面向產(chǎn)品設(shè)計的知識工程若干關(guān)鍵問題研究
發(fā)布時間：2018-11-02 10:10
【摘要】：知識是人類智能的基礎(chǔ),所以知識也是人工智能問題的求解的基礎(chǔ)。人工智能領(lǐng)域研究的主要問題就是如何從現(xiàn)實世界人類智慧的積累中獲取知識、如何合理地把已獲得的知識表示成計算機(jī)能夠識別和處理的形式以便于存儲、以及如何基于這些知識進(jìn)行推理來解決實際的問題,即知識獲取、知識表示和基于知識推理。上世紀(jì)90年代以來,人工智能、計算機(jī)技術(shù)和CAD技術(shù)不斷發(fā)展和結(jié)合,形成了基于知識工程(KBE)的研究,并且很快KBE已經(jīng)成為一個研究熱點。本論文圍繞著知識工程的一些關(guān)鍵問題進(jìn)行了系統(tǒng)的分析,并以此為基礎(chǔ),對知識建模、知識表達(dá)、知識推理和知識繁衍進(jìn)行了深入的和較為全面的研究,主要包括：(1)基于QFD的知識建模方法通過把顧客的需求有效地轉(zhuǎn)化為技術(shù)措施,并將顧客需求的價值排序反應(yīng)到技術(shù)措施的選擇當(dāng)中,從而能夠確定出滿足顧客需求的設(shè)計方案。以QFD為主線,采用情景分析法、KJ法、AHP法等工具,構(gòu)建基于QFD的產(chǎn)品概念設(shè)計和產(chǎn)品方案設(shè)計的知識模型。(2)面向?qū)ο蠛涂蚣芊椒ㄏ嘟Y(jié)合的知識表示方法現(xiàn)在產(chǎn)品設(shè)計的復(fù)雜性,不僅需要數(shù)值計算,而且需要用到非參數(shù)化知識,如啟發(fā)式經(jīng)驗等。單一知識表示法難以全面、有效地表達(dá)各種設(shè)計所需求的知識。本文基于面向?qū)ο笏枷牒涂蚣苤R表示法的優(yōu)勢,提出了基于面向?qū)ο笤O(shè)計思想,借用框架表示法中槽結(jié)構(gòu)的產(chǎn)品設(shè)計知識表示方法。(3)基于案例和基于規(guī)則集成的知識推理方法本文提出了一種智能化的產(chǎn)品設(shè)計知識推理機(jī)制,幫助設(shè)計人員解決技術(shù)難度大和設(shè)計時間長的問題。首先根據(jù)基于QFD產(chǎn)品設(shè)計知識建模方法確定的產(chǎn)品技術(shù)參數(shù)；然后采用基于案例推理的人工智能技術(shù),根據(jù)設(shè)計專家經(jīng)驗知識進(jìn)行推理,搜索產(chǎn)品設(shè)計案例庫中與QFD得出的產(chǎn)品技術(shù)參數(shù)最相似的產(chǎn)品設(shè)計方案；最后采用基于規(guī)則推理的方法,根據(jù)規(guī)則庫中領(lǐng)域?qū)＜液驮O(shè)計工程師設(shè)定的產(chǎn)品設(shè)計修改規(guī)則,提出修改建議,制定產(chǎn)品設(shè)計方案。(4)基于混沌開關(guān)的遺傳算法的知識繁衍方法因為傳統(tǒng)遺傳算法的局限性,同時復(fù)雜產(chǎn)品的優(yōu)化設(shè)計是一個離散性、多變量、非線性、多目標(biāo)混合型規(guī)劃問題,所以很難求解產(chǎn)品設(shè)計優(yōu)化問題。本文把遺傳算法和混沌理論相結(jié)合起來,提出了利用混沌搜索有效基因的方法：利用混沌的遍歷性特點,動態(tài)地搜索個體的基因座空間,并使搜索到的基因座上的等位基因產(chǎn)生變異,從而產(chǎn)生一個新的個體�，F(xiàn)代產(chǎn)品設(shè)計包括對知識的繼承、集成、創(chuàng)新和管理,它是一個知識驅(qū)動的創(chuàng)造性過程。本論文以變壓器智能設(shè)計為背景,設(shè)計了變壓器的主體和構(gòu)件的對象模型,以及以槽表示的數(shù)據(jù)和屬性模型；設(shè)計了產(chǎn)品和零件主模型的案例表示、索引機(jī)制、相似度模型,以及案例的搜索算法；設(shè)計了基于規(guī)則的推理網(wǎng)絡(luò)、規(guī)則的表示方法,以及基于規(guī)則的變壓器設(shè)計案例修改算法；最后,提出了基于混沌開關(guān)的遺傳算法求解模型,并基于變壓器的優(yōu)化設(shè)計模型進(jìn)行了實例驗證。
[Abstract]:Knowledge is the foundation of human intelligence, so knowledge is also the foundation of solving artificial intelligence problem. The main problem in the field of artificial intelligence is how to acquire knowledge from the accumulation of human intelligence in the real world, how to properly represent the acquired knowledge as the form of computer can recognize and process in order to facilitate storage, And how to solve practical problems based on these knowledge, namely knowledge acquisition, knowledge representation and knowledge-based reasoning. Since the 1990s, the development and integration of artificial intelligence, computer technology and CAD technology have formed the research of KBE based on knowledge engineering (KBE), and KBE has become a hot spot soon. This paper systematically analyzes some key problems about knowledge engineering, and makes a thorough and more comprehensive study on knowledge modeling, knowledge representation, knowledge reasoning and knowledge reproduction. (1) The knowledge modeling method based on QFD effectively transforms the customer's needs into technical measures and sorts the value ranking of customer requirements into the selection of technical measures, so as to determine the design scheme to meet the requirements of customers. Taking QFD as the main line, the knowledge model of product conceptual design and product design based on QFD is constructed by using tools such as scene analysis method, AHP method and AHP method. (2) The knowledge representation method combined with object-oriented and framework methods now has the complexity of product design, not only numerical calculation but also non-parametric knowledge, such as heuristic experience, etc. The single knowledge representation is difficult to fully and effectively express the knowledge of various design requirements. Based on the advantage of object-oriented idea and framework knowledge representation, this paper proposes a method for expressing product design knowledge based on the object-oriented design idea and the groove structure in the frame representation. (3) Based on case-based and rule-based knowledge reasoning method, an intelligent reasoning mechanism of product design knowledge is put forward to help designers solve the problems of large technical difficulty and long design time. firstly, according to the product technical parameters determined by the QFD product design knowledge modeling method, then adopting the case-based reasoning based artificial intelligence technology, reasoning according to the experience knowledge of the design experts, The product design scheme is the most similar to the product technical parameters obtained from QFD in the product design case library, and finally, based on the rule-based reasoning method, according to the product design modification rules set by the domain expert and the design engineer in the rule base, the modification suggestions are put forward and the product design plan is formulated. (4) The knowledge reproduction method of genetic algorithm based on Hash switch is the limitation of traditional genetic algorithm, and the optimization design of complex products is a problem of discrete, multi-variable, non-linear and multi-objective hybrid programming, so it is difficult to solve the problem of product design optimization. In this paper, the genetic algorithm and the genetic algorithm are combined, and the method for searching the effective gene by using the genetic algorithm is put forward: using the ergodic characteristics of the genetic algorithm, the locus space of an individual is dynamically searched, and the allele of the searched locus is mutated, thereby creating a new individual. Modern product design includes the inheritance, integration, innovation and management of knowledge, which is a creative process of knowledge-driven. Based on the transformer intelligent design, this paper designs the object model of the main body and the component of the transformer, and the data and attribute model represented by the slot, and designs the case representation, index mechanism, similarity model of the product and part master model, as well as the search algorithm of case. This paper designs a rule-based reasoning network, a rule-based representation method, and a rule-based transformer design case modification algorithm. Finally, a genetic algorithm solution model based on the rule-based switch is put forward, and an example verification is carried out based on the optimized design model of the transformer.
【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TB472;TP18
，
本文編號：2305725
[Abstract]:Knowledge is the foundation of human intelligence, so knowledge is also the foundation of solving artificial intelligence problem. The main problem in the field of artificial intelligence is how to acquire knowledge from the accumulation of human intelligence in the real world, how to properly represent the acquired knowledge as the form of computer can recognize and process in order to facilitate storage, And how to solve practical problems based on these knowledge, namely knowledge acquisition, knowledge representation and knowledge-based reasoning. Since the 1990s, the development and integration of artificial intelligence, computer technology and CAD technology have formed the research of KBE based on knowledge engineering (KBE), and KBE has become a hot spot soon. This paper systematically analyzes some key problems about knowledge engineering, and makes a thorough and more comprehensive study on knowledge modeling, knowledge representation, knowledge reasoning and knowledge reproduction. (1) The knowledge modeling method based on QFD effectively transforms the customer's needs into technical measures and sorts the value ranking of customer requirements into the selection of technical measures, so as to determine the design scheme to meet the requirements of customers. Taking QFD as the main line, the knowledge model of product conceptual design and product design based on QFD is constructed by using tools such as scene analysis method, AHP method and AHP method. (2) The knowledge representation method combined with object-oriented and framework methods now has the complexity of product design, not only numerical calculation but also non-parametric knowledge, such as heuristic experience, etc. The single knowledge representation is difficult to fully and effectively express the knowledge of various design requirements. Based on the advantage of object-oriented idea and framework knowledge representation, this paper proposes a method for expressing product design knowledge based on the object-oriented design idea and the groove structure in the frame representation. (3) Based on case-based and rule-based knowledge reasoning method, an intelligent reasoning mechanism of product design knowledge is put forward to help designers solve the problems of large technical difficulty and long design time. firstly, according to the product technical parameters determined by the QFD product design knowledge modeling method, then adopting the case-based reasoning based artificial intelligence technology, reasoning according to the experience knowledge of the design experts, The product design scheme is the most similar to the product technical parameters obtained from QFD in the product design case library, and finally, based on the rule-based reasoning method, according to the product design modification rules set by the domain expert and the design engineer in the rule base, the modification suggestions are put forward and the product design plan is formulated. (4) The knowledge reproduction method of genetic algorithm based on Hash switch is the limitation of traditional genetic algorithm, and the optimization design of complex products is a problem of discrete, multi-variable, non-linear and multi-objective hybrid programming, so it is difficult to solve the problem of product design optimization. In this paper, the genetic algorithm and the genetic algorithm are combined, and the method for searching the effective gene by using the genetic algorithm is put forward: using the ergodic characteristics of the genetic algorithm, the locus space of an individual is dynamically searched, and the allele of the searched locus is mutated, thereby creating a new individual. Modern product design includes the inheritance, integration, innovation and management of knowledge, which is a creative process of knowledge-driven. Based on the transformer intelligent design, this paper designs the object model of the main body and the component of the transformer, and the data and attribute model represented by the slot, and designs the case representation, index mechanism, similarity model of the product and part master model, as well as the search algorithm of case. This paper designs a rule-based reasoning network, a rule-based representation method, and a rule-based transformer design case modification algorithm. Finally, a genetic algorithm solution model based on the rule-based switch is put forward, and an example verification is carried out based on the optimized design model of the transformer.
【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TB472;TP18
，
本文編號：2305725
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