CN105138770B - Space product Reliablility simulation appraisal procedure based on indirect characteristic quantities - Google Patents
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Abstract
The invention discloses the space product Reliablility simulation appraisal procedure based on indirect characteristic quantities, by the functional relation for establishing test measurement parameter and indirect characteristic quantities, and using emulation sampling calculation method, obtain the probability distribution of indirect characteristic quantities, and then generalized stress strength model is used, assess the reliability of product；The calculating of calculating, single failure pattern probability of happening in indirect characteristic quantities, have in the reliability assessment of multiple faults Model Products, calculated three times using sampling emulation mode, this method is compared with analytic method, it is more applicable for the reliability assessment of large complicated space product, and accuracy height is calculated, it is easy to computer software programming realization.
Description
Technical field
The invention belongs to the reliability assessment technical field of space product, and in particular to one kind is based on indirect reliability characteristic
The space product Reliablility simulation appraisal procedure of amount.
Background technology
For reliability assessment, space product belongs to Small scale product.How the reliability of Small scale product is carried out
Assessment, domestic and international many scholars have carried out substantial amounts of research, have also achieved certain achievement.But space flight industry at present is big
Portioned product is still using the reliability of the reliability estimation method assessment product based on statistical analysis, this method validation reliability
The test sample amount that index needs is big, can not Feedback Design.Reliability estimation method based on mechanism model can be good at solving
Certainly this problem.But applied very in space flight industry reliability assessment based on the reliability estimation method of mechanism model
Limited, one of reason is exactly that this kind of reliability estimation method needs to carry out product deep analysis, extracts suitable reliability
Characteristic quantity, and by the means such as testing, the characteristic quantities of product are measured and statistical analysis, so as to fulfill product
Reliability assessment.
So-called space product characteristic quantities, be exactly in product testing or in-flight it is detectable, being capable of concentrated expression
The variable of product reliability level.For space product, extracting suitable characteristic quantities becomes based on mechanism mould
One of difficult point of reliability estimation method of type.
For many space flight complex products, test measurable parameter and be restricted sometimes, can only be by experiment after the completion of
Decomposition to product just will appreciate which kind of problem product occurs, and the continuous parameter during experiment can not directly obtain, at this moment
Occur：Test measurable parameter can not concentrated expression product reliability level；Being capable of concentrated expression product reliability level
Parameter again can not pass through experiment directly measurement.For example, for liquid-propellant rocket engine, the structure and working environment of its parts
All sufficiently complex, test method and testing equipment are all extremely limited.At present, for the crucial parts such as thrust chamber, turbine pump, still
It can only be tested by the test run of engine complete machine to examine its function and performance.In engine complete machine commissioning process, it can measure
Engine parameter is also extremely limited, mainly includes：Pressure, rotating speed, flow, temperature, vibration etc..These parameters can be in certain journey
On degree reflect engine function and performance characteristic, but measure any one index, all can not concentrated expression product it is reliable
Property it is horizontal.That is, can not directly measure the characteristic quantities of these parts by research technique, this is commented to reliability
Estimate and bring difficulty.
The content of the invention
In view of this, the present invention provides a kind of space product Reliablility simulation assessment based on indirect characteristic quantities
Method, to realize the application based on the reliability estimation method of mechanism model in complicated space product.
The space product Reliablility simulation appraisal procedure based on indirect characteristic quantities of the present invention, including following step
Suddenly：
Step 1, pass through all fault modes of analysis product, failure cause and failure mechanism, definite and each event
The corresponding one kind of barrier pattern can be by testing characteristic quantities measured directly or cannot be by testing measured directly
Connect characteristic quantities；
Step 2, combing can survey parameter by testing experiment measured directly, according to the operation principle of product and related reason
By the function of relation between parameter and indirect characteristic quantities can be surveyed by establishing characterization experiment；
Step 3, for each indirect characteristic quantities, collect each experiment in its corresponding function and can survey parameter and exist
Data message in each sampling test, probability distribution and the estimation of distributed constant sample of parameter can be surveyed by calculating each experiment
Value；
Step 4, for indirect characteristic quantities：The probability distribution and distributed constant of parameter can be surveyed according to each experiment
Sample estimate, using n generation random number of random digit generation method, and is updated to corresponding letter by the random number generated every time
In number, after the result of calculation of indirect characteristic quantities is calculated, using Statistical Inference, indirect reliability characteristic is calculated
The probability distribution of amount and distributed constant sample estimate；N values are more than 10000；
For characteristic quantities：Directly according to test measurement as a result, using Statistical Inference, reliability characteristic is calculated
The probability distribution of amount and the sample estimate of distributed constant；
Step 5, with generalized stress-strength theory, using the emulation methods of sampling, determine that each fault mode is corresponding
Reliability, concretely comprises the following steps：
S51, according to the corresponding characteristic quantities of each fault mode or the corresponding probability of indirect characteristic quantities
Distribution pattern and distributed constant sample estimate, random number is generated using random digit generation method, passes through method for parameter estimation, meter
Calculate characteristic quantities or the corresponding distributed constant totality estimate of indirect characteristic quantities；Further according to characteristic quantities or
The indirect corresponding probability distribution of characteristic quantities, distributed constant totality estimate and reliability is special when not breaking down
The threshold value of sign amount or indirect characteristic quantities, is calculated the corresponding reliability of fault mode, completes single sample；
S52, for each fault mode, carry out n times sampling by the method for S51, obtain N number of reliability of fault mode；N
Value is more than 10000；
S53, the sequence by the progress of N number of reliability from small to large, obtain the probability-distribution function of reliability；Finally obtain event
The reliability of barrier pattern；
Step 6, according to the logical relation between fault mode, establish reliability block diagram model；Based on the reliability block diagram
The reliability for each fault mode that model and step 5 obtain, obtains the reliability assessment result of product.
Preferably, in the step 5 and step 6, after step 5 obtains the reliability sequence of each fault mode, every
A reliability is randomly selected in one reliability sequence；According to the method for step 6, obtaining this time, to extract corresponding product reliable
Degree；After M times is extracted, the reliability of M product is obtained, and by order arrangement from small to large, obtain the probability of reliability
Distribution function；Finally obtain reliability of the product under given confidence level；M values are more than 10000.
Preferably, in the step 3, determine that each experiment can survey the probability distribution of parameter and distributed constant sample is estimated
The method of value includes Maximum-likelihood estimation, least square method and graphic evaluation.
Preferably, when experiment can be surveyed between parameter and indirect characteristic quantities and can not directly expressed by functional relation
When, the relation tested and can surveyed between parameter and indirect characteristic quantities is established using finite element simulation method, and the relation is claimed
For functional relation.
The present invention has the advantages that：
(1) present invention is by establishing the functional relation of test measurement parameter and indirect characteristic quantities, and uses emulation
Sampling calculation method, obtains the probability distribution of indirect characteristic quantities, and then uses generalized stress-strength model, assessment production
The reliability of product；The calculating of calculating, single failure pattern probability of happening in indirect characteristic quantities, have multiple faults pattern
In the reliability assessment of product, calculated three times using sampling emulation mode, this method is more applicable in compared with analytic method
In the reliability assessment of large complicated space product, and accuracy height is calculated, be easy to computer software programming realization.
(2) sampling emulation mode of the invention is compared with analytic method, under certain required precision, the sampling of this method
Number and calculation amount are unrelated with the complexity of reliability block diagram model, are relatively suitable for the reliability assessment of complication system；To being
The distribution pattern of each unit, the test data type etc. of uniting are unrestricted, it is not necessary to the conversion of distribution pattern and logical relation is carried out,
Enhance the accuracy of assessment result；Random number is generated for the actual distribution type of each product in Reliability Evaluation Model, is kept away
Influence of the approximate conversion process of analytic method calculating process to reliability assessment result is exempted from, has made assessment accuracy higher.
Brief description of the drawings
Fig. 1 is the implementing procedure figure of the present invention；
Fig. 2 is the embodiment figure of the embodiment of the present invention；
Fig. 3 is the reliability model of the embodiment of the present invention；
Fig. 4 is the stress-strength model emulated computation method of the embodiment of the present invention.
Embodiment
The present invention will now be described in detail with reference to the accompanying drawings and examples.
The present invention proposes a kind of space product Reliablility simulation appraisal procedure based on indirect characteristic quantities, is used for
The reliability of complicated space product is assessed.Current space product is to carry out space product reliability assessment, first
The reliability requirement of analysis product is needed, in terms of specifically including following four：
(1) task scope of assessment object and the border of product are defined, so that it is determined that the scope and depth of analysis；
(2) clear and definite product is undergone in practical work process varying environment condition, task function performance requirement and hold
Continuous time etc.；
(3) be specifically used for judge product whether the parameter of failure, i.e. failure criterion；
(4) dependability parameter of clear and definite product and index etc., the index quantified as reliability assessment.
The reliability assessment flow of the present invention is as shown in Figure 1, appraisal procedure includes the following steps：
Step 1, determine characteristic quantities
The chife failure models and failure cause of analysis product, analyze failure mechanism, the rule that research fault mode occurs.
For the chife failure models for carrying out reliability Work, analyze and determine that the corresponding characteristic quantities of fault mode (can pass through examination
Test direct measurement) and indirect characteristic quantities (cannot be by testing directly measurement).Every kind of fault mode and reliability characteristic
Amount or indirectly characteristic quantities one-to-one corresponding, to be assessed using the reliability estimation method based on mechanism model.
Identical product can use different reliability characteristics there may be various faults pattern for each fault mode
Amount or indirect characteristic quantities.Wherein, a part of fault mode may correspond to characteristic quantities, another part fault mode
Indirect characteristic quantities may be corresponded to.
Step 2, establish indirect characteristic quantities and test the functional relation that can be surveyed between parameter：
Combing can be by testing parameter measured directly, and for the operation principle and correlation theory of product, foundation indirectly may be used
The functional relation (hereinafter referred to as " function ") between parameter can be surveyed by property characteristic quantity and experiment.
If the relation directly between measurement parameter and indirect characteristic quantities is complex, can not be carried out by functional relation
Expression, can also establish the relation between direct measurement parameter and indirect characteristic quantities by finite element simulation method, herein will
It is known as " function " in the lump, that is, refers to express all forms of relation between direct measurement parameter and indirect characteristic quantities.
The statistical analysis of step 3, test data：
For each indirect characteristic quantities, parameter can be surveyed in each sample by collecting each experiment in its corresponding function
Data message in this experiment, the fault mode and failure mechanism of combination product, analyze the measurement for determining that each experiment can survey parameter
Data mode (for example, with time continually changing parameter, need to measurement parameter be at any time by the way of continuous measurement or discontinuous measurement
Between change), and collect the correlation test data of each sample, united using Maximum-likelihood estimation, least square method, graphic evaluation etc.
Estimating method is counted, determines that each experiment can survey the probability distribution and distributed constant sample estimate of parameter.
Step 4, the probability distribution of characteristic quantities and indirect characteristic quantities calculate：
The distribution pattern of the probability-distribution function of parameter can be surveyed according to experiment, using random digit generation method (common distribution
The generation method of random number is as shown in table 1) generation random number, and the random number generated every time is updated in corresponding function,
The result of calculation of indirect characteristic quantities is calculated.
The random-number generating method of 1 typical probability of table distribution
Note：U is the random number of (0,1), and other parameters are the distributed constant of corresponding distribution
Above sample calculation process is repeated, after n sampling, just obtains the calculating knot of n indirect characteristic quantities
Fruit.Using Statistical Inference, the probability distribution and distributed constant sample estimate of indirect characteristic quantities are calculated.For
Ensure computational accuracy, n is typically larger than 10000.
If product has multiple characteristic quantities indirectly, it is necessary to calculate each indirect reliability respectively using above method
The probability distribution of characteristic quantity.
, can be directly against examination due to can directly measure the size of characteristic quantity by testing for characteristic quantities
Test amount is as a result, using Statistical Inference, the probability distribution and distributed constant sample for calculating characteristic quantities are estimated
Value.
Step 5, reliability interval estimation
For a unknown quantity, in measurement or calculating, in addition to obtaining approximation, it is also necessary to take error into account, that is, need
Want the levels of precision of approximation.For the target component of reliability assessment, in addition to obtaining its point estimation, one should be also estimated
Scope, so that understanding this scope includes, the credibility of parameter true value.Such scope is usually provided in the form of section,
Provide the credibility that this section includes reliability objectives parameter at the same time.The estimation of this form is known as interval estimation.
With generalized stress-strength theory, using the emulation methods of sampling, determine that each fault mode is corresponding reliable
Degree, concretely comprises the following steps：
S51, according to the corresponding characteristic quantities of each fault mode or the corresponding probability of indirect characteristic quantities
Distribution pattern and distributed constant sample estimate, random number is generated using random digit generation method, passes through method for parameter estimation, meter
Calculate characteristic quantities or the corresponding distributed constant totality estimate of indirect characteristic quantities；Further according to characteristic quantities or
The indirect corresponding probability distribution of characteristic quantities, distributed constant totality estimate and reliability is special when not breaking down
Sign amount or indirect characteristic quantities and its trouble-proof threshold value (required value), it is corresponding to be calculated fault mode
Reliability, completes single sample；
S52, for each fault mode, carry out n times sampling by the method for S51, obtain N number of reliability；To ensure to calculate
Precision, N are more than 10000；
S53, the sequence by the progress of N number of reliability from small to large, obtain the probability-distribution function of reliability；Finally obtain event
The reliability of barrier pattern；
Step 6, according to the logical relation between fault mode, establish reliability block diagram model；Based on the reliability block diagram
The reliability for the fault mode that model and step 5 obtain, obtains the reliability assessment result of product.
Wherein,, can at each after step 5 obtains the reliability sequence of each fault mode in step 5 and step 6
A reliability is randomly selected in sorting by degree；According to the method for step 6, obtain this time and extract corresponding production reliability；Through
Cross M times after extracting, obtain the reliability of M product, and by order arrangement from small to large, obtain the probability distribution letter of reliability
Number；Finally obtain reliability of the product under given confidence level；To ensure computational accuracy, usual M need to be more than 10000.
The sampling emulation mode has the following advantages compared with analytic method：
1) under certain required precision, the frequency in sampling and calculation amount of this method and the complicated journey of reliability block diagram model
Spend unrelated, the reliability assessment relatively suitable for complication system；
2) distribution pattern to system each unit, test data type etc. are unrestricted, it is not necessary to carry out distribution pattern with
The conversion of logical relation, enhances the accuracy of assessment result；
3) the actual distribution type generation random number of each product in Reliability Evaluation Model is directed to, avoids analytic method meter
Influence of the approximate conversion process of calculation process to reliability assessment result, makes assessment accuracy higher.
Embodiment
This example by taking certain product as an example, using the present invention method carry out reliability assessment, embodiment as shown in Fig. 2,
Comprise the following steps that：
Step 1, determine indirect characteristic quantities
Analyzed by weak link recognition methods, product includes 2 main fault modes, is denoted as failure respectively altogether
Mode A and fault mode B.
Failure mechanism is analyzed, determines that the corresponding characteristic quantities of two fault modes are respectively u and v.Wherein, v can pass through
Correlation test directly measures, but since product structure reason, u can not directly be measured by testing, therefore, this feature amount is indirect
Characteristic quantities.
Step 2, establish indirect characteristic quantities and test the functional relation that can be surveyed between parameter
By combing the measurable parameter of product testing, the letter of indirect characteristic quantities u and each test measurement parameter are established
Number relations be：
Since the product includes two typical fault patterns, wherein, u is indirect characteristic quantities, and v is reliability characteristic
Amount, according to the logical relation of two fault modes, it is as shown in Figure 3 to establish reliability model.Two fault modes are series relationship, i.e., its
In any one fault mode occur, then product failure.
The statistical analysis of step 3, test data
Collect the data message of each test measurement parameter in function (1).The general of each parameter is obtained using statistical analysis technique
Rate distribution pattern and distributed constant, as shown in table 2.
The statistical analysis of 2 test data of table
Step 4, the probability distribution of indirect characteristic quantities calculate
Test data statistic analysis result in table 2, generates random number, brings into function (1), calculates indirect every time
The result of calculation that characteristic quantities u samples every time.It is 10000 times to set simulation times, and to simulation result, carries out statistical
Analysis, is fitted the probability distribution and distributed constant sample estimate of u.
Due to characteristic quantities v can by testing directly measurement acquisition, using the statistical analysis technique of step 3,
Test data is handled, is fitted the probability distribution and distributed constant sample estimate of v.
The statistic analysis result of two characteristic quantities is as shown in table 3.
3 characteristic quantities of table/indirect characteristic quantities statistic analysis result
Step 5, reliability interval estimation
According to the statistic analysis result of u and v, with reference to its performance requirement, with stress-strength model, sampled using emulation
Method, assesses the reliability level of product.Wherein, the required value of u is：[2100,2400], v required values are：[21,∞).
It is illustrated below with the calculating process of v, implementation is as shown in Figure 4.It is unilateral minimum stress limit-intensity in the figure
Model, i.e. v are more than the probability of required value L.The probability is the probability that fault mode B does not occur, and is denoted as R.
By sample X1,X2,…Xn, calculate sample averageWith sample variance S2, obtain distributed constant sample estimate；
Since i=1, for two mutually independent random number γ in any given (0,1) sectioni1, γi2, according to side
The method of estimation of difference calculates distributed constant totality estimateObtainingAfterwards, distribution is calculated according to the method for estimation of average
Parameter totality estimate μi；
For given limit stress L, corresponding reliability RiByIt is calculated；
I=i+1 is repeated the above process, and 1≤i≤N, N are simulation times；
It is ascending to sample value to be ranked up R1≤R2≤…RN, obtain the probability-distribution function of reliability；
Given confidence level γ, in the probability-distribution function of reliability, seeks the corresponding R of integer part of (1- γ) Ni, i.e.,
To give the reliability under confidence level γ.
It is as shown in table 4 with probability that fault mode B does not occur that fault mode A is obtained by calculation.
4 each fault mode of table not probability of happening result of calculation
Step 6, Reliability Assessment
Since product has two kinds of main fault modes, to assess the reliability of product, it is necessary to calculating knot according to table 4
Fruit, with reference to the reliability model of Fig. 3, reliability assessment result is obtained using sampling emulation mode：Point estimate is 0.994287,
Reliability under 0.7 confidence level is 0.992597.
In conclusion the foregoing is merely a prefered embodiment of the invention, it is not intended to limit the scope of the present invention.
Within the spirit and principles of the invention, any modification, equivalent replacement, improvement and so on, should be included in the present invention's
Within protection domain.
Claims (4)
1. a kind of space product Reliablility simulation appraisal procedure based on indirect characteristic quantities, it is characterised in that including such as
Lower step：
Step 1, pass through all fault modes of analysis product, failure cause and failure mechanism, definite and each failure mould
The corresponding one kind of formula can be by testing characteristic quantities measured directly or measured directly cannot indirectly may be used by testing
By property characteristic quantity；
Step 2, combing can survey parameter by testing experiment measured directly, according to the operation principle and correlation theory of product,
The function of relation between parameter and indirect characteristic quantities can be surveyed by establishing characterization experiment；
Step 3, for each indirect characteristic quantities, parameter can be surveyed each by collecting each experiment in its corresponding function
Data message in sampling test, the probability distribution and distributed constant sample estimate of parameter can be surveyed by calculating each experiment；
Step 4, for indirect characteristic quantities：The probability distribution and distributed constant sample of parameter can be surveyed according to each experiment
Estimate, using n generation random number of random digit generation method, and is updated to corresponding function by the random number generated every time
In, after the result of calculation of indirect characteristic quantities is calculated, using Statistical Inference, calculate indirect characteristic quantities
Probability distribution and distributed constant sample estimate；N values are more than 10000；
For characteristic quantities：Characteristic quantities are directly calculated as a result, using Statistical Inference according to test measurement
The sample estimate of probability distribution and distributed constant；
Step 5, with generalized stress-strength theory, using the emulation methods of sampling, determine that each fault mode is corresponding reliable
Degree, concretely comprises the following steps：
S51, according to the corresponding characteristic quantities of each fault mode or the corresponding probability distribution of indirect characteristic quantities
Type and distributed constant sample estimate, generate random number, by method for parameter estimation, calculating can using random digit generation method
By property characteristic quantity or the corresponding distributed constant totality estimate of indirect characteristic quantities；Further according to characteristic quantities or indirectly
The corresponding probability distribution of characteristic quantities, distributed constant totality estimate and characteristic quantities when not breaking down
Or the threshold value of indirect characteristic quantities, the corresponding reliability of fault mode is calculated, completes single sample；
S52, for each fault mode, carry out n times sampling by the method for S51, obtain N number of reliability of fault mode；N values
More than 10000；
S53, the sequence by the progress of N number of reliability from small to large, obtain the probability-distribution function of reliability；Finally obtain failure mould
The reliability of formula；
Step 6, according to the logical relation between fault mode, establish reliability block diagram model；Based on the reliability block diagram model
And the reliability of each fault mode that step 5 obtains, obtain the reliability assessment result of product.
2. a kind of space product Reliablility simulation appraisal procedure based on indirect characteristic quantities as claimed in claim 1,
It is characterized in that, in the step 5 and step 6, after step 5 obtains the reliability sequence of each fault mode, at each
A reliability is randomly selected in reliability sequence；According to the method for step 6, it is reliable that corresponding product is randomly selected in acquisition every time
Degree；After M times is extracted, the reliability of M product is obtained, and by order arrangement from small to large, obtain the probability of reliability
Distribution function；Finally obtain reliability of the product under given confidence level；M values are more than 10000.
3. a kind of space product Reliablility simulation appraisal procedure based on indirect characteristic quantities as claimed in claim 1,
It is characterized in that, in the step 3, determine that each experiment can survey the probability distribution and distributed constant sample estimate of parameter
Method includes Maximum-likelihood estimation, least square method and graphic evaluation.
4. a kind of space product Reliablility simulation appraisal procedure based on indirect characteristic quantities as claimed in claim 1,
It is characterized in that, when experiment can be surveyed and can not directly expressed by functional relation between parameter and indirect characteristic quantities,
The relation tested and can surveyed between parameter and indirect characteristic quantities is established using finite element simulation method, and the relation is known as letter
Number relation.
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| CN106169124B (en) * | 2016-07-21 | 2020-11-27 | 中国科学院数学与***科学研究院 | System-level product reliability comprehensive evaluation confidence inference method |
| CN108536972B (en) * | 2018-04-13 | 2022-02-01 | 中国人民解放军陆军装甲兵学院 | Complex system reliability simulation method and system based on self-adaptive agent |
| CN108491250B (en) * | 2018-04-13 | 2021-09-17 | 中国人民解放军陆军装甲兵学院 | Self-adaptive intelligent agent communication method and system for reliability simulation of complex system |
| CN109033556A (en) * | 2018-07-04 | 2018-12-18 | 哈尔滨工业大学 | The relay class single machine Estimation of The Storage Reliability method of combined process and reliability block diagram |
| CN109376407B (en) * | 2018-09-30 | 2023-06-20 | 中国人民解放军92942部队 | Reliability evaluation method for carrier-based aircraft catapult |
| CN110929442A (en) * | 2019-11-29 | 2020-03-27 | 湖北航天技术研究院总体设计所 | Reliability evaluation method and system for liquid distribution and spraying pipe based on fault physics |
| CN111581737B (en) * | 2020-04-03 | 2022-12-16 | 中国电子科技集团公司第三十八研究所 | Finite element simulation-based structural member reliability assessment method and system |
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| CN104182603A (en) * | 2013-05-24 | 2014-12-03 | 上海空间电源研究所 | Reliability evaluation method for long-service-life and high-reliability electronic product |
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