本文選題：子裝配體識(shí)別 + 帶權(quán)無向聯(lián)接圖　； 參考：《西安工業(yè)大學(xué)》2015年碩士論文

【摘要】：隨著國家工業(yè)化高速發(fā)展,裝配問題已成為產(chǎn)品成本居高不下的原因之一。裝配序列自動(dòng)規(guī)劃面臨的主要難題之一就是子裝配體的識(shí)別。隨著裝配體復(fù)雜程度的增加,裝配過程也往往需要各部門人員的共同分工完成。裝配體的子裝配體識(shí)別可有效實(shí)現(xiàn)裝配體的并行開發(fā)與規(guī)劃。本文著重研究裝配序列規(guī)劃問題中的子裝配體識(shí)別算法,使得對(duì)不同規(guī)模的裝配體都能夠識(shí)別生成子裝配體,以達(dá)到簡(jiǎn)化裝配序列,降低裝配難度與成本的目的。(1)對(duì)裝配序列規(guī)劃中的子裝配體進(jìn)行定義及分析,結(jié)合模糊集與聚類的方法,探究子裝配體識(shí)別算法的基本原理。選取帶權(quán)無向聯(lián)接圖定義裝配的結(jié)構(gòu)信息模型,然后把帶權(quán)無向聯(lián)接圖轉(zhuǎn)換為鄰接關(guān)聯(lián)矩陣,判定出零部件間的隸屬度關(guān)系,最終得出得到子裝配。(2)根據(jù)子裝配體識(shí)別的過程及原理進(jìn)行數(shù)學(xué)建模,在Matlab環(huán)境下對(duì)子裝配體識(shí)別算法進(jìn)行編程,通過三個(gè)具有不同代表性的實(shí)例進(jìn)行驗(yàn)證。第一個(gè)實(shí)例驗(yàn)證子裝配識(shí)別算法能否實(shí)現(xiàn)自主識(shí)別功能,第二個(gè)實(shí)例驗(yàn)證子裝配體識(shí)別算法對(duì)零件間關(guān)聯(lián)關(guān)系的準(zhǔn)確判定,第三個(gè)實(shí)例則是驗(yàn)證裝配模體零件數(shù)目較多時(shí)算法的準(zhǔn)確性。(3)選取算法中的重要因素中的子裝配體個(gè)數(shù)c及模糊指數(shù)m進(jìn)行參數(shù)影響分析。對(duì)參數(shù)取不同值時(shí),算法的有效性及收斂速度會(huì)產(chǎn)生的不同變化,通過分析與評(píng)價(jià),最后為參數(shù)的合理取值提出建議。
[Abstract]:With the rapid development of national industrialization, assembly problem has become one of the reasons of high product cost. One of the main problems in automatic assembly sequence planning is subassembly recognition. With the increase of assembly complexity, the assembly process often needs the common division of labor. Assembly subassembly recognition can effectively realize the parallel development and planning of assembly. In this paper, we focus on the subassembly recognition algorithm in assembly sequence planning, which makes it possible to identify the generated sub-assembly for different size assembly, so as to simplify the assembly sequence. The purpose of reducing the difficulty and cost of assembly is to define and analyze the subassembly in assembly sequence planning, and to explore the basic principle of subassembly recognition algorithm with the method of fuzzy set and clustering. The weighted undirected join graph is selected to define the assembly structure information model, and then the weighted undirected join graph is transformed into the adjacent correlation matrix, and the membership relationship between parts is determined. Finally, we get sub-assembly. 2) according to the process and principle of sub-assembly recognition, we model the mathematical model, program the algorithm of sub-assembly recognition in Matlab environment, and verify it by three representative examples. The first example verifies whether the sub-assembly recognition algorithm can realize the autonomous recognition function, and the second example verifies the accuracy of the sub-assembly recognition algorithm to determine the correlation relationship between parts. The third example is to verify the accuracy of the algorithm when the number of parts of the assembly die is more. (3) to select the number of subassemblies and the fuzzy exponent m of the important factors in the algorithm to analyze the influence of the parameters. The efficiency and convergence rate of the algorithm will vary with different values of parameters. Through analysis and evaluation, some suggestions are put forward for the reasonable selection of parameters.
【學(xué)位授予單位】：西安工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TG95

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本文編號(hào)：1915209