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研究生:吳立仁
研究生(外文):Li-Jen Wu
論文名稱:鋼板熱彎成形模擬分析研究
論文名稱(外文):Study on Simulation and Analysis of Heat Bending for Forming Steel Plates
指導教授:郭興家郭興家引用關係
指導教授(外文):Hsing-Chia Kuo
學位類別:博士
校院名稱:國立成功大學
系所名稱:造船及船舶機械工程學系
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:2001
畢業學年度:90
語文別:中文
論文頁數:129
中文關鍵詞:熱彎模糊控制器灰色溫度預測器
外文關鍵詞:Heat bendingFuzzy controllerGrey Predictor
相關次數:
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熱彎加工常使用於板金與造船工業彎板成形製程,加工過程常須依賴有經驗的技術人員。低製造成本及低人力朝向自動化的開發,是目前熱彎加工首要目標。研究中使用目前板金與造船廠常用的兩種入熱源─雷射與氧乙炔火炬熱源。針對入熱量Q、熱源移動速度V、限制條件(有限制及無限制條件)、加熱路徑(單一加熱線及12條加熱線)、熱影響區、溫度場、冷卻速率 、彎板熱彎變形(角變形、縱向變形及熱挫曲變形)等以熱彈塑性理論、三棒分析及二維動態溫度場分析研究鋼板熱彎成形的控制與模擬方法。本文目的於應用灰色建模方法與模糊控制理論,研究應用灰色預測器與熱彎鋼板模糊控制器於熱彎鋼板模擬分析。灰色溫度預測器的應用是協助鋼板溫度預測,及分析熱彈塑特性與預測下一量測點或下一時間點溫度信息,以協助熱彎回授控制及物理行為分析。在灰色建模方法,本文是採用新信息、置零新信息、等維新信息及置零等維新信息四種G(1,1) 建模方法建模比較,以探求不同維度M(=4~100)下溫度預測結果,由結果知置零等維新信息結果較佳誤差在2%以下,建模維度M=4和5所得效果最佳,顯示灰色溫度預測器低建模維度除具有較快回授,同時也具有較低的誤差值。熱彎鋼板模糊控制器的開發研究,是由溫度場分析與熱彎過程行為資訊與結果,架構出 模糊規則庫的控制器,以達成熱彎曲至預期設計放樣鋼板彎曲外型。研究中以給定一放樣鋼板設計曲面及12條加熱路徑與 值之加工條件,予以線上熱彎實驗,比較所設計之模糊熱彎鋼板系統的能力。結果顯示在10條量測線的比對條件,得誤差為8%的加工板形。在模糊控制器於馬達輸出的結果,也驗證模糊控制器於熱彎鋼板系統有良好的熱源移動速度控制能力。
The heat bending process has long been used for plate forming in the metal forming and shipbuilding industries, and has always depended on skilled workers. Since metal forming and shipbuilding companies need a reduction in production costs and in the number of workers they employ, an increased use of automation is desirable. This study discusses a laser source and an oxyacetylene torch source. The heat input intensity, Q, the speed of the servomotor, V, the constraint conditions, the heating paths, the heat affected zone, the temperature field, the cooling rate, , and the dynamic displacement of the plate during heat bending etc. are all discussed. Thermoplastic theories, three-bar analysis, and two dimensional temperature fields are used to study control methods and to simulate the heat bending processes. This paper considers the advantages of applying Grey and Fuzzy theories to the analysis and simulation of the heat bending process for steel plates by using a Grey predictor and an on-line Fuzzy controller. A Grey predictor is applied to assist in the prediction of the temperature within the steel plate, and in the analysis of its thermoplastic characteristics. The temperature of the steel plate at the next measuring data point is predicted, and this information can then be used as feedback within the controller. The Grey method uses four types of modeling algorithm with G(1,1) methods. These algorithms are constructed, discussed, and compared using different temperature dimensions, M, where M lies between 4 and 100. The four kinds of Grey G(1,1) modeling methods are the New-Dimension G(1,1) Grey Method (NDGM), the New-Dimension-Zero-First-Term G(1,1) Grey Method (NDZFTGM), the Same-Dimension G(1,1) Grey Method (SDGM), and the Same-Dimension-Zero-First-Term G(1,1) Method (SDZFTGM). The best prediction method of the boundary temperature is proven to be the SDZFTGM, and the optimal dimensions, M, of the temperature series are found to be 4 and 5. Under these conditions the error is under 2%, which is lower than the error given by the three other kinds of Grey methods. The fuzzy controller was developed based upon the simulation of the temperature field and the physical behaviors manifested in experimentation. The fuzzy controller fine-tunes the torch speed, V, by applying a set of rules and a set of membership functions. The results of the experiment verified the use of a fuzzy controller in heat bending experiments. The conditions of heat bending using 12 heating lines, and the values of during the heat bending experiments. The experimental results discussed in this paper use the conditions with fuzzy control to bend a plate into the required shape and to prove the performance of the heat bending fuzzy controller. During the heat bending process the average displacement along 10 measuring lines was compared with the displacement of the required shape. It was found that there was an 8% error in displacement. It was found that a fuzzy controller is effective in governing the speed of the servomotor driving the heat source.
授權書
考試合格證明書
中文摘要 I
英文摘要 III
致謝 V
目錄 VII
表目錄 X
圖目錄 XI
符號說明 XVII
第一章 緒論 1
1-1 研究動機 1
1-2 文獻回顧 3
1-3 研究方法及目的 6
第二章 理論分析與探討 8
2-1 熱彎板的彈塑性分析 8
2-1-1 溫度場與熱影響區分析 8
2-1-2 熱變形與three-bar分析 17
2-2 灰色理論於熱彎板溫度預測 37
2-3 模糊理論與分析 42
2-3-1 模糊理論 42
2-3-2 模糊控制鋼板熱彎系統 49
第三章 模擬與實驗方法 56
3-1 第一階段雷射熱彎鋼板實驗原理與方法 57
3-1-1 雷射熱彎鋼板實驗架設步驟 58
3-1-2 雷射熱彎實驗設備 62
3-1-3 雷射熱彎實驗步驟 64
3-1-4 雷射熱彎鋼板數值模擬 65
3-2 第二階段氧乙炔火炬熱彎鋼板實驗原理與方法 66
3-2-1 氧乙炔火炬熱彎鋼板實驗架設步驟 67
3-2-2 氧乙炔火炬熱彎實驗及模擬方法 70
第四章 模擬與實驗結果及討論 77
4-1 第一階段雷射熱彎鋼板實驗與模擬結果 77
4-1-1 灰色溫度預測器 82
4-1-2 雷射熱彎之形變實驗與模擬 87
4-1-3 雷射熱彎系統模糊控制之模擬 88
4-2 第二階段氧乙炔火炬熱彎鋼板實驗與模擬結果 90
4-2-1 氧乙炔火炬熱彎鋼板溫度場分佈及灰色溫度預測器應用 90
4-2-2 單一加熱線彎對無拘束條件(自由端)鋼板實驗結果與分析108
4-2-3 12條加熱線於氧乙炔火炬熱彎鋼板實驗結果 112
4-2-4 模糊控制在氧乙炔火炬熱彎鋼板系統 117
第五章 未來發展趨勢與結論 121
5-1 鋼板熱彎未來的發展趨勢 121
5-2 總結 123
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