A method for evaluating the residual life of an electrical component under the influence of stress fluctuations

Abstract

The application discloses a kind of suitable for the remaining life evaluation method of electrical component under the influence of stress fluctuation, first, the initial state information of electrical component is acquired, including characteristic parameter and its initial value.Next, static artificial accelerated aging corrosion test is carried out, and the change value of characteristic parameter with time is acquired.Based on these change values, the basic weight of each characteristic parameter is determined.The function relationship between characteristic parameter and time is established, and the aging process is described.The Arrhenius model is used to calculate the acceleration factor, and the model is adjusted to adapt to different temperature conditions.According to the acceleration factor and the function relationship, the characteristic parameter degradation model is obtained.When electrical component is only affected by environmental stress fluctuation, the degradation model considering this influence is further established.Finally, according to the operating state of electrical component, the corresponding model is used to evaluate the remaining life, and a scientific basis is provided for maintenance and management.This method considers multiple factors, improves the evaluation accuracy, and ensures the reliability and safety of the system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of remaining life prediction of electrical equipment, and particularly relates to a remaining life evaluation method for electrical components under the influence of stress fluctuation. BACKGROUND

[0002] In modern electronic equipment, the reliability and life evaluation of electrical components are of great significance. With the continuous progress of science and technology, electrical components play a key role in various complex application scenarios, and their performance stability and life length are directly related to the reliability and safety of the entire system. Accurate evaluation of the remaining life of electrical components not only optimizes the maintenance plan of the equipment and reduces maintenance costs, but also effectively prevents system failures caused by component failures and ensures the normal operation of the equipment. In addition, in the context of circular economy, the remaining life evaluation of electrical and electronic product components has important practical significance for the remanufacturability evaluation of old products, the ecological efficiency evaluation of product systems, and the market access and regulation of old products by the government.

[0003] However, the existing remaining life evaluation methods for electrical components have many limitations. Specifically, most existing evaluation methods focus on life prediction under storage conditions and design margins, often ignoring the influence of many internal and external stress fluctuations on the remaining life of electrical components in actual use, which makes the error of life evaluation larger and the guidance to actual production limited. For example, although the traditional accelerated life test method can obtain the failure rate and life of the component under normal use conditions in a short time, the accuracy of the extrapolated results may be affected due to the large difference between the harsh environment or stress applied and the actual use conditions. Although the reliability evaluation method based on performance degradation data can use different process models for life prediction according to different failure modes, when facing complex failure mechanisms of electrical components and coupling effects of multiple stress factors, a single performance degradation model is difficult to accurately describe the actual degradation process of the component.

[0004] In summary, the existing remaining life evaluation methods for electrical components still need to be further improved in terms of applicability and accuracy of prediction results. SUMMARY

[0005] The purpose of the present application is to solve the above technical problems, and to provide a remaining life evaluation method for electrical components under the influence of stress fluctuation, which can more accurately evaluate the remaining life of electrical components.

[0006] In order to solve the above problems, the present application is implemented according to the following technical solution:

[0007] The present application provides a remaining life evaluation method for electrical components under the influence of stress fluctuation, which comprises the following steps:

[0008] S100, obtaining initial state information of an electrical component to be evaluated, the initial state information including characteristic parameters of the electrical component to be evaluated and initial values of the characteristic parameters;

[0009] S200, performing a static artificial accelerated aging corrosion test on the electrical component to be evaluated to obtain variation values of the characteristic parameters over time;

[0010] S300, determining a basic weight ω of each of the characteristic parameters based on the variation values of the characteristic parameters over time i ;

[0011] S400, establishing a functional relationship between values of each of the characteristic parameters obtained during the static artificial accelerated aging corrosion test and time, the functional relationship being y i = f i (t), wherein t represents a time length of the static artificial accelerated aging corrosion test;

[0012] S500, calculating an acceleration factor AF according to an Arrhenius model , wherein F is a reaction rate constant, A is a frequency factor, E a is an activation energy of the electrical component to be evaluated, k is a Boltzmann constant, and T is an absolute temperature;

[0013] S600, obtaining a characteristic parameter degradation model of the electrical component to be evaluated according to the acceleration factor AF and the functional relationship in step S400

[0014] S700, when the electrical component to be evaluated is only affected by environmental stress fluctuation in actual use, establishing a characteristic parameter degradation model [B] = ∑ω i B i = ∑ω i f i (t, α1, α2, α3,..., α k ), wherein α1, α2, α3,..., α k are environmental stress fluctuation factors affecting the electrical component to be evaluated;

[0015] S800, when the electrical component to be evaluated is in a non-running state, evaluating a remaining life of the electrical component to be evaluated by the characteristic parameter degradation model [A], and the evaluated remaining life is denoted as Y A ; when the electrical component to be evaluated is only affected by environmental stress fluctuation in actual work, calculating a year limit Y BY1=Y A -Y B .

[0016] Preferably, the specific process of step S300 comprises:

[0017] S310, assuming that there are m characteristic parameters, and the observation value of each characteristic parameter at different time points is x ij , wherein i is the time point, j is the index of the characteristic parameter, and n is the number of observation values of each characteristic parameter;

[0018] S320, the observation value x ij of each characteristic parameter at different time points is normalized to calculate the normalized value p ij ;

[0019] S330, according to the normalized value p ij , the information entropy E j of each characteristic parameter is calculated;

[0020] S340, according to the information entropy E j , the basic weight ω i of each characteristic parameter is calculated.

[0021] Preferably, in step S320, the normalized value p

[0022] Preferably, in step S330, the information entropy E

[0023] Preferably, in step S340, the basic weight ω

[0024] Preferably, in step S500, the acceleration factor a , wherein T0 is the absolute temperature under normal state, and T test is the absolute temperature under accelerated state.

[0025] Preferably, step S700 further comprises: when the to-be-evaluated electrical element is only affected by working stress fluctuation in actual use, establishing a characteristic parameter degradation model [C] = ∑ω i C i = ∑ω i f i (t, β1, β2, β3,..., β k ), wherein β1, β2, β3,..., β k are working stress fluctuation influence factors affecting the to-be-evaluated electrical element.

[0026] Preferably, when the to-be-evaluated electrical component is only affected by working stress fluctuation in actual work, the characteristic parameter degradation model [C] is used to calculate the annual limit Y of the to-be-evaluated electrical component affected by environmental stress fluctuation C , and at this time, the actual remaining life Y2 of the to-be-evaluated electrical component is Y A -Y C .

[0027] Preferably, the step S700 further comprises: when the to-be-evaluated electrical component is affected by multiple stress fluctuations in actual use, a characteristic parameter degradation model [D] considering the influence of multiple stress fluctuations is established, D = ∑ω i D i = ∑ω i f i (t, θ1, θ2, θ3,..., θ k ), wherein the θ1, θ2, θ3,..., θ k are multiple stress fluctuation influence factors affecting the to-be-evaluated electrical component.

[0028] Preferably, when the to-be-evaluated electrical component is affected by multiple stress fluctuations in actual work, the characteristic parameter degradation model [D] is used to calculate the annual limit Y of the to-be-evaluated electrical component affected by multiple stress fluctuations D , and at this time, the actual remaining life Y3 of the to-be-evaluated electrical component is Y A -Y D .

[0029] Compared with the prior art, the present application has the following beneficial effects:

[0030] The present application provides an electrical component remaining life evaluation method suitable for stress fluctuation, which firstly obtains initial state information of the to-be-evaluated electrical component, including characteristic parameters and initial values, to provide basic data for subsequent evaluation. Then, the static artificial accelerated aging corrosion test is used to obtain the change value of the characteristic parameters with time, and these data are used to determine the basic weight of each characteristic parameter, so as to reflect the relative importance of each characteristic parameter in the electrical component life evaluation. By calculating the information entropy and the basic weight, the present application can more accurately evaluate the influence of the characteristic parameters on the electrical component life.

[0031] Further, the application establishes a functional relationship between the characteristic parameters and time, and calculates the acceleration factor according to the Arrhenius model, thereby obtaining the characteristic parameter degradation model of the electrical component. This model not only considers the influence of the temperature acceleration factor, but also establishes a more comprehensive degradation model by considering the environmental stress fluctuation factor. When the electrical component is affected by environmental stress fluctuation, working stress fluctuation, or multiple stress fluctuations in actual use, the application can calculate the actual remaining life of the electrical component through the corresponding degradation model, providing more accurate and reliable evaluation results.

[0032] In summary, the application is not only suitable for remaining life evaluation under simple conditions, but also suitable for remaining life evaluation of electrical components under complex conditions. By assigning reasonable weight ratios to the characteristic parameters, the application can more deeply understand the working mechanism of the electrical component, and provide more accurate prediction results. In addition, the application can comprehensively understand and optimize the performance of the electrical component throughout its entire life cycle, support the industrial system to establish a more effective health monitoring system, timely detect abnormal conditions and warn of possible impending failures, thereby ensuring the reliability and safety of the electrical component. This not only improves the accuracy of the evaluation, but also provides strong technical support for the maintenance and asset management of the industrial system. BRIEF DESCRIPTION OF DRAWINGS

[0033] The specific embodiments of the application will be further described in detail below with reference to the accompanying drawings, in which:

[0034] Figure 1 is a technical principle diagram of an electrical component remaining life evaluation method suitable for stress fluctuation according to the application. DETAILED DESCRIPTION

[0035] In order to enable those skilled in the art to better understand the application scheme, the technical solutions in the embodiments of the application will be described clearly and completely below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the application, not all. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the application.

[0036] The terms used in the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. Unless otherwise defined, the technical terms or scientific terms used in the specification should be understood as the general meaning understood by those skilled in the art. The terms "first", "second", and similar terms used in the specification and claims do not represent any order, quantity or importance, but are only used to distinguish different technical features.

[0037] The following describes the preferred embodiments of the present application, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application.

[0038] The present application provides a method for evaluating the residual life of an electrical component under the influence of stress fluctuation, which comprises the following steps:

[0039] S100, obtaining initial state information of the electrical component to be evaluated, the initial state information comprising characteristic parameters of the electrical component to be evaluated and initial values of the characteristic parameters;

[0040] It can be understood that the initial state information provides basic data for subsequent evaluation, ensuring that the starting point of the evaluation is accurate and reliable. In this embodiment, the characteristic parameters refer to various indicators that can reflect the performance and state of the electrical component, such as capacitance value, leakage current, equivalent series resistance, etc. The initial values of the characteristic parameters are the measured values of these parameters in the brand-new or initial state of the electrical component, providing a benchmark for subsequent changes.

[0041] S200, performing a static artificial accelerated aging corrosion test on the electrical component to be evaluated to obtain the changes of the characteristic parameters over time;

[0042] It should be noted that the static artificial accelerated aging corrosion test refers to performing an artificial accelerated aging corrosion test on the electrical component to be evaluated in a non-running or non-loaded state throughout the test, which can obtain the aging corrosion change rule of the electrical equipment in a short test period, obtain the cumulative damage information of the electrical component in a short time sequence, and obtain the normal life of the electrical component in the actual environment by comparing the artificial accelerated aging test conditions with the actual environmental conditions. The normal life refers to the life of the electrical component in a non-running state without stress fluctuation, i.e., close to the storage life of the electrical component. In this embodiment, the changes of the characteristic parameters over time are obtained through the static artificial accelerated aging corrosion test, which is crucial for understanding the performance degradation that the electrical component may experience in actual use, and provides experimental data support for subsequent establishment of the degradation model.

[0043] S300, determining the basic weight ω of each characteristic parameter based on the changes of the characteristic parameters over time i ;

[0044] Specifically, S310, assuming that there are m characteristic parameters, and the observation value of each characteristic parameter at different time points is x ij , wherein i is the time point, j is the index of the characteristic parameter, and n is the number of observation values of each characteristic parameter;

[0045] Further, S320, performing principal component analysis on the observation values x ijNormalization processing is performed to calculate a normalized value p ij Specifically,

[0046] Further, S330, according to the normalized value p ij Calculate the information entropy E of each feature parameter j Specifically,

[0047]

[0048] Further, S340, according to the information entropy E j Calculate the basic weight ω of each feature parameter i Specifically,

[0049]

[0050] It can be understood that the information entropy is an index for measuring the uncertainty of data, and the smaller the value is, the more the change of the feature parameter reflects the degradation of the electrical component, and therefore a higher weight should be given. By calculating the information entropy to quantify the basic weight of each feature parameter, it can ensure that in the comprehensive evaluation, the more important feature parameter has a greater impact on the final result.

[0051] S400, a function relationship between the value of each feature parameter obtained when carrying out the static artificial accelerated aging corrosion test and time is established, and the function relationship is y i = f i (t), where t represents the duration of the static artificial accelerated aging corrosion test;

[0052] It can be understood that the function relationship describes the change rule of the feature parameter with time, which is crucial for subsequent prediction of the expected value of the feature parameter at a given time point, thereby inferring the current state and future performance of the electrical component.

[0053] S500, according to the Arrhenius model Calculate the acceleration factor AF, where F is the reaction rate constant, A is the frequency factor, E a is the activation energy of the electrical component to be evaluated, k is the Boltzmann constant, and T is the absolute temperature;

[0054] It should be noted that the Arrhenius model is an empirical formula describing the relationship between chemical reaction rate and temperature, which is used here to quantify the effect of temperature on the aging rate of the electrical component. The acceleration factor AF reflects the difference in the aging rate of the electrical component under different temperature conditions. By calculating this factor, the data in the accelerated test can be extrapolated to the expected service life under actual use conditions.

[0055] Specifically, wherein T0 is an absolute temperature in a normal state, T is an absolute temperature in an accelerated state, F0 is a reaction rate constant in the normal state, F is a reaction rate constant in the accelerated state, and A is a frequency factor. test wherein T0 is an absolute temperature in a normal state, T is an absolute temperature in an accelerated state, F0 is a reaction rate constant in the normal state, F is a reaction rate constant in the accelerated state, and A is a frequency factor.

[0056] It should be noted that in the present embodiment, (1) the relationship between the reaction rate constant F and the temperature T is as follows: in the normal state, the absolute temperature of the to-be-evaluated electrical component when working is T0, and the reaction rate constant is F0, then in the accelerated state, the absolute temperature of the to-be-evaluated electrical component when working is T, and the reaction rate constant is F. test test (2) In order to find the ratio of the rate constants at the two temperatures, we take the ratio of the two equations: wherein since the frequency factor A is a constant, it can be removed, and thus the ratio can be simplified as: (3) The reaction rate constant F is inversely proportional to the lifetime L of the to-be-evaluated electrical component, and thus: i.e. (4) The acceleration factor AF is the ratio of the lifetime of the to-be-evaluated electrical component under normal working conditions to the lifetime under accelerated test conditions:

[0057] i.e.

[0058] S600, according to the acceleration factor AF and the functional relationship in step S400, the characteristic parameter degradation model of the to-be-evaluated electrical component is obtained

[0059] S700, when the to-be-evaluated electrical component is only affected by environmental stress fluctuations in actual use, a characteristic parameter degradation model considering the influence of environmental stress fluctuations is established: B =∑ω i B i =∑ω i f i (t,α1,α2,α3,...,α k ), wherein α1,α2,α3,...,α k are environmental stress fluctuation influence factors affecting the to-be-evaluated electrical component.

[0060] Preferably, step S700 further comprises: when the to-be-evaluated electrical component is only affected by working stress fluctuations in actual use, a characteristic parameter degradation model considering the influence of working stress fluctuations is established: C =∑ω i C i =∑ω i f i (t,β1,β2,β3,...,β k ), wherein β1,β2,β3,...,β k ​​The stress fluctuation influence factor affecting the electrical component to be evaluated;

[0061] Preferably, the step S700 further comprises: when the electrical component to be evaluated is affected by multiple stress fluctuation in actual use, establishing a characteristic parameter degradation model [D] =∑ω i D i =∑ω i f i (t,θ1,θ2,θ3,...,θ k ), wherein θ1,θ2,θ3,...,θ k are the multiple stress fluctuation influence factors affecting the electrical component to be evaluated;

[0062] S800, when the electrical component to be evaluated is in a non-running state, the remaining life of the electrical component to be evaluated is evaluated by the characteristic parameter degradation model [A], and the evaluated remaining life is recorded as Y A ; when the electrical component to be evaluated is only affected by environmental stress fluctuation in actual work, the environmental stress fluctuation damage year of the electrical component to be evaluated is calculated by the characteristic parameter degradation model [B], and the calculated result is recorded as Y B , then the actual remaining life Y1 of the electrical component to be evaluated is Y A -Y B .

[0063] In an embodiment, when the electrical component to be evaluated is only affected by working stress fluctuation in actual work, the environmental stress fluctuation damage year of the electrical component to be evaluated is calculated by the characteristic parameter degradation model [C], and the calculated result is recorded as Y C , then the actual remaining life Y2 of the electrical component to be evaluated is Y A -Y C .

[0064] In an embodiment, when the electrical component to be evaluated is affected by multiple stress fluctuation in actual work, the multiple stress fluctuation damage year of the electrical component to be evaluated is calculated by the characteristic parameter degradation model [D], and the calculated result is recorded as Y D , then the actual remaining life Y3 of the electrical component to be evaluated is Y A -Y D .

[0065] The beneficial effects of the present application are:

[0066] The application provides a kind of suitable for the remaining life evaluation method of electrical component under the influence of stress fluctuation, first, the initial state information of the electrical component to be evaluated is obtained by the application, including characteristic parameter and its initial value, which provides basic data for subsequent evaluation. Then, the change value of characteristic parameter with time is obtained by static artificial accelerated aging corrosion test, and these data are used to determine the basic weight of each characteristic parameter, so as to reflect the relative importance of each characteristic parameter in electrical component life evaluation. By calculating information entropy and basic weight, the application can more accurately evaluate the influence of characteristic parameter on electrical component life.

[0067] Further, the application establishes the functional relationship between characteristic parameter and time, and calculates the acceleration factor according to Arrhenius model, so as to obtain the characteristic parameter degradation model of electrical component. This model not only considers the influence of temperature acceleration factor, but also establishes a more comprehensive degradation model by considering the environmental stress fluctuation influence factor. When the electrical component is affected by environmental stress fluctuation, working stress fluctuation or multiple stress fluctuation in actual use, the application can calculate the actual remaining life of the electrical component through the corresponding degradation model, and provide more accurate and reliable evaluation results.

[0068] In summary, the application is not only suitable for remaining life evaluation under simple conditions, but also suitable for remaining life evaluation of electrical component under complex conditions. By giving reasonable weight ratio to characteristic parameter, the application can more deeply understand the working mechanism of electrical component, and provide more accurate prediction results. In addition, the application can also comprehensively understand and optimize the performance of electrical component in its entire life cycle, support industrial system to establish more effective health monitoring system, find abnormal conditions in time and warn possible impending failure, so as to ensure the reliability and safety of electrical component. This not only improves the accuracy of evaluation, but also provides strong technical support for maintenance and asset management of industrial system.

[0069] The above is only the preferred embodiment of the application, and does not limit the application in any form, so any modification, equivalent change and modification of the above embodiment according to the technical essence of the application, without departing from the technical solution content of the application, still belongs to the scope of the technical solution of the application.

Claims

1. A method for evaluating the residual life of an electrical component under the influence of stress fluctuations, characterized in that The method comprises the following steps: S100, acquiring initial state information of an electrical component to be evaluated, the initial state information comprising characteristic parameters of the electrical component to be evaluated and initial values of the characteristic parameters; S200, performing a static artificial accelerated aging corrosion test on the electrical component to be evaluated to acquire variation values of the characteristic parameters over time; S300、based on the change value of the feature parameter over time, determine the base weight ω of each feature parameter i ; S400, a function relationship between the value of each of the characteristic parameters obtained when the static artificial accelerated aging corrosion test is carried out and time is established, the function relationship is y i = f i (t), wherein t represents the duration of the static artificial accelerated aging corrosion test; S500, according to the Arrhenius model The acceleration factor AF is calculated, wherein F is the reaction rate constant, A is the frequency factor, E is the activation energy of the electrical component to be evaluated, k is the Boltzmann constant, and T is the absolute temperature. a is the activation energy of the electrical component to be evaluated, k is the Boltzmann constant, and T is the absolute temperature. S600、according to the acceleration factor AF and the function relationship in step S400, a characteristic parameter degradation model of the to-be-evaluated electrical component is obtained S700、when the to-be-evaluated electrical element is only affected by environmental stress fluctuation in actual use, a characteristic parameter degradation model [B] =∑ω i B i =∑ω i f i (t,α1,α2,α3,...,α k ), wherein the α1,α2,α3,...,α k are environmental stress fluctuation influence factors affecting the to-be-evaluated electrical element. S800, when the to-be-evaluated electrical element is in a non-operation state, evaluating the remaining life of the to-be-evaluated electrical element by a characteristic parameter degradation model [A], and the evaluated remaining life is denoted as Y A ; when the to-be-evaluated electrical element is only affected by environmental stress fluctuation in actual work, calculating the annual limit of the to-be-evaluated electrical element affected by environmental stress fluctuation by a characteristic parameter degradation model [B] to obtain Y B , at this time, the actual remaining life Y1 of the to-be-evaluated electrical element is Y A -Y B .

2. The method for evaluating the residual life of an electrical component under the influence of stress fluctuations according to claim 1, characterized in that, The specific process of step S300 comprises: S310、Suppose the characteristic parameters have m, each observation value of the characteristic parameters at different time points is x ij wherein, the i is the time point, j is the index of the characteristic parameters, and n is the number of observation values of each characteristic parameter. S320, observing x of each feature parameter at different time points ij carrying out normalization processing to calculate a normalized value p ij ; S330、according to the normalized value p ij The information entropy E is calculated for each feature parameter j ; S340、according to the information entropy E j The base weight ω of each feature parameter is calculated i .

3. The method according to claim 2, characterized in that: In step S320, the normalized value 4. The method according to claim 2, characterized in that: In step S330, the information entropy 5. The method according to claim 2, characterized in that: In step S340, the base weight 6. The method according to claim 1, characterized in that: In step S500, the acceleration factor wherein T0 is the absolute temperature in the normal state, and T test is the absolute temperature in the accelerated state.

7. The method for evaluating the residual life of an electrical component under the influence of stress fluctuation according to claim 1, wherein Step S700 further comprises: When the to-be-evaluated electrical component is only affected by working stress fluctuation in actual use, a characteristic parameter degradation model [C] =∑ω i C i =∑ω i f i (t,β1,β2,β3,...,β k ), wherein the β1,β2,β3,...,β k are working stress fluctuation influence factors affecting the to-be-evaluated electrical component.

8. The method according to claim 7, characterized in that: When the to-be-evaluated electrical component is only affected by working stress fluctuation in actual work, the environmental stress fluctuation damage year limit Y of the to-be-evaluated electrical component is calculated by the characteristic parameter degradation model [C] C , then at this time the actual remaining life Y2 of the to-be-evaluated electrical component = Y A -Y C .

9. The method for evaluating the residual life of an electrical component under the influence of stress fluctuation according to claim 1, wherein Step S700 further comprises: When the to-be-evaluated electrical component is affected by multiple stress fluctuations in actual use, a characteristic parameter degradation model [D] =∑ω i D i =∑ω i f i (t,θ1,θ2,θ3,...,θ k ), wherein θ1, θ2, θ3,..., θ k are multiple stress fluctuation influence factors affecting the to-be-evaluated electrical component.

10. The method according to claim 9, characterized in that: When the to-be-evaluated electrical component is affected by multiple stress fluctuations in actual work, the year limit Y of the to-be-evaluated electrical component under the multiple stress fluctuations is calculated through the characteristic parameter degradation model [D] D , then at this time the actual remaining life Y3 of the to-be-evaluated electrical component = Y A -Y D .

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