CN104915479B - Product automatic scheme Optimization Design based on performance component storehouse and graph grammar - Google Patents
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Abstract
The invention discloses a kind of product automatic scheme Optimization Design based on performance component model and graph grammar, comprise the following steps：One composite performance component model storehouse is established using Object--oriented method according to model evolution history；Using product function structure chart as reference model, information, energy and material flow in the graph grammar and performance component performance interface parameter and functional diagram that are obtained by products configuration and layout designs are matched come the dynamic generation of drive system performance model；System performance model is changed into using meta-model by the mathematical modeling comprising optimization aim model and its related constraint；The optimized algorithm for starting binding ability simulation frame solves the optimization design problem.The final result obtained after optimization includes allocation optimum and the best design parameter of performance component, and this method can search for the space bigger than traditional Optimization Design based on variable, so as to obtain more excellent result.
Description
Technical field
The invention belongs to Computer Aided Mechanical Design technical field, is related to the method that engineering goods scheme optimization designs.
Background technology
The decision-making that designer makes in the product scheme design stage has important influence to the design object of product, and this is
Because in this stage because the uncertainty of project analysis can cause a large amount of possible design options to be eliminated, so that finally
Optimization design scheme can only be limited in a less feasible design space.Do not known in the product scheme design stage
The research of analysis and optimization design under the conditions of property is less.In the product scheme design stage, in addition to parameter uncertainty,
Also it is widely present model uncertainty.Model uncertainty, otherwise referred to as structural uncertainty or nonparametric are uncertain, and one
As be defined as that neither one is unified, the licensable model for describing some problem.In the product scheme design stage, product mould
Type can be divided into design domain and performance domain model, wherein design domain model refers to comprising product function structure, physical effect, work knot
Model including structure and system configuration etc..The uncertainty structure of design domain has direct influence to properties of product domain model.Cause
This, considers the direct correlation relation between both, it is one directly to optimize combination to properties of product domain model and its parameter
The method that kind can directly eliminate the model being widely present in the product scheme design stage and parameter uncertainty, and ratio can be obtained
It is simple to carry out the more preferable design result of Parameters Optimal Design.
Existing technical literature is retrieved and found, at present on being carried out in product detailed design phase under condition of uncertainty
Product optimization design method has had many research, Yao etc. and Zang etc. to be reviewed, but is carried out in the schematic design phase
Model uncertainty is analyzed and optimizing research is seldom.Currently existing scheme design method such as quality function deployment (QFD), TRIZ are theoretical
Although Deng with the function of carrying out product scheme design, lack among these methods one kind can it is programmable, can be continuous
Processing structure does not know the model transform method of design problem.Although go out in network service and computer multiprocessing system
The method for having showed some systems and the design of component parallel optimization, as described in Thai and Pardalos and Kempf etc., but this
A little methods are difficult to be transplanted to mechanical design field, because a large amount of constraints present in Machine Design are difficult to be entered with these methods
Row processing.In consideration of it, the graph grammar rule accumulated in properties of product Component Gallery and design process based on proposition, the present invention propose
A kind of design method that the optimization simultaneously of system and performance component can be carried out in the Scheme Design of Machine Product stage.
The content of the invention
Present disclosure is in view of the shortcomings of the prior art, to propose a kind of product based on performance component storehouse and graph grammar
Automatic scheme Optimization Design.This method is using product system design as main application and field, by forming product
The performance component of system enters line translation, and product design domain can be explored in a wider context, to model and parameter not
During certainty is cleared up, while obtain the design result more excellent than traditional parameters and variable Optimization Design.
The present invention is realized by following technical scheme, and a kind of product based on performance component model and graph grammar is certainly
Dynamic scheme optimization design method, comprises the following steps：
(1) one composite performance component model storehouse is established using Object--oriented method according to performance model history of evolution；
Described performance model history of evolution refers to the performance for the different accuracy established for product scheme design process
Model, including for the expected performance model that principle designs, estimated performance model for work structuring design and for reality
The actual performance model of operating mode, these models are developed using the initial philosophy such as physically or chemically as according to constantly extension
Arrive；According to property evolution model, described composite performance component model includes the application layer of description design history of evolution, descriptive
Can the object layer of types of models and the computation layer of description performance illustraton of model structure；The calculating layer model is made up of node and side
Oriented structure chart, wherein node can be divided into design formula node and design variable node, and directed edge is then design variable node
Contact between design formula node；If directed edge points to formula node by variable nodes shows that variable is the defeated of formula
Enter, and show that variable is the output of formula if side is to point to variable nodes by formula node；The composite performance assembly mould
Type meets the actual demand of product design evolution, is easy to select different performance components in different Design Stages, together
When the model object layer and computation layer be easy to that designer carries out the reasoning of model and evaluation calculates, and based on graph model
Computation model is also convenient for the generation of follow-up system performance model；
(2) using product function structure chart as reference model, the graph grammar and property that are obtained by products configuration and layout designs
Energy assembly property interface parameters and information, energy and material flow in functional diagram, which are matched, carrys out the dynamic of drive system performance model
State generates；
Described product function structure chart refers to description product function composition and energy, the information established according to user's request
With the block diagram of Flow of Goods and Materials, the figure is used as the initial reference model of system performance model generation；Given birth in system performance model
During, function node in functional structure chart is transformed into performance component node according to the rewriting rule of graph grammar, in figure
Energy, signal and material flow are then transformed into the input/output variable of performance component；Used in system performance model generating process
Three rule-likes, i.e. the functional layer grammar rule based on products configuration demand, function-component mapping ruler and parameter layer rule.Rule
The works such as Rozenberg that specific form then see graph grammar writes《Handbook of Graph Grammars and
Computing by Graph Transformation》Deng.According to this three rule-like, initial function host model is transformed to
Systematic function component model can be divided into three sub-steps：In the first sub-step, the topological sum type of product function, identical function knot
The number of point and the quantitative requirement of functional attributes are determined；In the second sub-step, the instantiation of startup function node
Journey, function node are changed into performance component, meanwhile, energy, material and signal stream are changed into the input/output variable of performance component；
In the 3rd sub-step, the Public Design variable that each component includes is established first, then to each optimization design variable according to setting
The experience or design manual of meter personnel assigns a constant interval；
(3) system performance model is changed into using meta-model by the mathematical modulo comprising optimization aim model and its related constraint
Type, the form of the mathematical modeling are as follows：
Min Vo
Vo=F3(Vbdy5,Vini6,Vint1,Vint2,Vind31…,Vind3n)
Vint1=F1(Vbdy1,Vini2,Vind11…,Vind1l)
Vint2=F2(Vbdy3,Vini4,Vind21…,Vind2m)
Boundary condition：
Vbdy1,Vbdy3,Vbdy5
Primary condition：
Vini2,Vini4,Vini6
Optimized variable value constrains：
Vind1i u≤Vind1i≤Vind1i l(i=1 ..., l)
Vind2j u≤Vind2j≤Vind2j l(j=1 ..., m)
Vind3k u≤Vind3k≤Vind3k l(k=1 ..., n)
Wherein, the target capabilities variable that Vo optimizes for needs, F3(Vbdy5,Vini6,Vint1,Vint2,Vind31…,Vind3n) be
Optimization object function, Vint1=F1(Vbdy1,Vini2,Vind11…,Vind1l) and Vint2=F2(Vbdy3,Vini4,Vind21…,Vind2m)
For medium design variable and its function, Vbdy1,Vbdy3,Vbdy5For boundary condition variable, Vini2, Vini4, Vini6Become for primary condition
Amount, Vind1i, Vind2j, Vind3kFor independent design variable, l, m, n is the quantity of independent design variable in target and intermediate function,
Vind1i lAnd Vind1i uThe respectively upper and lower bound of independent design variable；
The meta-model is made up of four parts, i.e. 1. model calculates auxiliary information used, including material properties, border
With primary condition etc.；2. constraint equation or inequality formatting and calculating section；3. object function formats and calculating section；④
Function returning part；The part of centre two of the meta-model can be converted by systematic function component model, and utility
The association that the interface parameters of component model is established between constraint equation and target component；The systematicness obtained according to meta model template
Energy Optimized model, sometimes for line translation is entered before solution is optimized, these conversion should by variable replacement, agent model
The design problem of a complexity, coupling is changed into some submodels that can be solved with being changed etc. with optimization aim, or will
Single-object problem is changed into multi-objective optimization question, or to establish the discrete method for solving of model efficient, feasible to obtain
Method for solving；
(4) optimized algorithm for starting binding ability simulation frame solves the optimization design problem, is specially：Frame will be emulated
Frame is used for the solution of Optimized model, optimized algorithm is used to encoding optimized variable, assignment and objective appraisal；Optimized algorithm
Using genetic algorithm, simulation frame uses MatLab；
(5) check and preserve the design that step 2 obtains and optimization aim and optimized variable value that step 4 obtains；
If Optimized Iterative number now is less than preset rules number, iteration performs step 2-4；If regulation iteration time is reached
Number, then select optimal scheme and design variable and target from the design of preservation.
Compared with prior art, the present invention has the advantages that：The defined in designer is according to the present invention
After method establishes performance component storehouse, multiple product systems schemes can be quickly generated, and the parameter of these schemes is entered
Row optimization, so on the one hand save substantial amounts of manpower and be used for the generation of product new departure, while can carry out in a wider context
Scheme is preferred, while product scheme design efficiency is improved, can obtain the more preferable design of Parameters Optimal Design more simple than tradition
Scheme.
Brief description of the drawings
Fig. 1 is the product automatic scheme Optimization Design schematic diagram based on performance component storehouse and graph grammar；
Fig. 2 is to develop with the performance model of product scheme design process；
Fig. 3 is composite component model；
Fig. 4 is to illustrate composite component model library building method by taking hydro-pneumatic suspension system as an example
Fig. 5 is the system performance model dynamic generation based on graph grammar；
Fig. 6 is the generation of systematic function component drawings and transfer process；
Fig. 7 is the system optimization model assembling based on meta-model；
Fig. 8 encodes for optimized variable.
Embodiment
The present invention is described in further detail below in conjunction with the drawings and specific embodiments, the purpose of the present invention and effect will
Become readily apparent from.
The invention provides a kind of product automatic scheme Optimization Design based on performance component storehouse and graph grammar, such as schemes
Shown in 1.The product automatic scheme Optimization Design is by using component constitutional diagram grammar rule to by certain requirement foundation
Performance component storehouse is operable to dynamic generating system performance model, and the systematic function component model is converted into system optimization
Model and then the method solved.This method can carry out the exploration of product design scheme in two levels of model and parameter,
The efficiency of product scheme design can not only be improved, moreover it is possible to obtain the more preferable design of Parameters Optimal Design more simple than tradition.
In the method, properties of product model is write using MatLab, and schemes generation module is entered using GrGen.net
Row is write, and products configuration demand and performance component management and system optimization model generate and solved module and use Visual
Basic.net writes.According to model evolution history, it is proposed that three kinds of performance models as shown in Figure 2, with different accuracy.
On this basis, product composite performance component model storehouse as shown in Figure 3 is established, Fig. 4 provides by taking hydro-pneumatic suspension system as an example
Composite component model library example.After properties of product component model storehouse is established, described in detail with reference to Fig. 5-Fig. 8
The process of products scheme optimization design.
In products scheme process of optimization (shown in Fig. 6), it is first according to establish an initial product work(shown in Fig. 5
Can structure chart.The structure chart is expressed in graph form, can be decomposed, extended and be closed by product function layer graph grammar rule
And wait, to ultimately generate the product function structural model for meeting user's request.Then, will using function-component mapping ruler
The product function structural model established is mapped as product systems performance component model, the function node wherein in functional structure chart
It is changed into performance component node, energy, signal and the material flow in functional diagram become input and the output variable of performance component.Most
Afterwards, the variable of each component counts in the systematic function component drawings obtained to conversion, finds Public Design variable, avoids
Repeated encoding during optimization, while assign a constant interval to each optimization design variable.Obtaining systematic function modular construction
After figure, it is also necessary to which the structure chart is changed into can be used to the mathematical modeling of Optimization Solution.Employed in transfer process based on member
The transform method of model, as shown in Figure 7.In transfer process, two intermediate variable V in systematic function component drawingsint1And Vint2
Referred to as performance component F1、F2With component F3Associated variable, and in Optimized model turn between optimization aim and design constraint
Contact variable.Each performance component use a MatLab script function file edit, and its calling sequentially will be according to whether there is change
Amount incidence relation is determined.It is determined that after system function optimization model, the optimized variable determined in the 3rd step is encoded,
Cataloged procedure is as shown in figure 8, and starting genetic algorithm and optimizing calculating.
Model and parameter uncertainty when the present invention has taken into full account Scheme Design of Machine Product and to adapt to different productions
The Development of Module sex chromosome mosaicism of product design requirement, to solve product scheme design stage design poor information, reciprocal iteration, calculating work
The problems such as work amount is big provides a feasible program Optimization Design based on performance component storehouse and graph grammar.This method utilizes
Optimization is combined according to the performance model of extensive adaptability, while the product component configuration for being capable of Combined design personnel accumulation is known
Know, plus powerful calculating ability possessed by current computer, product design domain can be carried out in two levels of model and parameter
Search, it can efficiently obtain the parameter optimization more preferable design more simple than tradition.
The above-mentioned description to embodiment is understood that for ease of those skilled in the art and using this hair
It is bright.The method that the present invention is introduced obviously can be applied to their PRACTICE OF DESIGN by those skilled in the art, and right
This method makes appropriate modification, and this process is not required to by creative work.Those skilled in the art take off according to the present invention's
Show, the improvement and modification made for the present invention all should be within protection scope of the present invention.
Claims (1)
- A kind of 1. product automatic scheme Optimization Design based on performance component model and graph grammar, it is characterised in that including Following steps：(1) one composite performance component model storehouse is established using Object--oriented method according to performance model history of evolution；Described performance model history of evolution refers to the performance model for the different accuracy established for product scheme design process, Including the expected performance model designed for principle, estimated performance model for work structuring design and for actual condition Actual performance model, these models obtain using initial physically or chemically philosophy as according to constantly extension evolution；Plyability Energy component model includes the application layer of description design history of evolution, describes the object layer and description performance model of performance types of models The computation layer of graph structure；The oriented structure chart that the computation layer is made up of node and side, wherein node are divided into design formula knot Point and design variable node, directed edge is then the contact between design variable node and design formula node；When directed edge is by setting Meter variable nodes point to design formula node and show that variable is the input of formula, when directed edge is to be pointed to set by design formula node Meter variable nodes then show that variable is the output of formula；(2) using product function structure chart as reference model, the graph grammar rule, the performance that are obtained by products configuration and layout designs The matched rule of signal, energy and material flow in component model interface parameters and functional structure chart carrys out drive system performance model Dynamic generation；Described product function structure chart refers to the description product function composition and energy, signal and thing established according to user's request The block diagram of stream, the figure are used as the initial reference model of system performance model generation；In system performance model generating process In, function node in functional structure chart is transformed into performance component node according to the rewriting rule of graph grammar, energy, letter in figure Number and material flow be then transformed into the input/output variable of performance component；Three classes rule are used in system performance model generating process Then, i.e. the functional layer grammar rule based on products configuration demand, function-component mapping ruler and parameter layer rule, according to this three Rule-like, initial function host model are transformed to system performance model and are divided into three sub-steps：In the first sub-step, product The topological sum type of function, the number of identical function node and the quantitative requirement of functional attributes are determined；In the second son In step, the instantiation process of startup function node, function node is changed into performance component, meanwhile, energy, signal and material flow It is changed into the input/output variable of performance component；In the 3rd sub-step, the Public Design that each component includes is established first and is become Amount, then assign a constant interval according to the experience or design manual of designer to each optimization design variable；(3) system performance model is changed into by the mathematical modeling comprising optimization aim model and its related constraint using meta-model, The form of the mathematical modeling is as follows：Min VoVo=F3(Vbdy5,Vini6,Vint1,Vint2,Vind31…,Vind3n)Vint1=F1(Vbdy1,Vini2,Vind11…,Vind1l)Vint2=F2(Vbdy3,Vini4,Vind21…,Vind2m)Boundary condition：Vbdy1,Vbdy3,Vbdy5Primary condition：Vini2,Vini4,Vini6Optimized variable value constrains：Vind1i u≤Vind1i≤Vind1i l, i=1 ..., lVind2j u≤Vind2j≤Vind2j l, j=1 ..., mVind3k u≤Vind3k≤Vind3k l, k=1 ..., nWherein, the target capabilities variable that Vo optimizes for needs, F3(Vbdy5,Vini6,Vint1,Vint2,Vind31…,Vind3n) it is optimization Object function, Vint1=F1(Vbdy1,Vini2,Vind11…,Vind1l) and Vint2=F2(Vbdy3,Vini4,Vind21…,Vind2m) be Between design variable and its function, Vbdy1,Vbdy3,Vbdy5For boundary condition variable, Vini2, Vini4, Vini6For primary condition variable, Vind1i, Vind2j, Vind3kFor independent design variable, l, m, n is the quantity of independent design variable in intermediate function and object function, Vind1i lAnd Vind1i uThe respectively upper and lower bound of independent design variable；The meta-model is made up of four parts, i.e. 1. model calculates auxiliary information used, including material properties, border and just Beginning condition；2. constraint equation or inequality formatting and calculating section；3. object function formats and calculating section；4. function returns Go back to part；The part of centre two of the meta-model is converted by systematic function component model, and utility component model The association established between constraint equation and target component of interface parameters；The system function optimization mould obtained according to meta model template Type, needed before solution is optimized into during line translation, being changed by variable replacement, agent model application and optimization aim will One complexity, the optimization design problem of coupling are changed into some submodels that can be solved, or single-object problem is turned It is changed into multi-objective optimization question, or establishes the discrete method for solving of model；(4) optimized algorithm for starting binding ability simulation frame solves the optimization design problem, is specially：Simulation frame is used In the solution of Optimized model, optimized algorithm is used to encoding optimized variable, assignment and objective appraisal；Optimized algorithm uses Genetic algorithm, simulation frame use MatLab；(5) check and preserve the design that step (2) obtains and optimization aim and optimized variable value that step (4) obtains； If Optimized Iterative number now is less than preset rules number, iteration performs step (2)-(4)；If reach regulation to change Generation number, then optimal scheme and design variable and target are selected from the design of preservation.
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