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基于原理—结构—参数模型的机电产品设计研究
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摘要
进入21世纪以来,机电产品设计的节奏快速化、结构复杂化、功能集成化、需求个性化的发展趋势日益明显,从多个方面给产品设计理论以及设计者带了新的挑战。本文将研究定位在从概念设计到详细设计初期(Pahl的概念设计和物化设计)这一最为重要的设计阶段,从基于知识的设计角度出发,针对现有知识建模方法缺乏知识的连续性,难以支持多粒度、多领域知识表示,现有设计知识模型将各个设计阶段割裂,难以有效集成,现有基于知识的设计方法忽视产品设计的系统整体性,无法对功能拓扑和结构拓扑的构建进行有效支持等问题,提出了原理-结构-参数模型以及基于该模型的知识建模和设计求解方法,以有效支撑这一阶段的设计工作。本文的主要研究内容如下:
     (1)研究了基于原理-结构-参数模型的知识表示方法。在功能原理设计、物理结构设计、物化参数设计三个设计阶段划分的基础上,针对各个设计阶段知识粒度和知识形态的差异性,提出了功能知识元建模、功能实例建模和参变量约束建模等知识建模方法;在原理-结构-参数模型的统一框架下,对各设计阶段的知识进行建模和表示,实现了从定性设计知识到定量设计知识的连续过渡表达。
     (2)研究了功能原理设计的求解方法。提出了基于功能相似度推理的设计原理选择方法,研究了基于功能流形态及形态转换的功能拓扑设计方法;提出了基于功能草图的原理解可视化方法,并给出了原理解的评价方法。
     (3)研究了物理结构设计的求解方法。提出了基于约束包容相似度的功能实例选择方法,提出了基于功能拓扑映射的功能流接口设计方法,以及基于功能流接口强度的结构元安装接口设计方法,并给出了结构方案评价原则。
     (4)研究了物化参数设计的求解方法。提出了基于功能流形态的物化求解轨迹的规划方法,研究了基于参变量关联矩阵变换对参变量方程组进行梯次降维、分割求解的方法;针对“病态”参变量方程组,提出了复合运动粒子群算法;给出了物化方案的装配设计和验证优化方法。
     (5)进行了系统原型开发和理论实践应用。开发了基于原理-结构-参数模型的机电产品设计的计算机辅助系统原型——Design Synthesis Lab;以全自动数字化显微镜机电系统设计为例,对本文理论方法进行了应用,验证了本文理论方法的有效性。
Entering the21st century, the requirement on rapidity, complexity,integration and individuation in electromechanical product design becomesmore and more important. As a result, product design theory faces newchallenges from several aspects. Current knowledge modeling methodsinterrupting the continuity of design knowledge, it is difficult to supportmulti-granularity, multi-domain knowledge representation; current designmodel isolating the design phases, it is hard for integration; current designmethod ignoring the system integrity of product design, it is unable to supporteffective design of functional topology and structural topology. This paperfocuses on the wide design stage from conceptual design to the beginning ofdetailed design (Pahl’s conceptual design and embodiment design), which is themost important design phase. Principle-Structure-Parameter Model is proposedto support the design events in this stage. Main content of this paper isstructured as follows:
     (1) Researched on knowledge representation based on Principle-Structure-Parameter Model. On the basis of three design phase division, i.e. functionalprinciple design stage, physical structure design stage and parametricembodiment design stage, based on differences in knowledge granularity andpattern between each stage, functional knowledge cell modeling, functionalcase modeling and structure parameter-behavior variable constraints modelingare applied to modeling and represent the knowledge in the three design stages.As a result, qualitative-to-quantitative transition knowledge representationbetween multiple design phases is achieved.
     (2) Researched on principle design method. Functional similarityreasoning is proposed for functional principle selection, functional flow morphology and transfer of functional morphology are investigated forfunctional topology design. Functional sketch is proposed to visualize principlesolutions. Evaluation method on principle solution is also discussed.
     (3) Researched on physical structure design method. Constrainedinclusive similarity algorithm is proposed for functional case selection.Functional topology to structure topology mapping based flow interfaceselection method is researched, as well as functional flow interface strengthbased mounting interface design. Evaluation method for physical structuresolution is discussed as well.
     (4) Researched on parametric embodiment design method. Functionalflow morphology based embodiment design trajectory planning method isproposed. Structure parameter-behavior variable coupling matrix based echelondimensionality reduction-partial solving method for structure parameter-behavior variable equations is investigated. A composite movement particleswarm algorithm is proposed to cope with “morbid” structureparameter-behavior variable equations. Assembly validation and optimizationof embodiment solutions is also discussed.
     (5) Prototype system development and theory application are implemented.A computer aided design prototype system named Design Synthesis Lab isdeveloped, which is based on Principle-Structure-Parameter Model. Themethods introduced in this paper are applied in design of electromechanicalsystem of automated numerical microscope to verify the effectiveness of thetheory.
引文
[1]谭建荣.机电产品现代设计:理论,方法与技术[M].北京:高等教育出版社,2009.
    [2] French M. Conceptual design for engineers[M]. London: Springer,1998.
    [3]彭颖红,胡洁. KBE技术及其在产品设计中的应用[M].上海:上海交通大学出版社,2007.
    [4] Pahl G. Engineering design: a systematic approach[M]. London: Springer,2007.
    [5]祖耀.功能特征驱动的机械产品概念设计研究[D].武汉:华中科技大学,2009.
    [6]邹慧君.机械设计原理[M].上海:上海交通大学出版社,1995.
    [7] Vattam S, Helms M E, Goel A K. A content account of creative analogies inbiologically inspired design[J]. AI EDAM,2010,24(4):467-481.
    [8] Feng S C, Song E Y. Information modeling of conceptual design integrated withprocess planning[C]//Proceedings of Symposia for Design for Manufacturability in the2000International Mechanical Engineering Congress and Exposition, Orlando, FL,USA,2000.
    [9] Welch R V, Dixon J R. Guiding conceptual design through behavioral reasoning[J].Research in Engineering Design,1994,6(3):169-188.
    [10] Hoover C W, Jones J B. Improving Engineering Design: Designing for CompetitiveAdvantage[M]. Washington, D. C: National Academy Press,1991.
    [11] Wood III W H, Agogino A M. Case-based conceptual design information server forconcurrent engineering[J]. Computer-Aided Design,1996,28(5):361-369.
    [12] Goel A K. Design, analogy, and creativity[J]. IEEE expert,1997,12(3):62-70.
    [13] Zheng Zhou K. Innovation, imitation, and new product performance: the case of China[J]. Industrial Marketing Management,2006,35(3):394-402.
    [14] Mak T W, Shu L H. Abstraction of biological analogies for design[J]. CIRPAnnals-Manufacturing Technology,2004,53(1):117-120.
    [15] Regli W C, Cicirello V A. Managing digital libraries for computer-aided design[J].Computer-Aided Design,2000,32(2):119-132.
    [16]王玉,邢渊,阮雪榆.机械产品设计重用策略研究[J].机械工程学报,2002,38(5):145-148.
    [17] Vattam S, Helms M E, Goel A K. Biologically-inspired innovation in engineeringdesign: a cognitive study[R]. Technical Report GIT-GVU-07-07, Graphics,Visualization and Usability Center, Georgia Institute of Technology,2007.
    [18] Bar-Cohen Y. Biomimetics: mimicking and inspired-by biology[C]//Proceedings of theSPIE Smart Structures Conference, San Diego, CA.,2005.
    [19] Akao Y. Quality function deployment: integrating customer requirements into productdesign[M]. Cambridge MA: Productivity Press,1990.
    [20]熊伟.质量机能展开[M].北京:化学工业出版社,2005.
    [21] Cristiano J J, Liker J K, White C C. Customer‐Driven Product DevelopmentThrough Quality Function Deployment in the US and Japan[J]. Journal of ProductInnovation Management,2000,17(4):286-308.
    [22] Miguel P A C. The state-of-the-art of the Brazilian QFD applications at the top500companies[J]. International Journal of Quality&Reliability Management,2003,20(1):74-89.
    [23] Chan L K, Wu M L. Quality function deployment: a comprehensive review of itsconcepts and methods[J]. Quality Engineering,2002,15(1):23-35.
    [24] Carnevalli J A, Miguel P C. Review, analysis and classification of the literature onQFD—Types of research, difficulties and benefits[J]. International Journal ofProduction Economics,2008,114(2):737-754.
    [25] Al t uller G S. The innovation algorithm: TRIZ, systematic innovation and technicalcreativity[M]. Worcester, MA: Technical Innovation Center, Inc.,1999.
    [26]檀润华.创新设计: TRIZ发明问题解决理论[M].北京:机械工业出版社,2002.
    [27]根里奇阿奇舒勒.创新40法TRIZ创造性解决技术难题的法则[M].黄玉林,范怡红,译.成都:西南交通大学出版社,2004.
    [28] Dowell J, Long J. Target Paper: Conception of the cognitive engineering designproblem[J]. Ergonomics,1998,41(2):126-139.
    [29] W. Visser. The cognitive artifacts of designing[M]. New York: Routledge,2006.
    [30] Goel A K, Vattam S, Wiltgen B, et al. Cognitive, collaborative, conceptual andcreative—Four characteristics of the next generation of knowledge-based CADsystems: A study in biologically inspired design[J]. Computer-Aided Design,2012,44(10):879-900.
    [31] Freeman P, Newell A. A model for functional reasoning in design[C]//Proceedings ofthe Second International Joint Conference on Artifical Intelligence, London,1971:621–633
    [32] Chakrabarti A, Bligh T P. A scheme for functional reasoning in conceptual design[J].Design Studies,2001,22(6):493-517.
    [33] Gero J S. Design prototypes: a knowledge representation schema for design[J]. AImagazine,1990,11(4):26.
    [34] Gero J S, Kannengiesser U. A framework for situated design optimization[C]//Innovations in Design&Decision Support Systems in Architecture and UrbanPlanning. Springer Netherlands,2006:309-324.
    [35] Qian, L.,Gero, J. S. Function–behavior–structure paths and their role in analogy-baseddesign[J]. Artificial Intelligence for Engineering, Design, Analysis and Manufacturing,1996,10(04):289-312.
    [36] Umeda, Y.,Ishii, M.,Yoshioka, M., et al. Supporting conceptual design based on thefunction-behavior-state modeler[J]. AIEDAM: Artificial Intelligence for Engineering,Design, and Manufacturing,1996,10(04):275-288.
    [37] Deng Y M, Tor S B, Britton G A. A computerized design environment for functionalmodeling of mechanical products[C]//Proceedings of the fifth ACM symposium onSolid modeling and applications, ACM,1999:1-12.
    [38] Cao G, Tan R. FBES model for product conceptual design[J]. International Journal ofProduct Development,2007,4(1):22-36.
    [39] Christophe F, Bernard A, Coatanéa é. RFBS: A model for knowledge representation ofconceptual design[J]. CIRP Annals-Manufacturing Technology,2010,59(1):155-158.
    [40] Gu C C, Hu J, Peng Y H, et al. FCBS model for functional knowledge representationin conceptual design[J]. Journal of Engineering Design,2012,23(8):577-596.
    [41]苗鸿宾.基于FMBS模型的计算机辅助概念设计方法研究[D].上海:同济大学,2008.
    [42] Maher M L, Zhang D M. CADSYN: A case-based design process model[J]. AI EDAM,1993,7(2):97-110.
    [43] Goel A K, Craw S. Design, innovation and case-based reasoning[J]. KnowledgeEngineering Review,2005,20(3):271-276.
    [44] Murdock J W, Goel A K. Meta-case-based reasoning: Using functional models toadapt case-based agents[C]//Proceedings of the Fourth International Conference onCase-Based Reasoning, Vancouver, Canada,2001:407-421.
    [45] Murdock J W, Goel A K. Meta-case-based reasoning: self-improvement throughself-understanding[J]. Journal of Experimental&Theoretical Artificial Intelligence,2008,20(1):1-36.
    [46] Wills L M, Kolodner J L. Towards more creative case-based design systems[C]//Proceedings of the twelfth annual national conference on artificial intelligence (AAAI),Menlo Park, Calif.,1994:50-55.
    [47] Lee D, Lee K H. An approach to case-based system for conceptual ship designassistant[J]. Expert Systems with Applications,1999,16(2):97-104.
    [48]孫書煌,陳家豪. Knowledge representation and reasoning methodology based onCBR algorithm for modular fixture design[J].中國機械工程學刊,2007,28(6):593-604.
    [49] Liu Q, Xi J. Case-based parametric design system for test turntable[J]. Expert Systemswith Applications,2011,38(6):6508-6516.
    [50] Suh N P. The Principle of Design [M]. New York: Oxford University Press,1990.
    [51] Albano L D, Suh N P. Axiomatic approach to structural design[J]. Research inEngineering Design,1992,4(3):171-183.
    [52] Suh N P. Designing-in of quality through axiomatic design[J]. Reliability, IEEETransactions on,1995,44(2):256-264.
    [53] Suh N P. Axiomatic Design: Advances and Applications[M]. New York: OxfordUniversity Press,2001.
    [54] Thielma n J, Ge P. Applying axiomatic design theory to the evaluation andoptimization of large-scale engineering systems[J]. Journal of Engineering Design,2006,17(1):1-16.
    [55] Wu S F, Wang Z Y, Pang L L. Rapid design platform for mechanical products based onCBR[J]. Advanced Materials Research,2010,102:262-266.
    [56]钟掘.复杂机电系统耦合设计理论与方法[M].北京:机械工业出版社,2007.
    [57] Kurtoglu T, Campbell M I. Automated synthesis of electromechanical designconfigurations from empirical analysis of function to form mapping[J]. Journal ofEngineering Design,2009,20(1):83-104.
    [58] Ji Y J, Long K, Qi G N. Research on Knowledge Navigation Supporting Rapid Designof Complex Product[J]. Advanced Materials Research,2011,201:779-789.
    [59]程强.面向可适应性的产品模块化设计方法与应用研究[D].武汉:华中科技大学,2009.
    [60]钟小强.个性化产品快速响应设计方法研究[D].合肥:中国科学技术大学,2008.
    [61]马铁强.支持产品快速设计的CAD模型重用技术研究[D].大连:大连理工大学,2009.
    [62]陈旭玲.机电产品技术演化与升级创新的概念设计研究[D].南京:南京航空航天大学,2011.
    [63] He B, Feng P. Research on collaborative conceptual design based on distributedknowledge resource[J]. The International Journal of Advanced ManufacturingTechnology,2013,5(8):1-18.
    [64] Gu C C, Hu J, Peng Y H. Functional case modelling for knowledge-driven conceptualdesign[J]. Proceedings of the Institution of Mechanical Engineers, Part B: Journal ofEngineering Manufacture,2012,226(4):757-771.
    [65] Liu Z L, Chen Y, Xie Y B. A knowledge-based system for multi-disciplinaryconceptual design synthesis[J]. Proceedings of the Institution of Mechanical Engineers,Part C: Journal of Mechanical Engineering Science,2012,226(12):2950-2966.
    [66]李沛刚.基于功构模式的产品概念设计理论和方法研究[D].济南:山东大学,2010.
    [67]胡晓.支持机械产品概念设计的功能知识聚类方法研究[D].上海:上海交通大学,2011.
    [68] Kitamura Y, Mizoguchi R. Ontology-based description of functional designknowledge and its use in a functional way server[J]. Expert Systems with Applications,2003,24(2):153-166.
    [69]唐敦兵,钱晓明,刘建刚.基于设计结构矩阵DSM的产品设计与开发[M].北京:科学出版社,2009.
    [70] Helms M, Vattam S S, Goel A K. Biologically inspired design: process and products[J].Design Studies,2009,30(5):606-622.
    [71] Wilson J O. A systematic approach to bio-inspired conceptual design[M]. Cambridge:ProQuest,2008.
    [72] Nagel J K S, Stone R B. A computational concept generation technique forbiologically-inspired, engineering design[C]//Proceeding of Design Computing andCognition’10, Stuttgart, Germany,2010:721-740.
    [73] Deng Y M. Function and behavior representation in conceptual mechanical design[J].AI EDAM,2002,16(5):343-362.
    [74] Erden M S, Komoto H, Van Beek T J, et al. A review of function modeling:approaches and applications[J]. Artificial Intelligence for Engineering Design,Analysis and Manufacturing,2008,22(02):147-169.
    [75] Deng Y M, Britton G A, Tor S B. A design perspective of mechanical function and itsobject-oriented representation scheme[J]. Engineering with Computers,1998,14(4):309-320.
    [76] Stone R B, Wood K L. Development of a functional basis for design[J]. Journal ofMechanical Design,2000,122(4):359-370.
    [77] Hirtz J, Stone R B, McAdams D A, et al. A functional basis for engineering design:reconciling and evolving previous efforts[J]. Research in engineering design,2002,13(2):65-82.
    [78] Neches R, Fikes R E, Finin T, et al. Enabling technology for knowledge sharing[J]. AImagazine,1991,12(3):16-36.
    [79] Kitamura Y, Mizoguchi R. Functional ontology for functionalunderstanding[C]//Twelfth International Workshop on Qualitative Reasoning (QR-98),Cape Cod, USA,1998:77-87.
    [80] Kitamura Y, Sano T, Namba K, et al. A functional concept ontology and its applicationto automatic identification of functional structures[J]. Advanced EngineeringInformatics,2002,16(2):145-163.
    [81] Kitamura Y, Mizoguchi R. Ontology-based systematization of functional knowledge[J].Journal of Engineering Design,2004,15(4):327-351.
    [82]王朝瑞.图论[M].北京:北京理工大学出版社,2002.
    [83] Cardone A, Gupta R K, Karnik M. A survey of shape similarity assessment algorithmsfor product design and manufacturing applications[J]. Journal of Computing andInformation Science in Engineering,2003,3:109-118.
    [84] Bustos B, Keim D, Saupe D, et al. Content-based3D object retrieval[J]. ComputerGraphics and Applications, IEEE,2007,27(4):22-27.
    [85] Tangelder J W H, Veltkamp R C. A survey of content based3D shape retrievalmethods[J]. Multimedia tools and applications,2008,39(3):441-471.
    [86]祝耀昌.产品环境工程概论[M].北京:航空工业出版社,2003:12.
    [87] Myung S, Han S. Knowledge-based parametric design of mechanical products basedon configuration design method[J]. Expert Systems with Applications,2001,21(2):99-107.
    [88] Sánchez D, Batet M, Isern D. Ontology-based information content computation[J].Knowledge-Based Systems,2011,24(2):297-303.
    [89] Suh N P. Axiomatic design theory for systems[J]. Research in engineering design,1998,10(4):189-209.
    [90] Tversky A. Features of similarity[J]. Psychological review,1977,84(4):327-352.
    [91] Yuan X, Zou Y. Financial forecasting of Chinese listed companies based on OR-CBRin the principle of K-nearest neighbors[C]//Computer and Automation Engineering(ICCAE),2010The2nd International Conference on, Singapore,2010:217-220.
    [92] Cheng Z H, Jia X S, Gao P, et al. A framework for intelligent reliability centeredmaintenance analysis[J]. Reliability Engineering and System Safety,2008,93(6):784-792.
    [93] Kwong C K, Tam S M. Case-based reasoning approach to concurrent design of lowpower transformers[J]. Journal of Materials Processing Technology,2002,128(1):136-141.
    [94] Pal S K, Shiu S C K. Foundation of Soft Case-Based Reasoning[M]. New Jersey: JohnWiley&Sons,2004.
    [95] Yu W, Liu Y. Hybridization of CBR and numeric soft computing techniques formining of scarce construction databases[J]. Automation in Construction,2006,15(1):33-46.
    [96] Elhadi M T. Bankruptcy support system: taking advantage of information retrieval andcase-based reasoning[J]. Expert Systems with Applications,2000,18(3):215-219.
    [97] Souza R, Carvalho F. Dynamic clustering of interval data based on adaptiveChebyshev distances[J]. Electronics Letters,2004,40(11):658-660.
    [98] Fyson M, Toll D G. Case-based system for slope design[J]. Computers andGeotechnics,2008,35(3):468-478.
    [99] Slonim T Y, Schneider M. Design issues in fuzzy case-based reasoning[J]. Fuzzy Setsand Systems,2001,117(2):251-267.
    [100] Qi J, Hu J, Peng Y H, et al. A case retrieval method combined with similaritymeasurement and multi-criteria decision making for concurrent design[J]. ExpertSystems with Applications,2009,36(7):10357-10366.
    [101] Chang P C, Liu C H, Lai R K. A fuzzy case-based reasoning model for salesforecasting in print circuit board industries[J]. Expert Systems with Applications,2008,34(3):2049-2058.
    [102] Nuutila E. E cient transitive closure computation in large digraphs[D]. Espoo, Finland:Helsinki University of Technology,1995.
    [103] Courtois N, Klimov A, Patarin J, et al. Efficient algorithms for solving overdefinedsystems of multivariate polynomial equations[M]//Bart Preneel. Advances inCryptology—EUROCRYPT2000. Heidelberg, Berlin: Springer,2000:392-407.
    [104] Goldberg D E. Genetic Algorithms in search, optimization, and machine learning[M].New York: Addsin-Wesley Publishing Company,1989.
    [105] Keane A J. Genetic algorithm optimization of multi-peak problems: studies inconvergence and robustness[J]. Artificial Intelligence in Engineering,1995,9(2):75-83.
    [106] Michalewicz Z. Genetic algorithms, numerical optimization, and constraints[C]//Proceedings of the Sixth International Conference on Genetic Algorithms. MorganKaufmann, San Mateo, CA,1995:151-158.
    [107] Kennedy J. Particle swarm optimization[M]//Claude S, Geoffrey W I. Encyclopediaof Machine Learning. New York, US: Springer,2010:760-766.
    [108] Brits R, Engelbrecht A P, Bergh F V D. Solving systems of unconstrained equationsusing particle swarm optimization[C]//Proceedings of the IEEE Conference onSystems, Man and Cybernetics, Hammamet, Tunisia,2002:102-107.
    [109] Doria M M, Gubernatis J E, Rainer D. Solving the Ginzburg-Landau equations bysimulated annealing[J]. Physical Review B,1990,41(10):6335-6340.
    [110] Aarts E, Korst J, Michiels W. Simulated annealing[M]//Edmund K, Burke G K,Search methodologies. New York, US: Springer,2005:187-210.
    [111] Angeline P J. Evolutionary optimization versus particle swarm optimization:Philosophy and performance differences[C]//Evolutionary Programming VII,Heidelberg, Berlin,1998:601-610.
    [112] Hansen N, Ros R, Mauny N, et al. PSO facing non-separable and ill-conditionedproblems[R]. France: INRIA,2008.
    [113] Shi Y, Eberhart R. A modified particle swarm optimizer[C]//IEEE InternationalConference on Evolutionary Computation, Piscataway,1998:69-73.
    [114] Liang J J, Qin A K, Suganthan P N, et al. Comprehensive learning particle swarmoptimizer for global optimization of multimodal functions[J]. EvolutionaryComputation, IEEE Transactions on,2006,10(3):281-295.
    [115] Jia D L, Zheng G X, Qu B Y, et al. A hybrid particle swarm optimization algorithm forhigh-dimensional problems[J]. Computers&Industrial Engineering,2011,61(4):1117-1122.

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