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Multi-objective design optimization of toggle mechanism for a injection machine 俞瀚翔、紀華偉

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Multi-objective design optimization of toggle mechanism for a injection machine 俞瀚翔、紀華偉

E-mail: [email protected]

ABSTRACT

Toggle mechanism is a kind of reciprocating motion cycle, it can be generated in the toggle effect of body, when the body reaches the toggle position, its fixed axis of rotation of the connecting rod and the output to the template of the connecting rod into a position of line, in theory, the output rod of the force can produce infinite.Toggle mechanism because of great interest, and the mechanical characteristics of toggle effect, widely used in the required output power of the great occasions, such as injection molding machines, stamping machines of various types of machinery. Therefore, this study focused on plastic injection molding machine toggle clip of model agencies. First analysis of injection molding machine paper folder mode characteristic equation of motion of bodies, comparison of the design parameters for the velocity ratio, lateral force, and the relationship between stroke, and using the genetic algorithm NSGA-II multi-objective optimization design. In order to achieve maximum mechanical advantage to meet the toggle body size.

Keywords : injection molding、toggle mechanism、genetic algorithm、clamping mechanism Table of Contents

目錄 封面內頁 簽名頁 博碩士論文暨電子檔案上網授權書...iii 中文摘要...iv ABSTRACT...v 誌謝...vi 目錄...vii 圖目錄...x 表目 錄...xii 第一章 緒論...1 1.1 前言...1 1.2 射出成型機之類別...4 1.2.1 肘節式夾模系統...7 1.2.2 直壓式夾模系統...10 1.2.3 複合式 夾模系統...12 1.3 肘節機構的夾模力...13 1.4 文獻回顧...16 1.5 研究動機與目的...17 1.6 論文架構...18 第二章 機構運動特性分 析...19 2.1 肘節機構運動...19 2.2 機構運動分析...19 2.3 設計參數對於運動特性之影響...25 2.3.1 連桿1與連桿2對運動特性的 影響...26 2.3.2 連桿4與連桿5對運動特性的影響...31 2.3.3 設計要點...34 第三章 基因演算法...35 3.1 基因演算法由來與簡 介...35 3.2 演化流程與基本架構...35 3.2.1 初始化(Initial)...38 3.2.2 基因編碼(Gene Encoding)...39 3.2.3 適應值評估(fitness value evaluation)...41 3.2.4 複製(Reproduction)...42 3.2.5 交配(Crossover)...43 3.2.6 突變(Mutation)...46 3.2.7 族群的取代...47 3.2.8 搜 尋終止條件...48 3.3 基因演算法與傳統方法之比較...48 3.4 多目標基因演算法...50 3.5 柏拉圖最佳解...53 第四章 最佳化設計 與分析...56 4.1 設計變數與設計目標...56 4.2 多目標最佳化分析...60 4.2.1 機構倍率極大化與側向力極小化...60 4.2.2 機構倍 率極大化與輸出端速度比值極小化...63 4.2.3 討論...67 第五章 結論...69 5.1 結論...69 5.2 未來展望...69 參考文獻...71 REFERENCES

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參考文獻

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