Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 盧彥男 | en_US |
dc.contributor.author | 秦繼華 | en_US |
dc.date.accessioned | 2014-12-12T01:15:25Z | - |
dc.date.available | 2014-12-12T01:15:25Z | - |
dc.date.issued | 2008 | en_US |
dc.identifier.uri | http://140.113.39.130/cdrfb3/record/nctu/#GT009514528 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/38519 | - |
dc.description.abstract | 本論文主要討論BTA深孔鑽(Boring and Trepanning Association)之加工品質,我們依據圓孔的粗糙度值來評斷工件品質的好壞,其最終目的為在一定的加工條件下獲得最佳的工件品質。 深孔鑽削是一項複雜的加工過程,各項加工參數對最後加工結果有很大的影響。本研究依加工情況把實驗分為四組:單純供油實驗、貧油實驗、制振實驗、貧油與制振混合實驗。藉由上述實驗討論粗糙度值與各項加工參數(主軸轉速、刀具進給率、MR damper位置、MR damper電流、壓縮氣壓)之間的關係。 實驗規劃為利用田口式直交表作參數因子的安排,以達到節省實驗組數的目的。實驗結果的分析為利用田口式參數設計作第一階段的最佳化設計,而第二階段的最佳化為利用倒傳遞類神經網路進行。經實驗結果顯示,經兩階段最佳化後的參數條件可以加工出較好的圓孔品質。 | zh_TW |
dc.language.iso | zh_TW | en_US |
dc.subject | 深孔鑽 | zh_TW |
dc.subject | 田口氏法 | zh_TW |
dc.subject | 類神經網路 | zh_TW |
dc.subject | 參數設計 | zh_TW |
dc.subject | 貧油 | zh_TW |
dc.subject | 制振 | zh_TW |
dc.subject | deep-hole drilling | en_US |
dc.subject | Taguchi method | en_US |
dc.subject | Neural Network | en_US |
dc.subject | parameters design | en_US |
dc.subject | minimal quantity of lubricant | en_US |
dc.subject | vibration suppression | en_US |
dc.title | 以類神經網路與田口氏法分析貧油潤滑及磁流變液制振器對深孔鑽加工品質之影響 | zh_TW |
dc.title | Taguchi Method and Neural Network Analyses of Drilling Quality of Deep Hole Drilling Influenced by Minimal Quantity Lubrication and Magneto-Rheological Fluid Vibration Damper | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | 機械工程學系 | zh_TW |
Appears in Collections: | Thesis |
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