CN108763736A - A kind of space product performance based on gray theory and test integrated design parameter choosing method - Google Patents
A kind of space product performance based on gray theory and test integrated design parameter choosing method Download PDFInfo
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Abstract
The space product performance that the present invention relates to a kind of based on gray theory and test integrated design parameter choosing method, are suitable for space product design field.Its method and step is as follows：(1) design parameter and evaluation index are chosen, scheme collection and property set are respectively constituted；(2) it is scored design parameter according to evaluation index, constitutes objective making decision matrix；(3) ideal optimal vector is built, standardization processing is carried out to objective making decision matrix, calculates the grey incidence coefficient between specification objective making decision matrix element and Ideal Optimization Scheme vector；(4) it calculates grey relation coefficient and obtains gray relation grades with weight；(5) it is ranked up by gray relation grades size, intercepting principle according to parameter selects design parameter number.Beneficial effects of the present invention are：(1) it has been put forward for the first time quantitative space product performance and test integrated design parameter choosing method, the performance of product and efficiency can be made to be optimal；(2) selection of parameter is carried out according to the weight of relevance and evaluation index between design parameter and evaluation index, choosing method is more scientific and reasonable；(3) performance of product and efficiency can be made to be optimal；(4) in the case of Decision Makings with Weights Unknown, design parameter can also be chosen.
Description
Technical field
The invention belongs to space product design field, it can be used for instructing space product to carry out performance and test integrated design
When choose design parameter.
Background technology
In the case where solving to have the guidance of no problem thought, performance and functional parameter are usually paid much attention to and pay close attention to space product
Design and realization (abbreviation performance design), set the universal qualities characteristic such as the reliability of product, maintainability, testability, protection
Meter (referred to as test design) does not take much count of, and performance and test design phase separation during product development, this makes product exist
High failure rate during use, short life, the problems such as testing and diagnosing time is long, maintenance support is difficult, are than more prominent.Studies have shown that
The test, diagnosis and maintenance problem of product are just considered when product design, carry out performance is with test integrated Parallel Design
The important channel fundamentally to solve the above problems.
In recent years, domestic scholars are for performance and reliability, testability, reliability and maintanability, r&m protection (RMS) integration
Certain research has been carried out in design, and the document delivered includes mainly：《Electronic product performance analyzes skill with reliability integrated design
Art research》,《Testability is studied with performance integrated design method》,《Helicopter performance is ground with the comprehensive integrated designs of RMS
Study carefully》Deng.These literature research Integrated Algorithm, Integrated Model, integrated design environment, integrated design platform etc., but
Lacking research in terms of for how to choose performance and test design parameter, typically directly choosing, lacking foundation.Design parameter is out
Premise and the input of design are opened up, whether design parameter selection rationally directly affects product efficiency and benefit, research fund and period
Deng.So far, there is not yet the report of performance and the research of test integrated design parameter choosing method.
Invention content
The technical problem to be solved by the present invention is to be provided with test integrated design parameter scientifically and rationally to choose performance
Foundation proposes a kind of performance and test integrated design parameter choosing method.Using this method, design parameter itself is both considered
The objectivity of correlation degree between design object, it is also considered that decision-maker is according to its expertise and experience to design parameter
Subjective preferences.
In order to solve the above technical problems, proposed by the present invention a kind of for space product performance and test integrated design ginseng
Number choosing method, including objective making decision matrix structure, subjective preferences matrix structure, Ideal Optimization Scheme vector calculate, gray relative
Degree calculating and etc., the specific method is as follows：
A kind of space product performance based on gray theory and test integrated design parameter choosing method, including it is following several
A step：
Step 1：Calculating correlation；
(1) fighting efficiency, Support Effectiveness, Operational Suitability, life cycle cost etc. are chosen and is used as evaluation index, use tjTable
Show, weight wjIt indicates, j is index number, j=1 ..., m, by tjThe vector of composition is as property set, with T={ t1,t2,…,
tmIndicate, by wjThe vector of composition is as weight sets, with w={ w1,w2,…,wm' indicate；
(2) the relevance grey relation coefficient of performance and test integrated design parameter and evaluation index is setIt indicates,
I=1 ..., n, j=1 ..., m, byThe matrix of composition is known as grey incidence coefficient matrix, usesIt indicates；
(3) performance and test integrated design parameter and the gray relation grades of evaluation index are by Grey Incidence MatrixWith
Weight wjIt is calculated, usesIt indicates, value shows that more greatly the bigger design parameter and the evaluation index degree of association the heavier
It wants, if weight wjIt is known that being calculated using following formula：
Step 2：It is cut according to design parameter selection principle and selects design parameter；
It is ranked up according to the gray relation grades size of calculating, intercepting principle according to design parameter selects the ginseng to be designed
Number；
Step one grey correlation matrix as a preferred embodiment of the above solution,Solution the specific steps are：
(1) according to product design requirement and design object, the performance and test design parameter of product is combed, s is usediIt indicates, i
For number of parameters, i=1 ..., n, by siThe vector of composition is as scheme collection, with S={ s1,s2,…,snIndicate；
(2) fighting efficiency, Support Effectiveness, Operational Suitability, life cycle cost etc. are chosen and is used as evaluation index, use tjTable
Show, j is index number, j=1 ..., m, by tjThe vector of composition is as property set, with T={ t1,t2,…,tmIndicate；
(3) it is scored according to the incidence relation between design parameter and evaluation index, with non-negative interval numberIt indicates, WithIt indicates respectivelyMinimum value and maximum value, byThe square of composition
Battle array is known as objective making decision matrix, usesIt indicates；
(4) to objective making decision matrixStandardization processing is carried out, eliminates dimension and the order of magnitude to decision knot
The influence of fruit, the profitable type of matrix element and cost type, profit evaluation model refer to that element value is the bigger the better, and cost type refers to that attribute value is got over
Small better, the normalizing of profit evaluation model and cost type is respectively：
Objective making decision matrixThe specification objective making decision matrix obtained after standardization processing is usedIt indicates,
(5) rememberM is claimed to tie up non-negative Interval Gray Number vectorFor Ideal Optimization Scheme vector, whereinIdeal Optimization Scheme vector
The vector that the highest design parameter of evaluation score is constituted is indicated, with optimal design parameters closer to showing that design parameter is more important；
(6) interval number is setWithThenWithDistance
It is defined as：
Specification objective making decision matrix elementWith Ideal Optimization Scheme vector elementGrey incidence coefficient definition
For：
Wherein, ρ ∈ [0,1] are resolution ratio；
If preferably, the step one weight wjUnknown solution the specific steps are：
(1) designer considers products characteristics, mission task, the patterns of warfare, mission profile, use environment, development
Progress, research fund, technical maturity and risk etc., according to expertise and experience, i.e. subjective preferences carry out design parameter
Scoring, uses interval numberIt indicates,ByIt builds matrix and is known as subjectivity partially
Good matrix
(2) use the method described in claim 2 step (4) to subjective preferences matrixStandardize
Processing, obtained specification subjective preferences matrix are usedIt indicates,
(3) the sum of the deviation for remembering specification objective making decision matrix element and specification subjective preferences matrix element is Di(w),
It enablesThe problem for solving evaluation criterion weight vector is equivalent to solve
Following optimization problem,
It can acquire,
Advantageous effect
The present invention, which compares prior art, has following remarkable advantage：
The present invention gives a kind of quantitative space product performance and test integrated design parameter choosing method, this method
Using gray theory, the relevance between research and design parameter and evaluation index, and according between design parameter and evaluation index
The degree of association and evaluation index weight carry out parameter selection.Wherein, evaluation index represents design object or requirement.When
In the case that evaluation criterion weight is unknown, give a kind of inclined according to objective making decision matrix element and subjective preferences matrix element
Poor minimum weight method for solving.Design parameter choosing method using the present invention is more scientific and reasonable, can make the performance of product
It is optimal with efficiency.
Description of the drawings
Fig. 1 is that the performance of the method for the present invention and test integrated design parameter choose flow chart.
Fig. 2 is that the grey correlation matrix of the method for the present invention solves flow chart.
Fig. 3 is that the weight of the method for the present invention solves flow chart.
Specific implementation mode
The specific implementation mode of the present invention is described further below in conjunction with attached drawing.
A kind of space product performance based on gray theory and test integrated design parameter choosing method, including it is following several
A step：
Step 1：Calculating correlation；
(1) fighting efficiency, Support Effectiveness, Operational Suitability, life cycle cost etc. are chosen and is used as evaluation index, use tjTable
Show, weight wjIt indicates, j is index number, j=1 ..., m, by tjThe vector of composition is as property set, with T={ t1,t2,…,
tmIndicate, by wjThe vector of composition is as weight sets, with w={ w1,w2,…,wm' indicate；
(2) the relevance grey relation coefficient of performance and test integrated design parameter and evaluation index is setIt indicates,
I=1 ..., n, j=1 ..., m, byThe matrix of composition is known as grey incidence coefficient matrix, usesIt indicates；
(3) performance and test integrated design parameter and the gray relation grades of evaluation index are by Grey Incidence MatrixWith
Weight wjIt is calculated, usesIt indicates, value shows that more greatly the bigger design parameter and the evaluation index degree of association the heavier
It wants, if weight wjIt is known that being calculated using following formula：
Step 2：It is cut according to design parameter selection principle and selects design parameter；
It is ranked up according to the gray relation grades size of calculating, intercepting principle according to design parameter selects the ginseng to be designed
Number；
Step one grey correlation matrix as a preferred embodiment of the above solution,Solution the specific steps are：
(2) according to product design requirement and design object, the performance and test design parameter of product is combed, s is usediIt indicates, i
For number of parameters, i=1 ..., n, by siThe vector of composition is as scheme collection, with S={ s1,s2,…,snIndicate；
(2) fighting efficiency, Support Effectiveness, Operational Suitability, life cycle cost etc. are chosen and is used as evaluation index, use tjTable
Show, j is index number, j=1 ..., m, by tjThe vector of composition is as property set, with T={ t1,t2,…,tmIndicate；
(3) it is scored according to the incidence relation between design parameter and evaluation index, with non-negative interval numberIt indicates, WithIt indicates respectivelyMinimum value and maximum value, byThe square of composition
Battle array is known as objective making decision matrix, usesIt indicates；
(4) to objective making decision matrixStandardization processing is carried out, eliminates dimension and the order of magnitude to decision knot
The influence of fruit, the profitable type of matrix element and cost type, profit evaluation model refer to that element value is the bigger the better, and cost type refers to that attribute value is got over
Small better, the normalizing of profit evaluation model and cost type is respectively：
Objective making decision matrixThe specification objective making decision matrix obtained after standardization processing is usedIt indicates,
(5) rememberM is claimed to tie up non-negative Interval Gray Number vectorFor Ideal Optimization Scheme vector, whereinIdeal Optimization Scheme vector
The vector that the highest design parameter of evaluation score is constituted is indicated, with optimal design parameters closer to showing that design parameter is more important；
(6) interval number is setWithThenWithDistance
It is defined as：
Specification objective making decision matrix elementWith Ideal Optimization Scheme vector elementGrey incidence coefficient definition
For：
Wherein, ρ ∈ [0,1] are resolution ratio；
If preferably, the step one weight wjUnknown solution the specific steps are：
(1) designer considers products characteristics, mission task, the patterns of warfare, mission profile, use environment, development
Progress, research fund, technical maturity and risk etc., according to expertise and experience, i.e. subjective preferences carry out design parameter
Scoring, uses interval numberIt indicates,ByIt builds matrix and is known as subjectivity partially
Good matrix
(2) use the method described in claim 2 step (4) to subjective preferences matrixStandardize
Processing, obtained specification subjective preferences matrix are usedIt indicates,
(3) the sum of the deviation for remembering specification objective making decision matrix element and specification subjective preferences matrix element is Di(w),
It enablesThe problem for solving evaluation criterion weight vector is equivalent to solve such as
Lower optimization problem,
It can acquire,
The present invention gives a kind of quantitative space product performance and test integrated design parameter choosing method, this method
Using gray theory, the relevance between research and design parameter and evaluation index, and according between design parameter and evaluation index
The degree of association and evaluation index weight carry out parameter selection.Wherein, evaluation index represents design object or requirement.When
In the case that evaluation criterion weight is unknown, give a kind of inclined according to objective making decision matrix element and subjective preferences matrix element
Poor minimum weight method for solving.Design parameter choosing method using the present invention is more scientific and reasonable, can make the performance of product
It is optimal with efficiency.
Claims (3)
1. a kind of space product performance based on gray theory and test integrated design parameter choosing method, which is characterized in that
The choosing method includes following steps：
Step 1：Calculating correlation；
(1) fighting efficiency, Support Effectiveness, Operational Suitability, life cycle cost are chosen as evaluation index, uses tjIt indicates, weight
Use wjIt indicates, j is index number, j=1 ..., m, by tjThe vector of composition is as property set, with T={ t1,t2,…,tmIndicate,
By wjThe vector of composition is as weight sets, with w={ w1,w2,…,wm' indicate；
(2) the relevance grey relation coefficient of performance and test integrated design parameter and evaluation index is setIt indicates, i=
1 ..., n, j=1 ..., m, byThe matrix of composition is known as grey incidence coefficient matrix, usesIt indicates；
(3) performance and test integrated design parameter and the gray relation grades of evaluation index are by Grey Incidence MatrixWith weight wj
It is calculated, usesIt indicates, is calculated using following formula：
Step 2：It is cut according to design parameter selection principle and selects design parameter；
It is ranked up according to the gray relation grades size of calculating, intercepting principle according to design parameter selects the parameter to be designed.
2. the space product performance according to claim 1 based on gray theory and test integrated design parameter selection side
Method, which is characterized in that grey correlation matrix in the step 1Solution procedure be：
The first step combs the performance and test design parameter of product, uses s according to product design requirement and design objectiIt indicates, i
For number of parameters, i=1 ..., n, by siThe vector of composition is as scheme collection, with S={ s1,s2,…,snIndicate；
Second step chooses fighting efficiency, Support Effectiveness, Operational Suitability, life cycle cost as evaluation index, uses tjIt indicates,
J is index number, j=1 ..., m, by tjThe vector of composition is as property set, with T={ t1,t2,…,tmIndicate；
Third walks, and is scored according to the incidence relation between design parameter and evaluation index, with non-negative interval numberIt indicates, WithIt indicates respectivelyMinimum value and maximum value, byThe square of composition
Battle array is known as objective making decision matrix, usesIt indicates；
4th step, to objective making decision matrixStandardization processing is carried out, eliminates dimension and the order of magnitude to decision knot
The influence of fruit, the profitable type of matrix element and cost type, profit evaluation model refer to that element value is the bigger the better, and cost type refers to that attribute value is got over
Small better, the normalizing of profit evaluation model and cost type is respectively：
Objective making decision matrixThe specification objective making decision matrix obtained after standardization processing is usedIt indicates,
5th step, noteM is claimed to tie up non-negative Interval Gray Number vectorFor Ideal Optimization Scheme vector, whereinIdeal Optimization Scheme vector
The vector that the highest design parameter of evaluation score is constituted is indicated, with optimal design parameters closer to showing that design parameter is more important；
6th step, if interval numberWithThenWithDistance
It is defined as：
Specification objective making decision matrix elementWith Ideal Optimization Scheme vector elementGrey incidence coefficient be defined as：
Wherein, ρ ∈ [0,1] are resolution ratio.
3. space product performance according to claim 2 and test integrated design parameter choosing method, which is characterized in that
If weight w in the step 1jUnknown solution the specific steps are：
(1) designer consider products characteristics, mission task, the patterns of warfare, mission profile, use environment, development progress,
Research fund, technical maturity and risk, subjective preferences score to design parameter, use interval numberIt indicates,ByStructure matrix is known as subjective preferences matrix
(2) use the method described in second step to subjective preferences matrixCarry out standardization processing, obtained rule
Model subjective preferences matrix is usedIt indicates,
(3) the sum of the deviation for remembering specification objective making decision matrix element and specification subjective preferences matrix element is Di(w),
It enablesThe problem for solving evaluation criterion weight vector is equivalent to solve as follows most
Optimization problem,
It can acquire,
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109344362A (en) * | 2018-09-03 | 2019-02-15 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Electronic component nature storehouse stores sensitive stress quantitative evaluating method |
| CN110941904A (en) * | 2019-11-28 | 2020-03-31 | 西安工业大学 | Sensing equipment combination and collocation method based on different combat weather |
| CN113098712A (en) * | 2021-03-26 | 2021-07-09 | 中国航空无线电电子研究所 | Physical architecture balancing method of comprehensive radio frequency system based on grey correlation degree |
| CN113836485A (en) * | 2021-09-29 | 2021-12-24 | 中国人民解放军战略支援部队航天工程大学 | Method for grey correlation of set-to-matrix for multi-scheme analysis |
| CN115828437A (en) * | 2023-02-17 | 2023-03-21 | 中汽研汽车检验中心（天津）有限公司 | Automobile performance index comprehensive optimization method and computing equipment |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109344362A (en) * | 2018-09-03 | 2019-02-15 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Electronic component nature storehouse stores sensitive stress quantitative evaluating method |
| CN110941904A (en) * | 2019-11-28 | 2020-03-31 | 西安工业大学 | Sensing equipment combination and collocation method based on different combat weather |
| CN113098712A (en) * | 2021-03-26 | 2021-07-09 | 中国航空无线电电子研究所 | Physical architecture balancing method of comprehensive radio frequency system based on grey correlation degree |
| CN113836485A (en) * | 2021-09-29 | 2021-12-24 | 中国人民解放军战略支援部队航天工程大学 | Method for grey correlation of set-to-matrix for multi-scheme analysis |
| CN115828437A (en) * | 2023-02-17 | 2023-03-21 | 中汽研汽车检验中心（天津）有限公司 | Automobile performance index comprehensive optimization method and computing equipment |
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