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頁籤選單縮合
題名 | 使用類神經網路預估碳化鎢材料放電加工性能=Using Neuro_Networks to Predict the Performance in the EDM Processing of Tungsten Carbide Material |
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作者 | 何明果; 翁豐在; | 書刊名 | 大同學報 |
卷期 | 28 1998.11[民87.11] |
頁次 | 頁335-341+474 |
分類號 | 446.893 |
關鍵詞 | 類神經網路; 碳化鎢材料; 放電加工; |
語文 | 中文(Chinese) |
中文摘要 | 本文之主要內容係以類神經網路來預估碳化鎢放電加工之性能。針對電流、電壓、電極表面粗糙度和衝擊係數等參數分別建立對於碳化鎢之加工速度、表面粗糙度、放電間隙、電極消耗等放電加工性能之加工模型。當電流、電壓、電極表面粗糙度和衝擊係數等加工參數決定時,所建類神經網路可以有效預估碳化鎢放電加工性能。實驗結果證實此類神經網路有良好的適用性。 |
英文摘要 | In this paper, neuro-network models are constructed to predict the performance in EDM processing of tungsten carbide material. For a given set parameters of current, voltage, surface roughness of electrode and the wear of the electrode, the neuro network models can predict the performance with respect to the material removal rate, surface roughness, gap (clearance) and the wear of the electrode in the EDM processing. Experimental results have shown that the performance can be effectively predicted by the developed neuro-network model. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。