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研究生:蔡松均
研究生(外文):Song - Jun Tsai
論文名稱:光纖雷射鋁合金對接焊製程最佳化之研究
論文名稱(外文):Study on Optimization Process of Fiber Laser Butt Welding of Aluminum Alloys
指導教授:楊永光楊永光引用關係
指導教授(外文):Yung - Kuang Yang
口試委員:蔡志弘呂鴻猷
口試委員(外文):Chih - Hung TsaiHung - Yu Lu
口試日期:102.06.21
學位類別:碩士
校院名稱:明新科技大學
系所名稱:精密機電工程研究所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2013
畢業學年度:101
語文別:中文
論文頁數:104
中文關鍵詞:光纖雷射焊接中央合成設計反應曲面法類神經網路基因演算法
外文關鍵詞:Fiber Laser Butt WeldingCentral Composite DesignResponse Surface MethodArtificial Neural NetworkGenetic Algorithm
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本研究係應用實驗計劃法探討光纖雷射6061T6鋁合金焊接製程最佳化,選定雷射功率(Laser Power)、加工速度(Processing Speed)、脈衝頻率(Pulse Frequency)、氣體流量(Gas Flow)為焊接之製程參數,研討對接焊的焊道表面結構、斷面與拉伸強度對於製程參數之關係。

首先利用反應曲面法(Response Surface Method, RSM)之中央合成設計(Central Composite Design,CCD)規劃不同的雷射加工參數組合執行實驗;同時,本研究亦藉由光學顯微鏡觀察焊道表面結構、斷面與拉伸強度之影響,最後進行數據分析與研討。

藉由變異數分析(Analysis of Variance, ANOVA)了解光纖雷射對接焊之製程參數對拉伸強度的重要影響因子,並分別應用反應曲面法(Response Surface Method, RSM)之迴歸分析(Regression Analysis)統計技術,完成建構光纖雷射對接焊的製程參數與拉伸強度之反應曲面方程式(Response Surface Equation),以及運用類神經網路(Artificial Neural Network, ANN)搭配基因演算法(Genetic Algorithms, GA),透過系統輸入與輸出所構成的資料,建立系統預測模型,進而求得最佳製程參數組合;再藉由殘差分析對所建構之模型,進行模型適當性檢驗,並比較兩種方法之精確性。

經由研究結果顯示,雷射功率與加工速度係影響熔池深度與拉伸強度的最主要焊接參數,並比較上述兩種方法之殘差預測結果,發現類神經網路搭配基因演算法(GA)稍微優於反應曲面法(RSM)。

關鍵詞:光纖雷射焊接,中央合成設計,反應曲面法,類神經網路,基因演算法
This study is analyzed variations of tensile strength that depend on the fiber laser butt welding process during the micro-spot welding of the 6061T6 aluminum.

This paper applies Design-Expert to generate the technology of central composite design (CCD) which integrating response surface methodology(RSM), and back-propagation neural network (BPNN) integrate the genetic algorithm(GA) method are proposed to optimize the laser welding process. By regression analysis, a mathematical predictive model fiber laser butt welding process parameters and the tensile strength of the response surface equation were developed in terms of the process parameter. The combining BPNN/GA optimization method can be obtained for the appropriate combinations of the optimal parameter settings. In addition, analysis of variance (ANOVA) was implemented to identify significant factors for the fiber laser butt welding process parameters, and results from the BPNN with integrated GA were compared with those from the RSM approach. At the same time, used an optical microscope to observe the bead shape, size, penetration and fracture surface of the fusion zone. A confirmation experiment run was also conducted in order to validate the optimal setting of welding process parameters.

The results found that the laser power and processing speed is the most important welding parameters affect the pool depth and tensile strength. That the proposed algorithm of GA approach has better prediction and confirmation results than the RSM method.

Keywords: Fiber Laser Butt Welding, Central Composite Design, Response Surface Method, Artificial Neural Network, Genetic Algorithm.
摘 要 i
Abstract ii
誌 謝 iii
目 錄 iv
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 研究目的與動機 1
1.2 文獻探討 4
1.3 本文架構 9
第二章 研究理論 11
2.1 光纖雷射焊接加工方法 11
2.1.1 光纖雷射原理 11
2.1.2 光纖雷射特性與優點 12
2.1.3 光纖雷射焊接形式 13
2.2 實驗設計法 14
2.2.1 田口品質工程 15
2.2.1.1 田口方法步驟 15
2.2.1.2 信號雜音比 16
2.2.1.3 直交表 17
2.2.2 中央合成設計 18
2.2.2.1 旋轉性 19
2.2.2.2 球面的CCD 20
2.2.2.3 CCD的中心點試驗 20
2.2.2.4 立方體範圍 20
2.2.2.5 區集劃分 22
2.2.3 田口與中央合成設計之比較 23
2.3 反應曲面法 24
2.3.1 統計檢定理論 26
2.3.2 變異數分析 27
2.3.3 迴歸分析 30
2.3.4 殘差檢定 32
2.3.5 期望函數 33
2.4 類神經網路 35
2.4.1 類神經網路簡介 36
2.4.2 倒傳遞類神經網路 38
2.4.2.1 倒傳遞網路的架構 39
2.4.2.2 倒傳遞網路的訓練 41
2.4.2.3 網路演算法 41
2.4.3 倒傳遞網路之重要因子 44
2.4.4 類神經網路的優點 45
2.5 基因演算法演算流程 46
2.5.1 基因演算流程 46
2.5.2 複製 48
2.5.3 交配 48
2.5.4 交配機率 49
2.5.5 突變 49
2.5.6 突變機率 49
2.5.7 適應函數 50
2.5.8 編碼與字串長度 50
2.5.9 終止條件 51
第三章 實驗之規劃與研究流程 52
3.1 定義目標 53
3.2 實驗材料 53
3.3 中央合成設計之規劃 56
3.4 實驗設備 58
3.4.1 光纖雷射焊接試驗機台 58
3.4.2 品質特性測量儀器 58
3.5 分析工具 59
3.5.1 反應曲面法 60
3.5.2 類神經網路結合基因演算法 62
第四章 實驗結果與分析 65
4.1 實驗規劃結果 65
4.2 拉伸實驗結果 66
4.3 斷面觀測與焊道表面結構觀測 67
4.3.1 焊道斷面觀測 67
4.3.2 焊道表面結構觀測 69
4.4 反應曲面法 70
4.4.1 變異數分析 70
4.4.2 迴歸模型建構 71
4.4.3 殘差分析 72
4.4.4 最佳化結果 77
4.4.5 三維反應曲面圖 78
4.5 類神經網路預測結果 78
4.6 基因演算法最佳化預測結果 80
4.7 驗證實驗 80
第五章 結論與未來展望 81
5.1 結論 81
5.2 未來展望 82
參考文獻 83
附錄A 達到95%信心水準之最小F值 89
附錄B 光纖雷射焊接機台詳細規格 90
附錄C 動態疲勞試驗機詳細規格 91
附錄D 影像量測顯微鏡 92
作者簡介 93

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