CN112611952B - Acceleration coefficient determination method, acceleration coefficient determination device, electronic equipment and readable storage medium - Google Patents

Acceleration coefficient determination method, acceleration coefficient determination device, electronic equipment and readable storage medium Download PDF

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CN112611952B
CN112611952B CN202011368163.7A CN202011368163A CN112611952B CN 112611952 B CN112611952 B CN 112611952B CN 202011368163 A CN202011368163 A CN 202011368163A CN 112611952 B CN112611952 B CN 112611952B
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test value
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CN112611952A (en
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唐文涛
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Chengdu Haiguang Microelectronics Technology Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/2851—Testing of integrated circuits [IC]
    • G01R31/2855—Environmental, reliability or burn-in testing
    • G01R31/2872—Environmental, reliability or burn-in testing related to electrical or environmental aspects, e.g. temperature, humidity, vibration, nuclear radiation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/2851—Testing of integrated circuits [IC]
    • G01R31/2855—Environmental, reliability or burn-in testing
    • G01R31/2872—Environmental, reliability or burn-in testing related to electrical or environmental aspects, e.g. temperature, humidity, vibration, nuclear radiation
    • G01R31/2874—Environmental, reliability or burn-in testing related to electrical or environmental aspects, e.g. temperature, humidity, vibration, nuclear radiation related to temperature
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/2851—Testing of integrated circuits [IC]
    • G01R31/2855—Environmental, reliability or burn-in testing
    • G01R31/2872—Environmental, reliability or burn-in testing related to electrical or environmental aspects, e.g. temperature, humidity, vibration, nuclear radiation
    • G01R31/2879—Environmental, reliability or burn-in testing related to electrical or environmental aspects, e.g. temperature, humidity, vibration, nuclear radiation related to electrical aspects, e.g. to voltage or current supply or stimuli or to electrical loads
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/2851—Testing of integrated circuits [IC]
    • G01R31/2855—Environmental, reliability or burn-in testing
    • G01R31/2872—Environmental, reliability or burn-in testing related to electrical or environmental aspects, e.g. temperature, humidity, vibration, nuclear radiation
    • G01R31/2881—Environmental, reliability or burn-in testing related to electrical or environmental aspects, e.g. temperature, humidity, vibration, nuclear radiation related to environmental aspects other than temperature, e.g. humidity or vibrations

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  • Engineering & Computer Science (AREA)
  • Environmental & Geological Engineering (AREA)
  • Health & Medical Sciences (AREA)
  • Toxicology (AREA)
  • Computer Hardware Design (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Tests Of Electronic Circuits (AREA)

Abstract

The application provides an acceleration coefficient determining method, an acceleration coefficient determining device, electronic equipment and a readable storage medium, wherein the method comprises the following steps: acquiring a plurality of test values of a target variable and time of each test value aiming at a preset sample under a first condition, and establishing a prediction model of the target variable and the test time of the preset sample under the first condition; acquiring the time when the target variable reaches the first target test value and the second target test value during the test of the preset sample under the second condition; predicting the time when the target variable reaches the first target test value and the second target test value under the first condition by using a prediction model; and determining the acceleration coefficient of the first physical variable to be tested according to the time of the first target test value and the second target test value under the first condition and the second condition. Therefore, the determination of the acceleration coefficient under different conditions can be realized through single-batch samples, and the problems of the existing mode that multiple batches and large sample quantity are required to be tested and the cost is high are solved.

Description

Acceleration coefficient determination method, acceleration coefficient determination device, electronic equipment and readable storage medium
Technical Field
The present application relates to the field of testing technologies, and in particular, to a method and apparatus for determining an acceleration coefficient, an electronic device, and a readable storage medium.
Background
Currently, integrated circuit products are required to be subjected to reliability tests to verify the usability of the product prior to mass production.
The reliability test of integrated circuits is an accelerated test that utilizes short-time testing to estimate long-term service life. Reliability tests require knowledge of the acceleration coefficients of a number of physical variables that actually affect the useful life of the product. Typically, physical variables that actually affect the useful life of an integrated circuit product include physical variables such as voltage, temperature, humidity, and the like.
The current conventional acceleration coefficient measuring method comprises the following steps: and selecting a plurality of batches of samples, respectively performing test experiments for changing a single physical variable (namely, test experiments for controlling all the conditions except a certain physical variable to be unchanged and only changing the value of the physical variable), and presuming the acceleration coefficient corresponding to the physical variable according to each experiment result. For example, 3 batches of integrated circuit products can be tested at different temperatures under the condition that the conditions except the temperature are kept the same, and after a certain period of time, the temperature acceleration coefficient can be estimated through the test results of the three test experiments. In addition, under the condition that the other 3 batches of integrated circuit products are kept the same except the voltage, test experiments are carried out under different voltages, and after a certain time, the voltage acceleration coefficient is estimated through the experimental results of the three test experiments.
However, the conventional acceleration coefficient measurement method at present needs to test a plurality of batches and a large sample amount, so that the problem of high cost exists. In addition, because multiple batches of samples are necessary, uncertainty caused by differences between samples exists, which affects the accuracy of the acceleration coefficient.
Disclosure of Invention
The embodiment of the application aims to provide a method, a device, electronic equipment and a readable storage medium for determining an acceleration coefficient so as to determine the acceleration coefficient.
The embodiment of the application provides a method for determining an acceleration coefficient, which comprises the following steps: acquiring a plurality of test values of a target variable and time of each test value under a first condition aiming at a preset sample; the first condition includes a plurality of physical variables, and each of the physical variables has a set value; the target variable changes with test time and with a change in the value of any one of the physical variables in the first condition; establishing a prediction model of the target variable and the test time of the preset sample under the first condition according to each test value and the time of each test value; acquiring the preset sample, and performing test under a second condition, wherein the target variable reaches a first target test value and a second target test value; the second condition is a condition obtained by changing the value of a first physical variable to be tested in the first condition, and the first physical variable to be tested is any physical variable in the first condition; predicting the time when the target variable reaches the first target test value and the second target test value under the first condition by using the prediction model; and determining the acceleration coefficient of the first physical variable to be tested according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing.
In the implementation process, firstly, a prediction model of a target variable and test time under a first condition is constructed through a plurality of test values under the first condition and the time of each test value. And then, changing the value of a first physical variable to be tested in the first condition to obtain a second condition, and obtaining the time when the variable of the test time scale of the preset sample under the second condition reaches the first target test value and the second target test value. In addition, a prediction model is adopted to predict the time when the target variable reaches the first target test value and the second target test value under the first condition of the preset sample. And then determining the acceleration coefficient of the first physical variable to be tested according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing. In the implementation process, the same time period only needs to be tested under one condition aiming at a preset sample, and the time for reaching the same target test value under the first condition is predicted by the prediction model, so that the determination of the acceleration coefficient under different conditions can be realized through a single batch of samples, and the problems that multiple batches, large sample quantity test and high cost are needed in the existing mode are solved. In addition, because multiple batches of samples are not needed, the problem that the accuracy of the acceleration coefficient is affected due to uncertainty caused by differences among the samples is avoided.
Further, determining the acceleration coefficient of the physical variable to be tested according to the predicted time of the first target test value and the second target test value under the first condition and the time of the first target test value and the second target test value under the second condition, including: obtaining a value of an acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition according to the time of the first target test value and the second target test value under the first condition which are obtained through prediction and the time of the first target test value and the second target test value under the second condition which are obtained through testing; determining the value of the acceleration factor of the first physical variable to be tested according to a preset acceleration coefficient model of the first physical variable to be tested according to the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition, the value of the first physical variable to be tested under the second condition and the value of the first physical variable to be tested under the first condition; substituting the value of the acceleration factor into the acceleration coefficient model to obtain the acceleration coefficient of the first physical variable to be tested.
It should be understood that, in practical applications, the acceleration coefficient corresponding to the physical variable is often a function associated with the value of the physical variable, where a constant in the function is called an acceleration factor, so that the acceleration coefficient corresponding to the physical variable can be quickly determined by determining the acceleration factor corresponding to the physical variable.
For example, for a physical variable that is a voltage in an integrated circuit product, the corresponding acceleration factor can be characterized by V-model (V model, a voltage corresponding acceleration factor model) as EXP (beta (V2-V1)). In the formula, EXP represents an exponential function based on a natural constant e, beta is an acceleration factor related to an acceleration coefficient in a V-model, the value is a constant, and V1 and V2 are two different voltage values under the influence of self factors such as materials, structures and the like of a product, so that after the value of beta is determined, the acceleration coefficient corresponding to the voltage as a physical variable can be determined.
Furthermore, the acceleration factor may also be correlated with the time under which the same test value is obtained for two different values of the physical variable under different conditions. For example, for a physical variable of voltage in an integrated circuit product, assuming that the voltage in the first condition is V1, the time to reach the first target test value is t n, the time to reach the second target test value is t n+1, the voltage in the second condition is V2, the time to reach the first target test value is t m, the time to reach the second target test value is t m+1, and then the acceleration coefficient when the voltage changes from V1 to V2 is equal to (t n+1-tn)/(tm+1-tm).
Accordingly, in the implementation process, the acceleration factor can be easily determined by predicting the time of the first target test value and the second target test value under the first condition, the time of the first target test value and the second target test value under the second condition, and the preset acceleration factor model of the first physical variable to be tested, so as to determine the acceleration factor of the first physical variable to be tested. The whole determination process is realized by using the predicted value of the prediction model and the actual test value under the second condition, the realization is simple, the test can be realized by single batch of samples, the test period is shorter and the cost is lower, the test is realized on the same sample, the test result is not influenced by the uncertainty caused by the difference between different samples, and the test result is more accurate.
Further, the second target test value is a plurality of; the obtaining the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing, includes: obtaining acceleration coefficients corresponding to the second target test values under the second condition according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing; and determining the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition according to the acceleration coefficient corresponding to each second target test value.
In the implementation process, the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition is determined through a plurality of second target test values. Therefore, when the first condition is changed into the second condition, the value of the acceleration coefficient corresponding to the first physical variable to be tested is determined, and a plurality of test results can be synthesized, so that the accuracy of the value of the acceleration coefficient corresponding to the first physical variable to be tested is improved when the determined condition is changed into the second condition, and the finally determined acceleration coefficient can be more accurate.
Further, determining, according to the acceleration coefficient corresponding to each second target test value, the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition changes to the second condition, includes: determining an average value of acceleration coefficients corresponding to the second target test values; the average value is the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition.
Further, the second target test value is a plurality of; the obtaining the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing, includes: obtaining an acceleration coefficient of the value of the first physical variable to be tested according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing;
Correspondingly, according to the value of the acceleration factor corresponding to the first physical variable to be tested when the first condition is changed into the second condition, the value of the first physical variable to be tested under the second condition and the value of the first physical variable to be tested under the first condition, determining the value of the acceleration factor of the first physical variable to be tested according to a preset acceleration factor model of the first physical variable to be tested, including: according to the acceleration coefficient corresponding to each second target test value under the second condition, the value of the first physical variable to be tested under the second condition and the value of the first physical variable to be tested under the first condition, determining the value of the acceleration factor corresponding to each second target test value according to a preset acceleration coefficient model of the first physical variable to be tested; and determining the value of the acceleration factor of the first physical variable to be tested according to the value of the acceleration factor corresponding to each second target test value.
In the implementation process, the value of the acceleration factor of the first physical variable to be tested is determined through a plurality of second target test values. Therefore, for the determination of the value of the acceleration factor, a plurality of test results can be synthesized, so that the accuracy of the determined value of the acceleration factor is improved, and the finally determined acceleration coefficient can be more accurate.
Further, the method further comprises: acquiring the preset sample, and performing test under a third condition, wherein the time when the target variable reaches a third target test value and a fourth target test value; the third condition is a condition obtained by changing a value of a second physical variable to be tested in the first condition, and the second physical variable to be tested is any physical variable except the first physical variable to be tested in the first condition; predicting the time when the target variable reaches the third target test value and the fourth target test value under the first condition by using the prediction model; and determining the acceleration coefficient of the second physical variable to be tested according to the time of the third target test value and the fourth target test value under the first condition obtained by prediction and the time of the third target test value and the fourth target test value under the third condition obtained by testing.
In the implementation process, the value of another physical variable is changed on the basis of the first condition again, so that the determination of the acceleration coefficient of the other physical variable can be continuously realized on the same sample, namely the determination of the acceleration coefficients of a plurality of physical variables can be realized on the basis of a single batch of samples without adopting a plurality of batches, the test cost and the period are reduced, and meanwhile, the influence of uncertainty caused by the difference between different batches of products is avoided, so that the test result is more accurate.
Further, the establishing a prediction model of the target variable and the test time of the preset sample under the first condition according to each test value and the time of each test value includes: fitting each coordinate point determined by the test value and the time of each test value in a coordinate system taking the test value and the test time as coordinate axes to obtain a fitting function of the test value and the time of each test value; the fitting function is a predictive model of the target variable and the test time of the preset sample under the first condition.
In the implementation process, the change rule between the target variable and the test time under the first condition can be reflected well through a fitting mode, so that the prediction result of the prediction model can be more attached to the actual result, and the accuracy of the acceleration coefficient determined by the scheme is improved.
The embodiment of the application also provides an acceleration coefficient determining device, which comprises: the model building module and the processing module;
The model building module is used for obtaining a plurality of test values of a target variable and time of each test value of a preset sample under a first condition, and building a prediction model of the target variable and test time of the preset sample under the first condition according to each test value and time of each test value; the first condition includes a plurality of physical variables, and each of the physical variables has a set value; the target variable changes with test time and with a change in the value of any one of the physical variables in the first condition;
The processing module is used for acquiring the preset sample, and the time when the target variable reaches a first target test value and a second target test value during the test under the second condition; the second condition is a condition obtained by changing the value of a first physical variable to be tested in the first condition, and the first physical variable to be tested is any physical variable in the first condition; predicting the time when the target variable reaches the first target test value and the second target test value under the first condition by using the prediction model; and determining the acceleration coefficient of the first physical variable to be tested according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing.
In the implementation process, the same time period only needs to be tested under one condition aiming at a preset sample, and the time for reaching the same target test value under the first condition is predicted by the prediction model, so that the determination of the acceleration coefficient under different conditions can be realized through a single batch of samples, and the problems that multiple batches, large sample quantity test and high cost are needed in the existing mode are solved. In addition, because multiple batches of samples are not needed, the problem that the accuracy of the acceleration coefficient is affected due to uncertainty caused by differences among the samples is avoided.
The embodiment of the application also provides electronic equipment, which comprises: a processor, a memory, and a communication bus; the communication bus is used for realizing connection communication between the processor and the memory; the processor is configured to execute one or more programs stored in the memory to implement any of the acceleration factor determining methods described above.
The embodiment of the application also provides a readable storage medium, which stores one or more programs, and the one or more programs can be executed by one or more processors to implement any one of the above methods for determining the acceleration coefficient.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a method for determining an acceleration factor according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an initial curve of a prediction model according to an embodiment of the present application;
FIG. 3 is a schematic diagram showing a curve change when a physical variable V is tested according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a curve change when the physical variable T is continuously tested according to an embodiment of the present application;
FIG. 5 is a schematic structural diagram of an acceleration factor determining device according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application.
Embodiment one:
In order to achieve reliable determination of the acceleration coefficient, an acceleration coefficient determination method is provided in the embodiment of the application. Referring to fig. 1, fig. 1 is a flowchart of a method for determining an acceleration factor according to an embodiment of the present application, including:
s101: a plurality of test values of a target variable and time of each test value are obtained for a preset sample under a first condition.
The first condition includes a plurality of physical variables, and each physical variable has a set value. Further, the target variable described in the embodiments of the present application refers to a variable that can be changed with a test time and a change in the value of any one of the physical variables in the first condition. In the embodiment of the application, the physical variables can be voltage, temperature, humidity and other physical variables influencing the use of the product.
In the embodiment of the application, the engineer can find the variables influenced by the values of the physical variables according to the physical variables to be tested as target variables. By way of example, the target variable may be the minimum operating voltage of the product, the maximum signal frequency of the product, or other variables.
In the embodiment of the present application, the kind of the physical variable provided in the first condition and the value of each physical variable in the first condition may be set by an engineer according to actual needs.
In embodiments of the present application, the predetermined sample may be selected by an engineer from among the produced product samples according to the product to be tested. After the sample is selected (the selected sample is the preset sample), the preset sample can be placed under the first condition for testing, so that a plurality of test values and the time of each test value are obtained.
It should be understood that if the type of product to be tested is different, the physical variables that are often set, as well as the target variables that are employed, will also be different. Therefore, physical variables specifically set in the test process and target variables adopted can be selected and configured by engineers according to the actual needs of the products to be tested.
S102: and establishing a predictive model of the target variable and the test time of the preset sample under the first condition according to each test value and the time of each test value.
In an exemplary embodiment of the present application, each coordinate point determined by the test value and the time of each test value may be fitted in a coordinate system with the test value and the test time as coordinate axes, so as to obtain a fitting function of the test value and the time of each test value. At this time, the obtained fitting function is a predictive model of the target variable and the test time of the preset sample under the first condition.
It should be understood that, in addition to the foregoing implementation of the prediction model by fitting, the prediction model may be implemented by a method such as a smoothing method, an autoregressive model, a moving average model, an autoregressive differential moving average model, and the embodiment of the present application is not limited thereto.
It should be understood that, in general, the more test values of the target variable and the time for each test value are obtained, i.e. the more samples, the more the constructed prediction model can conform to the actual law, the more accurate the prediction result is, but the more time it takes to construct the prediction model accordingly.
For this reason, in the embodiment of the present application, the engineer may set the test value required to be acquired in step S101 and the number of times for each test value according to the actual test requirement.
S103: and acquiring a preset sample, and during the test under the second condition, the time when the target variable reaches the first target test value and the second target test value.
It should be noted that, the second condition in the embodiment of the present application refers to a condition obtained by changing the value of the first physical variable to be tested in the first condition and keeping the values of the remaining physical variables in the first condition unchanged. The first physical variable to be tested is a physical variable to be tested in the round, and the first physical variable can be any physical variable in the first condition.
For example, the first condition includes three physical variables of voltage, temperature and humidity, and the values are voltage V1, temperature T1 and humidity R1 respectively. Assume that the present wheel wishes to determine the acceleration factor corresponding to the voltage. The second condition may be set to: voltage V2, temperature T1, humidity R1, wherein V2 is not equal to V1.
S104: and predicting the time when the target variable reaches the first target test value and the second target test value under the first condition by using a prediction model.
In the embodiment of the application, the first target test value and the second target test value can be set by engineers according to actual needs.
It should be noted that there may be no timing limitation between steps S103 and S104.
Optionally, in the embodiment of the present application, the first target test value may be a target scalar value at the beginning of the test under the second condition, so that the time when the test begins under the second condition may be quickly obtained, thereby obtaining the time corresponding to the first target test value.
S105: and determining the acceleration coefficient of the first physical variable to be tested according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing.
It should be understood that in practical applications, the acceleration coefficient corresponding to a physical variable is often a function associated with the value of the physical variable, and a constant in the function is called an acceleration factor.
For example, for a physical variable that is a voltage in an integrated circuit product, the corresponding acceleration factor can be characterized by V-model (V model, a voltage corresponding acceleration factor model) as EXP (beta (V2-V1)). In the formula, EXP represents an exponential function based on a natural constant e, beta is an acceleration factor related to an acceleration coefficient in a V-model, the value is a constant, the value is influenced by self factors such as a material, a structure and the like of a product, and V1 and V2 are two different voltage values.
Therefore, in the embodiment of the present application, in order to determine the acceleration coefficient of the first physical variable to be tested, the value of the acceleration factor corresponding to the first physical variable to be tested needs to be determined first.
It should be noted that, under two conditions where two specific values of the physical variable are specified, the acceleration coefficient is also related to the time at which the same test value is obtained under both conditions. For example, it may be correlated with the time difference between the first target test value and the second target test value obtained under both conditions.
For example, for a physical variable of voltage in an integrated circuit product, assuming that the voltage in the first condition is V1, the time to reach the first target test value is t n, and the time to reach the second target test value is t n+1; assuming that the voltage is V2 in the second condition, the time to reach the first target test value is t m, and the time to reach the second target test value is t m+1, the acceleration coefficient when the voltage changes from V1 to V2 is equal to (t n+1-tn)/(tm+1-tm).
Therefore, in the embodiment of the present application, the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed to the second condition (such as (t n+1-tn)/(tm+1-tm) in the above example) may be obtained first according to the time of the first target test value and the second target test value under the first condition (such as t n and t n+1 in the above example) obtained by prediction, and the time of the first target test value and the second target test value under the second condition (such as t m and t m+1 in the above example) obtained by testing.
And then, determining the value of the acceleration factor of the first physical variable to be tested according to the preset acceleration coefficient model of the first physical variable to be tested according to the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition, the value of the first physical variable to be tested under the second condition and the value of the first physical variable to be tested under the first condition.
For example, for the above example, (t n+1-tn)/(tm+1-tm) =exp (beta (V2-V1)), the value of the acceleration factor beta can be determined.
And substituting the value of the acceleration factor into the acceleration coefficient model to obtain the acceleration coefficient of the first physical variable to be tested.
For example, for the above example, assuming that the value of beta is 1, the acceleration coefficient of the physical variable of the voltage can be determined to be EXP (beta (Vx-Vy)), where Vx and Vy are voltage values.
It should be understood that in an ideal test environment, the acceleration coefficients obtained should be uniform, in theory, regardless of the change in the values of the first target test value and the second target test value. However, in practical application, the test environment is not an ideal state, so that acceleration coefficients often obtained by different target test values have certain deviation.
In order to improve the reliability of the determined acceleration coefficient, in a feasible implementation manner of the embodiment of the present application, a plurality of second target test values may be taken, so that the acceleration coefficient may be comprehensively determined based on the plurality of second target test values.
In an optional manner of the foregoing feasible implementation manner, the acceleration coefficient corresponding to each second target test value under the second condition may be obtained according to the predicted time of the first target test value and each second target test value under the first condition, and the time of the first target test value and each second target test value under the second condition.
And then, determining the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition according to the acceleration coefficient corresponding to each second target test value.
And then according to the determined value of the acceleration factor corresponding to the first physical variable to be tested when the first condition is changed into the second condition, and then according to the mode, determining the value of the acceleration factor corresponding to the first physical variable to be tested, and further determining the acceleration factor corresponding to the first physical variable to be tested.
Alternatively, in the above manner, an average value of the acceleration coefficients corresponding to the respective second target test values may be determined so that the average value is taken as the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed to the second condition.
Illustratively, taking still the physical variable of voltage in the integrated circuit product as an example, assume 3 second target test values, K1, K2, K3, respectively. Assuming that the voltage in the first condition is V1, the time for reaching the first target test value is t n, and the time for reaching K1, K2 and K3 is t n+1、tn+2 and t n+3 respectively; assuming that the voltage in the second condition is V2, the time to reach the first target test value is t m, and the time to reach K1, K2, and K3 is t m+1、tm+2 and t m+3.
Then, the value of the acceleration coefficient when the voltages corresponding to K1, K2, K3 respectively change from V1 to V2 can be determined: (t n+1-tn)/(tm+1-tm)、(tn+2-tn)/(tm+2-tm) and (t n+3-tn)/(tm+3-tm). At this time, the value of the acceleration coefficient when the finally determined voltage is changed from V1 to V2 is ：((tn+1-tn)/(tm+1-tm)+(tn+2-tn)/(tm+2-tm)+(tn+3-tn)/(tm+3-tm))/3.
It should be understood that the above-mentioned manner of taking the average value as the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed to the second condition is only an alternative manner in the embodiment of the present application, and is not limited thereto. In fact, in the embodiment of the present application, any manner of synthesizing the acceleration coefficients corresponding to the second target test values may be used to determine the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed to the second condition. For example, the maximum value and the minimum value of the acceleration coefficient values corresponding to the second target test values may be removed, and then the remaining values may be averaged to obtain the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed to the second condition.
In another alternative of the foregoing possible implementation manner, the acceleration coefficient of the value of the first physical variable to be tested corresponding to each second target test value under the second condition may be obtained according to the predicted time of the first target test value and each second target test value under the first condition and the time of the first target test value and each second target test value under the second condition.
And then, according to the acceleration coefficient corresponding to each second target test value under the second condition, the value of the first physical variable to be tested under the second condition and the value of the first physical variable to be tested under the first condition, and according to a preset acceleration coefficient model of the first physical variable to be tested, determining the value of the acceleration factor corresponding to each second target test value.
And determining the value of the acceleration factor of the first physical variable to be tested according to the value of the acceleration factor corresponding to each second target test value, and substituting the value of the acceleration factor into the acceleration coefficient model in the mode to obtain the acceleration coefficient of the first physical variable to be tested.
Alternatively, in the above alternative manner, an average value of the values of the acceleration factors corresponding to the second target test values may be determined, so that the average value is used as the value of the acceleration factor of the first physical variable to be tested.
Illustratively, taking still the physical variable of voltage in the integrated circuit product as an example, assume 3 second target test values, K1, K2, K3, respectively. Assuming that the voltage in the first condition is V1, the time for reaching the first target test value is t n, and the time for reaching K1, K2 and K3 is t n+1、tn+2 and t n+3 respectively; assuming that the voltage in the second condition is V2, the time for reaching the first target test value is t m, and the time for reaching K1, K2 and K3 is t m+1、tm+2 and t m+3; the acceleration coefficient model is V-model.
Then, the value of the acceleration coefficient when the voltages corresponding to K1, K2, K3 respectively change from V1 to V2 can be determined: (t n+1-tn)/(tm+1-tm)、(tn+2-tn)/(tm+2-tm) and (t n+3-tn)/(tm+3-tm) (for convenience of description, (t n+1-tn)/(tm+1-tm)、(tn+2-tn)/(tm+2-tm) and (t n+3-tn)/(tm+3-tm) are respectively denoted as K11, K21 and K31), so that there are k11=exp (beta 1 (V2-V1)), k21=exp (beta 2 (V2-V1)) and k31=exp (beta 3 (V2-V1)).
Then, the average number of beta1, beta2 and beta3 may be calculated, so that the value of the acceleration factor of the first physical variable to be tested is (beta 1+ beta2+ beta 3)/3.
It should be understood that the above-mentioned manner of taking the average value as the value of the acceleration factor of the first physical variable to be tested is only an alternative manner in the embodiment of the present application, and is not intended to be limiting. In fact, in the embodiment of the present application, any manner of synthesizing the values of the acceleration factors corresponding to the second target test values may be used to determine the values of the acceleration factors of the first physical variable to be tested.
It should be noted that, in the embodiment of the present application, if the acceleration coefficients corresponding to a plurality of physical variables need to be determined, after the acceleration coefficient of one physical variable is determined, the value of the second physical variable to be tested in the first condition may be changed based on the first condition, and the values of the remaining physical variables in the first condition may be kept unchanged, so as to obtain the third condition. The second physical variable to be tested is a physical variable to be tested in the round, and may be any physical variable except the tested physical variable in the first condition.
Similar to the second condition, the time when the target variable reaches the third target test value and the fourth target test value during the test of the preset sample under the third condition may be obtained. And predicting the time when the target variable reaches the third target test value and the fourth target test value under the first condition by using the prediction model.
And determining the acceleration coefficient of the second physical variable to be tested according to the time of the third target test value and the fourth target test value under the first condition obtained by prediction and the time of the third target test value and the fourth target test value under the third condition obtained by testing.
It will be appreciated that the process of determining the acceleration factor of the second physical variable to be tested under this third condition is consistent in nature with the process of determining the acceleration factor of the first physical variable to be tested under the second condition, except that the type of physical variable that changes value is different, and that the target test value set may be different. Therefore, referring to the above-described process of determining the acceleration coefficient of the first physical variable to be tested under the second condition, the description of the process of determining the acceleration coefficient of the second physical variable to be tested under the third condition will not be given here.
It should be understood that if the acceleration coefficients of two physical variables are determined and then the acceleration coefficients of another physical variable are also required to be determined, the fourth condition, the fifth condition, and so on may be determined in a similar manner to the determination of the third condition, and further the acceleration coefficients of the remaining physical variables may be determined with reference to the determination of the acceleration coefficients of the first physical variable to be tested under the second condition.
It should be noted that, the scheme of the embodiment of the present application may be applied to various scenes where an acceleration coefficient needs to be determined, for example, may be applied to a reliability test scene.
According to the scheme provided by the embodiment of the application, firstly, a prediction model of a target variable and test time under a first condition is constructed through a plurality of test values and the time of each test value under the first condition. And then, changing the value of a first physical variable to be tested in the first condition to obtain a second condition, and obtaining the time when the variable of the test time scale of the preset sample under the second condition reaches the first target test value and the second target test value. In addition, a prediction model is adopted to predict the time when the target variable reaches the first target test value and the second target test value under the first condition of the preset sample. And then determining the acceleration coefficient of the first physical variable to be tested according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing. Therefore, the same time period only needs to perform test under one condition on a preset sample (the test result under the other condition is obtained through prediction by the prediction model), so that the determination of the acceleration coefficient under different conditions can be realized through a single-batch sample (even a single sample in extreme cases), and the problems of the existing mode that multiple batches, a large number of samples are required to be tested and the cost is high are solved. In addition, because multiple batches of samples are not needed, the problem that the accuracy of the acceleration coefficient is affected due to uncertainty caused by differences among the samples is avoided.
Embodiment two:
the present embodiment further illustrates the scheme of the present application based on the first embodiment by taking a specific acceleration coefficient determining process as an example.
The physical variables to be tested are assumed to be voltage V and temperature T. The target variable is F (V, T, T), where T is the time variable.
First, a batch of samples was selected as experimental samples, which were tested under the first condition (v=v1, t=t1), the values of the target variable F at the first n time points (T 1 to T n) were recorded, and a predictive model was obtained by fitting, as shown in fig. 2.
The prediction model is also substantially a reliability degradation model under the first condition.
Then, the value of the voltage V was changed to obtain a second condition (v=v2, t=t1), and the test sample was continuously tested under the second condition for T n+1 time, to obtain a target variable value of F (V2, T1, T n+1).
Using the predictive model, the time T m at which the F (V2, T1, T n+1) values were obtained is extrapolated, as shown in fig. 3.
Calculating the value of an acceleration coefficient caused by the change of the physical variable voltage V: AFV= (tm-tn)/(tn+1-tn) =EXP (beta (V2-V1))= (V2/V1)/(gamma). AFV characterizes the value of the acceleration factor.
Thus, the value of the voltage acceleration factor beta (beta is the voltage acceleration factor when the V-model is used) or the value of the voltage acceleration factor gamma (gamma is the voltage acceleration factor when the Power Law model is used) can be obtained.
The beta and gamma can be selected to obtain one or all of them according to actual needs.
Assume that the acceleration factor of the above physical variable V is tested at point t n+1.
The above method may be continued to test the target variable F (V1, T2, T n+2) at T n+2 under the third condition (V1, T2).
The time value T m+1 for equal to F (V1, T2, T n+2) was extrapolated using a model, as shown in FIG. 4.
The acceleration coefficient of the physical variable T is calculated as avt= (T m+1-tm)/(tn+2-tn+1) =exp ((Ea/k) (1/T1-1/T2)), thereby obtaining the activation energy Ea.
By the scheme of the embodiment, the acceleration coefficient and the acceleration factor value can be tested according to single-batch samples, and fluctuation caused by batch difference is avoided. In addition, reliability degradation models and acceleration factor values can be obtained during testing. In addition, the acceleration coefficient and the acceleration factor value of a plurality of physical variables can be obtained by sequentially changing the physical variables.
Embodiment III:
Based on the same inventive concept, the embodiment of the application also provides an acceleration coefficient determining device. Referring to fig. 5, fig. 5 shows an acceleration coefficient determining apparatus 100 corresponding to the acceleration coefficient determining method shown in the first embodiment. It should be appreciated that the specific functions of the apparatus 100 may be found in the above description, and detailed descriptions are omitted here as appropriate to avoid repetition. The device 100 includes at least one software functional module that can be stored in memory in the form of software or firmware or cured in the operating system of the device 100. Specifically:
referring to fig. 5, the acceleration coefficient determining apparatus 100 includes: a model building module 101 and a processing module 102. Wherein:
The model building module 101 is configured to obtain a plurality of test values of a target variable and time of each test value for a preset sample under a first condition, and build a prediction model of the target variable and test time of the preset sample under the first condition according to each test value and time of each test value; the first condition includes a plurality of physical variables, and each of the physical variables has a set value; the target variable changes with test time and with a change in the value of any one of the physical variables in the first condition.
The processing module 102 is configured to obtain the preset sample, and perform a test under a second condition, where the target variable is a time when the target variable reaches a first target test value and a second target test value; the second condition is a condition obtained by changing the value of a first physical variable to be tested in the first condition, and the first physical variable to be tested is any physical variable in the first condition; predicting the time when the target variable reaches the first target test value and the second target test value under the first condition by using the prediction model; and determining the acceleration coefficient of the first physical variable to be tested according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing.
In a possible implementation manner of the embodiment of the present application, the processing module 102 is specifically configured to obtain, according to the predicted time of the first target test value and the second target test value under the first condition, and the time of the first target test value and the second target test value under the second condition obtained by testing, a value of an acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed to the second condition; determining the value of the acceleration factor of the first physical variable to be tested according to a preset acceleration coefficient model of the first physical variable to be tested according to the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition, the value of the first physical variable to be tested under the second condition and the value of the first physical variable to be tested under the first condition; substituting the value of the acceleration factor into the acceleration coefficient model to obtain the acceleration coefficient of the first physical variable to be tested.
In one possible example of the above possible implementation manner, the second target test value is a plurality of second target test values; the processing module 102 is specifically configured to obtain an acceleration coefficient corresponding to each second target test value under the second condition according to the predicted time of the first target test value and each second target test value under the first condition, and the time of the first target test value and each second target test value under the second condition; and determining the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition according to the acceleration coefficient corresponding to each second target test value.
In the above possible examples, determining an average value of acceleration coefficients corresponding to each of the second target test values; the average value is the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition.
In the foregoing possible implementation manner, the processing module 102 is specifically configured to determine an average value of acceleration coefficients corresponding to each of the second target test values; the average value is the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition.
In one possible example of the above possible implementation manner, the second target test value is a plurality of second target test values; the processing module 102 is specifically configured to obtain an acceleration coefficient of the value of the first physical variable to be tested corresponding to each second target test value under the second condition according to the predicted time of the first target test value and each second target test value under the first condition and the time of the first target test value and each second target test value under the second condition; according to the acceleration coefficient corresponding to each second target test value under the second condition, the value of the first physical variable to be tested under the second condition and the value of the first physical variable to be tested under the first condition, determining the value of the acceleration factor corresponding to each second target test value according to a preset acceleration coefficient model of the first physical variable to be tested; and determining the value of the acceleration factor of the first physical variable to be tested according to the value of the acceleration factor corresponding to each second target test value.
In the embodiment of the present application, the processing module 102 is further configured to obtain the preset sample, and perform, under a third condition, a test period when the target variable reaches a third target test value and a fourth target test value; predicting the time when the target variable reaches the third target test value and the fourth target test value under the first condition by using the prediction model; and determining the acceleration coefficient of the second physical variable to be tested according to the time of the third target test value and the fourth target test value under the first condition obtained by prediction and the time of the third target test value and the fourth target test value under the third condition obtained by testing. Wherein:
The third condition is a condition obtained by changing a value of a second physical variable to be tested in the first condition, and the second physical variable to be tested is any physical variable except the first physical variable to be tested in the first condition.
In the embodiment of the present application, the model building module 101 is specifically configured to perform fitting on each coordinate point determined by the test value and the time of each test value in a coordinate system taking the test value and the test time as coordinate axes, so as to obtain a fitting function of the test value and the time of each test value; the fitting function is a predictive model of the target variable and the test time of the preset sample under the first condition.
It should be understood that, for simplicity of description, the descriptions in the first embodiment are omitted in this embodiment.
Embodiment four:
The present embodiment provides an electronic device, which may be seen in fig. 6, comprising a processor 601, a memory 602 and a communication bus 603. Wherein:
The communication bus 603 is used to enable connected communication between the processor 601 and the memory 602.
The processor 601 is configured to execute one or more programs stored in the memory 602 to implement the acceleration factor determining method in the first/second embodiment described above.
It will be appreciated that the configuration shown in fig. 6 is merely illustrative, and that the electronic device may also include more or fewer components than those shown in fig. 6, or have a different configuration than that shown in fig. 6, and is not limiting in embodiments of the present application.
The present embodiment also provides a readable storage medium, such as a floppy disk, an optical disk, a hard disk, a flash memory, a usb disk, an SD (Secure Digital Memory Card, secure digital Card) Card, an MMC (Multimedia Card) Card, or the like, in which one or more programs implementing the above steps are stored, and the one or more programs may be executed by one or more processors to implement the acceleration coefficient determining method in the above first/second embodiments. And will not be described in detail herein.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
Further, the units described as separate units may or may not be physically separate, and units displayed as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
Furthermore, functional modules in various embodiments of the present application may be integrated together to form a single portion, or each module may exist alone, or two or more modules may be integrated to form a single portion.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
Herein, a plurality refers to two or more.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and variations will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims (9)

1. A method for determining an acceleration factor, comprising:
Acquiring a plurality of test values of a target variable and time of each test value under a first condition aiming at a preset sample; the first condition includes a plurality of physical variables, and each of the physical variables has a set value; the target variable changes with test time and with a change in the value of any one of the physical variables in the first condition;
establishing a prediction model of the target variable and the test time of the preset sample under the first condition according to each test value and the time of each test value;
Acquiring the preset sample, and performing test under a second condition, wherein the target variable reaches a first target test value and a second target test value; the second condition is a condition obtained by changing the value of a first physical variable to be tested in the first condition, and the first physical variable to be tested is any physical variable in the first condition;
Predicting the time when the target variable reaches the first target test value and the second target test value under the first condition by using the prediction model;
Determining an acceleration coefficient of the first physical variable to be tested according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing;
Determining an acceleration coefficient of the physical variable to be tested according to the predicted time of the first target test value and the second target test value under the first condition and the time of the first target test value and the second target test value under the second condition, including:
Obtaining a value of an acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition according to the time of the first target test value and the second target test value under the first condition which are obtained through prediction and the time of the first target test value and the second target test value under the second condition which are obtained through testing;
Determining the value of the acceleration factor of the first physical variable to be tested according to a preset acceleration coefficient model of the first physical variable to be tested according to the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition, the value of the first physical variable to be tested under the second condition and the value of the first physical variable to be tested under the first condition;
Substituting the value of the acceleration factor into the acceleration coefficient model to obtain the acceleration coefficient of the first physical variable to be tested.
2. The acceleration factor determining method of claim 1, wherein the second target test value is a plurality of;
The obtaining the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing, includes:
Obtaining acceleration coefficients corresponding to the second target test values under the second condition according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing;
And determining the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition according to the acceleration coefficient corresponding to each second target test value.
3. The acceleration factor determining method of claim 2, wherein determining the value of the acceleration factor corresponding to the first physical variable to be tested when the first condition changes to the second condition based on the acceleration factor corresponding to each of the second target test values, comprises:
determining an average value of acceleration coefficients corresponding to the second target test values; the average value is the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition.
4. The acceleration factor determining method of claim 1, wherein the second target test value is a plurality of;
The obtaining the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing, includes:
obtaining an acceleration coefficient of the value of the first physical variable to be tested according to the time of the first target test value and the second target test value under the first condition obtained by prediction and the time of the first target test value and the second target test value under the second condition obtained by testing;
Correspondingly, according to the value of the acceleration factor corresponding to the first physical variable to be tested when the first condition is changed into the second condition, the value of the first physical variable to be tested under the second condition and the value of the first physical variable to be tested under the first condition, determining the value of the acceleration factor of the first physical variable to be tested according to a preset acceleration factor model of the first physical variable to be tested, including:
according to the acceleration coefficient corresponding to each second target test value under the second condition, the value of the first physical variable to be tested under the second condition and the value of the first physical variable to be tested under the first condition, determining the value of the acceleration factor corresponding to each second target test value according to a preset acceleration coefficient model of the first physical variable to be tested;
And determining the value of the acceleration factor of the first physical variable to be tested according to the value of the acceleration factor corresponding to each second target test value.
5. The acceleration factor determining method of any one of claims 1-4, further comprising:
Acquiring the preset sample, and performing test under a third condition, wherein the time when the target variable reaches a third target test value and a fourth target test value; the third condition is a condition obtained by changing a value of a second physical variable to be tested in the first condition, and the second physical variable to be tested is any physical variable except the first physical variable to be tested in the first condition;
Predicting the time when the target variable reaches the third target test value and the fourth target test value under the first condition by using the prediction model;
And determining the acceleration coefficient of the second physical variable to be tested according to the time of the third target test value and the fourth target test value under the first condition obtained by prediction and the time of the third target test value and the fourth target test value under the third condition obtained by testing.
6. The acceleration factor determining method of any one of claims 1-4, wherein the building a predictive model of the target variable and test time of the preset sample under the first condition based on each of the test values and the time of each of the test values, comprises:
fitting each coordinate point determined by the test value and the time of each test value in a coordinate system taking the test value and the test time as coordinate axes to obtain a fitting function of the test value and the time of each test value; the fitting function is a predictive model of the target variable and the test time of the preset sample under the first condition.
7. An acceleration factor determining apparatus, comprising: the model building module and the processing module;
The model building module is used for obtaining a plurality of test values of a target variable and time of each test value of a preset sample under a first condition, and building a prediction model of the target variable and test time of the preset sample under the first condition according to each test value and time of each test value; the first condition includes a plurality of physical variables, and each of the physical variables has a set value; the target variable changes with test time and with a change in the value of any one of the physical variables in the first condition;
The processing module is used for acquiring the preset sample, and the time when the target variable reaches a first target test value and a second target test value during the test under the second condition; the second condition is a condition obtained by changing the value of a first physical variable to be tested in the first condition, and the first physical variable to be tested is any physical variable in the first condition; predicting the time when the target variable reaches the first target test value and the second target test value under the first condition by using the prediction model; obtaining a value of an acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition according to the time of the first target test value and the second target test value under the first condition which are obtained through prediction and the time of the first target test value and the second target test value under the second condition which are obtained through testing; determining the value of the acceleration factor of the first physical variable to be tested according to a preset acceleration coefficient model of the first physical variable to be tested according to the value of the acceleration coefficient corresponding to the first physical variable to be tested when the first condition is changed into the second condition, the value of the first physical variable to be tested under the second condition and the value of the first physical variable to be tested under the first condition; substituting the value of the acceleration factor into the acceleration coefficient model to obtain the acceleration coefficient of the first physical variable to be tested.
8. An electronic device, comprising: a communication module, a processor, and a memory;
The communication module is used for being in communication connection with the image shooting device so as to acquire the image acquired by the image shooting device and processing the image by the processor;
the processor is configured to execute one or more programs stored in a memory to implement the acceleration factor determining method of any of claims 1 to 6.
9. A readable storage medium storing one or more programs executable by one or more processors to implement the acceleration factor determining method of any of claims 1-6.
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2004146030A (en) * 2002-08-28 2004-05-20 Matsushita Electric Ind Co Ltd Accelerated test method for ferroelectric memory apparatus
KR20100027540A (en) * 2008-09-02 2010-03-11 한국철도기술연구원 System for the reliability demonstration of railway train control equipment, and its method
CN101923124A (en) * 2009-06-17 2010-12-22 上海华虹Nec电子有限公司 Method for determining acceleration factors in EM testing structure
CN109857974A (en) * 2018-11-23 2019-06-07 广电计量检测（北京）有限公司 Lifetime estimation method and device
CN110399658A (en) * 2019-07-09 2019-11-01 湖北文理学院 Accelerated factor value calculating method, device, equipment and the storage medium of battery
CN111351637A (en) * 2020-03-20 2020-06-30 广东省计量科学研究院（华南国家计量测试中心） Method for testing and evaluating service life of organic electroluminescent device
CN111832151A (en) * 2020-05-27 2020-10-27 北京航空航天大学云南创新研究院 Exponential time function-based Wiener accelerated degradation model construction method and system

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2004146030A (en) * 2002-08-28 2004-05-20 Matsushita Electric Ind Co Ltd Accelerated test method for ferroelectric memory apparatus
KR20100027540A (en) * 2008-09-02 2010-03-11 한국철도기술연구원 System for the reliability demonstration of railway train control equipment, and its method
CN101923124A (en) * 2009-06-17 2010-12-22 上海华虹Nec电子有限公司 Method for determining acceleration factors in EM testing structure
CN109857974A (en) * 2018-11-23 2019-06-07 广电计量检测（北京）有限公司 Lifetime estimation method and device
CN110399658A (en) * 2019-07-09 2019-11-01 湖北文理学院 Accelerated factor value calculating method, device, equipment and the storage medium of battery
CN111351637A (en) * 2020-03-20 2020-06-30 广东省计量科学研究院（华南国家计量测试中心） Method for testing and evaluating service life of organic electroluminescent device
CN111832151A (en) * 2020-05-27 2020-10-27 北京航空航天大学云南创新研究院 Exponential time function-based Wiener accelerated degradation model construction method and system

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
esearch on an Acceleration Factor Estimation Method for Accelerated Life Testing of High Precision Quartz Flexible Accelerometer;Guangze Pan 等;2018 9th International Conference on Information Technology in Medicine and Education (ITME);20181227;943-947 *
基于应力分析的机载电子设备可靠性加速增长试验技术研究;张蕊 等;环境技术;20120430;第30卷(第04期);40-45 *
基于随机参数逆高斯过程的加速退化建模方法;王浩伟 等;北京航空航天大学学报;20160930;第42卷(第09期);1843-1850 *

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