantages: This invention provides a method and apparatus for predicting fatigue safety factors. The method includes: Step S1, acquiring the physical parameters, structural characteristic information, nonlinear factors, and material fatigue properties of the mechanical system to be predicted; Step S2, constructing a dimensionless nonlinear multibody dynamics model based on the physical parameters, structural characteristic information, and nonlinear factors; Step S3, simulating the dimensionless nonlinear multibody dynamics model using the harmonic balance method to obtain the system dynamic response; Step S4, calculating the stress-strain response data of a preset part in the mechanical system to be predicted based on the system dynamic response; Step S5, calculating the predicted life value of the preset part using a preset life calculation expression, combined with the stress-strain response data and the material fatigue properties. The harmonic balance method accurately captures the nonlinear characteristics in the nonlinear multibody dynamics model of the mechanical system to be predicted, simplifies the solution process, reduces computational complexity and resource consumption, and improves the accuracy of fatigue life estimation. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the steps of a method for predicting fatigue safety factors according to the present invention. Figure 2 This is a flowchart illustrating the second embodiment of the fatigue safety factor prediction method of the present invention. Figure 3 This is a schematic diagram of an automobile suspension system, illustrating a second embodiment of the fatigue safety factor prediction method of the present invention. Figure 4 The time-displacement curve obtained by the fourth-order Runge-Kutta algorithm; Figure 5 The amplitude-frequency response curve obtained by the fourth-order Runge-Kutta algorithm; Figure 6 This is one of the phase diagrams obtained using the fourth-order Runge-Kutta algorithm; Figure 7 The second phase diagram obtained using the fourth-order Runge-Kutta algorithm; Figure 8 The Poincaré map obtained by the fourth-order Runge-Kutta algorithm; Figure 9 The time-displacement curve obtained by the harmonic balance method; Figure 10 The amplitude-frequency response curve obtained by the harmonic balance method; Figure 11 This is one of the phase diagrams obtained through the harmonic balance method; Figure 12 The second phase diagram obtained by the harmonic balance method; Figure 13 The Poincaré map obtained by the harmonic balance method; Figure 14 A schematic diagram of stress and strain data for preset parts of the suspension system; Figure 15 This is a structural block diagram of an embodiment of a fatigue safety factor prediction device according to the present invention. Detailed Implementation

[0018] This invention provides a method and apparatus for predicting fatigue safety factor, which estimates the fatigue life of a multibody dynamic system using the harmonic balance method, so as to quickly predict the fatigue failure process of the mechanical system.

[0019] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0020] Example 1 Please see Figure 1 , Figure 1 This is a flowchart illustrating the steps of a method for predicting fatigue safety factors according to an embodiment of the present invention. The method includes: Step S1: Obtain the physical parameters, structural characteristics, nonlinear factors, and material fatigue properties of the mechanical system to be predicted; This application takes an automotive suspension system as an example to obtain its physical parameters, including the mass of each component, spring stiffness, and damping coefficient; structural characteristic information, including geometric parameters, spring cross-sectional area, and component connection relationships; nonlinear factors, including the nonlinear characteristics of materials and contact nonlinearity; and material fatigue properties, including material fatigue limit, effective stress concentration factor, size factor, surface condition factor, and average stress reduction factor.

[0021] Step S2: Based on the physical parameters, the structural characteristic information, and the nonlinear factors, construct a dimensionless nonlinear multibody dynamics model; In this embodiment of the application, a nonlinear multibody dynamics model including components such as springs, shock absorbers, and connecting rods is established. Then, the nonlinear multibody dynamics model is dimensionless to obtain a dimensionless nonlinear multibody dynamics model.

[0022] Step S3: Simulate the dimensionless nonlinear multibody dynamics model using the harmonic balance method to obtain the system dynamic response; In this embodiment, the harmonic balance method is used to simulate a dimensionless nonlinear multibody dynamics model. An expression for the assumed solution is derived, and this assumed solution is substituted into the dynamic equations to obtain an equation where each harmonic coefficient equals 0. The harmonic coefficients are then solved to obtain the system's dynamic response.

[0023] Step S4: Based on the system dynamic response, calculate the stress-strain response data of a preset part in the mechanical system to be predicted; In this application, after obtaining the displacement response, the damping force and stiffness force are calculated based on the dynamic response, and then divided by the cross-sectional area of ​​the spring to obtain the stress-strain response data of the key parts of the suspension system.

[0024] Step S5: Using a preset life calculation expression, combined with the stress-strain response data and the material fatigue properties, calculate the predicted life value of the preset part.

[0025] In this embodiment of the application, based on structural dynamics theory, a preset life calculation expression is used, combined with stress-strain response data and material fatigue properties, to calculate the predicted life value of a preset part, including calculating the failure probability and remaining life at each stage.

[0026] This invention provides a method for predicting fatigue safety factors, comprising: Step S1, acquiring physical parameters, structural characteristic information, nonlinear factors, and material fatigue properties of the mechanical system to be predicted; Step S2, constructing a dimensionless nonlinear multibody dynamics model based on the physical parameters, structural characteristic information, and nonlinear factors; Step S3, simulating the dimensionless nonlinear multibody dynamics model using the harmonic balance method to obtain the system dynamic response; Step S4, calculating the stress-strain response data of a preset part in the mechanical system to be predicted based on the system dynamic response; and Step S5, calculating the predicted life value of the preset part using a preset life calculation expression, combined with the stress-strain response data and the material fatigue properties. The harmonic balance method accurately captures the nonlinear characteristics in the nonlinear multibody dynamics model of the mechanical system to be predicted, simplifies the solution process, reduces computational complexity and resource consumption, and improves the accuracy of fatigue life estimation.

[0027] Example 2 Please see Figure 2 , Figure 2 This is a flowchart illustrating a second embodiment of the fatigue safety factor prediction method of the present invention. The steps include: Step S201: Obtain the physical parameters, structural characteristic information, nonlinear factors, and material fatigue properties of the mechanical system to be predicted; the structural characteristic information includes: geometric parameters and spring cross-sectional area; the material fatigue properties include: material fatigue limit, effective stress concentration factor, size factor, surface condition factor, and average stress reduction factor. This application takes an automobile suspension as an example. The structural characteristic information includes: geometric parameters and spring cross-sectional area; the material fatigue properties include: material fatigue limit, effective stress concentration factor, size factor, surface condition factor and mean stress reduction factor.

[0028] Step S202: Based on the physical parameters, the structural characteristic information, and the nonlinear factors, establish the nonlinear multibody dynamic differential equation of the mechanical system to be predicted using the Newton-Euler method or the Lagrange method. In the embodiments of this application, according to Figure 3 The physical parameters, structural characteristics, and nonlinear factors of the automotive suspension system are analyzed. Nonlinear multibody dynamic differential equations are established using the Newton-Euler method or the Lagrange method, incorporating the various components of the suspension system, such as springs, shock absorbers, and linkages. Specifically: ; ; in, For the sprung mass, for The damping coefficient of the main shock absorber. for The first derivative of the absolute displacement, This refers to the tire damping coefficient. for The first derivative of the absolute displacement, The main spring stiffness coefficient, for absolute displacement, The first nonlinear stiffness coefficient, for absolute displacement, This is the second nonlinear stiffness coefficient. This is the tire spring stiffness coefficient. Input acceleration to the road surface, For unsprung mass, For The second derivative of the absolute displacement.

[0029] Step S203: The nonlinear multibody dynamics differential equation is dimensionless to obtain the dimensionless nonlinear multibody dynamics model. The equations are dimensionless, transforming them into a dimensionless nonlinear multibody dynamics model to simplify calculations and analysis.

[0030] The nonlinear multibody dynamics differential equations are then treated dimensionlessly to obtain a dimensionless nonlinear multibody dynamics model, such as by treating the equations as follows: ; ; in, For the first dimensionless displacement, For the first dimensionless velocity, For the first dimensionless acceleration, The first relative damping ratio, The second relative damping ratio, It is a nonlinear strength coefficient. The excitation frequency is dimensionless. For dimensionless time, This is the second dimensionless displacement. For the second dimensionless velocity, For the second dimensionless acceleration, This refers to the mass ratio.

[0031] Step S204: Assume the solution of the dimensionless nonlinear multibody dynamics model is in harmonic form; In this embodiment of the application, the expression for the solution is assumed to be: ; ; in, Let ω be the system response angular frequency. For time, , , , This is the harmonic amplitude coefficient.

[0032] Step S205: Substitute the solution in the harmonic form into the dimensionless nonlinear multibody dynamics model, and transform the differential equation into a system of nonlinear algebraic equations about the harmonic coefficients using the harmonic balance method. In the embodiments of this application, the assumed harmonic form solution is substituted into the dimensionless dynamic model, and according to the harmonic balance principle, each harmonic coefficient is made equal to 0, resulting in a system of nonlinear algebraic equations about the harmonic coefficients.

[0033] Step S206: Solve the nonlinear algebraic equations to obtain the harmonic coefficients, and then obtain the dynamic response of the system; It should be noted that traditional nonlinear multibody dynamics models usually use numerical solutions to simulate the results. However, the new theory of harmonic balance can transform the nonlinear dynamic response of a structure into an approximate steady-state periodic response, which is an effective means of solving nonlinear dynamics.

[0034] Please see Figures 4-8 , Figures 4-8 This is a schematic diagram of the result of the fourth-order Runge-Kutta algorithm. In this embodiment, the fourth-order Runge-Kutta method is used to directly solve the differential equation established in step S202 to obtain the system's time-varying response. Figure 4 The figure shows the time displacement curve obtained by the fourth-order Runge-Kutta algorithm. As can be seen from the figure, the curve starts from the initial conditions, goes through a period of obvious oscillation, and then gradually converges to the steady-state periodic motion. Figure 5 The amplitude-frequency response curve obtained by the fourth-order Runge-Kutta algorithm is shown in the figure. As can be seen from the figure, the curve is composed of discrete points. In practical applications, it is necessary to perform time-domain integration for a long time at each frequency point to ensure that the transient response has decayed completely and only the steady-state data is retained. Figure 6 This is one of the phase diagrams obtained using the fourth-order Runge-Kutta algorithm. Figure 7 The second phase diagram obtained by the fourth-order Runge-Kutta algorithm shows that the trajectory starts from the initial point and gradually approaches and eventually forms a closed loop in a spiral or complex manner. Figure 8 The Poincaré map obtained using the fourth-order Runge-Kutta algorithm is shown in the figure. As can be seen from the figure, the points of the Poincaré map are initially scattered, but eventually converge to a point set. However, due to numerical errors and truncation errors, the points may not completely coincide and may have slight dispersion.

[0035] Please see Figures 9-13 , Figures 9-13 This is a schematic diagram of the results obtained through the harmonic balance method. In another aspect, this embodiment of the application uses the harmonic balance method to directly solve the differential equation established in step S202 to obtain the system's response over time. Figure 9 The figure shows the time displacement curve obtained by the harmonic balance method. As can be seen from the figure, the curve is a perfect periodic motion with stable amplitude from the beginning, without an initial transient process. Figure 10 The amplitude-frequency response curve obtained by the harmonic balance method is shown in the figure. As can be seen from the figure, the steady-state response amplitude curve is smooth throughout the entire frequency range. Figure 11 This is one of the phase diagrams obtained through the harmonic balance method. Figure 12 The second phase diagram obtained by the harmonic balance method shows that the trajectory is a clear, continuous loop that does not contain any transient paths leading to the limit loop. Figure 13 The Poincaré map obtained by the harmonic balance method consists of one or more distinct discrete points, which are idealized, scatter-free, and precise points.

[0036] This application uses the harmonic balance method to solve a system of nonlinear algebraic equations to obtain the harmonic coefficients, which are: a1=0.1217, a2= 0.1, b1= 0.0007836, b2= 0.6334, and thus the system dynamic response is obtained.

[0037] Step S207: Based on the system's dynamic response, determine the damping force and stiffness force; Based on information such as displacement in the system's dynamic response, the damping force and stiffness force are calculated.

[0038] Step S208: Based on the damping force and stiffness force and the geometric parameters of the preset part, and in combination with the cross-sectional area, calculate the stress-strain response data of the preset part; In this embodiment, the damping force and stiffness force are divided by the cross-sectional area of ​​the spring, and combined with the geometric parameters of the preset location, the stress-strain data of the preset location (critical location) of the suspension system are obtained, such as... Figure 14 As shown.

[0039] Step S209: Using a preset life calculation expression, combined with the stress-strain response data and the material fatigue properties, calculate the predicted life value of the preset part. The lifetime calculation expression is as follows: ; in, For fatigue life, The fatigue limit of the material. The effective stress concentration factor, This is a size factor. The surface state coefficient, For equivalent alternating stress, This is the average stress reduction factor. This is the equivalent average stress.

[0040] In this embodiment of the application, the life prediction value of a preset part is calculated by using the life calculation expression, combined with stress-strain response data and material fatigue properties, including failure probability and remaining life.

[0041] In an optional embodiment, after calculating the predicted life value of the preset location using a preset life calculation expression, combined with the stress-strain response data and the material fatigue properties, the method further includes: The mechanical system to be predicted is designed and optimized based on the predicted lifespan. If the fatigue life does not meet the preset target, the physical parameters and / or the structural characteristic information and / or the nonlinear factor system are adjusted, and steps S201 to S209 are repeated until the fatigue life meets the preset target.

[0042] In this embodiment, the design of the suspension system is optimized based on the fatigue life prediction results, such as improving material selection, adjusting structural design, and optimizing manufacturing processes. If the fatigue life does not meet the preset target, the relevant parameters are readjusted, and calculations and analyses are performed again until the requirements are met, thereby improving its fatigue life and reliability under various operating conditions and reducing maintenance costs and failure risks.

[0043] This invention provides a method for predicting fatigue safety factors, comprising: Step S1, acquiring physical parameters, structural characteristic information, nonlinear factors, and material fatigue properties of the mechanical system to be predicted; Step S2, constructing a dimensionless nonlinear multibody dynamics model based on the physical parameters, structural characteristic information, and nonlinear factors; Step S3, simulating the dimensionless nonlinear multibody dynamics model using the harmonic balance method to obtain the system dynamic response; Step S4, calculating the stress-strain response data of a preset part in the mechanical system to be predicted based on the system dynamic response; and Step S5, calculating the predicted life value of the preset part using a preset life calculation expression, combined with the stress-strain response data and the material fatigue properties. The harmonic balance method accurately captures the nonlinear characteristics in the nonlinear multibody dynamics model of the mechanical system to be predicted, simplifying the solution process, reducing computational complexity and resource consumption, and improving the accuracy of fatigue life estimation. Furthermore, theoretical modeling and numerical simulation reduce reliance on experimental data, lower costs and experimental difficulty, while improving the method's versatility and generalizability.

[0044] Example 3 Please see Figure 15 , Figure 15 This is a structural block diagram of an embodiment of a fatigue safety factor prediction device according to the present invention. The device includes: The acquisition module 301 is used to acquire the physical parameters, structural characteristics, nonlinear factors, and material fatigue properties of the mechanical system to be predicted. The model building module 302 is used to build a dimensionless nonlinear multibody dynamics model based on the physical parameters, the structural characteristic information and the nonlinear factors. Simulation module 303 is used to simulate the dimensionless nonlinear multibody dynamics model using the harmonic balance method to obtain the system dynamic response; The response data calculation module 304 is used to calculate the stress-strain response data of a preset part in the mechanical system to be predicted based on the system dynamic response; The prediction module 305 is used to calculate the predicted life value of the preset part by using a preset life calculation expression, combined with the stress-strain response data and the material fatigue properties.

[0045] In an optional embodiment, the model building module 302 includes: The equation establishment submodule is used to establish the nonlinear multibody dynamic differential equations of the mechanical system to be predicted based on the physical parameters, the structural characteristic information and the nonlinear factors, using the Newton-Euler method or the Lagrange method. The dimensionless processing submodule is used to perform dimensionless processing on the nonlinear multibody dynamics differential equations to obtain the dimensionless nonlinear multibody dynamics model.

[0046] In an optional embodiment, the simulation module 303 includes: A submodule is set up to assume that the solution of the dimensionless nonlinear multibody dynamics model is in harmonic form; The transformation submodule is used to substitute the solution in the harmonic form into the dimensionless nonlinear multibody dynamics model, and transform the differential equation into a system of nonlinear algebraic equations about the harmonic coefficients through the harmonic balance method. The solution submodule is used to solve the nonlinear algebraic equations to obtain the harmonic coefficients, and then to obtain the dynamic response of the system.

[0047] In an optional embodiment, the structural characteristic information includes: geometric parameters and cross-sectional area; the response data calculation module 304 includes: The damping force and stiffness force determination submodule is used to determine the damping force and stiffness force based on the dynamic response of the system. The stress-strain response data calculation submodule is used to calculate the stress-strain response data of the preset part based on the damping force, stiffness force, and geometric parameters of the preset part, combined with the cross-sectional area.

[0048] In an optional embodiment, the material fatigue properties include: material fatigue limit, effective stress concentration factor, size factor, surface condition factor, and mean stress reduction factor; the life calculation expression is: ; in, For fatigue life, The fatigue limit of the material. The effective stress concentration factor, This is a size factor. The surface state coefficient, For equivalent alternating stress, This is the average stress reduction factor. This is the equivalent average stress.

[0049] In an optional embodiment, it further includes: The optimization module is used to optimize the design of the mechanical system to be predicted based on the predicted life value. If the fatigue life does not meet the preset target, the physical parameters and / or the structural characteristic information and / or the nonlinear factor system are adjusted, and the acquisition module 301 to acquisition module 305 are repeated until the fatigue life meets the preset target.

[0050] Example 4 This invention also provides an electronic device, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of a fatigue safety factor prediction method according to any embodiment.

[0051] Example 5 This invention also provides a computer storage medium storing a computer program thereon, wherein the computer program, when executed by the processor, implements the steps of a fatigue safety factor prediction method according to any embodiment.

[0052] Example 6 This invention also provides a computer program product having a computer program stored thereon, wherein when the computer program is executed by the processor, it implements the steps of a fatigue safety factor prediction method according to any embodiment.

[0053] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0054] In the several embodiments provided in this application, it should be understood that the methods, apparatuses, electronic devices, and storage media disclosed in this invention can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0055] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0056] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0057] If the integrated unit 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 technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned readable storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0058] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting fatigue safety factor, characterized in that, include: Step S1: Obtain the physical parameters, structural characteristics, nonlinear factors, and material fatigue properties of the mechanical system to be predicted; Step S2: Based on the physical parameters, the structural characteristic information, and the nonlinear factors, construct a dimensionless nonlinear multibody dynamics model; Step S3: Simulate the dimensionless nonlinear multibody dynamics model using the harmonic balance method to obtain the system dynamic response; Step S4: Based on the system dynamic response, calculate the stress-strain response data of a preset part in the mechanical system to be predicted; Step S5: Using a preset life calculation expression, combined with the stress-strain response data and the material fatigue properties, calculate the predicted life value of the preset part.

2. The method for predicting the fatigue safety factor according to claim 1, characterized in that, Step S2 includes: Based on the physical parameters, the structural characteristic information, and the nonlinear factors, the nonlinear multibody dynamic differential equations of the mechanical system to be predicted are established using the Newton-Euler method or the Lagrange method. The nonlinear multibody dynamics differential equations are made dimensionless to obtain the dimensionless nonlinear multibody dynamics model.

3. The method for predicting the fatigue safety factor according to claim 1, characterized in that, Step S3 includes: The solution of the dimensionless nonlinear multibody dynamics model is assumed to be in harmonic form; Substituting the solution in the harmonic form into the dimensionless nonlinear multibody dynamics model, the differential equation is transformed into a system of nonlinear algebraic equations about the harmonic coefficients using the harmonic balance method. Solving the nonlinear algebraic equations yields the harmonic coefficients, which in turn provide the system's dynamic response.

4. The method for predicting the fatigue safety factor according to claim 1, characterized in that, The structural characteristic information includes: geometric parameters and cross-sectional area; step S4 includes: Based on the system's dynamic response, determine the damping force and stiffness force; Based on the damping force, stiffness force, and geometric parameters of the preset location, and in conjunction with the cross-sectional area, the stress-strain response data of the preset location are calculated.

5. The method for predicting the fatigue safety factor according to claim 1, characterized in that, Material fatigue properties include: material fatigue limit, effective stress concentration factor, size factor, surface condition factor, and mean stress reduction factor; the life calculation expression is: ； in, For fatigue life, The fatigue limit of the material. The effective stress concentration factor, This is a size factor. The surface state coefficient, For equivalent alternating stress, This is the average stress reduction factor. This is the equivalent average stress.

6. The method for predicting the fatigue safety factor according to claim 1, characterized in that, After step S5, the method further includes: The mechanical system to be predicted is designed and optimized based on the predicted life value. If the fatigue life does not meet the preset target, the physical parameters and / or the structural characteristic information and / or the nonlinear factor system are adjusted, and steps S1 to S5 are repeated until the fatigue life meets the preset target.

7. A device for predicting fatigue safety factors, characterized in that, include: The acquisition module is used to acquire the physical parameters, structural characteristics, nonlinear factors, and material fatigue properties of the mechanical system to be predicted. The model building module is used to construct a dimensionless nonlinear multibody dynamics model based on the physical parameters, the structural characteristic information, and the nonlinear factors. The simulation module is used to simulate the dimensionless nonlinear multibody dynamics model using the harmonic balance method to obtain the system dynamic response. The response data calculation module is used to calculate the stress-strain response data of a preset part in the mechanical system to be predicted based on the dynamic response of the system. The prediction module is used to calculate the predicted life value of the preset location by using a preset life calculation expression, combined with the stress-strain response data and the material fatigue properties.

8. An electronic device, characterized in that, It includes a processor and a memory, the memory storing computer-readable instructions that, when executed by the processor, perform the method as described in any one of claims 1-6.

9. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it performs the method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1-6.

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