CN105868543B - The storage life test accelerated factor appraisal procedure being distributed based on the inverse Gauss service life - Google Patents
The storage life test accelerated factor appraisal procedure being distributed based on the inverse Gauss service life Download PDFInfo
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Abstract
The invention discloses a kind of storage life test accelerated factor appraisal procedures being distributed based on the inverse Gauss service life, including the electronic system product storage life model that step inverse Gauss service life of the foundation based on competing failure is distributed；Calculate separately the average storage service life of the electronic system product being distributed based on the inverse Gauss service life under active usage conditions and the average storage service life under the conditions of accelerated stress；According to the average storage service life under the actual service conditions and the average storage service life under the conditions of accelerated stress, the accelerated factor of electronic system product is calculated.Therefore, the storage life test accelerated factor appraisal procedure being distributed based on the inverse Gauss service life can realize the accurately assessment to electronic system product storage life accelerated factor.
Description
Technical field
The present invention relates to reliability tests and assessment technology field, particularly relate to a kind of storage being distributed based on the inverse Gauss service life
Deposit life test accelerated factor appraisal procedure.
Background technology
Currently, storage life is an important war skill index as defined in equipment contract (or charter).Carrying out complete machine
Storage-life accelerated test verify in evaluation process, since machine product is it includes multiple components and material, and different components
Rate of ageing it is different to the susceptibility of accelerated stress.When increasing stress with accelerated storage failure procedure, some of which is weak
The accelerated factor of link product is just more larger than other weak link products, thus will produce and accelerates inconsistent problem.If appointing
Select the accelerated factor of a weak element as complete machine accelerated factor, result is difficult to reflect actual conditions.
Invention content
In view of this, it is an object of the invention to propose a kind of storage life test acceleration being distributed based on the inverse Gauss service life
Factor appraisal procedure can realize the assessment accurately to electronic system product storage life accelerated factor.
Based on the above-mentioned purpose storage life test accelerated factor assessment provided by the invention being distributed based on the inverse Gauss service life
Method, including step：
The electronic system product storage life model that inverse Gauss service life of the foundation based on competing failure is distributed；
According to life model, electronic system product that the inverse Gauss service life be distributed putting down under active usage conditions is calculated separately
Equal storage life and the average storage service life under the conditions of accelerated stress；
According to the average storage service life under the actual service conditions and the average storage service life under the conditions of accelerated stress, meter
Calculation obtains the accelerated factor of electronic system product.
In some embodiments, the electronic system product storage being distributed based on the inverse Gauss service life for establishing competing failure
Life model, including：
Based on competing failure model, the Reliability Model of electronic system product is established；
According to the Reliability Model of electronic system product, it is distributed using the inverse Gauss service life and carries out storage life modeling.
In some embodiments, described to be based on competing failure model, establish the step of the Reliability Model of electronic system product
Suddenly include：
Competitive fault model is defined as：If machine product has n kind Failure Factors, and each Failure Factors is all independent
Act on the machine product, and all correspond to certain out-of-service time, any of which Failure Factors can all cause complete machine
Product failure when that earliest caused Failure Factors occur, will cause machine product to fail in all Failure Factors,
I.e. the machine product out-of-service time is：
T=min { T1,T2,...,Tn,
Wherein, T is machine product out-of-service time, TiFor the out-of-service time of arbitrary Failure Factors, n is appointing more than or equal to 1
Meaning natural number；
Assuming that Fi(t) be arbitrary Failure Factors out-of-service time accumulative failure distribution function, then machine product is accumulative
Failure distribution function is：
Wherein, Fi(t) be similar and different distribution, but it must be independent that above formula, which requires this n distribution, when them it
Between not only immediately, i.e., in the case that a kind of Failure Factors can cause another Failure Factors, then must take into consideration each Failure Factors it
Between influence each other, need to be modified above formula：
When any Failure Factors work, corresponding reliability is：
Wherein, λi(t) it is the crash rate for corresponding to i-th of Failure Factors, when n factor works simultaneously, machine product
Reliability Model will be：
In some embodiments, the Reliability Model according to machine product is distributed using the inverse Gauss service life and is store
The step of depositing modeling for life include：
For electronic or electromechanical complicated machine product, it is generally recognized that its building block, device service life be distributed as inverse Gauss
Distribution：
In formula：μ is known as location parameter；ν becomes form parameter.
Therefore, it is the service life distribution of the electronic or electromechanical complicated machine product to enable dead wind area, if any composition portion
Part, device parameter be ui,vi, then any building block, device probability density function be：
It is the service life distribution of the electronic or electromechanical complicated machine product to enable dead wind area, if the ginseng of any Failure Factors
Number is ui,vi, then the probability density function of any Failure Factors be：
Overall to the service life for obeying dead wind area, the mean time between failures is：Ti=ui, therefore, the electronics
Or the storage life modeling formula of electromechanical complicated machine product is：
In some embodiments, the electronic system product being distributed based on the inverse Gauss service life that calculates is in actual service conditions
Under average storage service life and accelerated stress under the conditions of the average storage service life, including：
The average storage service life is electronic system product under active usage conditions：
If a certain component of machine product under a certain environment accelerated stress conditioning weak link i (i=1,2 ...,
N) corresponding accelerated factor is Ai, average life span of the electronic system product under accelerated stress level be：
Wherein, μAAverage life span under the conditions of accelerated stress of-complete machine；AequipmentThe practical accelerated factor of-complete machine；μ0—
Average life span under the conditions of complete machine normal stress；μi- corresponding to the average life span of weak link i under use condition；N-complete machine is thin
Weak link product number.
In some embodiments, under the conditions of according to the average storage service life under active usage conditions and accelerated stress
The average storage service life, the practical accelerated factor of computing device complete machine is：
According to the average life span under the accelerated stress, show that the accelerated factor of inverse Gauss model electronic system product is：
From the above it can be seen that the electronic system product provided by the invention that is distributed based on the inverse Gauss service life accelerate because
Sub- appraisal procedure, on the basis of machine product storage life models, according to product under natural storage state with acceleration mode
Under the equal principle of storage reliability, being directed to the service life obeys the electronic system product of dead wind area and gives storage life
Test the appraisal procedure of accelerated factor.
Description of the drawings
Fig. 1 is the stream for the storage life test accelerated factor appraisal procedure that the embodiment of the present invention was distributed based on the inverse Gauss service life
Journey schematic diagram；
Fig. 2 is the electronic system product storage longevity being distributed based on the inverse Gauss service life that the embodiment of the present invention establishes competing failure
Order the flow diagram of model.
Specific implementation mode
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with specific embodiment, and reference
Attached drawing, the present invention is described in more detail.
It should be noted that all statements for using " first " and " second " are for differentiation two in the embodiment of the present invention
The non-equal entity of a same names or non-equal parameter, it is seen that " first " " second " only for the convenience of statement, does not answer
It is interpreted as the restriction to the embodiment of the present invention, subsequent embodiment no longer illustrates this one by one.
As the embodiment of the present invention, as shown in fig.1, the storage being distributed based on the inverse Gauss service life for the embodiment of the present invention
The flow diagram of life test accelerated factor appraisal procedure.The storage life test being distributed based on the inverse Gauss service life is added
The method of fast factor assessment includes：
Step 101, the electronic system product storage life model of competing failure being distributed based on the inverse Gauss service life is established.Tool
Body implementation process is as follows, as shown in Figure 2：
Step 201：Based on competing failure model, the Reliability Model of electronic system product is established；
Competing failure is a kind of important failure mode of product.In reliability theory, product loses the function of defined
Referred to as fail.The object of product failure is caused due to its internal structure and its complexity of external working environment for large product
Reason, chemical reason often there are many, if any type reason, which occurs, leads to product failure, this product is referred to as Tests With Competing Causes of Failure under Exponential Distribution
(Competing Failure Modes).The reason of leading to product failure referred to as product failure mechanism (Failure
Mechanism).For example, in the life test of cable, the reason of leading to cable failure, has:Cable is breakdown, leakage current
Index is more than regulation critical point and artificial disconnection etc., and any of which reason is referred to as the failure mechanism of product.
Specifically, in some optional embodiments, above-mentioned steps can further comprise the steps：
Competitive fault model is defined as：If machine product has n kind Failure Factors, and each Failure Factors is all independent
Act on the machine product, and all correspond to certain out-of-service time, any of which Failure Factors can all cause complete machine
Product failure when that earliest caused Failure Factors occur, will cause machine product to fail in all Failure Factors,
I.e. the machine product out-of-service time is：
T=min { T1,T2,...,Tn(1),
Wherein, T is machine product out-of-service time, TiFor the out-of-service time of arbitrary Failure Factors, n is appointing more than or equal to 1
Meaning natural number；
Assuming that Fi(t) be arbitrary Failure Factors out-of-service time accumulative failure distribution function, then machine product is accumulative
Failure distribution function is：
Wherein, Fi(t) can be similar and different distribution, but above formula (2) require this n be distributed must be it is independent,
When not only immediately, i.e., in the case that a kind of Failure Factors can cause another Failure Factors, then must take into consideration each mistake between them
Influencing each other between effect factor, therefore, it is necessary to be modified to above formula (2)：
When any Failure Factors work, corresponding reliability is：
Wherein, λi(t) it is the crash rate for corresponding to i-th of Failure Factors, when n factor works simultaneously, machine product
Reliability Model will be：
Total crash rate of machine product by be corresponding moment t the sum of n independent crash rates, i.e.,：
λ (t)=λ1(t)+λ2(t)+...+λn(t)(5)
Formula (5) is known as to the addition criterion of Tests With Competing Causes of Failure under Exponential Distribution crash rate.
Step 202：According to the Reliability Model of machine product, it is distributed using the inverse Gauss service life and carries out storage life modeling.
For electronic or electromechanical complex device, generally it can be thought that the service life of its building block, device is distributed as inverse Gauss
Distribution：
In formula：μ is known as location parameter；ν becomes form parameter.
Therefore, it is the service life distribution of the electronic or electromechanical complicated machine product to enable dead wind area, if any composition portion
Part, device parameter be ui,vi, then any building block, device probability density function be：
Overall to the service life for obeying dead wind area, the mean time between failures is：Ti=ui, therefore, the electronics
Or the storage life modeling formula of electromechanical complicated machine product is：
Step 102, the electronic system product being distributed based on the inverse Gauss service life under active usage conditions flat is calculated separately
Equal storage life and the average storage service life under the conditions of accelerated stress.
As one embodiment, the electronic system product being distributed based on the inverse Gauss service life that calculates is in actual service conditions
Under average storage service life and accelerated stress under the conditions of the average storage service life, including：The a certain component of electronic system product is in reality
Average life span is under the use condition of border：
If weak link i (i=1,2 ..., n) corresponding acceleration of a certain component of complete machine under a certain action of environmental stresses
The factor is Ai.Average life span of the complete machine under accelerated stress level be：
Wherein, μAAverage life span under the conditions of accelerated stress of-complete machine；AequipmentThe practical accelerated factor of-complete machine；μ0—
Average life span under the conditions of complete machine normal stress；μi- corresponding to the average life span of weak link i under use condition；N-complete machine is thin
Weak link product number.
Step 103, according to the average storage service life under the actual service conditions and the average storage under the conditions of accelerated stress
The service life is deposited, the accelerated factor of electronic system product is calculated.
In embodiment, according to flat under the conditions of the average storage service life under active usage conditions and accelerated stress
Equal storage life can show that the accelerated factor of inverse Gauss model equipment is：
From above-described embodiment as can be seen that the equipment accelerated factor assessment provided by the invention being distributed based on the inverse Gauss service life
Method can make full use of the accelerated test information of primer, component and parts, and as a result confidence level is high；And consider
The accelerated factor of all parts is therefore more reasonable to the weights influence of complete machine accelerated factor；Finally, it is entire described based on
The equipment accelerated factor appraisal procedure that the inverse Gauss service life is distributed is compact, it is easy to accomplish.
Those of ordinary skills in the art should understand that：The discussion of any of the above embodiment is exemplary only, not
It is intended to imply that the scope of the present disclosure (including claim) is limited to these examples；Under the thinking of the present invention, above example
Or can also be combined between the technical characteristic in different embodiments, step can be realized with random order, and be existed such as
Many other variations of the different aspect of the upper present invention, for simplicity, they are not provided in details.
In addition, to simplify explanation and discussing, and in order not to obscure the invention, it can in the attached drawing provided
To show or can not show that the well known power ground with integrated circuit (IC) chip and other components is connect.Furthermore, it is possible to
Device is shown in block diagram form, to avoid obscuring the invention, and this has also contemplated following facts, i.e., about this
The details of the embodiment of a little block diagram arrangements is the platform that height depends on to implement the present invention (that is, these details should
It is completely within the scope of the understanding of those skilled in the art).Detail (for example, circuit) is being elaborated to describe the present invention's
In the case of exemplary embodiment, it will be apparent to those skilled in the art that can be in these no details
In the case of or implement the present invention in the case that these details change.Therefore, these descriptions should be considered as explanation
Property rather than it is restrictive.
Although having been incorporated with specific embodiments of the present invention, invention has been described, according to retouching for front
It states, many replacements of these embodiments, modifications and variations will be apparent for those of ordinary skills.Example
Such as, other memory architectures (for example, dynamic ram (DRAM)) can use discussed embodiment.
The embodiment of the present invention be intended to cover fall within the broad range of appended claims it is all it is such replace,
Modifications and variations.Therefore, all within the spirits and principles of the present invention, any omission, modification, equivalent replacement, the improvement made
Deng should all be included in the protection scope of the present invention.
Claims (4)
1. a kind of storage life test accelerated factor appraisal procedure being distributed based on the inverse Gauss service life, which is characterized in that including step
Suddenly：
The electronic system product storage life model that inverse Gauss service life of the foundation based on competing failure is distributed；
According to life model, the electronic system product being distributed based on the inverse Gauss service life under active usage conditions flat is calculated separately
Equal storage life and the average storage service life under the conditions of accelerated stress；
According to the average storage service life under the actual service conditions and the average storage service life under the conditions of accelerated stress, calculate
To the accelerated factor of electronic system product；
Wherein establishing the electronic system product storage life model that the inverse Gauss service life based on competing failure is distributed includes：Based on competing
Failure model is striven, the Reliability Model of electronic system product is established；According to the Reliability Model of electronic system product, using inverse height
The distribution of this service life carries out storage life modeling；The step of Reliability Model for establishing electronic system product includes：Competitive failure
Model is defined as：If machine product has a n kind Failure Factors, and each Failure Factors is all independent acts on the complete machine production
Product, and certain out-of-service time is all corresponded to, any of which Failure Factors can all cause machine product to fail, in all mistakes
In effect factor, when that earliest caused Failure Factors occur, machine product will be caused to fail, i.e. the machine product out-of-service time
For：
T=min { T1,T2,...,Tn,
Wherein, T is machine product out-of-service time, TiFor the out-of-service time of arbitrary Failure Factors, n is the arbitrary nature more than or equal to 1
Number；
Assuming that Fi(t) be arbitrary Failure Factors out-of-service time accumulative failure distribution function, then the accumulative failure of machine product point
Cloth function is：
Wherein, Fi(t) be similar and different distribution, but above formula require this n be distributed must be it is independent, when between them not
When independent, i.e., in the case that a kind of Failure Factors can cause another Failure Factors, then it must take into consideration between each Failure Factors
It influences each other, needs to be modified above formula：
When any Failure Factors work, corresponding reliability is：
Wherein, λi(t) be corresponding i-th of Failure Factors crash rate, when n factor while when working, machine product it is reliable
Spending model will be：
2. according to the method described in claim 1, it is characterized in that, the Reliability Model according to electronic system product, is adopted
Being distributed the step of carrying out storage life modeling with the inverse Gauss service life includes：
For electronic or electromechanical complicated machine product, it is generally recognized that its building block, device service life be distributed as dead wind area：
In formula：μ is known as location parameter；ν becomes form parameter；
Therefore, it is the service life distribution of the electronic or electromechanical complicated machine product to enable dead wind area, if any building block, device
The parameter of part is ui,vi, then any building block, device probability density function be：
Overall to the service life for obeying dead wind area, Mean period of storage is：Ti=ui, therefore, the electronics or machine
The average storage modeling for life formula for replying miscellaneous machine product by cable is：
Wherein, TequipmentThe average storage service life of-electronic system product.
3. according to the method described in claim 1, it is characterized in that, described calculate the complete electronic set being distributed based on the inverse Gauss service life
The average storage service life of product under active usage conditions and the average storage service life under the conditions of accelerated stress, including：
The average storage service life is electronic system product under active usage conditions：
If weak link i corresponding accelerated factor of a certain component of machine product under a certain environment accelerated stress conditioning is
Ai, average life span of the electronic system product under accelerated stress level be：
Wherein, μAAverage life span under the conditions of accelerated stress of-complete machine；AequipmentThe practical accelerated factor of-complete machine；μ0- complete machine
Average life span under the conditions of normal stress；μi- corresponding to the average life span of weak link i under use condition；N-complete machine weakness ring
Save product number.
4. according to the method described in claim 3, it is characterized in that, according to the average storage longevity under active usage conditions
Average storage service life under the conditions of life and accelerated stress, the practical accelerated factor of computing device complete machine are：
According to the average life span under the accelerated stress, show that the accelerated factor of inverse Gauss model electronic system product is：
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| CN106407555B (en) * | 2016-09-14 | 2019-04-26 | 中国人民解放军海军航空大学 | Acceleration degraded data analysis method based on accelerated factor principle of invariance |
| CN108333208B (en) * | 2018-01-22 | 2020-10-09 | 航天科工防御技术研究试验中心 | Whole machine grade product storage life accelerated test method |
| CN108399278B (en) * | 2018-01-24 | 2021-11-30 | 航天科工防御技术研究试验中心 | Electronic equipment multi-factor acceleration factor calculation method |
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| CN110263487A (en) * | 2019-07-02 | 2019-09-20 | 中国航空综合技术研究所 | A kind of engineering goods accelerate fatigue life test method |
| CN110414086B (en) * | 2019-07-10 | 2023-01-17 | 北京华安中泰检测技术有限公司 | Sensitivity-based comprehensive stress acceleration factor calculation method |
| CN111898236B (en) * | 2020-05-25 | 2024-01-09 | 中国航天标准化研究所 | Acceleration factor analysis method for accelerated storage test based on failure big data |
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