- 學位論文
雕模放電加工之排渣模式及其波列分析與應用
Development of the Debris Flushing Model and A Die-Sinking EDM Pulse Train Analyzer
摘要
雕模放電加工(EDM)系統模型的建立，過去是以電子物理與熱傳學的角度，研究電漿作用及熱加工金屬去除行為等方面。然而影響加工性能的因素，不僅與單發能量傳遞、分配有關，也與所產生的渣如何排出有關。因此雕模放電加工模型的建立，應該將排渣行為的研究視為重要的一環。本文企圖對常見平底圓筒的盲孔加工，透過理論分析以建立排渣模型。首先利用排渣高度與加工深度的組合分析，分別建立四組排渣模式(1,2,3,4)，運用渣量不滅及體積不滅定律，導出差分方程式。然後利用流體混合作用及氣泡作用，改良這四組排渣模式，以嵌合多個加工實驗數據曲線。根據所得的排渣模型指出一般的放電加工過程，隨著加工由淺至深時，如果跳躍高度不變，其排渣模式皆是由底部區與外部區流體直接交換的模式1，進入流體無法直接交換卻只有側部區混合交換作用的模式2，再進入具有長時間側部區混合交換模式3。然而在跳躍高度不足下的淺加工情況下，由於側部區混合不足無法進入模式3。淺加工發生模式2渣濃度劇升現象，是因為混合時間不足，但因為氣泡推升流體，增強排渣，使得發生模式2渣濃度劇升的深度位置比預期加深很多。此一改良排渣模型能呈現混合作用及氣泡作用隨加工深度漸深而消長的現象。 另外，本文也從另一個方式建立加工模型，首先，為研究渣粒影響加工間隙與波列動態特徵，開發一套可同步記錄位置與大量波列資訊的放電波列分析儀(T&S EDM Pulse Analyzer)。將所記錄的資料透過無監督類神經網路Fuzzy ART工具進行狀態分類，並以機率狀態轉移流程圖，描述這些放電波列的波列與空間狀態的變遷情形。透過波列狀態變遷情形的描繪，呈現出加工模型的隨機程序。接著利用此一新式分析儀器，調查不同排渣模式下的加工行為。比較排渣模式1與排渣模式3下，結果發現兩者的放電波列的狀態變遷過程存在很大的差異。本文所建立的研究方法與工具，可以讓未來的放電研究，具備一個完整精確的比較平台，同時也對高速主軸運動所需的技術規格，提供足供參考的理論基礎。
並列摘要
Modeling of the die-sinking Electrical Discharge Machining (EDM) process in the past was mainly focused on the plasma effect or heat related metal removal behavior based on physics and heat transfer theories. But machining performance depends not only on energy distribution of single discharge pulse, but also on the debris removal process. It is therefore important in modeling of EDM process by taking the behavior of debris into account. A debris flushing model for blind hole machining by a flat end cylindrical electrode that provides a means for theoretical analysis and satisfies the experimental results given by other investigators is developed in this dissertation. Four debris flushing modes are classified according to various combinations of jump height of the electrode and machining depth. Difference equations are derived for each mode based on two conservation laws: conservation of debris and conservation of fluid volume. The equations are further modified to take mixing effect and bubbling effect of the fluid into account so as to better match the experimental results. According to the proposed model, the first mode where the external fluid and the fluid beneath the electrode can exchange each other governs the debris flushing process at the beginning stage of machining under normal machining conditions with a fixed jump height. As machining depth is increased, it moves to the second mode where external fluid can no longer exchange with the fluid under the electrode but it is mixed with the fluid in the side gap. Eventually the third mode where the mixing effect is amplified due to a longer time available for mixing is reached. However it should be noted that during a shallow machining the mixing effect would be too weak to bring the process into mode 3 if the jump height is too small. In this case the process remains in mode 2 and the debris concentration increases divergently. It is noted also, the bubbles resulting from machining push the internal fluid and debris upward and a deeper break point than the theoretical one is observed under this condition. Hence the improved debris flushing model can illustrate the dependence of mixing effect and bubble effect on the machining depth. Besides theoretical modeling and simulation, an instrument (T&S EDM Pulse Analyzer) is built to analyze the influences of the debris on the machining gap condition and pulse train characteristics. The instrument is designed to record both of the electrode position and pulse trains information. An unsupervised neural network Fuzzy ART technique is then employed for learning and clustering the collected data. Finally a stochastic process model based on the states of the learned data is developed. Experiments under different debris flushing conditions are carried out. It is found that different flushing modes result in different stochastic models. The analysis method and instrument can provide a better platform to the researcher in the EDM field, especially for the development of high speed jumping for debris flushing.