CN110889077A - Kendall correlation coefficient-based consistency inspection method for degraded data of accelerated storage and natural storage - Google Patents

Kendall correlation coefficient-based consistency inspection method for degraded data of accelerated storage and natural storage Download PDF

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CN110889077A
CN110889077A CN201811049762.5A CN201811049762A CN110889077A CN 110889077 A CN110889077 A CN 110889077A CN 201811049762 A CN201811049762 A CN 201811049762A CN 110889077 A CN110889077 A CN 110889077A
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CN110889077B (en
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孙权
冯静
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Hunan Gingko Reliability Technology Research Institute Co Ltd
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Abstract

The invention provides a Kendall correlation coefficient-based consistency test method for degraded data of accelerated storage and natural storage. The method is to perform regression fitting on the data from accelerated storage tests to obtain a test time series required to be experienced at a level of degradation such as natural storage data. And judging the correlation between the two groups of sequences by calculating Kendall correlation coefficients of each acceleration stress level and the corresponding test time interval sequence under natural storage, thereby deducing whether the failure mechanism under the acceleration storage and the natural storage is consistent. The consistency test method verifies the implementation scheme of the accelerated test and the validity of test data thereof so as to ensure the validity of product life prediction and verification.

Description

Kendall correlation coefficient-based consistency inspection method for degraded data of accelerated storage and natural storage
One, the technical field
The invention relates to a method for testing consistency of degradation data of a product under different test stress levels, in particular to a method for testing consistency of degradation data of accelerated storage and natural storage based on Kendall correlation coefficients, belongs to the field of reliability modeling technology and life prediction analysis, and is used for verifying the implementation scheme of an accelerated test and the effectiveness of test data of the accelerated test so as to ensure the effectiveness of product life prediction and verification.
Second, background Art
For long-term storage products, their effective storage life is one of the important design and use criteria. However, the state of the long-storage product changes very slowly under normal storage stress, and in order to obtain the storage failure rule of the product as soon as possible and predict the storage life, the storage failure of the product is accelerated by adopting a stress increasing mode. For some long-storage products, failure life data are difficult to observe even under accelerated stress, and the storage life of the product under normal stress can be predicted only by monitoring the degradation failure rule of some key performance parameters of the product. To ensure the credibility of this statistical inference, it must be demonstrated that the products have the same failure mechanism when stored under normal stress and accelerated stress, i.e. increasing the stress level only increases the failure rate without changing the failure mechanism. The method is an important premise for carrying out accelerated storage degradation test design and also solves the key problem and the basic problem of predicting the storage life of long-storage products. At present, the research on the consistency test method of the failure mechanism of the accelerated test in domestic and foreign documents is mainly divided into three categories: the first type is consistency test of failure mechanism of burst failure products, such as consistency of normal distribution variance; the second type is a degraded failure product with a clear failure mechanism, and a parameter method is generally adopted to test whether the degraded tracks under two stresses belong to the same family and have random processes with different parameters; the third category is a degenerate failure product with an undefined failure mechanism, and is generally judged qualitatively by expert experience, and the conclusion has certain subjectivity and is difficult to popularize and apply. On one hand, the difficulty of determining a product degradation failure mechanism is correspondingly increased due to the improvement of the process complexity of modern long-storage products, and on the other hand, the types and the quantity of collected product detection data are relatively sufficient due to the improvement of the product detection level. Therefore, the non-parametric inspection method based on data driving can effectively improve the level of test data consistency inspection. The Kendall correlation coefficient test is a nonparametric test method for binary overall correlation. The consistency test of the accelerated storage and natural storage degradation data is carried out based on Kendall correlation coefficients, and the implementation scheme of an accelerated test and the validity of the test degradation data can be verified.
Third, the invention
Object (a)
The invention aims to carry out consistency check on accelerated storage degradation data and natural storage degradation data, and the consistency check can check the effectiveness of the accelerated storage degradation data: on one hand, the degradation mechanism of the product is ensured to be consistent in the test process, and the effectiveness of the accelerated test is verified; on the other hand, the reliability and the precision of product life prediction and verification are improved.
(II) technical scheme
The invention discloses a consistency inspection method for degraded data of accelerated storage and natural storage based on Kendall correlation coefficients, which is a method for inspecting the effectiveness of accelerated storage data by a data-driven nonparametric inspection method.
In the invention, considering that the failure mechanism under accelerated storage and natural storage is consistent, test time interval sequences corresponding to the same degradation increment sequence are respectively calculated under two stresses, and the two groups of time interval sequences have cooperative correlation. That is, if a certain degradation increment interval is elapsed for a long time in a natural storage environment, the elapsed time of the degradation increment interval is also relatively long in an accelerated storage environment. The method comprises the following steps:
step 1, collecting basic information of a natural storage degradation test and an accelerated storage degradation test, and respectively collecting natural storage degradation data and accelerated storage degradation data, wherein the collection mode of the natural storage degradation data is usually a special natural storage test or product field detection, and the accelerated storage degradation data is collected in degradation data of different levels under the same stress (usually temperature, humidity, salt spray and the like) in the accelerated storage test.
And 2, performing regression analysis on the degradation data to obtain a regression equation representing the relationship between the degradation quantity and the storage time, wherein the regression equation under the natural storage environment can be obtained by naturally storing the degradation data, and the regression equations under different stress levels can be obtained by using the degradation data under different accelerated stress levels.
And 3, obtaining the time required by the product to reach the equal-interval degradation amount under each stress level by using regression equations under different acceleration stress levels, wherein the equal-interval degradation amount is divided on the premise that the initial degradation amount (namely, the degradation amount is 0) of the product and the failure degradation amount (namely, the failure threshold value) of the product are determined.
And 4, calculating time intervals corresponding to the equal degradation increments of the products at all stress levels, namely, utilizing the time length required by the adjacent equal degradation increments at the same level of stress obtained in the step 3 to make a difference.
And 5, calculating Kendall cooperative correlation coefficients under natural storage and each stress level by using the equal degeneration increment time interval sequence.
And 6, judging the degradation failure process under the natural storage and the corresponding stress level by utilizing Kendall cooperative correlation coefficients, wherein the judgment rule generally comprises the following three types: the method has no correlation, certain positive correlation and certain negative correlation, wherein the more the absolute value of the Kendall collaborative correlation coefficient is close to 1, the stronger the characterization correlation is.
In the selection of the accelerated test, the accelerated storage test conducted on the product was a constant stress accelerated degradation test. The constant stress accelerated degradation test is the most common accelerated test type which is most conveniently carried out in engineering, and if the actually carried accelerated test is step stress or sequential stress, a certain statistical method is adopted to equivalently convert the data into the data under the constant stress accelerated test.
Wherein, the "basic information" in step 1 means that the method of the present invention is performed on the basis of the following basic information, and the basic information includes:
(1) and (4) selecting a test object. The products of the invention are long-storage degradation failure type products, long-time continuous working degradation failure type products and discontinuous working degradation failure type products.
(2) And (4) selecting the type of the accelerated test. The accelerated storage test carried out on the product is a constant stress accelerated degradation test. The constant stress accelerated degradation test is the most common accelerated test type which is most conveniently carried out in engineering, and if the actually carried accelerated test is step stress or sequential stress, a certain statistical method is adopted to equivalently convert the data into the data under the constant stress accelerated test.
(3) Accelerating the setting of the amount of the sample to be tested in the storage test. The common engineering practice is to put one or more samples under each accelerated storage stress level for performance testing and to obtain performance monitoring data of each sample.
(4) And (5) acquiring test data. And at least one performance monitoring data of the same type of product is obtained under the natural storage environment. Under the natural storage environment, if performance monitoring data of a plurality of products of the same type are obtained at the same time, firstly, interpolation is carried out on the performance data by adopting an interpolation method according to the monitoring time point of each product, and the testing time of each product is aligned; then obtaining the sample mean value of each test moment; and then the sequence of the sample mean value changing along with the storage time is regarded as single sample performance change data, so that the multi-sample data under the natural storage environment is converted into single sample degradation sequence data. And at least obtaining performance monitoring data of the same type of product under the accelerated storage environment. Under the accelerated storage environment, if performance monitoring data of a plurality of products of the same type are obtained at the same time, firstly, interpolation is carried out on the performance data by adopting an interpolation method according to the monitoring time point of each product, and the testing time of each product is aligned; then obtaining the sample mean value of each test moment; and then the sequence of the sample mean value changing along with the storage time is regarded as single sample performance change data, so that the multi-sample data under the accelerated storage stress is converted into single sample degradation sequence data.
(III) the invention has the advantages that:
(1) according to the invention, on the basis of considering the principles of sufficiency, necessity, conformity with engineering habits, testability, designability and verifiability, a method for checking the consistency of the natural degradation data is designed according to the data characteristics of the accelerated degradation test of the product, so that the validity of the accelerated degradation test of the product and the validity of the accelerated degradation test data are verified;
(2) the method can be used for verifying the consistency of failure mechanisms of the product in an accelerated storage test and a natural storage test so as to ensure the reliability and the precision of the product life prediction analysis.
Description of the drawings
FIG. 1 is a flow chart of a data consistency checking method of the present invention;
fig. 2 is a schematic diagram of a sequence of equal degeneration delta time intervals. Wherein, the abscissa represents the test time, and the ordinate represents the performance degradation test result;
Figure DEST_PATH_IMAGE002
to a failure threshold value;
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The representation is based on natural storage (stress level of
Figure DEST_PATH_IMAGE006
) Regression equations of the data;
Figure DEST_PATH_IMAGE008
presentation is based on accelerated storage (stress level of
Figure DEST_PATH_IMAGE010
) Regression equations of the data;
Figure DEST_PATH_IMAGE012
a division point representing equally spaced degradation increments;
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expressed in natural storage stress
Figure 157979DEST_PATH_IMAGE006
Lower degradation increment from
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Is degraded to
Figure DEST_PATH_IMAGE018
The length of time elapsed;
Figure DEST_PATH_IMAGE020
indicating storage stress at accelerated speed
Figure 449414DEST_PATH_IMAGE010
Lower degradation increment from
Figure 903005DEST_PATH_IMAGE016
Is degraded to
Figure 300488DEST_PATH_IMAGE018
The length of time elapsed;
fifth, detailed description of the invention
The invention discloses a consistency inspection method for degraded data of accelerated storage and natural storage based on Kendall correlation coefficients, which is a method for inspecting the effectiveness of accelerated storage data by a data-driven nonparametric inspection method. The method is based on the basic information of natural storage test and accelerated storage test of long-storage products. The basic information comprises a test object, an accelerated test type, a reference sample amount setting and test data acquisition. The content of each aspect of information is specifically as follows:
(1) the test objects are long-storage degradation failure type products, long-time continuous working degradation failure type products and discontinuous working degradation failure type products;
(2) the accelerated storage test carried out on the product is a constant stress accelerated degradation test. The test type is the most common accelerated test type which is most conveniently developed in engineering, and if the product which needs to verify the consistency does not meet the test type, namely the actually-performed accelerated test is step stress or sequence stress, a certain statistical method is adopted to equivalently convert the data into the data under the constant stress accelerated test;
(3) description of the amount of the reference sample for accelerated storage test. The common engineering practice is to put in a few products at each stress level, i.e. one or more samples at each accelerated storage stress level for performance testing, and to obtain performance monitoring data of each sample.
(4) For a description of data collection in the experiment. And at least obtaining performance monitoring data of the same type of product under the natural storage environment and the accelerated storage environment. Under the natural storage environment, if performance monitoring data of a plurality of products of the same type are obtained at the same time, firstly, interpolation is carried out on the performance data by adopting an interpolation method according to the monitoring time point of each product, and the testing time of each product is aligned; then obtaining the sample mean value of each test moment; and then the sequence of the sample mean value changing along with the storage time is regarded as single sample performance change data, so that the multi-sample data under the natural storage environment is converted into single sample degradation sequence data. Similar processing is also performed for multi-sample data under accelerated storage testing.
As shown in FIG. 1, the consistency test method of degraded data of accelerated storage and natural storage based on Kendall correlation coefficient comprises the following steps:
step 1, collecting basic information of a natural storage degradation test and an accelerated storage degradation test, and respectively collecting natural storage degradation data and accelerated storage degradation data, wherein the collection mode of the natural storage degradation data is usually a special natural storage test or product field detection, and the accelerated storage degradation data is collected in degradation data of different levels under the same stress (usually temperature, humidity, salt spray and the like) in the accelerated storage test.
Step 2, carrying out regression analysis according to test data under natural storage to obtain a regression equation representing the relationship between the degradation amount and the storage time under the natural storage environment
Figure 29410DEST_PATH_IMAGE004
(ii) a According to stress level
Figure 921273DEST_PATH_IMAGE010
Performing regression analysis on the test data to obtain the characterization stress level
Figure 481568DEST_PATH_IMAGE010
Regression equation of lower degradation quantity and storage time relation
Figure DEST_PATH_IMAGE022
Figure DEST_PATH_IMAGE024
Number of stress levels for constant stress accelerated degradation testing.
Step 3, assuming that the degradation amount of the new product is 0, according to the failure threshold value
Figure DEST_PATH_IMAGE026
Will be
Figure DEST_PATH_IMAGE028
Is divided into
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A sequence of equally spaced degenerate increments, order
Figure DEST_PATH_IMAGE032
Specifying
Figure DEST_PATH_IMAGE034
Figure DEST_PATH_IMAGE036
,…,
Figure DEST_PATH_IMAGE038
,…
Figure DEST_PATH_IMAGE040
,. Order to
Figure DEST_PATH_IMAGE042
. Solving the regression equation to obtain the stress level
Figure 168727DEST_PATH_IMAGE010
Reach a given level of degradation
Figure 447261DEST_PATH_IMAGE016
Required elapsed test time
Figure DEST_PATH_IMAGE044
I.e. by
Figure DEST_PATH_IMAGE046
Wherein
Figure DEST_PATH_IMAGE048
Indicating the natural storage stress level.
And 4, calculating time intervals corresponding to the equal-spacing degradation increments under different stress levels. Order to
Figure DEST_PATH_IMAGE050
Wherein, in the step (A),
Figure 457330DEST_PATH_IMAGE048
representing a natural storage environment.
Step 5, storing the data of the equal-spacing degeneration increment time interval sequence under the stress level in a natural way and cooperating with the correlation coefficient
Figure DEST_PATH_IMAGE052
I.e. by
Figure DEST_PATH_IMAGE054
Figure DEST_PATH_IMAGE056
,
Wherein sgn is a sign function,
Figure DEST_PATH_IMAGE058
.
sgn reflects the synergy between pairs of numbers. sgn =1, the pair of expression numbers is a pair of cooperation numbers, and the number of the pair of cooperation numbers is recorded as
Figure DEST_PATH_IMAGE060
(ii) a sgn = -1, the number pair is represented as uncoordinated number pair, and the number of uncoordinated number pair is recorded as
Figure DEST_PATH_IMAGE062
. Stress level
Figure 246032DEST_PATH_IMAGE010
Data co-correlation coefficient of
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Can also be expressed as
Figure DEST_PATH_IMAGE066
.
And 6, judging the rule. The judgment result includes the following three types: has no correlation, a certain positive correlation and a certain negative correlation, wherein
Figure 63947DEST_PATH_IMAGE064
The closer the absolute value of (d) is to 1, the stronger the correlation is characterized. The specific judgment rule is as follows: given a
Figure DEST_PATH_IMAGE068
Calculating a standard normal distribution
Figure DEST_PATH_IMAGE070
Quantile
Figure DEST_PATH_IMAGE072
If, if
Figure DEST_PATH_IMAGE074
Then the natural storage can be preliminarily determined
Figure 267262DEST_PATH_IMAGE006
And stress level
Figure 750196DEST_PATH_IMAGE010
The lower degradation failure process has no correlation; on the contrary, if
Figure DEST_PATH_IMAGE076
Then the natural storage can be preliminarily determined
Figure 98132DEST_PATH_IMAGE006
And stress level
Figure 759052DEST_PATH_IMAGE010
The underlying degenerative failure processes have some correlation (positive or negative).
The following embodiments are given:
in this case, an XX type propellant is taken as an example to show the application of the method for checking the consistency of the degradation data of the accelerated storage and the natural storage.
The basic information situation of the present case is as follows:
(1) test subjects:
subject type XX propellant is a typical long-storage degenerative failure product.
(2) The type of accelerated test:
the test is an accelerated degradation test under constant high temperature stress.
(3) Sample amount of the samples:
one part of the propellant which is newly delivered from a factory is arranged under the stress of five temperatures.
(4) Data acquisition:
the test times were measured for the remaining contents of different active ingredients in the propellant powder.
And (4) performing the consistency check work of the degradation data of the XX type propellant powder accelerated storage and the natural storage on the basis of the basic information of the XX type propellant powder.
The case implementation flow is the above five steps. For the case, basic information of the XX type propellant is obtained in the first step, and the acquired data are shown in table 1; after the second step, the third step and the fourth step, time intervals corresponding to the equal-spacing degradation increments under different stress levels are calculated and are shown in table 2; after statistics in the fifth step, Kendall correlation coefficients are obtained and are shown in Table 3; therefore, through the calculation of the step six, the consistency test result of the accelerated storage test data and the natural storage test data is obtained:
Figure DEST_PATH_IMAGE078
when the temperature of the water is higher than the set temperature,
Figure DEST_PATH_IMAGE080
,
Figure DEST_PATH_IMAGE082
Figure DEST_PATH_IMAGE084
therefore, it is considered that the storage failure mechanism under 5 accelerated stresses is consistent with the failure mechanism in natural storage and is not changed. The accelerated storage test data and the natural storage test data pass consistency check.
TABLE 1 test times at different temperature stress levels
Figure DEST_PATH_IMAGE086
TABLE 2 time intervals corresponding to equidistant degradation increments
Figure DEST_PATH_IMAGE088
TABLE 3 data collaborative correlation coefficient table
Temperature/. degree.C
Figure DEST_PATH_IMAGE090
Figure DEST_PATH_IMAGE092
Figure DEST_PATH_IMAGE094
50℃ 39 6 0.733
60℃ 44 1 0.956
70℃ 44 1 0.956
80℃ 44 1 0.956
90℃ 44 1 0.956
The symbols in table 3 illustrate:
Figure DEST_PATH_IMAGE095
the number of the cooperative number pairs;
Figure DEST_PATH_IMAGE096
the number of uncoordinated pairs;
Figure 488543DEST_PATH_IMAGE052
the data is co-correlated with the coefficient.

Claims (7)

1. A consistency test method of degradation data of accelerated storage and natural storage based on Kendall correlation coefficient is based on the premise of basic information of accelerated degradation test of products, the basic information comprises a test object, an accelerated test type, a sample amount setting for participating in the test and a test data acquisition method,
the method comprises the following specific steps:
step 1, collecting basic information of a natural storage degradation test and an accelerated storage degradation test, and respectively collecting natural storage degradation data and accelerated storage degradation data, wherein the collection mode of the natural storage degradation data is usually a special natural storage test or product field detection, and the accelerated storage degradation data is collected in degradation data of different levels under the same stress (usually temperature, humidity, salt spray and the like) in the accelerated storage test;
step 2, regression analysis is carried out on the degradation data to obtain a regression equation representing the relation between the degradation quantity and the storage time, wherein the regression equation under the natural storage environment can be obtained by naturally storing the degradation data, and the regression equations under different stress levels can be obtained by using the degradation data under different accelerated stress levels;
step 3, obtaining the time length required by the product to reach the equal-interval degradation amount under each stress level by using regression equations under different acceleration stress levels, wherein the equal-interval degradation amount is divided on the premise that the initial degradation amount (namely, the degradation amount is 0) of the product and the failure degradation amount (namely, the failure threshold value) of the product are determined;
step 4, calculating time intervals corresponding to the equal degradation increments of the products under each stress level, namely, utilizing the time length required by the adjacent equal degradation increments under the same level of stress obtained in the step 3 to make a difference;
step 5, calculating Kendall cooperative correlation coefficients of natural storage and each stress level by using the equal degeneration increment time interval sequence;
and 6, judging the degradation failure process under the natural storage and the corresponding stress level by utilizing Kendall cooperative correlation coefficients, wherein the judgment rule generally comprises the following three types: the method has no correlation, certain positive correlation and certain negative correlation, wherein the more the absolute value of the Kendall collaborative correlation coefficient is close to 1, the stronger the characterization correlation is.
2. The method for checking consistency of degraded data in accelerated storage and natural storage based on Kendall correlation coefficients as claimed in claim 1, wherein the "basic information" comprises:
(1) the selection of the subject to be tested is carried out,
the products in the invention are long-storage degradation failure type products, long-time continuous working degradation failure type products and discontinuous working degradation failure type products;
(2) the selection of the type of the accelerated test,
the accelerated storage test carried out on the product is a constant stress accelerated degradation test,
the constant stress accelerated degradation test is the most common accelerated test type which is most conveniently carried out in engineering, and if the actually carried accelerated test is step stress or sequential stress, a certain statistical method is adopted to equivalently convert the data into the data under the constant stress accelerated test;
(3) the setting of the amount of the sample to be tested in the storage test is accelerated,
the common method in engineering is that one or more samples are respectively put into each accelerated storage stress level to carry out performance test, and performance monitoring data of each sample is obtained;
(4) the principle of collecting the test data is that,
at least one performance monitoring data of the same type product is obtained under the natural storage environment,
under the natural storage environment, if performance monitoring data of a plurality of products of the same type are obtained at the same time, firstly, interpolation is carried out on the performance data by adopting an interpolation method according to the monitoring time point of each product, and the testing time of each product is aligned; then obtaining the sample mean value of each test moment; then the sequence of the sample mean value changing along with the storage time is regarded as the single sample performance change data, thus converting the multi-sample data under the natural storage environment into the single sample degradation sequence data,
at least one performance monitoring data of the same type product is obtained under the accelerated storage environment,
under the accelerated storage environment, if performance monitoring data of a plurality of products of the same type are obtained at the same time, firstly, interpolation is carried out on the performance data by adopting an interpolation method according to the monitoring time point of each product, and the testing time of each product is aligned; then obtaining the sample mean value of each test moment; and then the sequence of the sample mean value changing along with the storage time is regarded as single sample performance change data, so that the multi-sample data under the accelerated storage stress is converted into single sample degradation sequence data.
3. The Kendall correlation coefficient-based consistency test method for the degraded data of accelerated storage and natural storage according to claim 2, wherein the step of obtaining a regression equation which characterizes the degradation amount and the storage time relation is as follows: performing regression analysis according to test data under natural storage to obtain regression equation representing relationship between degradation amount and storage time under natural storage environment
Figure 588350DEST_PATH_IMAGE001
(ii) a According to stress level
Figure 466438DEST_PATH_IMAGE002
Performing regression analysis on the test data to obtain the characterization stress level
Figure 303944DEST_PATH_IMAGE002
Regression equation of lower degradation quantity and storage time relation
Figure 870055DEST_PATH_IMAGE003
Figure 358674DEST_PATH_IMAGE004
Number of stress levels for constant stress accelerated degradation testing.
4. The Kendall correlation coefficient-based consistency verification method for degradation data of accelerated storage and natural storage according to claim 3, wherein the step of obtaining the time length required for the product to reach the degradation amount at equal intervals at each stress level comprises the following steps: assuming that the degradation amount of the new product is 0, the new product is determined according to the failure threshold
Figure 656931DEST_PATH_IMAGE005
Will be
Figure 729536DEST_PATH_IMAGE006
Is divided into
Figure 37020DEST_PATH_IMAGE007
A sequence of equally spaced degenerate increments, order
Figure 114567DEST_PATH_IMAGE008
Specifying
Figure 849305DEST_PATH_IMAGE009
Figure 458140DEST_PATH_IMAGE010
,…,
Figure 320048DEST_PATH_IMAGE011
,…,
Order to
Figure 268413DEST_PATH_IMAGE012
Solving the regression equation to obtain the stress level
Figure 423319DEST_PATH_IMAGE002
Reach a given level of degradation
Figure 457135DEST_PATH_IMAGE013
Required elapsed test time
Figure 860084DEST_PATH_IMAGE014
I.e. by
Figure 662955DEST_PATH_IMAGE015
Wherein
Figure 614861DEST_PATH_IMAGE016
Indicating the natural storage stress level.
5. The Kendall correlation coefficient-based consistency verification method for degraded data in accelerated storage and natural storage according to claim 4, wherein the time interval corresponding to equal degradation increment refers to: calculating the time intervals corresponding to the equally spaced degradation increments at different stress levels,
order to
Figure 135973DEST_PATH_IMAGE017
Wherein, in the step (A),
Figure 572639DEST_PATH_IMAGE016
representing a natural storage environment.
6. The Kendall correlation coefficient-based method for testing consistency of degraded data in accelerated storage and natural storage according to claim 5, wherein the Kendall co-correlation coefficient is: natural storage and cooperative correlation coefficient of data of equal-spacing degradation increment time interval under stress level
Figure 495596DEST_PATH_IMAGE018
I.e. by
Figure 490840DEST_PATH_IMAGE019
Figure 561564DEST_PATH_IMAGE020
Wherein the content of the first and second substances,
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in order to be a function of the sign,
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.
Figure 997728DEST_PATH_IMAGE021
the cooperative relationship between the pairs of numbers is reflected,
Figure 978584DEST_PATH_IMAGE021
=1, the number of the representing number pairs is the number of cooperation pairs
Figure 773365DEST_PATH_IMAGE023
Figure 654602DEST_PATH_IMAGE021
= -1, the number of the representing number pair is uncoordinated number pair, and the number of the uncoordinated number pair is recorded as
Figure 71544DEST_PATH_IMAGE024
Stress level
Figure 680642DEST_PATH_IMAGE002
Data co-correlation coefficient of
Figure 262802DEST_PATH_IMAGE025
Can also be expressed as
Figure 749278DEST_PATH_IMAGE026
7. The Kendall correlation coefficient-based consistency verification method for degraded data in accelerated storage and natural storage according to claim 5, wherein the "decision rule" refers to: given a
Figure 522806DEST_PATH_IMAGE027
Calculating a standard normal distribution
Figure 727522DEST_PATH_IMAGE028
Quantile
Figure 113373DEST_PATH_IMAGE029
If, if
Figure 142771DEST_PATH_IMAGE030
Then the natural storage can be preliminarily determined
Figure 339398DEST_PATH_IMAGE031
And stress levelThe lower degradation failure process has no correlation; on the contrary, if
Figure 17689DEST_PATH_IMAGE032
Then the natural storage can be preliminarily determined
Figure 478758DEST_PATH_IMAGE031
And stress level
Figure 599947DEST_PATH_IMAGE002
The underlying degenerative failure processes have some correlation (positive or negative).
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