CN111177931A - Method and device for determining storage life of elastic element - Google Patents
Method and device for determining storage life of elastic element Download PDFInfo
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Abstract
The application discloses a method and a device for determining the storage life of an elastic element, wherein the method comprises the following steps: establishing a response surface model of fusion stress relaxation according to at least one group of preset characteristic parameters corresponding to each elastic element, wherein the response surface model of fusion stress relaxation comprises a stress relaxation response surface and is used for simulating a first elastic value of the elastic element; calculating to obtain a variation curve of the elastic value of each elastic element along with time according to the response surface model with the fused stress relaxation and the at least one group of characteristic parameters; determining the storage life of each elastic element according to the variation curve. The method and the device solve the technical problem that the service life prediction result of the elastic element is low in accuracy in the prior art.
Description
Technical Field
The present application relates to the field of elastic element storage technologies, and in particular, to a method and an apparatus for determining a storage life of an elastic element.
Background
Typically, the resilient elements in a ballistic engine need to be stored in a warehouse for a period of time after mass production, referred to as the shelf life of the element. In the long-term storage process, the elastic element is a typical weak storage link, is in a stressed installation state on the engine for a long time, and can generate a stress relaxation phenomenon due to long-term storage. In order to identify the storage rule of the elastic force of the element in different stages of the storage period, the elastic element needs to be subjected to fusion analysis of experimental measured data and simulation in the storage process.
At present, the elastic element is usually subjected to fusion analysis of experimental measured data and simulation by a finite element simulation method. Due to the problems of long time consumption, incapability of determining test conditions and the like of a stress relaxation test method, stress relaxation related research is difficult to realize, and the problems of uncertainty of a finite element model and parameters and the like of the conventional finite element simulation method, the service life prediction result of the elastic element in the prior art is low in accuracy.
Disclosure of Invention
The technical problem that this application was solved is: the accuracy of the service life prediction result of the elastic element in the prior art is low. The application provides a method and a device for determining the storage life of an elastic element, and the accuracy of the life prediction result of the elastic element is improved by fusing a stress relaxation response surface by combining a stress relaxation failure mechanism on the basis of a traditional stress relaxation response surface model.
In a first aspect, an embodiment of the present application provides a method for determining a storage life of an elastic element, the method including:
establishing a response surface model of fusion stress relaxation according to at least one group of preset characteristic parameters corresponding to each elastic element, wherein the response surface model of fusion stress relaxation comprises a stress relaxation response surface and is used for simulating a first elastic value of the elastic element;
calculating to obtain a variation curve of the elastic value of each elastic element along with time according to the response surface model with the fused stress relaxation and the at least one group of characteristic parameters;
determining the storage life of each elastic element according to the variation curve.
In the scheme provided by the embodiment of the application, a fused stress relaxation response surface model is established, and the fused stress relaxation response surface model comprises a stress relaxation response surface, namely the stress relaxation response surface is fused in the traditional fused stress relaxation response surface model, and stress relaxation process analysis is carried out to obtain the mathematical relation between the long storage characteristic and the storage life, so that the long storage performance simulation analysis of the elastic element is realized. Therefore, in the scheme provided by the embodiment of the application, the stress relaxation response surface is fused by combining the stress relaxation failure mechanism on the basis of the traditional stress relaxation response surface model, so that the accuracy of the service life prediction result of the elastic element is improved.
Optionally, establishing a response surface model of the fusion stress relaxation according to at least one set of preset characteristic parameters corresponding to each elastic element, including:
determining variable parameters of the stress-relaxed response surface model by a weighted stepwise regression analysis method;
calculating a first coefficient of the response surface model of the fusion stress relaxation according to the at least one group of characteristic parameters;
and establishing a response surface model of the fusion stress relaxation according to the first coefficient and the variable parameter.
Optionally, calculating a first coefficient of the response surface model of the fusion stress relaxation according to the at least one set of characteristic parameters includes:
calculating at least one group of second coefficients of the response surface model with the fused stress relaxation according to the at least one group of characteristic parameters, wherein the group number of the characteristic parameters corresponding to each elastic element is the same as the number of the variable parameters of the response surface model with the fused stress relaxation;
and weighting the at least one group of second coefficients to obtain the first coefficient.
Optionally, calculating a variation curve of the elastic force value of each elastic element with time according to the response surface model of the fusion stress relaxation and the at least one set of characteristic parameters, including:
determining the value range of each characteristic parameter in the group of characteristic parameters according to at least one group of preset characteristic parameters corresponding to each elastic element;
fitting according to the value range of each characteristic parameter and the response surface model data of the fusion stress relaxation to obtain a first elastic force value of each elastic element, wherein the difference between the first elastic force value and the actual elastic force value of each elastic element is smaller than a preset first threshold value;
determining each characteristic parameter value corresponding to the first elasticity value, and calculating the elasticity value of each elastic element at different moments according to each characteristic parameter value;
and obtaining a change curve of the elastic force value of each elastic element along with time according to the elastic force value of each elastic element at different moments.
Optionally, determining the storage life of each elastic element from the variation curve comprises:
determining a corresponding time point when the elasticity value is equal to a preset second threshold value according to the change curve;
determining a storage life of each of the elastic elements from the time points.
In a second aspect, embodiments of the present application provide an apparatus for determining a shelf life of an elastic element, the apparatus comprising:
the modeling unit is used for establishing a response surface model with fusion stress relaxation according to at least one group of preset characteristic parameters corresponding to each elastic element, wherein the response surface model with fusion stress relaxation comprises a stress relaxation response surface and is used for simulating a first elastic value of the elastic element;
the calculation unit is used for calculating a change curve of the elastic value of each elastic element along with time according to the response surface model with the fused stress relaxation and at least one preset group of characteristic parameters corresponding to each elastic element;
a determination unit for determining the storage life of each elastic element according to the variation curve.
Optionally, the modeling unit is specifically configured to:
determining variable parameters of the stress-relaxed response surface model by a weighted stepwise regression analysis method;
calculating a first coefficient of the response surface model of the fusion stress relaxation according to the at least one group of characteristic parameters;
and establishing a response surface model of the fusion stress relaxation according to the first coefficient and the variable parameter.
Optionally, the computing unit is specifically configured to:
calculating at least one group of second coefficients of the response surface model with the fused stress relaxation according to the at least one group of characteristic parameters, wherein the group number of the characteristic parameters corresponding to each elastic element is the same as the number of the variable parameters of the response surface model with the fused stress relaxation;
and weighting the at least one group of second coefficients to obtain the first coefficient.
Optionally, the computing unit is specifically configured to:
determining the value range of each characteristic parameter in the group of characteristic parameters according to at least one group of preset characteristic parameters corresponding to each elastic element;
fitting according to the value range of each characteristic parameter and the response surface model data of the fusion stress relaxation to obtain a first elastic force value of each elastic element, wherein the difference between the first elastic force value and the actual elastic force value of each elastic element is smaller than a preset first threshold value;
determining each characteristic parameter value corresponding to the first elasticity value, and calculating the elasticity value of each elastic element at different moments according to each characteristic parameter value;
and obtaining a change curve of the elastic force value of each elastic element along with time according to the elastic force value of each elastic element at different moments.
Optionally, the determining unit is specifically configured to:
determining a corresponding time point when the elasticity value is equal to a preset second threshold value according to the change curve;
determining a storage life of each of the elastic elements from the time points.
In a third aspect, the present application provides an electronic device, comprising:
a memory for storing instructions for execution by at least one processor;
a processor for executing instructions stored in a memory to perform the method of the first aspect.
In a fourth aspect, the present application provides a computer readable storage medium having stored thereon computer instructions which, when run on a computer, cause the computer to perform the method of the first aspect.
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FIG. 1 is a flow chart of a method for determining a storage life of a resilient element according to an embodiment of the present disclosure;
FIG. 2 is a schematic structural diagram of an apparatus for determining the storage life of an elastic element according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to better understand the technical solutions, the technical solutions of the present application are described in detail below with reference to the drawings and specific embodiments, and it should be understood that the specific features in the embodiments and examples of the present application are detailed descriptions of the technical solutions of the present application, and are not limitations of the technical solutions of the present application, and the technical features in the embodiments and examples of the present application may be combined with each other without conflict.
A method for determining the storage life of an elastic element provided in an embodiment of the present application is described in further detail below with reference to the drawings, and a specific implementation manner of the method may include the following steps (a flow of the method is shown in fig. 1):
step 101, establishing a response surface model with fusion stress relaxation according to at least one group of preset characteristic parameters corresponding to each elastic element, wherein the response surface model with fusion stress relaxation comprises a stress relaxation response surface, and is used for simulating a first elastic force value of the elastic element.
Specifically, in the solution provided in the embodiment of the present application, there are various ways to establish the response surface model of the fusion stress relaxation, and a preferred way is taken as an example for description below.
In one possible implementation, establishing a response surface model of the fusion stress relaxation according to at least one set of preset characteristic parameters corresponding to each elastic element includes: determining variable parameters of the stress-relaxed response surface model by a weighted stepwise regression analysis method; calculating a first coefficient of the response surface model of the fusion stress relaxation according to the at least one group of characteristic parameters; and establishing a response surface model of the fusion stress relaxation according to the first coefficient and the variable parameter.
Specifically, in the solution provided in the embodiment of the present application, each set of characteristic parameters includes a plurality of characteristic parameters, for example, each set of characteristic parameters includes a shear modulus relaxation coefficient, a bulk modulus relaxation coefficient, and a time relaxation coefficient of each elastic element. There are various models of the response surface of the fusion stress relaxation, and a preferred model will be described as an example.
The response surface model for stress relaxation is as follows:
wherein F is an elastic value and alphai(i 1, 2.. k) is a coefficient of the response surface model, and x is a coefficient of the response surface modeli(i 1, 2.. k), a, b are parameters of the response surface model.
Further, determining variable parameters of the stress relaxation response surface model by a weighted stepwise regression analysis method, where the variable parameters are elastic element characteristic parameters of a preset threshold value having a large influence on the stress relaxation response surface model, for example, shifting any one of the variable parameter values by 10% of an average value, calculating an elasticity value, and then determining a variable having an influence on the elasticity value greater than the preset threshold value as the variable parameters of the stress relaxation response surface model according to the calculated elasticity value, where the variable parameters include a shear modulus relaxation coefficient, a bulk modulus relaxation coefficient, a time relaxation coefficient, and the like of each elastic element.
Further, after the variable parameters of the stress relaxation response surface model are determined, at least one group of preset characteristic parameters of the elastic element are brought into the stress relaxation response surface model, and a first coefficient of the stress relaxation response surface model is obtained through calculation.
In one possible implementation, calculating a first coefficient of the response surface model of the fusion stress relaxation from the at least one set of characteristic parameters includes: calculating at least one group of second coefficients of the response surface model with the fused stress relaxation according to the at least one group of characteristic parameters, wherein the group number of the characteristic parameters corresponding to each elastic element is the same as the number of the variable parameters of the response surface model with the fused stress relaxation; and weighting the at least one group of second coefficients to obtain the first coefficient.
Further, after determining the first coefficient, establishing a response surface model of the fusion stress relaxation according to the first coefficient and the variable parameter.
102, calculating to obtain a change curve of the elastic value of each elastic element along with time according to the response surface model with the fused stress relaxation and the at least one group of characteristic parameters.
In one possible implementation manner, the calculating a variation curve of the elastic force value of each elastic element with time according to the response surface model of the fusion stress relaxation and the at least one set of characteristic parameters includes:
determining the value range of each characteristic parameter in the group of characteristic parameters according to at least one group of preset characteristic parameters corresponding to each elastic element;
fitting according to the value range of each characteristic parameter and the response surface model data of the fusion stress relaxation to obtain a first elastic force value of each elastic element, wherein the difference between the first elastic force value and the actual elastic force value of each elastic element is smaller than a preset first threshold value;
determining each characteristic parameter value corresponding to the first elasticity value, and calculating the elasticity value of each elastic element at different moments according to each characteristic parameter value;
and obtaining a change curve of the elastic force value of each elastic element along with time according to the elastic force value of each elastic element at different moments.
Specifically, in the solution provided in the embodiment of the present application, there are various ways to obtain the first elasticity value of each elastic element according to the value range of each characteristic parameter and the fitting of the response surface model data of the fusion stress relaxation, for example, a least square method, an interpolation method, and the like.
And 103, determining the storage life of each elastic element according to the change curve.
In one possible implementation, determining the storage life of each elastic element from the variation curve comprises:
determining a corresponding time point when the elasticity value is equal to a preset second threshold value according to the change curve;
determining a storage life of each of the elastic elements from the time points.
To facilitate an understanding of the above-described process of determining the shelf life of the elastic element, the following description is given by way of example.
Example (c): the pressure spring material of a certain elastic element is a cold-drawn steel wire 1Cr18Ni9Ti which is always in a stressed installation state on an engine, and in the process of prolonging the service life, the stress relaxation phenomenon of some samples after being stored for a long time is discovered. A large number of actual stored samples are utilized, original data of the pressure spring and actual measured data after storage are collected, and test data can be obtained after simple data processing and elimination of abnormal values.
The specific implementation method comprises the following steps: assuming that a stress relaxation phenomenon of an elastic element pressure spring of the engine obeys a stress relaxation constitutive model, and failure determination can be performed by detecting functional parameters (elasticity exceeds a rated tolerance range) of the elastic element, a storage life prediction method based on the fusion of an actual storage life test and simulation of the elastic element is provided according to the description to perform simulation material parameter optimization and reliability evaluation.
The method comprises the following steps: and (4) finite element simulation.
Firstly, the pressure spring is subjected to pretreatment analysis, the analysis step of the quasi-static compression process of the pressure spring is set to be 1s, and the analysis step of the stress relaxation analysis process is set to be 1.58 multiplied by 1012ms; setting a boundary condition, wherein the pressure spring is positioned between the upper rigid flat plate and the lower rigid flat plate, the bottom flat plate is fixed, and the top flat plate is compressed downwards to obtain the elasticity value of the pressure spring. Step two: solution of optimal simulation material parameters
Firstly, three parameters g are obtained through decentralized processing on the basis of the approximate value range of stress relaxation simulation parameters of the pressure spring material1,k1,τ1The statistical characteristics of (a) were designed as shown in table 1, assuming that all three variables obeyed a normal distribution.
TABLE 1 mean values and coefficients of variation of compression spring parameters
Secondly, in the selection of the test design method, as three material parameters need to be determined in the case of the design method, which belongs to the three-level design problem, the Box-Behnken test design method which is most commonly used in the traditional response surface method is adopted, as shown in Table 2. The Box-Behnken test design method has 15 groups of test numbers per se, including three groups of center point tests, and because the calculation results obtained by inputting specific conditions are the same when simulation analysis is carried out in finite element software, only one group of the three groups of center point tests is selected for simulation calculation, and finally only 13 groups of test numbers are selected.
Table 2 pressure spring BBD test design
Modeling and BBD test design of actually measured stored data of the pressure spring to obtain 13 groups of data weighted stepwise regression with different parameter combinations to perform coefficient estimation on a response surface equation of the fusion stress relaxation model, and obtaining the response surface equation of the fusion stress relaxation of the pressure spring as follows:
k can be obtained from the above equation of the response surface1Parameters are taken at [0,0.0002 ]]And (3) the influence on the fitting result is not obvious in the range, and the least square method is adopted to carry out parameter estimation on the formula to obtain the following optimal parameter combination result: when three simulation parameters g1＝0.152,k1＝0.0001,τ1＝3.3×1011When combined, make
Wherein n is the measured sample size, FkThe measured elastic force value of the kth sample size. Fki' is the simulated elasticity value at the storage time corresponding to the kth sample size. I.e. such that the response surface is closest to the measured stored value.
Step three: and (4) considering the individual difference of the elastic elements, and calculating the reliability to predict the service life.
And step two, finishing the estimation of parameters and coefficients of the response surface model fused with stress relaxation, considering the difference of individuals, controlling the simulation parameters and the model coefficients to be unchanged, solving initial values of different individuals of the pressure spring, and obtaining different response surface models based on stress relaxation:
wherein, i is 1,2, 3.
According to the distribution test, obtain
Then
I.e., N (. mu. "(t), 10.71312) Assume each FiTherefore, for the failure criterion of the compression spring, the threshold L is 260N, and the reliability functions under different years under the failure criterion 260N can be obtained as follows:
wherein μ "(t) is the mean value of the elastic force when the storage time is t.
Therefore, the reliability under different years can be obtained, and the reliability changes along with the storage time under the condition that the failure criterion is 260N.
Step four: method contrast verification
Firstly, modeling and parameter estimation are carried out on measured data; based on the stress relaxation model, in order to evaluate the reliability of the elastic element, the elastic value of the elastic element is set to be F (t), and the initial conditions of the compression spring are known as follows: when t is 0, the initial value of the elastic force is about 308.3062. And establishing the following model for the one-dimensional viscoelastic stress relaxation model:
wherein, the random variable Z-N (mu, sigma)2) Storage time of ti(i＝1,2,3,L,n)，FiRepresents tiThe ith elastic value of the moment, then
And each FiAre independent of each other.
Estimating model parameters by using equation (9) and the measured data and using maximum likelihood, wherein the parameter estimation result is as follows:
considering the difference of the individual bodies, controlling the estimated parameter result to be unchanged, solving the initial values of different individual models of the pressure spring to obtain a stress relaxation model as follows:
according to the distribution test, Z is obtainedi～N(274.4243,10.68252) Then each FiIndependent of each other， 
Given a failure criterion of the compression spring, i.e., a threshold value l is 260N, the reliability functions of the compression spring in different years under the failure criterion 260N can be obtained as follows:
where μ' (t) is the mean value of the spring force when the storage time is t.
Therefore, the reliability of the measured data in different years can be obtained. In order to verify the feasibility and the reasonableness of the method, the statistical analysis result obtained based on the actual measurement data is used as a standard, the service life prediction result obtained by the method is compared with the service life prediction result of the traditional analysis method for verification, and the reliability of the obtained typical elastic element compression spring is compared.
In the scheme provided by the embodiment of the application, a fused stress relaxation response surface model is established, and the fused stress relaxation response surface model comprises a stress relaxation response surface, namely the stress relaxation response surface is fused in the traditional fused stress relaxation response surface model, and stress relaxation process analysis is carried out to obtain the mathematical relation between the long storage characteristic and the storage life, so that the long storage performance simulation analysis of the elastic element is realized. Therefore, in the scheme provided by the embodiment of the application, the stress relaxation response surface is fused by combining the stress relaxation failure mechanism on the basis of the traditional stress relaxation response surface model, so that the accuracy of the service life prediction result of the elastic element is improved.
Based on the same inventive concept as the method shown in fig. 1, the embodiment of the present application provides a device for determining the storage life of an elastic element, referring to fig. 2, the device comprises:
the modeling unit 201 is configured to establish a response surface model with fusion stress relaxation according to at least one preset set of characteristic parameters corresponding to each elastic element, where the response surface model with fusion stress relaxation includes a stress relaxation response surface, and is used to simulate a first elastic value of the elastic element;
the calculating unit 202 is configured to calculate a change curve of the elastic value of each elastic element along with time according to the response surface model of the fusion stress relaxation and at least one preset set of characteristic parameters corresponding to each elastic element;
a determining unit 203 for determining the storage life of each elastic element according to the variation curve.
Optionally, the modeling unit 201 is specifically configured to:
determining variable parameters of the stress-relaxed response surface model by a weighted stepwise regression analysis method;
calculating a first coefficient of the response surface model of the fusion stress relaxation according to the at least one group of characteristic parameters;
and establishing a response surface model of the fusion stress relaxation according to the first coefficient and the variable parameter.
Optionally, the computing unit 202 is specifically configured to:
calculating at least one group of second coefficients of the response surface model with the fused stress relaxation according to the at least one group of characteristic parameters, wherein the group number of the characteristic parameters corresponding to each elastic element is the same as the number of the variable parameters of the response surface model with the fused stress relaxation;
and weighting the at least one group of second coefficients to obtain the first coefficient.
Optionally, the computing unit 202 is specifically configured to:
determining the value range of each characteristic parameter in the group of characteristic parameters according to at least one group of preset characteristic parameters corresponding to each elastic element;
fitting according to the value range of each characteristic parameter and the response surface model data of the fusion stress relaxation to obtain a first elastic force value of each elastic element, wherein the difference between the first elastic force value and the actual elastic force value of each elastic element is smaller than a preset first threshold value;
determining each characteristic parameter value corresponding to the first elasticity value, and calculating the elasticity value of each elastic element at different moments according to each characteristic parameter value;
and obtaining a change curve of the elastic force value of each elastic element along with time according to the elastic force value of each elastic element at different moments.
Optionally, the determining unit 203 is specifically configured to:
determining a corresponding time point when the elasticity value is equal to a preset second threshold value according to the change curve;
determining a storage life of each of the elastic elements from the time points.
Referring to fig. 3, the present application provides an electronic device, comprising:
a memory for storing instructions for execution by at least one processor;
a processor for executing instructions stored in memory to perform the method described in fig. 1.
A computer-readable storage medium having stored thereon computer instructions which, when executed on a computer, cause the computer to perform the method of fig. 1.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. A method of determining the shelf life of an elastic element, comprising:
establishing a response surface model of fusion stress relaxation according to at least one group of preset characteristic parameters corresponding to each elastic element, wherein the response surface model of fusion stress relaxation comprises a stress relaxation response surface and is used for simulating a first elastic value of the elastic element;
calculating to obtain a variation curve of the elastic value of each elastic element along with time according to the response surface model with the fused stress relaxation and the at least one group of characteristic parameters;
determining the storage life of each elastic element according to the variation curve.
2. The method of claim 1, wherein establishing a model of a response surface for fusion stress relaxation based on at least one predetermined set of characteristic parameters for each elastic element comprises:
determining variable parameters of the stress-relaxed response surface model by a weighted stepwise regression analysis method;
calculating a first coefficient of the response surface model of the fusion stress relaxation according to the at least one group of characteristic parameters;
and establishing a response surface model of the fusion stress relaxation according to the first coefficient and the variable parameter.
3. The method of claim 2, wherein calculating a first coefficient of the fused stress-relaxed response surface model from the at least one set of characteristic parameters comprises:
calculating at least one group of second coefficients of the response surface model with the fused stress relaxation according to the at least one group of characteristic parameters, wherein the group number of the characteristic parameters corresponding to each elastic element is the same as the number of the variable parameters of the response surface model with the fused stress relaxation;
and weighting the at least one group of second coefficients to obtain the first coefficient.
4. The method of claim 3, wherein calculating a change in the elastic force value of each elastic element over time based on the model of the response surface for the fusion stress relaxation and the at least one set of characteristic parameters comprises:
determining the value range of each characteristic parameter in the group of characteristic parameters according to at least one group of preset characteristic parameters corresponding to each elastic element;
fitting according to the value range of each characteristic parameter and the response surface model data of the fusion stress relaxation to obtain a first elastic force value of each elastic element, wherein the difference between the first elastic force value and the actual elastic force value of each elastic element is smaller than a preset first threshold value;
determining each characteristic parameter value corresponding to the first elasticity value, and calculating the elasticity value of each elastic element at different moments according to each characteristic parameter value;
and obtaining a change curve of the elastic force value of each elastic element along with time according to the elastic force value of each elastic element at different moments.
5. The method according to any one of claims 1 to 4, wherein determining the shelf life of each elastic element from the variation profile comprises:
determining a corresponding time point when the elasticity value is equal to a preset second threshold value according to the change curve;
determining a storage life of each of the elastic elements from the time points.
6. An apparatus for determining the shelf life of an elastic element, comprising:
the modeling unit is used for establishing a response surface model with fusion stress relaxation according to at least one group of preset characteristic parameters corresponding to each elastic element, wherein the response surface model with fusion stress relaxation comprises a stress relaxation response surface and is used for simulating a first elastic value of the elastic element;
the calculation unit is used for calculating a change curve of the elastic value of each elastic element along with time according to the response surface model with the fused stress relaxation and the at least one group of characteristic parameters;
a determination unit for determining the storage life of each elastic element according to the variation curve.
7. The apparatus of claim 6, wherein the modeling unit is specifically configured to:
determining variable parameters of the stress-relaxed response surface model by a weighted stepwise regression analysis method;
calculating a first coefficient of the response surface model of the fusion stress relaxation according to the at least one group of characteristic parameters;
and establishing a response surface model of the fusion stress relaxation according to the first coefficient and the variable parameter.
8. The apparatus of claim 7, wherein the computing unit is specifically configured to:
calculating at least one group of second coefficients of the response surface model with the fused stress relaxation according to the at least one group of characteristic parameters, wherein the group number of the characteristic parameters corresponding to each elastic element is the same as the number of the variable parameters of the response surface model with the fused stress relaxation;
and weighting the at least one group of second coefficients to obtain the first coefficient.
9. The apparatus of claim 8, wherein the computing unit is specifically configured to:
determining the value range of each characteristic parameter in the group of characteristic parameters according to at least one group of preset characteristic parameters corresponding to each elastic element;
fitting according to the value range of each characteristic parameter and the response surface model data of the fusion stress relaxation to obtain a first elastic force value of each elastic element, wherein the difference between the first elastic force value and the actual elastic force value of each elastic element is smaller than a preset first threshold value;
determining each characteristic parameter value corresponding to the first elasticity value, and calculating the elasticity value of each elastic element at different moments according to each characteristic parameter value;
and obtaining a change curve of the elastic force value of each elastic element along with time according to the elastic force value of each elastic element at different moments.
10. The apparatus according to any of claims 6 to 9, wherein the determining unit is specifically configured to:
determining a corresponding time point when the elasticity value is equal to a preset second threshold value according to the change curve;
determining a storage life of each of the elastic elements from the time points.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007108843A (en) * | 2005-10-11 | 2007-04-26 | Toshiba Corp | Semiconductor device design support method, semiconductor device design support system and semiconductor device design support program |
| CN102507114A (en) * | 2011-10-19 | 2012-06-20 | 天津大学 | Method for predicting relaxation life of spiral spring on basis of stress relaxation theory of temperature accelerating material |
| CN102589977A (en) * | 2012-01-13 | 2012-07-18 | 北京航空航天大学 | Method for predicting rubber storage life on basis of compression stress relaxation test equipment |
| CN105300673A (en) * | 2015-10-10 | 2016-02-03 | 中国空间技术研究院 | Reliability determination method based on compression spring stress relaxation testing data |
| CN105842087A (en) * | 2016-03-03 | 2016-08-10 | 安阳工学院 | Designing and prediction method for converting high-temperature stress relaxation data into creep data |
-
2019
- 2019-12-31 CN CN201911420170.4A patent/CN111177931B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007108843A (en) * | 2005-10-11 | 2007-04-26 | Toshiba Corp | Semiconductor device design support method, semiconductor device design support system and semiconductor device design support program |
| CN102507114A (en) * | 2011-10-19 | 2012-06-20 | 天津大学 | Method for predicting relaxation life of spiral spring on basis of stress relaxation theory of temperature accelerating material |
| CN102589977A (en) * | 2012-01-13 | 2012-07-18 | 北京航空航天大学 | Method for predicting rubber storage life on basis of compression stress relaxation test equipment |
| CN105300673A (en) * | 2015-10-10 | 2016-02-03 | 中国空间技术研究院 | Reliability determination method based on compression spring stress relaxation testing data |
| CN105842087A (en) * | 2016-03-03 | 2016-08-10 | 安阳工学院 | Designing and prediction method for converting high-temperature stress relaxation data into creep data |
Non-Patent Citations (4)
| Title |
|---|
| 崔海涛;汪震;温卫东;徐颖;: "微动疲劳寿命可靠性分析方法", 航空动力学报 * |
| 薛彩军;谭伟;徐奋进;戴建华;: "基于响应面模型的结构疲劳寿命优化方法", 南京理工大学学报 * |
| 陈乐平;朱雷平;: "基于响应面法的注塑件残余应力优化", 塑料 * |
| 高鹏;陆山;: "考虑应力松弛的涡轮盘蠕变持久寿命可靠性分析方法", 机械科学与技术 * |
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