本文選題：材料選擇系統(tǒng) + 人工神經(jīng)網(wǎng)絡(luò)��； 參考：《北京交通大學(xué)》2013年碩士論文

【摘要】：現(xiàn)代設(shè)計(jì)理論認(rèn)為,產(chǎn)品的性能和成本的70%在設(shè)計(jì)階段就被決定了。材料的選擇又是機(jī)械產(chǎn)品設(shè)計(jì)工作中一個(gè)極其重要的組成部分。很多機(jī)械的重大失效并不是在于它的運(yùn)動(dòng)設(shè)計(jì)和動(dòng)力設(shè)計(jì),而在于材料的種類和牌號(hào)選擇不當(dāng)。近年來,越來越多的新材料被使用,以減輕產(chǎn)品的重量,提高產(chǎn)品的質(zhì)量,降低產(chǎn)品的成本。另外,創(chuàng)新設(shè)計(jì)也需要材料選用方面的創(chuàng)新給予支持。因此如何在數(shù)量巨大的材料庫中選擇最優(yōu)的材料就成了國內(nèi)外學(xué)者研究的熱點(diǎn)。 本文研究和實(shí)現(xiàn)了一個(gè)人機(jī)結(jié)合智能材料選擇系統(tǒng),建立了材料數(shù)據(jù)庫和知識(shí)庫,著重研究了BP神經(jīng)網(wǎng)絡(luò)和專家系統(tǒng)在材料選擇方面的應(yīng)用。本文的工作包括以下幾個(gè)方面： 一、論述了傳統(tǒng)材料選擇過程中存在的問題,分析了國內(nèi)外關(guān)于選材方法和專家系統(tǒng)的研究現(xiàn)狀。根據(jù)選材來源不同,彈簧鋼選材采用人工神經(jīng)網(wǎng)絡(luò),螺紋連接件選材采用專家系統(tǒng)。 二、建立知識(shí)庫,系統(tǒng)通過對(duì)樣本學(xué)習(xí)和總結(jié)歸納獲取專家知識(shí),存放在知識(shí)庫中,根據(jù)知識(shí)庫中的知識(shí)建立系統(tǒng)的選材模塊,包含一個(gè)BP神經(jīng)網(wǎng)絡(luò)和一個(gè)決策樹,通過提問的方式為設(shè)計(jì)人員推薦材料,并且能夠?qū)x材結(jié)果做出合理的解釋。 三、建立測題庫,并通過測題庫生成知識(shí)譜圖,制定判定用戶是否是專家的準(zhǔn)則,對(duì)普通用戶正常選材,對(duì)專家用戶有添加選材樣本的功能。 四、系統(tǒng)采用B/S結(jié)構(gòu),所有服務(wù)都在服務(wù)器上實(shí)現(xiàn),減少客戶端載荷,使用戶能夠更加簡單方便的使用。 文章最后通過一個(gè)應(yīng)用實(shí)例,驗(yàn)證了系統(tǒng)的有效性。本系統(tǒng)不僅可以給設(shè)計(jì)人員推薦合適的材料,也可以為經(jīng)驗(yàn)不足的用戶積累選材知識(shí),具有廣泛的應(yīng)用價(jià)值。
[Abstract]:The modern design theory holds that the 70% of the product's performance and cost is determined at the design stage. The selection of materials is an extremely important part of the design of mechanical products. The major failures of many machinery are not its motion design and dynamic design, but the improper selection of material types and grades in recent years. More and more new materials are used to reduce the weight of the products, improve the quality of the products and reduce the cost of the products. In addition, innovative design needs the support of the innovation of material selection. Therefore, how to select the best material in a large quantity of material has become a hot spot of research at home and abroad.
In this paper, a personal computer combined with intelligent material selection system is studied and implemented. The material database and knowledge base are established. The application of BP neural network and expert system in material selection is emphatically studied. The work of this paper includes the following aspects:
First, the problems in the selection process of traditional materials are discussed, and the research status of the material selection method and expert system at home and abroad is analyzed. According to the different sources of material selection, artificial neural network is adopted in material selection of spring steel, and the expert system is adopted for the selection of threaded connection parts.
Two, the knowledge base is established, and the system is stored in the knowledge base by learning and summarizing the samples, and is stored in the knowledge base. According to the knowledge in the knowledge base, the selection module of the system is set up, including a BP neural network and a decision tree. The material is recommended for the designer by the way of questioning, and it can make a reasonable solution to the material selection results. Release.
Three, establish the test question bank, and generate knowledge spectrum through the test database, make the criterion of judging whether the user is the expert, the normal selection of the ordinary user, and the function of adding the material samples to the expert users.
Four, the system uses B/S structure, all services are implemented on the server, reducing client load, enabling users to be more simple and convenient to use.
At the end of this paper, the effectiveness of the system is verified by an application example. This system can not only recommend suitable materials for designers, but also accumulate material for users with insufficient experience, and has extensive application value.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP182;TH122

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本文編號(hào)：2096256