Stress relaxation life prediction method for push rod spring and computer readable storage medium

Abstract

The invention relates to the technical field of spring stress relaxation life prediction, in particular to a stress relaxation life prediction method for a push rod spring and a computer readable storage medium, and the method comprises the following steps: S1, installing test equipment and a spring; s2, testing spring stress relaxation data and drawing a curve; s3, drawing a natural logarithm curve of the natural logarithm of the stress loss rate and the natural logarithm curve of the time, and fitting a regression equation; s4, drawing a relation curve of the relaxation coefficient and the temperature and fitting a regression equation; s5, calculating the relaxation coefficient of the test spring at the actual use temperature; s6, calculating the stress relaxation life of the test spring; according to the method, stress relaxation curves and stress loss rate logarithm and time logarithm curves at different experimental temperatures are obtained in a temperature acceleration mode, and a stress relaxation equation of the logarithm of the stress loss rate with respect to the temperature T and the time t is finally obtained, so that the working life of the spring at the actual working temperature is accurately predicted; and the experimental period is shortened while the prediction accuracy is relatively high.

Description

Technical Field

[0001] The present invention relates to the technical field of predicting spring stress relaxation life, and in particular to a stress relaxation life prediction method for a push rod spring and a computer-readable storage medium. Background Art

[0002] In the field of aerospace, push rod springs are often used in spacecraft docking mechanisms and are important components for docking and separation processes. Push rod springs not only play a certain buffering role in the docking process of the docking mechanism, but also serve as the only power in the separation process to push the other spacecraft to reach the predetermined separation speed and separation angular velocity, so that the two spacecraft can be successfully separated. In the construction of space stations, the docking mechanism of spacecraft needs to be used for a long time, for several years or even more than ten years. With the increase in the number of rendezvous and docking times and the on-orbit service time of spacecraft, the push rod spring will produce stress relaxation failure, making it unable to push the spacecraft to reach the predetermined separation speed and angular velocity, thus resulting in separation failure, which seriously affects the reliability of the spacecraft docking mechanism during the docking and separation process. Therefore, it is necessary to accurately predict the life of the stress relaxation of the push rod spring to ensure that the docking mechanism works within the service life of the push rod spring, so as to improve the reliability of the docking mechanism during the docking and separation process.

[0003] At present, the main methods for predicting the life of springs include bending test method, torsion test method and bolt and nut compression method. Since the push rod spring adopts a spiral compression spring, its stress state is relatively complex. In addition to the bending load, it also bears torsion load. Therefore, the reliability of using the bending test method and torsion test method to predict the life of the push rod spring is not high. The traditional bolt and nut compression method is to compress the spring to the working height, measure the corresponding initial load, and then compress the spring to the working state with the bolt and nut, unload it at regular intervals to measure its load under the working state, and draw the measured data into a curve to predict the service life of the spring. Although this method is simple, it has the disadvantages of complicated procedures, large human errors in measurement data, and long experimental cycle due to the need for multiple loading and unloading. Since the stress relaxation failure time of the push rod spring is very long (generally 10 5 h), so it will be extremely time-consuming to conduct stress relaxation experiments according to the traditional bolt and nut compression method. Summary of the invention

[0004] The object of the present invention is to provide a fast and accurate stress relaxation life prediction method for a push rod spring.

[0005] Based on the above purpose, the present invention adopts the following technical solution:

[0006] A stress relaxation life prediction method for a push rod spring comprises the following steps:

[0007] S1. Install the test equipment and spring: Install the test spring on the fatigue testing machine through the fixture, and set up heating equipment around the test spring; the fatigue testing machine can be the MTS Landmark fatigue testing machine, and the heating equipment can be the MTS653 series high temperature furnace;

[0008] S2. Test spring stress relaxation data and draw curves: select multiple temperature points with equal temperature difference within the temperature range and conduct stress relaxation experiments respectively; draw the load and time variation curves at each temperature point respectively with the test spring load collected in the experiment as the ordinate and the corresponding time as the abscissa;

[0009] S3. Draw the curve of the natural logarithm of the stress loss rate and the natural logarithm of time and fit the regression equation: according to the collected stress and running time data, the natural logarithm of the stress loss rate of the test spring and the natural logarithm of time are respectively drawn at each temperature point with the natural logarithm of the spring stress loss rate as the ordinate and the natural logarithm of time as the abscissa; use Origin software to perform linear regression on the drawn curve to obtain a linear regression equation containing the relaxation coefficient;

[0010] S4, plotting the relationship curve between relaxation coefficient and temperature and fitting the regression equation: using the linear regression equation in step S3 to plot the natural logarithm of stress loss rate and natural logarithm of time in two stages of stress relaxation of the push rod spring at different temperatures, and performing linear regression on the curve to obtain the linear regression equation at different temperatures; using the linear regression equation at different temperatures to obtain the fitting values ​​of relaxation coefficients at different temperatures respectively;

[0011] S5, calculating the relaxation coefficient of the test spring at the actual use temperature; using the relaxation coefficient fitting values ​​at different temperatures in step S4 to perform secondary normalization processing, and establishing a relationship between the relaxation coefficient and the temperature;

[0012] S6. Calculate the stress relaxation life of the test spring: Substitute the relaxation coefficient determined in step S5 into the linear regression equation obtained in step S3 to obtain the stress relaxation equation of the test spring at the actual use temperature; through the stress relaxation equation, the time corresponding to a given stress loss rate at any temperature can be determined, or the stress loss rate of the spring under the known service life of the spring can be determined.

[0013] Preferably, in step S1, the clamp includes an upper clamp and a lower clamp, each of the upper clamp and the lower clamp includes a clamping section, and a limit platform is provided at one end of the clamping section; the limit platform is vertically arranged to the clamping section, and an extension section is provided on the other side of the limit platform of the upper clamp; the extension section, the clamping section and the limit platform are coaxially arranged; the diameter of the extension section is smaller than the inner diameter of the test spring, and the outer diameter of the test spring is smaller than the diameter of the limit platform.

[0014] Preferably, a water cooling platform is provided on the clamping sections of the upper clamp and the lower clamp, and a two-branch pipe hole is provided in the water cooling platform, and the two-branch pipe hole is connected to a water cooling device through a pipeline; three K-type thermocouples are evenly distributed on the outside of the heating device.

[0015] Preferably, the process of step S2 of testing spring stress relaxation data and drawing a curve comprises:

[0016] During the stress relaxation experiment, the temperature data of the test spring is obtained through a thermocouple; the real-time stress data of the test spring is collected through the force sensor in the fatigue testing machine, and the displacement change data of the test spring in the experiment is obtained through the displacement sensor, and the displacement data and stress data are recorded in real time on the computer; in the stress relaxation experiment, 4-7 temperature points are selected with equal temperature differences in the temperature range of 25-325℃; the test spring and the fixture are preheated for 1h, and after the temperature reaches the selected temperature point, the test spring is compressed downward by 30mm at a loading speed of 2-5mm / min and the experiment is started. The duration of one experiment is greater than 24h; after completing one experiment, the test temperature is changed, and the experiment is repeated until all the selected temperature points are completed.

[0017] Preferably, the process of drawing a curve of the natural logarithm of the stress loss rate and the natural logarithm of time and fitting a regression equation in step S3 includes:

[0018] The linear regression equation is obtained:

[0019]

[0020] From the above formula, we can get the spring stress relaxation life decay model:

[0021]

[0022] Where: It is called stress loss rate; ΔF is the compression stress attenuation, ΔF = F0-F t ; F0 is the initial compressive stress; F t is the compressive stress at any time, and A and B are relaxation coefficients related to temperature.

[0023] The stress relaxation life test method for a push rod spring according to claim 4 is characterized in that the relaxation coefficients A and B are derived from the Arrhenius formula:

[0024]

[0025] Where: v s is the stress loss rate, defined as Q is the activation energy (eV) required for a dislocation to cross an obstacle under a certain stress; γ is a constant; T is the test temperature (K); k is the Boltzmann constant (8.6×10-5eV·K-1);

[0026] The derivatives of both sides of formula (1) with respect to lnt are: Substituting into formula (3) we get:

[0027]

[0028] Taking the logarithm of both sides of formula (4) yields:

[0029]

[0030] That is, ln B and There is a linear relationship.

[0031] Preferably, the process of calculating the relaxation coefficient of the test spring at the actual use temperature in step S5 includes:

[0032] According to A and ln B respectively The linear relationship between the relaxation coefficients A and B and the temperature T can be established by performing secondary normalization processing using the A and B fitting values ​​obtained in step S4; the actual use temperature of the test spring is brought in to obtain the values ​​of the relaxation coefficients A and B of the spring at the actual use temperature.

[0033] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, any step in the above-mentioned method for predicting the stress relaxation life of a push rod spring is implemented.

[0034] The beneficial effects of the present invention are as follows:

[0035] The present invention adopts the MTS Landmark fatigue testing machine to perform stress relaxation experiment on the push rod spring. Compared with the traditional stress relaxation test method, it can not only ensure the stability of the load during the experiment, but also has the function of real-time monitoring, realizes the experimental requirements such as continuous dynamic, simple and stable operation, and ensures the measurement accuracy and reliability of the measurement data.

[0036] This application uses an MTS653 series high-temperature furnace to heat and control the temperature of the push rod spring during the experiment, and multiple groups of experiments can be performed at different temperature points to deduce the relationship between stress relaxation and temperature of the push rod spring; since the effect of temperature on stress relaxation is positively correlated, that is, the higher the temperature, the faster the stress relaxation rate, therefore, not only can the stress relaxation at the actual use temperature of the spring be extrapolated based on the law of the effect of temperature on stress relaxation, thereby accurately predicting the stress relaxation life of the push rod spring, but it can also greatly shorten the time consumption of the experiment, making the experiment more efficient.

[0037] The present application can obtain the stress relaxation curve and the logarithm of the stress loss rate and the logarithm of the time at a higher experimental temperature by means of temperature acceleration, and fit a linear regression equation, thereby deducing the values ​​of the relaxation coefficients A and B in the stress relaxation equation of the push rod spring, and finally obtaining the stress relaxation equation of the push rod spring; the logarithm of the stress loss rate in this equation is a function of the temperature T and the time t, and the stress relaxation life of the spring can be calculated by knowing the actual use temperature T, and the stress loss rate of the push rod spring under the known service life t can be calculated, and whether the push rod spring meets the service life requirement can be judged by the stress loss rate; this method has a high prediction accuracy, and at the same time greatly reduces the experimental cycle, effectively improves efficiency, and saves costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is the overall schematic diagram of the experimental device of the present invention;

[0039] Figure 2 It is an assembly diagram of the clamp and the push rod spring of the present invention;

[0040] Figure 3 A state diagram of the spring of the present invention installed on a fatigue testing machine;

[0041] Figure 4 It is a schematic diagram of the upper clamp structure of the present invention;

[0042] Figure 5 It is a schematic diagram of the lower clamp structure of the present invention;

[0043] Figure 6 is the stress relaxation curve of the push rod spring of the present invention;

[0044] Figure 7 The logarithm of stress loss rate and time of the present invention at 298K;

[0045] Figure 8 The logarithm of the stress loss rate and the logarithm of time of the present invention at 398K;

[0046] Fig. 9 The logarithm of stress loss rate and time of the present invention at 498K;

[0047] Fig.10 The logarithm of the stress loss rate and the logarithm of time of the present invention at 598K;

[0048] Fig.11 For the present invention Univariate linear regression plot;

[0049] Fig.12 For the present invention Univariate linear regression plot.

[0050] In the figure: upper fixture 1; upper clamping section 11; extending section 12; upper limit platform 13; upper two-branch through hole 14; lower fixture 2; lower clamping section 21; lower limit platform 22; lower two-branch through hole 23; high temperature furnace 3; thermocouple 4; water cooling device 5. DETAILED DESCRIPTION

[0051] The following is a further explanation of the present invention in combination with a specific embodiment. This embodiment is a stress relaxation life prediction method for a push rod spring, comprising the following steps:

[0052] S1. Install the test equipment and spring: Install the test spring on the fatigue testing machine through the fixture, and set up heating equipment around the test spring:

[0053] In this embodiment, a push rod spring made of 1Cr18Ni9 austenitic stainless steel wire is used for testing. The basic parameters of the spring are d=4mm, D=20mm, t=7.26mm, and H0=200mm. The experimental equipment used in this embodiment includes an MTSLandmark fatigue testing machine, such as Figure 1 As shown; the spring is mounted on the fatigue testing machine through a pair of clamps, such as Figure 2 and Figure 3 As shown; an MTS653 high temperature furnace 3 is provided outside the fixture and the spring, which can heat the spring to a predetermined temperature during the experiment.

[0054] The specific structure of the fixture is as follows: Figure 4 and Figure 5 As shown, it is divided into an upper fixture 1 and a lower fixture 2. The upper fixture 1 includes an upper clamping section 11, an upper limit platform 13 is arranged at the end of the upper clamping section 11, a water cooling platform is arranged in the middle of the upper clamping section 11, and an upper two-branch through hole 14 is provided in the water cooling platform; the structure of the lower fixture 2 is similar to that of the upper fixture 1, including a lower clamping section 21, a lower limit platform 22 and a lower two-branch through hole 23 in the water cooling platform; the difference from the lower fixture 2 is that the upper fixture 1 is provided with a protruding section 12 at the other end of the upper limit platform 13; as shown in FIG. Figure 2 As shown, when assembled with the spring, the spring is sleeved outside the extension section 12, and the upper limit platform 13 and the lower limit platform 22 are used to clamp the two ends of the spring; the upper two branch pipe through holes 14 and the lower two branch pipe through holes 23 are respectively connected to the water cooling device 5, as shown in FIG. Figure 3 As shown, it is used to cool the fixture during the experiment; three K-type thermocouples 4 are also arranged on the high-temperature furnace 3, which can obtain the temperature of the spring in real time to control the temperature of the spring within the target temperature range.

[0055] S2. Test spring stress relaxation data and draw a curve: Before the experiment, first preheat the instrument and fixture for 1 hour to eliminate the impact of thermal expansion of the fixture on the experiment; select 25℃, 125℃, 225℃ and 325℃ as the accelerated stress relaxation experiment temperature, first compress the test spring downward by 30mm at a loading speed of 5mm / min and then start the experiment; then compress the push rod spring at a speed of 5mm / min until the length of the push rod spring reaches the storage height H during actual working; the stress relaxation time is 36h, and the data in the stress relaxation experiment is collected autonomously by the computer system through the various sensors of the fatigue testing machine, and the collection frequency is once per minute.

[0056] At four temperature points, from the loading moment to the unloading moment, about 1440 points were collected at each temperature point; Origin software was used to draw the stress relaxation curve of the push rod spring based on the data of these collected points with time (t) as the horizontal axis and stress (F) as the horizontal axis, as shown in the figure: Figure 6 shown.

[0057] S3. Draw the natural logarithm of stress loss rate and the natural logarithm of time and fit the regression equation: Based on the collected stress and running time data, take the logarithm of time (lnt) as the horizontal axis and the logarithm of stress loss rate (lnt) as the horizontal axis. As the vertical axis, the logarithm of stress loss rate and logarithm of time at each temperature point are plotted, such as Figure 7-10 shown.

[0058] Then use Origin software to perform linear regression on the drawn curve and obtain the linear regression equation at different temperatures:

[0059] Table 1: Stress loss rate logarithm-time logarithm fitting equation at different temperatures

[0060] Temperature / T Fitting equation Correlation coefficient r 298 <![CDATA[ln(ΔP / P0)=-6.88175+0.63600ln t]]> 0.99088 398 <![CDATA[ln(ΔP / P0)=-6.3027+0.70385ln t]]> 0.98674 498 <![CDATA[ln(ΔP / P0)=-4.68793+0.83783ln t]]> 0.96374 598 <![CDATA[ln(ΔP / P0)=-4.79789+0.93361ln t]]> 0.98354

[0061] S4. Draw the relationship curve between relaxation coefficient and temperature and fit the regression equation: Since the stress relaxation rate of the first stage of stress relaxation of the push rod spring is large but the duration is short, and the stress relaxation rate of the second stage of stress relaxation is small but the duration is long, both stages need to be considered in order to accurately predict the stress relaxation life of the push rod spring; based on the relaxation rate logarithm-time logarithm fitting equation at each temperature obtained in step S3, the stress relaxation life decay model of the push rod spring as well as the fitting A value and fitting B value can be derived:

[0062] Table 2: Stress relaxation life model of push rod spring at different temperatures

[0063] Temperature T / K Fitting life decay model to test data Fitting A value Fitting B value 298 <![CDATA[ΔF / F0=e -6.88175+0.63600lnt ]]> -6.88175 0.63600 398 <![CDATA[ΔF / F0=e -6.3027+0.70385lnt ]]> -6.3027 0.70385 498 <![CDATA[ΔF / F0=e -4.68793+0.83783lnt ]]> -4.68793 0.83783 598 <![CDATA[ΔF / F0=e -4.79789+0.93361lnt ]]> -4.79789 0.93361

[0064] S5. Calculate the relaxation coefficient of the test spring at the actual use temperature. According to the data analysis in Table 2, A shows a significant decreasing trend with the increase of temperature. Therefore, the relationship between A and temperature T is normalized. Plot the relationship between A and temperature T. The fitting curve of Fig.11 shown.

[0065] From the fitting curve, we can get:

[0066] From the analysis of formula (6), we can know that A and The linear relationship is significant.

[0067] According to formula (5), ln B and There is a linear relationship between ln B and Perform univariate linear regression analysis and draw a fitting curve as shown in Fig.12 .

[0068] From the fitting curve, we can get:

[0069] That is, B = e -0.38767–274.13(1 / T) .

[0070] S6. Calculate the stress relaxation life of the test spring: Substitute the relaxation coefficient determined in step S5 into the linear regression equation obtained in step S3 to obtain the stress relaxation life decay equation of the test spring at the actual use temperature:

[0071]

[0072] From this equation, it can be obtained that when the stress loss rate of the push rod spring is 10% at room temperature, its service life is 7.8 years.

[0073] The above description is only a further explanation of the present invention in combination with specific embodiments. All descriptions do not limit the scope of protection of the present invention. Any changes or replacement schemes that can be easily thought of by any technician in this field within the technical scope disclosed by the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A stress relaxation life prediction method for a push rod spring, comprising the following steps: S1. Install the test equipment and spring: install the test spring on the fatigue testing machine through the fixture, and set the heating equipment around the test spring; S2. Test spring stress relaxation data and draw curves: select multiple temperature points with equal temperature difference within the temperature range and conduct stress relaxation experiments respectively; draw the load and time variation curves at each temperature point respectively with the test spring load collected in the experiment as the ordinate and the corresponding time as the abscissa; S3. Draw the curve of the natural logarithm of the stress loss rate and the natural logarithm of time and fit the regression equation: according to the collected stress and running time data, the natural logarithm of the stress loss rate of the test spring and the natural logarithm of time are respectively drawn at each temperature point with the natural logarithm of the spring stress loss rate as the ordinate and the natural logarithm of time as the abscissa; use Origin software to perform linear regression on the drawn curve to obtain a linear regression equation containing the relaxation coefficient; S4, plotting the relationship curve between relaxation coefficient and temperature and fitting the regression equation: using the linear regression equation in step S3 to plot the natural logarithm of stress loss rate and natural logarithm of time in two stages of stress relaxation of the push rod spring at different temperatures, and performing linear regression on the curve to obtain the linear regression equation at different temperatures; using the linear regression equation at different temperatures to obtain the fitting values ​​of relaxation coefficients at different temperatures respectively; S5, calculating the relaxation coefficient of the test spring at the actual use temperature; using the relaxation coefficient fitting values ​​at different temperatures in step S4 to perform secondary normalization processing, and establishing a relationship between the relaxation coefficient and the temperature; S6. Calculate the stress relaxation life of the test spring: Substitute the relaxation coefficient determined in step S5 into the linear regression equation obtained in step S3 to obtain the stress relaxation equation of the test spring at the actual use temperature; through the stress relaxation equation, the time corresponding to a given stress loss rate at any temperature can be determined, or the stress loss rate of the spring under the known service life of the spring can be determined.

2. The stress relaxation life prediction method for a push rod spring according to claim 1, characterized in that: In step S1, the clamp includes an upper clamp and a lower clamp, each of which includes a clamping section, and a limit platform is provided at one end of the clamping section; the limit platform is vertically arranged to the clamping section, and an extension section is provided on the other side of the limit platform of the upper clamp; the extension section, the clamping section and the limit platform are coaxially arranged; the diameter of the extension section is smaller than the inner diameter of the test spring, and the outer diameter of the test spring is smaller than the diameter of the limit platform.

3. The stress relaxation life prediction method for a push rod spring according to claim 2, characterized in that: The clamping sections of the upper clamp and the lower clamp are both provided with a water cooling platform, and the water cooling platform is provided with a two-branch pipe hole, and the two-branch pipe hole is connected to a water cooling device through a pipeline; three K-type thermocouples are evenly distributed on the outside of the heating device.

4. The stress relaxation life test method for a push rod spring according to claim 3, characterized in that: The process of step S2 testing the spring stress relaxation data and drawing a curve includes: During the stress relaxation experiment, the temperature data of the test spring is obtained through a thermocouple; the real-time stress data of the test spring is collected through the force sensor in the fatigue testing machine, and the displacement change data of the test spring in the experiment is obtained through the displacement sensor, and the displacement data and stress data are recorded in real time on the computer; in the stress relaxation experiment, 4-7 temperature points are selected with equal temperature differences in the temperature range of 25-325℃; the test spring and the fixture are preheated for 1h, and after the temperature reaches the selected temperature point, the test spring is compressed downward by 30mm at a loading speed of 2-5mm / min and the experiment is started. The duration of one experiment is greater than 24h; after completing one experiment, the test temperature is changed, and the experiment is repeated until all the selected temperature points are completed.

5. The stress relaxation life test method for a push rod spring according to claim 4, characterized in that: The process of drawing the natural logarithm curve of the stress loss rate and the natural logarithm curve of time and fitting the regression equation in step S3 includes: The linear regression equation is obtained: From the above formula, we can get the spring stress relaxation life decay model: Where: It is called stress loss rate; ΔF is the compression stress attenuation, ΔF = F0-F t ; F0 is the initial compressive stress; F t is the compressive stress at any time, and A and B are relaxation coefficients related to temperature.

6. The stress relaxation life test method for a push rod spring according to claim 5, characterized in that: The relaxation coefficients A and B are derived from the Arrhenius formula: Where: v s is the stress loss rate, defined as Q is the activation energy (eV) required for a dislocation to cross an obstacle under a certain stress; γ is a constant; T is the test temperature (K); k is the Boltzmann constant (8.6×10-5eV·K-1); The derivatives of both sides of formula (1) with respect to lnt are: Substituting into formula (3) we get: Taking the logarithm of both sides of formula (4) yields: That is, ln B and There is a linear relationship.

7. The stress relaxation life test method for a push rod spring according to claim 6, characterized in that: The process of calculating the relaxation coefficient of the test spring at the actual use temperature in step S5 includes: According to A and ln B respectively The linear relationship between the relaxation coefficients A and B and the temperature T can be established by performing secondary normalization processing using the A and B fitting values ​​obtained in step S4; by substituting the actual use temperature of the test spring, the values ​​of the relaxation coefficients A and B of the spring at the actual use temperature can be obtained.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, any step of the method for predicting the stress relaxation life of a push rod spring as described in any one of claims 1 to 6 is implemented.

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