Method, system and device for evaluating the life of a closing spring and storage medium

Abstract

The embodiment of the application discloses a closing spring life evaluation method, system, device and storage medium, the closing time of the closing spring under different stress loss rates is obtained, and a mapping model between the stress loss rate and the closing time is constructed; the stress loss rate threshold of the closing spring is obtained according to the mapping model and a preset closing time range, and the failure state of the closing spring is determined; the service life of the closing spring under different temperatures is obtained according to the spring loss rate of the closing spring under different temperatures and the stress loss rate threshold, so that the service life of the closing spring is accurately evaluated.

Description

[0001] The application relates to the technical field of power system equipment, in particular to a closing spring life evaluation method, system, device and storage medium.

[0002] The fault types of a high-voltage circuit breaker are generally divided into insulation abnormalities, power supply abnormalities and mechanical abnormalities. Among them, the deterioration of mechanical performance is usually caused by the deformation or damage of materials due to long-term stress. In engineering, the opening and closing performance of the circuit breaker is usually used as an important standard for evaluating the mechanical performance. Unstable opening and closing performance often indicates that the circuit breaker is facing potential failure risks. Under actual working conditions, the closing spring is in a state of energy storage compression for a long time, and problems such as strength degradation and stress relaxation are inevitable. These problems not only affect the closing performance of the circuit breaker, but also may cause damage to the spring, thereby causing power grid accidents. The current technical solutions mainly focus on monitoring the state of the closing spring installed on the working circuit breaker, and the purpose is to judge the working state of the closing spring in real time through data collection and analysis. However, the existing solutions can realize real-time monitoring of the running state of the spring, but cannot predict the future running state of the spring, so the service life of the spring cannot be reasonably evaluated.

[0003] Therefore, the application provides a closing spring life evaluation method, system, device and storage medium.

[0004] The specific technical scheme of the first embodiment of the application is as follows: a closing spring life evaluation method, the method comprising: acquiring closing times of a closing spring under different stress loss rates; constructing a mapping model between stress loss rates and closing times according to the closing times under different stress loss rates and the different stress loss rates; acquiring a stress loss rate threshold of the closing spring according to the mapping model and a preset closing time range; and acquiring service lives of the closing spring at different temperatures according to spring loss rates of the closing spring at different temperatures and the stress loss rate threshold.

[0005] Preferably, the stress loss rate is obtained by the following method: acquiring a first stress required for compressing the closing spring to a preset length at a first time; acquiring a second stress required for compressing the closing spring to the preset length at a second time; the second time is later than the first time; and obtaining the stress loss rate according to the first stress and the second stress.

[0006] Preferably, the mapping model between the stress loss rate and the closing time is obtained by the following formula:

[0007] t(s)~G(m(s),k(s,s'))​​​

[0008] wherein t(s) is the closing time under the stress loss rate s, g is a Gaussian distribution, m(s) is a mean function of the stress loss rate s, and k(s, s') is a covariance function of the stress loss rate s.

[0009] Preferably, the obtaining of the stress loss rate threshold of the closing spring according to the mapping model and the preset closing time range comprises: mapping the preset closing time range to the stress loss rate of the mapping model by using a Gaussian process regression and a Bayesian inference method to obtain a probability that the closing time of the closing spring under different stress losses is within the preset closing time range; and solving the probability according to a preset confidence level to obtain the stress loss rate threshold of the closing spring.

[0010] Preferably, the probability is obtained by using the following formula:

[0011] P(t)=P(t min ≤t(s)≤t max )

[0012] wherein P(t) is the probability, t min is a minimum value of time in the preset closing time range, t max is a maximum value of time in the preset closing time range, and t(s) is the closing time under the stress loss rate s.

[0013] Preferably, the obtaining of the service life of the closing spring under different temperatures according to the spring loss rate of the closing spring under different temperatures and the stress loss rate threshold comprises: fitting the spring loss rate of the closing spring under different temperatures and the energy storage time of the closing spring to obtain a stress loss rate of the closing spring under different temperatures; and obtaining the service life of the closing spring under different temperatures according to the stress loss rate of the closing spring and a preset service life model.

[0014] Preferably, the service life of the closing spring under different temperatures is obtained by using the following formula:

[0015]

[0016] s max =e (a-b / T) ·lnt+c

[0017] wherein k is the stress loss rate, A is an Arrhenius constant, E a is an activation energy, T is a temperature, a, b and c are constants, R is a Boltzmann constant, s max is a preset spring failure threshold, and t is the service life of the closing spring under the temperature T.

[0018] The specific technical scheme of the second embodiment of the application is: a closing spring life evaluation system, the system comprises: a closing time acquisition module, a model mapping module, a threshold acquisition module and a service life acquisition module; the closing time acquisition module is used to acquire the closing time of the closing spring under different stress loss rates; the model mapping module is used to construct a mapping model between the stress loss rate and the closing time according to the closing time under different stress loss rates and different stress loss rates; the threshold acquisition module is used to acquire the stress loss rate threshold of the closing spring according to the mapping model and a preset closing time range; and the service life acquisition module is used to acquire the service life of the closing spring under different temperatures according to the spring loss rate of the closing spring under different temperatures and the stress loss rate threshold.

[0019] The specific technical scheme of the third embodiment of the application is: a closing spring life evaluation device, comprising a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to make the processor execute the steps of the method in any one of the first embodiments of the application.

[0020] The specific technical scheme of the fourth embodiment of the application is: a computer readable storage medium, storing a computer program, the computer program is executed by the processor to make the processor execute the steps of the method in any one of the first embodiments of the application.

[0021] The embodiments of the application have the following beneficial effects:

[0022] The application acquires the closing time of the closing spring under different stress loss rates, constructs a mapping model between the stress loss rate and the closing time, acquires the stress loss rate threshold of the closing spring according to the mapping model and a preset closing time range, determines the failure state of the closing spring, acquires the service life of the closing spring under different temperatures according to the spring loss rate of the closing spring under different temperatures and the stress loss rate threshold, and thus accurately evaluates the service life of the closing spring. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description are only some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0024] Figure 1 The step flow chart of the closing spring life evaluation method;

[0025] Figure 2 The installation schematic diagram for the long-term energy storage test of the closing spring;

[0026] Figure 3a The spring stress loss curve at different temperatures;

[0027] Figure 3b The spring stress loss rate at different temperatures;

[0028] Figure 4 The schematic diagram of the relationship between the spring stress loss and the closing time;

[0029] Figure 5 The structural schematic diagram of the service life evaluation system of the closing spring;

[0030] Figure 6 The internal structure diagram of the computer equipment;

[0031] Wherein, 201, temperature monitoring meter; 202, environmental test chamber; 203, spring fixing pressing plate support rod; 204, displacement sensor; 205, closing spring; 206, spring fixing pressing plate; 301, closing time acquisition module; 302, model mapping module; 303, threshold acquisition module; 304, service life acquisition module.

DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0033] The terms “first”, “second”, and the like in the specification and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms “include” and “have” and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not limited to the listed steps or modules, but can optionally include steps or modules that are not listed, or can optionally include other steps or modules inherent to the process, method, product, or device.

[0034] In this document, the term “embodiment” means that a specific feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it mutually exclusive or alternative to other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0035] Closing spring is a key component in circuit breaker for storing elastic potential energy. In normal working state, the closing spring is tightly compressed and placed inside the circuit breaker, waiting for the trigger signal. When the circuit breaker needs to be triggered, the closing spring quickly releases its elastic potential energy, thus quickly closing, realizing the function of circuit breaker to cut off the circuit.

[0036] Please refer to Figure 1 The flow chart of the life evaluation method of the closing spring in the first embodiment of the application is shown, so as to accurately evaluate the service life of the closing spring. The method comprises the following steps:

[0037] Step 101, obtaining the closing time of the closing spring under different stress loss rates;

[0038] Step 102, constructing a mapping model between the stress loss rate and the closing time according to the closing time under different stress loss rates and the different stress loss rates;

[0039] Step 103, obtaining the stress loss rate threshold of the closing spring according to the mapping model and a preset closing time range;

[0040] Step 104, obtaining the service life of the closing spring at different temperatures according to the spring loss rate of the closing spring at different temperatures and the stress loss rate threshold.

[0041] Specifically, for the performance degradation simulation of the closing spring in long-term closing operation, the test equipment as shown in Figure 2 is adopted, which comprises a temperature monitoring meter 201, an environmental test box 202, a spring fixing press plate support rod 203, a displacement sensor 204, a closing spring 205, and a spring fixing press plate 206. The spring fixing press plate is used to compress the closing spring and make it reach the preset stress F2 / height H2 of closing. The environmental simulation test box can simulate in the temperature range of-20℃ to 150℃. The displacement sensor monitors the compression height of the closing spring in real time, ensuring that it remains at the preset stress / height.

[0042] The spring is compressed and fixed by the spring fixing press plate, so that the closing spring reaches the preset stress F2 / height H2 of closing. The closing spring after compression and fixation is placed in the environmental simulation test box. The compression height of the closing spring is monitored in real time by the support rod of the fixing press plate and the displacement sensor, so as to ensure that it can be maintained at the preset stress F2 / height H2, so as to simulate the energy storage state of the closing spring in a long term. The temperature of the environmental simulation test box is set, and the working temperature influence test is carried out according to the test requirements. The test can be carried out for 10-36 months according to different voltage levels of the closing spring type. The stress value F of the spring when compressed to H2 is measured and recorded every certain period of time (such as half a month or a month). testand install it in the circuit breaker to close, record the closing time t. Through the above test steps, the spring stress change corresponding to the test conditions and the closing time data are recorded.

[0043] Through the simulation of different temperature environments and working states (such as long-term energy storage state and repeated closing operation), the stress relaxation characteristics of the closing spring can be comprehensively analyzed. The test process does not require complex equipment and operation steps, and has the characteristics of simple operation and high efficiency.

[0044] According to the closing spring performance degradation test described above, the spring closing time data under different stress loss rates can be obtained, and the stress loss rate s and the closing time t are obtained. Therefore, the data set collected can be represented as {(s i ,t i )|i=1,2,...,n}, and a mapping model between the stress loss rate and the closing time is constructed. According to the mapping model and the preset closing time range, the stress loss rate threshold of the closing spring is obtained; wherein the preset closing time range can be set according to the actual situation, and the value of the preset closing time range is not limited by the present application. According to the spring loss rate of the closing spring at different temperatures and the stress loss rate threshold, the service life of the closing spring at different temperatures is obtained.

[0045] It should be noted that since the sizes of the closing springs of circuit breakers of different voltage levels are different, the sizes of the corresponding test equipment will also be different. The above Figure 2 Not drawn to scale, for clarity of expression, some details are enlarged and some details are omitted. Figure 2 The shapes of various regions, layers and their relative size and position relationship shown in the above-mentioned structure diagram are only examples, and there may be deviations caused by manufacturing tolerances or technical limitations in actual manufacturing process. A person skilled in the art can design regions or layers with different shapes, sizes and relative positions according to actual needs. For ease of illustration, the graphical expression is simplified in the structure diagram.

[0046] The method in the embodiment acquires the closing time of the closing spring under different stress loss rates, constructs a mapping model between the stress loss rate and the closing time, acquires the stress loss rate threshold of the closing spring according to the mapping model and the preset closing time range, determines the failure state of the closing spring, and acquires the service life of the closing spring at different temperatures according to the spring loss rate of the closing spring at different temperatures and the stress loss rate threshold, thereby accurately evaluating the service life of the closing spring.

[0047] In specific embodiments, the stress loss rate is obtained by the following method: obtaining a first stress required when the closing spring is compressed to a preset length at a first time; obtaining a second stress required when the closing spring is compressed to the preset length at a second time; the second time is later than the first time; obtaining the stress loss rate according to the first stress and the second stress.

[0048] Specifically, a first stress F2 required when the closing spring is compressed to a preset length at a non-use time is obtained, and a first stress F test required when the closing spring is compressed to the preset length after being used for a period of time is obtained. The stress loss rate s is obtained according to the formula

[0049] In specific embodiments, the mapping model between the stress loss rate and the closing time is obtained by the following formula:

[0050]

[0051] where t(s) is the closing time under the stress loss rate s, is a Gaussian distribution, m(s) is a mean function of the stress loss rate s, and k(s, s') is a covariance function of the stress loss rate s.

[0052] Specifically, the Gaussian distribution is a distribution for describing the shape of continuous data, and its probability density function is a bell-shaped curve, which can well fit the data distribution in many natural phenomena and social phenomena. Therefore, when the relationship between the stress loss rate and the closing time conforms to the Gaussian distribution, the mapping model established by using the Gaussian distribution can more accurately describe the correlation between the two, thereby improving the prediction accuracy of the model.

[0053] In specific embodiments, the stress loss rate threshold of the closing spring is obtained according to the mapping model and a preset closing time range, including: mapping the preset closing time range to the stress loss rate of the mapping model by using a Gaussian process regression and a Bayesian inference method, to obtain a probability that the closing time of the closing spring under different stress losses is within the preset closing time range; and solving the probability according to a preset confidence level to obtain the stress loss rate threshold of the closing spring.

[0054] Specifically, if the model parameter is θ, and the observation data is D = {(s i , t i ), then the posterior distribution is:

[0055]

[0056] where p(θ|D) is the likelihood function, representing the probability of observing the data D given the parameter θ; p(θ) is the prior distribution, representing the prior belief of the parameter θ; and p(D) is the evidence, representing the total probability of observing the data D.

[0057] According to the circuit breaker technical manual, the closing time of the closing spring generally lies in the range of [t min ,t max ], therefore, by using the Gaussian process regression and Bayesian inference method, the closing time operating range [t min ,t max ] is mapped to the stress loss rate to obtain the probability of the closing time of the closing spring under different stress losses within the preset closing time range.

[0058] In specific embodiments, the probability is obtained by the following formula:

[0059] P(t)=P(t min ≤t(s)≤t max )

[0060] where P(t) is the probability, t min is the minimum value of time in the preset closing time range, t max is the maximum value of time in the preset closing time range, and t(s) is the closing time under the stress loss rate s.

[0061] Specifically, the probability is solved according to the preset confidence level by the following formula:

[0062] P(t min ≤t(s)≤t max )≥α

[0063] where α is the confidence level, generally taken as 0.95. Solving this inequality can obtain the stress loss rate threshold [s min ,s max ] of the closing spring. Since the stress level of the closing spring gradually declines in normal actual working conditions, s max can be taken as the stress loss rate threshold when the closing spring fails. Solving the probability by using the confidence level can enhance the reliability of the result. By setting a higher confidence level, the accuracy of the estimation result can be ensured to be higher, thereby reducing the risk of misjudgment.

[0064] In a specific embodiment, obtaining the service life of the closing spring at different temperatures based on the spring loss rate of the closing spring at different temperatures and the stress loss rate threshold includes: fitting the spring loss rate of the closing spring at different temperatures and the energy storage time of the closing spring to obtain the stress loss rate of the closing spring at different temperatures; and obtaining the service life of the closing spring at different temperatures based on the stress loss rate of the closing spring and a preset service life model.

[0065] Specifically, the Arrhenius accelerated model can be used to describe the degradation process of the closing spring performance. This model is applicable to the influence of temperature on material aging and life prediction, and its formula is as follows: In the formula, k is the degradation rate (spring stress loss rate); A is the Arrhenius constant; E a Let be the activation energy; T be the absolute temperature; and R be the Boltzmann constant. By taking the logarithm of the Arrhenius equation to improve the Arrhenius model, it can be transformed into a linear form: a and b are constants. Based on experiments, the lifespan prediction of the closing spring under long-term energy storage conditions is performed: the relationship between the closing spring's loss rate and energy storage time is generally in the ln form, therefore it can be expressed as s = k·lnt + c. k is the stress loss rate; t is the energy storage time in months; c is a constant. When t = 1 month, s = c, therefore the constant c can be obtained from the spring stress loss rate obtained after 1 month of testing at different temperatures. By fitting the data of 1-month test durations at different operating temperatures, c = h(T) can be obtained, where T is the absolute temperature during the test. By performing ln fitting on the relationship between the spring loss rate and energy storage time at different temperatures T, the stress loss rate k at different temperatures can be obtained. Substituting k and T into... The values ​​of a and b can be obtained.

[0066] Therefore, in summary, the combined s max =k·lnt max +c=k·lnt max +h(T) and The service life of the closing spring at different temperatures can be obtained from two equations.

[0067] In a specific embodiment, the service life of the closing spring at different temperatures is obtained using the following formula:

[0068]

[0069] s max =e (a-b / T) ·lnt+c

[0070] Where k is the stress loss rate, A is the Arrhenius constant, and Ea is the activation energy, T is the temperature, a, b and c are constants, R is the Boltzmann constant, s max is the preset spring failure threshold, t is the service life of the closing spring at temperature T. Specifically, when the temperature rises, the closing spring will absorb heat, causing the molecular activity to intensify and the thermal vibration intensity to increase, which will cause the grain boundary of the closing spring to bend, dislocate, slip and split, thereby reducing the elastic modulus and yield strength. In a low-temperature environment, the closing spring has a slow cooling speed and weak molecular activity. This will cause the closing spring elastic modulus to increase, and the hardness and elastic strength to be higher, so the temperature has a great influence on the performance change of the closing spring.

[0071] In specific embodiments, the parameters of the 110 kV closing spring are shown in Table 1:

[0072] Parameter Value Material 60Si2CrVA Free height 380mm Wire diameter 22mm Effective turns 7.5 Total turns 9.5 Maximum compression length 135mm Stiffness 125±8 Standard working height [H1 = 347 mm, H2 = 245 mm] Closing time 50~80ms

[0073] Table 1: Parameters of 110 kV closing spring

[0074] Figure 3a and Figure 3b The change of the stress loss rate corresponding to the stress loss value of the 110 kV closing spring of the circuit breaker in the range of -10°C to 110°C can be found that in the temperature range of -15°C to 50°C, the stress loss rate of the spring is in the interval of 2.33%-2.64% after 11 months. When the temperature rises to the extreme condition of 110°C, the stress loss rate of the spring reaches 5.21%. The relationship between the spring stress loss and the closing time is shown in Figure 4 .

[0075] Reading the circuit breaker technical manual of the closing spring, it can be known that the closing time of the closing spring is in the range of 50-80 ms, so the Gaussian process regression and Bayesian inference method are used to map the closing time operating range [t min = 50, t max = 80] to the stress loss rate, i.e. P(t min ≤ t(s) ≤ t max ) ≥ 0.95, and s max = 4.5, i.e. the closing spring failure threshold is 4.5% stress loss rate. Table 2 is the linear regression equation s = k·lnt + c between the load loss rate and the logarithm of time at different temperatures.

[0076] Temperature (°C) Regression equation Stress loss rate k Determination coefficient R 2 ]]> -10 s = 0.563 • ln(t) + 0.981 0.563 0.983 10 s = 0.569 • ln(t) + 1.025 0.569 0.990 30 s = 0.571 • ln(t) + 1.176 0.571 0.987 50 s = 0.592 • ln(t) + 1.226 0.592 0.986 110 s = 0.957 • ln(t) + 1.907 0.957 0.921

[0077] Table 2: Linear regression equation between load loss rate and logarithm of time at different temperatures

[0078]

[0079] When t = 1 month, s = c, so the constant c can be obtained from the spring stress loss rate at the time of the 1-month test at different temperatures. By fitting the data of the 1-month test at different working temperatures, c = h(T) = e (1.236-356.092) · 1 / T, T is the absolute temperature at the time of the test.

[0080] Therefore, when the spring failure threshold s max = 4.5, and the working temperature is room temperature 25 degrees Celsius (298.15K), the spring service life prediction equation can be obtained as follows:

[0081] Calculation can obtain the spring service life when the stress relaxation threshold, that is, the maximum stress loss rate of the spring, is 4.5% at 25℃, which is t = 373.34 months, i.e. 31.11 years.

[0082] The embodiment adopts the method of Gaussian process regression and Bayesian inference to establish the mapping relationship between the stress loss rate and the closing time. Gaussian process regression can effectively capture the complex nonlinear relationship in the data, not just linear or simple polynomial relationship. Uncertainty estimation: the Bayesian inference method can provide uncertainty estimation of the parameters, so that the prediction of the spring closing failure threshold is more accurate.

[0083] The embodiment is based on the improved Arrhenius acceleration model, and establishes a more accurate life prediction method. This method can combine the actual working temperature and stress loss rate to accurately predict the service life of the closing spring, so as to provide a scientific basis for the maintenance and replacement of high-voltage circuit breakers.

[0084] By using the method in the embodiment, the service life of the closing spring of the high-voltage circuit breaker can be predicted, preventive maintenance and replacement can be performed in advance, and high repair costs and power loss caused by sudden failures can be avoided. Provide a basis for equipment maintenance.

[0085] In specific embodiments, please refer to Figure 5As shown in FIG. 2, a structure diagram of a life evaluation system of a closing spring in a second embodiment of the present application is shown, and the system comprises a closing time acquisition module 301, a model mapping module 302, a threshold acquisition module 303 and a service life acquisition module 304. The closing time acquisition module 301 is configured to acquire closing times of the closing spring under different stress loss rates. The model mapping module 302 is configured to construct a mapping model between the stress loss rate and the closing time according to the closing times under the different stress loss rates and the different stress loss rates. The threshold acquisition module 303 is configured to acquire a stress loss rate threshold of the closing spring according to the mapping model and a preset closing time range. The service life acquisition module 304 is configured to acquire service lives of the closing spring under different temperatures according to spring loss rates of the closing spring under the different temperatures and the stress loss rate threshold.

[0086] The system in the embodiment acquires the closing times of the closing spring under the different stress loss rates, constructs the mapping model between the stress loss rate and the closing time, acquires the stress loss rate threshold of the closing spring according to the mapping model and the preset closing time range, determines the failure state of the closing spring, and acquires the service lives of the closing spring under the different temperatures according to the spring loss rates of the closing spring under the different temperatures and the stress loss rate threshold, so as to accurately evaluate the service life of the closing spring.

[0087] In specific embodiments, the third embodiment of the present application provides a life evaluation device of a closing spring, comprising a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor to make the processor execute the steps of the method in any one of the first embodiments of the present application. The device in the embodiment acquires the closing times of the closing spring under the different stress loss rates, constructs the mapping model between the stress loss rate and the closing time, acquires the stress loss rate threshold of the closing spring according to the mapping model and the preset closing time range, determines the failure state of the closing spring, and acquires the service lives of the closing spring under the different temperatures according to the spring loss rates of the closing spring under the different temperatures and the stress loss rate threshold, so as to accurately evaluate the service life of the closing spring.

[0088] In specific embodiments, the fourth embodiment of the present application provides a computer readable storage medium storing a computer program, the computer program being executed by a processor to make the processor execute the steps of the method according to any one of the first embodiment of the present application. The storage medium in the embodiment acquires the closing time of the closing spring under different stress loss rates, and constructs a mapping model between the stress loss rate and the closing time; acquires the stress loss rate threshold of the closing spring according to the mapping model and a preset closing time range, and determines the failure state of the closing spring; and acquires the service life of the closing spring under different temperatures according to the spring loss rate of the closing spring under different temperatures and the stress loss rate threshold, so as to accurately evaluate the service life of the closing spring.

[0089] Figure 6 An internal structure diagram of a computer device in an embodiment is shown. The computer device can be a terminal or a server. Please refer to Figure 6 , which includes a processor, a memory and the like connected through a system bus. Among them, the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system, and can also store a computer program, which, when executed by the processor, can make the processor implement the method in the embodiment. The internal memory can also store a computer program, which, when executed by the processor, can make the processor execute the method in the embodiment. Those skilled in the art can understand Figure 6 that the structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0090] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent of the present application. It should be noted that for those skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

[0091] The above is only the preferred embodiment of the present application, and is not a limitation on other forms of the present application. Any person skilled in the art can make changes or modifications to the equivalent embodiments applied to other fields by using the disclosed technical content, but any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application still belongs to the protection scope of the technical solution of the present application.

Claims

1. A method for evaluating the life of a closing spring, characterized by, The method comprises: obtaining closing time of a closing spring under different stress loss rates; constructing a mapping model between stress loss rate and closing time according to the closing time under different stress loss rates and different stress loss rates; mapping a preset closing time range into the stress loss rate of the mapping model by using a Gaussian process regression and a Bayesian inference method to obtain a probability of the closing time of the closing spring under different stress losses within the preset closing time range; obtaining a stress loss rate threshold of the closing spring according to a preset confidence level; fitting spring loss rates of the closing spring at different temperatures and energy storage times of the closing spring to obtain stress loss rates of the closing spring at different temperatures; obtaining service life of the closing spring at different temperatures according to the stress loss rates of the closing spring and a preset service life model; the probability is obtained by using the following formula: wherein, is the probability, is a minimum value of time in the preset closing time range, is a maximum value of time in the preset closing time range, is a stress loss rate s the closing time under the stress loss rate. the service life of the closing spring at different temperatures is obtained by using the following formula: wherein, k is the stress loss rate, A is the Arrhenius constant, is the activation energy, is the temperature, a , b and c is a constant, is the Boltzmann constant, is a predetermined spring failure threshold, t is the service life of the closing spring at a temperature T .

2. The method of evaluating the life of a closing spring according to claim 1, wherein the stress loss rate is obtained by using the following method: obtaining a first stress required for compressing the closing spring to a preset length at a first time; obtaining a second stress required for compressing the closing spring to the preset length at a second time; the second time is later than the first time; obtaining the stress loss rate according to the first stress and the second stress.

3. The method of evaluating the life of a closing spring according to claim 1, wherein the mapping model between the stress loss rate and the closing time is obtained by using the following formula: wherein is the stress loss rate s is the closing time, is a Gaussian distribution, is the stress loss rate s is a mean function, is the stress loss rate s is a covariance function.

4. A closing spring life evaluation system for use in the closing spring life evaluation method according to claim 1, characterized by The system comprises a closing time acquisition module, a model mapping module, a threshold acquisition module and a service life acquisition module; the closing time acquisition module is used to obtain closing time of a closing spring under different stress loss rates; the model mapping module is used to construct a mapping model between stress loss rate and closing time according to the closing time under different stress loss rates and different stress loss rates; the threshold acquisition module is used to obtain a stress loss rate threshold of the closing spring according to the mapping model and a preset closing time range; the service life acquisition module is used to obtain service life of the closing spring at different temperatures according to spring loss rates of the closing spring at different temperatures and the stress loss rate threshold.

5. A closing spring life evaluation device comprising a memory and a processor, characterized by, The memory stores a computer program, and the computer program is executed by the processor to make the processor execute the steps of the method in any one of claims 1 to 3.

6. A computer readable storage medium storing a computer program, characterized in that, The computer program is executed by the processor to make the processor execute the steps of the method in any one of claims 1 to 3.

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