| Summary: | 博士 === 國立臺灣大學 === 機械工程學研究所 === 94 === 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.
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