CN108121882A - Demand matter-element structure match method based on the degree of correlation - Google Patents

Demand matter-element structure match method based on the degree of correlation Download PDF

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Publication number
CN108121882A
CN108121882A CN201810034201.1A CN201810034201A CN108121882A CN 108121882 A CN108121882 A CN 108121882A CN 201810034201 A CN201810034201 A CN 201810034201A CN 108121882 A CN108121882 A CN 108121882A
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China
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matter
mrow
demand
feature
magnitude
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Inventor
毛保全
赵俊严
吴东亚
杨雨迎
徐振辉
韩小平
白向华
张天意
辛学敏
郑博文
朱锐
李俊
冯帅
李程
王之千
李晓刚
兰图
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Academy of Armored Forces of PLA
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Academy of Armored Forces of PLA
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Priority to CN201810034201.1A priority Critical patent/CN108121882A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/17—Mechanical parametric or variational design
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/20—Configuration CAD, e.g. designing by assembling or positioning modules selected from libraries of predesigned modules

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Mathematical Analysis (AREA)
  • Computer Hardware Design (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
  • Computational Mathematics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The present invention relates to a kind of demand matter-element structure match methods based on the degree of correlation, are related to matter-element structure match technical field.The present invention is during products configuration, it is contemplated that the degree of correlation between feature is completed to configure, available for realizing the configuration design of Remote Control Weapon Station module.

Description

Demand matter-element structure match method based on the degree of correlation
Technical field
The present invention relates to matter-element structure match technical fields, and in particular to a kind of demand matter-element structure based on the degree of correlation Change matching process.
Background technology
Configuration design (Configuration Design) is found and is combined into a series of parts designed It meets certain requirements, meets the product design method centainly constrained and process.The configuration design of Remote Control Weapon Station module is exactly in mould On the basis of block storehouse, according to module race allocation models, according to the restriction relation of intermodule and specific military's demand, one is selected Group module meets the modular product of military's demand to form.At present, Configuration knowledge is concentrated mainly on to the research of products configuration Expression, configuration modeling and allocation problem solution in terms of.Mainly there are rule-based, constraint, money in the expression of Configuration knowledge The methods of source, logical program.Allocation models, the product based on GBOM for mainly having object-oriented in terms of the modeling of products configuration Allocation models etc..In terms of the solution of allocation problem, main Constrained meets method, method of Case-based Reasoning etc..
The extraction problem of case retrieval, that is, preferred example, preferred example refer to the example most like with current problem, therefore Most important problem is the differentiation of example similitude in case retrieval.When carrying out case-based reasoning currently with similar topology degree, by In configuration feature magnitude, oneself knows, therefore can easily calculate product knot in demand structure feature and case library using distance Similarity degree between structure feature.However in profile instance reasoning process, since most users are not technical specialist, they The detailed construction of product is not understood really, and the demand condition that they propose often is qualitative demand characteristic, and demand parameter has one Surely remaining is changed, at this moment cannot directly be calculated using similarity algorithm.
The content of the invention
(1) technical problems to be solved
The technical problem to be solved by the present invention is to：How demand matter-element structure match products configuration during is realized.
(2) technical solution
In order to solve the above technical problem, the present invention provides the demand matter-element structure match method based on the degree of correlation, Comprise the following steps：
Step 1: qualitative demand characteristic conversion
Initially set up the relation between qualitative magnitude and configuration feature magnitude；
Step 2: the magnitude extraction of qualitative demand characteristic
After qualitative demand characteristic is completed to convert, using following demand characteristic magnitude value mode：
Cumulative type demand characteristic：When x is more than predetermined threshold value, cumulative process terminates；Assuming that given things Title N, it is V on the magnitude of feature C, with orderly triple R=(N, C, V) as the substantially first of description things, abbreviation object Member, the structure feature that relatedness computation can be carried out in matter-element case library with transformed qualitative demand characteristic by being located at share n, viFor corresponding i-th of the magnitude of i-th of structure feature；
Step 3: the qualitative demand structure based on the degree of correlation
If i-th of demand matter-element input by user is RSji=[Nsi,csi,vji], character pair matter-element interval value is RSi= [Nsi,csi,X0i], wherein X0i=[min0i,max0i]；
Step 3.1, the search all parameter attributes identical with qualitative demand characteristic：Being located in matter-element case library can be with the need Feature is asked to carry out in n structure feature of relatedness computation, j-th of parameter attribute is denoted as Cij, corresponding structure is Nij, structure NijCijThe average of feature is The proportion for accounting for the sum of all averages is rateij, C in case libraryijAvailable area between magnitude Xij=[minimum value minij, maximum maxij]；
Step 3.2 searches for all N in matter-element case libraryijExample, if m shared, it is equal to calculate feature according to formula (1) Value：
Step 3.3, according to formula (2) calculated specific gravity, and by rateijDescending arrangement rearrangement, proportion is descending, phase The feature answered is denoted as Ci1,…,Cin；
Step 3.4 makes sumrate=ratei1, according to Pareto principle, if sumrateMeet sumrate>=80% stops It calculates, otherwise sumrate=sumrate+ratei2, and so on, until sumrateMeet sumrate>=80% stops calculating, if stopping The feature for the proportion minimum got when only calculating is Cip；
Step 3.5, by CipWith the structure N in matter-element case libraryipMatter-element relatedness computation is carried out, if the degree of correlation is more than 0, Then structure combination is used as demand structure as a result, retrieving example matter-element N from matter-element case libraryipIt meets the requirements；If phase Guan Du is less than 0, then structurizing process stops.
(3) advantageous effect
The present invention proposes a kind of demand matter-element structure match method based on the degree of correlation, during products configuration, It completes to configure in view of the degree of correlation between feature, be designed available for realizing that Remote Control Weapon Station module configures.
Specific embodiment
To make the purpose of the present invention, content and advantage clearer, with reference to embodiment, to the specific reality of the present invention The mode of applying is described in further detail.
The present invention is during products configuration, it is contemplated that the degree of correlation between feature is completed to configure.
Degree of correlation k (x) is the index for weighing correlation degree between relation matter-element feature, and feature has：
1) when two structure features are identical, characterizing magnitudes are also identical, then the two structural relation matter-element auto-correlations；
2) no matter whether two structure features are identical, and all there may be correlations；
3) foundation of similarity function S is on condition that two structure features are identical, with similar features number SnReduction, S is also reducing；Work as Sn=0, then the two structures are completely dissimilar；At this point, if there are certain extension alternation T to cause matter-element feature Corresponding matter-element name can be caused to change in the case of changing, i.e. matter-element R1Itself changes, then the phase of two structures Pass degree may increase.
Based on principles above, the demand matter-element structure match method of the invention based on the degree of correlation comprises the following steps：
Step 1: qualitative demand characteristic conversion
The relation between qualitative magnitude and configuration feature magnitude is initially set up, with reference to military standard, if table 1 is with effective range Exemplified by illustrate, other features with reference to formulate：
1 customer's qualitative description of table and effective range relation
Step 2: the magnitude extraction of qualitative demand characteristic
After qualitative demand characteristic is completed to convert, demand characteristic magnitude value mode includes two kinds：
Cumulative type demand characteristic：When x is more than predetermined threshold value, cumulative process terminates；It is located at matter-element case library In the structure feature of relatedness computation can be carried out with transformed qualitative demand characteristic share n, viFor i-th of structure feature Corresponding i-th of magnitude；
Most value type demand characteristic：X=magnitude minimum values vminOr x=magnitude maximums vmax；
Stupid step takes the first in addition, it further provides that the dimension of homogenous characteristics (including demand characteristic and parameter attribute) is identical, Dimension such as length and width is all mm, and cannot be cm or m.
Step 3: the qualitative demand structure based on the degree of correlation
The title N of given things, it is V on the magnitude of feature C, with orderly triple R=(N, C, V) as description thing Substantially first, the abbreviation matter-element of object.If i-th of demand matter-element input by user is RSji=[Nsi,csi,vji], character pair matter-element Interval value is RSi=[Nsi,csi,X0i], wherein X0i=[min0i,max0i]。
Step 3.1, the search all parameter attributes identical with qualitative demand characteristic.Being located in matter-element case library can be with this Demand characteristic is carried out in n structure feature of relatedness computation, and j-th of parameter attribute is denoted as Cij, corresponding structure is Nij, knot Structure NijCijThe average of feature is The proportion for accounting for the sum of all averages is rateij, C in case libraryijThe available area area of a room Value Xij=[minimum value minij, maximum maxij]。
Step 3.2 searches for all N in matter-element case libraryijExample, if m shared, it is equal to calculate feature according to formula (1) Value：
Step 3.3, according to formula (2) calculated specific gravity, and by rateijDescending arrangement rearrangement, proportion is descending, phase The feature answered is denoted as Ci1,…,Cin。
Step 3.4 makes sumrate=ratei1, according to Pareto principle, if sumrateMeet sumrate>=80% stops It calculates, otherwise sumrate=sumrate+ratei2, and so on, until sumrateMeet sumrate>=80% stops calculating.If stop The feature for the proportion minimum got when only calculating is Cip。
Step 3.5, by CipWith the structure N in matter-element case libraryipMatter-element relatedness computation is carried out, if the degree of correlation is more than 0, Then structure combination can be used as one of demand structure result, i.e., example matter-element N is retrieved from matter-element case libraryipIt conforms to It asks；If the degree of correlation is less than 0, structurizing process stops.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art For member, without departing from the technical principles of the invention, several improvement and deformation can also be made, these are improved and deformation Also it should be regarded as protection scope of the present invention.

Claims (1)

  1. A kind of 1. demand matter-element structure match method based on the degree of correlation, which is characterized in that comprise the following steps：
    Step 1: qualitative demand characteristic conversion
    Initially set up the relation between qualitative magnitude and configuration feature magnitude；
    Step 2: the magnitude extraction of qualitative demand characteristic
    After qualitative demand characteristic is completed to convert, using following demand characteristic magnitude value mode：
    Cumulative type demand characteristic：When x is more than predetermined threshold value, cumulative process terminates；Assuming that the title of given things N, it on feature C magnitude for V, with substantially member of the orderly triple R=(N, C, V) as description things, abbreviation matter-element, if The structure feature that can carry out relatedness computation with transformed qualitative demand characteristic in matter-element case library shares n, viFor Corresponding i-th of the magnitude of i-th of structure feature；
    Step 3: the qualitative demand structure based on the degree of correlation
    If i-th of demand matter-element input by user is RSji=[Nsi,csi,vji], character pair matter-element interval value is RSi=[Nsi, csi,X0i], wherein X0i=[min0i,max0i]；
    Step 3.1, the search all parameter attributes identical with qualitative demand characteristic：Being located in matter-element case library can be special with the demand Sign is carried out in n structure feature of relatedness computation, and j-th of parameter attribute is denoted as Cij, corresponding structure is Nij, structure Nij's CijThe average of feature is The proportion for accounting for the sum of all averages is rateij, C in case libraryijAvailable area between magnitude Xij= [minimum value minij, maximum maxij]；
    Step 3.2 searches for all N in matter-element case libraryijExample, if m shared, characteristic mean is calculated according to formula (1)：
    <mrow> <mover> <msub> <mi>x</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>&amp;OverBar;</mo> </mover> <mo>=</mo> <mfrac> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>s</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>x</mi> <mrow> <mi>i</mi> <mi>j</mi> <mi>s</mi> </mrow> </msub> </mrow> <mi>m</mi> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>
    Step 3.3, according to formula (2) calculated specific gravity, and by rateijDescending arrangement rearrangement, proportion is descending, accordingly Feature is denoted as Ci1,…,Cin；
    Step 3.4 makes sumrate=ratei1, according to Pareto principle, if sumrateMeet sumrate>=80% stops calculating, Otherwise sumrate=sumrate+ratei2, and so on, until sumrateMeet sumrate>=80% stops calculating, if stopping meter The feature for the proportion minimum got during calculation is Cip；
    Step 3.5, by CipWith the structure N in matter-element case libraryipMatter-element relatedness computation is carried out, if the degree of correlation is more than 0, the knot Structure combination is as demand structure as a result, retrieving example matter-element N from matter-element case libraryipIt meets the requirements；If the degree of correlation is small In 0, then structurizing process stops.
CN201810034201.1A 2018-01-15 2018-01-15 Demand matter-element structure match method based on the degree of correlation Pending CN108121882A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108121826A (en) * 2018-01-15 2018-06-05 中国人民解放军陆军装甲兵学院 Based on the structure feature search method that can open up similarity

Citations (3)

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Publication number Priority date Publication date Assignee Title
CN1790351A (en) * 2005-12-16 2006-06-21 浙江工业大学 Product concept design method based on extension information matter-element
US8538972B1 (en) * 2009-07-10 2013-09-17 Google Inc. Context-dependent similarity measurements
CN104915485A (en) * 2015-05-28 2015-09-16 杭州电子科技大学 Product requirement-structure mapping method based on effect

Patent Citations (3)

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Publication number Priority date Publication date Assignee Title
CN1790351A (en) * 2005-12-16 2006-06-21 浙江工业大学 Product concept design method based on extension information matter-element
US8538972B1 (en) * 2009-07-10 2013-09-17 Google Inc. Context-dependent similarity measurements
CN104915485A (en) * 2015-05-28 2015-09-16 杭州电子科技大学 Product requirement-structure mapping method based on effect

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Application publication date: 20180605