臺灣博碩士論文加值系統

本研究探討兩臺不同結構國產五軸大型龍門工具機的熱變位特性，主要為環境溫度變化對於整機結構溫升及熱變形的影響。在實驗量測部分，於機台上設置多個關鍵溫度測量點，同時使用非接觸式渦電流位移計量測機台結構關鍵位置以及切削點即時的熱變位。本研究並透過實驗量測的環境與結構溫度以及切削點熱變位修正模擬分析設定之邊界條件，建立可分析機台溫升、溫度分佈以及熱變形的熱、流、固多重物理耦合模型。
為達到靈活的機台結構關鍵點熱平衡溫度調控，本研究嘗試於橫樑上設置多個小型溫控裝置。以本研究所建立且經過實驗結果修正及驗證的多重物理耦合熱變位模型為基礎，獲得環境與橫樑溫度觀測及控制點與機台結構熱變位的模擬實驗數據，再將觀測點的溫度值以及所對應的切削點熱變位數據輸入類神經網路進行學習訓練，建立可有效準確預測機台結構溫升熱變形的類神經網路模型。透過此類神經網路模型，同時搭配運用粒子群最佳化演算法，於機台橫樑上配置多個冷卻水塊，測試調整冷卻水塊的冷卻點參數，調控機台關鍵結構的溫度分佈，進而控制橫樑彎曲幅度及切削點的熱變位。
從側掛式機型觀察到主要為橫樑受環境溫度變化下，使橫樑結構溫度分佈不均，造成刀尖點x軸產生熱變位變化最大。運用風扇以及冷卻水塊針對刀尖點x軸和橫樑彎曲幅度改善；而Box-in-box式機型同樣為橫樑受環境溫度變化下，使橫樑結構溫度分佈不均，造成刀尖點z軸產生熱變位變化最大。運用冷卻水塊針對橫樑彎曲幅度改善，於補償下較容易改善刀尖點z軸熱變位。後續驗證實驗於侧掛式機型，利用模擬所得出參數改善，在風扇實驗改善約10%刀尖點x軸熱變位量，而運用冷卻水塊最高改善約45%的刀尖點x軸熱變位量。

This study investigated the thermal displacement characteristics of two domestic 5-axis large gantry type CNC machining center with different structures, mainly affecting the temperature variation and thermal deformation of the entire machine structure due to environmental temperature changes. In the experimental measurement section, multiple critical temperature measurement points are placed on the machine, and the non-contact eddy current displacement meter is used to obtain the instantaneous thermal displacement. Based on the experimental measurements, a multi-physics simulation model was constructed.
In order to achieve more flexible thermal balance technology to temperature control of the key points of the machine structure, this study attempts to use small cooling water blocks for temperature control on the beam. The study based on the multiple physical coupled thermal displacement model established, the temperature value of the measured point and the corresponding cutting point thermal displacement input neural network are used for learning and training, and a neural network model for effectively predicting the temperature variation and thermal deformation of the machine structure is established respectively. Through the neural network model, multiple cooling water blocks are placed on the beam area of machine tools, adjust the cooling point parameters of multiple cooling water blocks to control the temperature distribution of the key structural positions of the machine, and then achieve the control of the thermal displacement of the cutting point and the bending degree of the beam.
The temperature of the beam is unevenly distributed due to the change of the ambient temperature was observed from the side-mounted model, which causes the thermal displacement of the x-axis of the tool tip to change the most. Use fan and cooling water block to improve the x-axis of the tool tip point and the bending degree of the beam. The Box-in-box model is also caused by the variation of the ambient temperature of the beam, which makes the temperature distribution of the beam structure uneven, resulting in the largest thermal displacement change of the z-axis of the tool tip point. The cooling water block is used to improve the bending degree of the beam, and it is easier to improve the z-axis thermal displacement of the tool tip point under compensation. The follow-up verification experiment was carried out on the side-mounted model, and the parameters obtained by the simulation were improved. In the fan experiment, the x-axis thermal displacement amount of the tool tip point was improved by about 10%, and the cooling water block was used to improve the x-axis thermal displacement amount of the tool tip point about 45%.

中文摘要 i
Abstract ii
目錄 iv
圖目錄 vi
表目錄 xii
第1章 緒論 1
1.1 前言 1
1.2 文獻回顧 2
1.3 研究目的與動機 6
第2章 理論簡介 7
2.1 模擬原理 7
2.1.1 連續方程式 7
2.1.2 動量方程式 7
2.1.3 能量方程式 8
2.1.4 熱彈性力學方程式 9
第3章 數值模擬及最佳化分析 11
3.1 數值分析 11
3.2 模擬流程 11
3.3 物理模型 12
3.3.1 模型建立 12
3.3.2 材料性質 15
3.4 邊界條件設定 16
3.4.1 馬達熱源 16
3.4.2 軸承熱源 17
3.4.3 自然對流邊界 17
3.5 網格收斂性 18
3.6 最佳化分析 24
3.6.1 類神經網路系統原理 24
3.6.2 粒子群最佳化演算法原理 29
第4章 實驗架構 36
4.1 機台設備 36
4.2 溫度測量系統 38
4.3 位移量測系統 42
4.4 冷卻系統 45
第5章 結果與討論 46
5.1 模擬結果 46
5.1.1 側掛式初始模擬模型 46
5.1.2 側掛式模擬風扇改善 53
5.1.3 側掛式模擬冷卻水塊改善 57
5.1.4 Box-in-box式初始模擬模型 73
5.1.5 側掛式與Box-in-box式機型受環溫差異 87
5.1.6 Box-in-box式模擬冷卻水塊改善 88
5.2 實驗結果 96
5.2.1 風扇調控的實驗結果 96
5.2.2 冷卻水塊調控的實驗結果 98
第6章 結論與建議 114
Reference 117

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