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研究生:謝博雄
研究生(外文):Po-Syong Xie
論文名稱:遠距即時預測磨削加工之磨削力與表面粗糙度
論文名稱(外文):Remoting Real-Time Prediction Grinding Force and Surface Roughness in the Grinding Process
指導教授:蔡曜陽蔡曜陽引用關係
口試委員:王世明廖運炫
口試日期:2013-07-29
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:機械工程學研究所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2013
畢業學年度:101
語文別:中文
論文頁數:108
中文關鍵詞:磨削力表面粗糙度即時預測粒度切線速度工件速度輪磨深度
外文關鍵詞:grinding forcessurface roughnessreal-time predictiongrain grittangential velocityworkpiece feeddepth of cut
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磨削加工為精密加工中常見的加工方式,機械加工過程中磨削加工是屬於最後的加工階段同時也是最重要的過程,因為關係著尺度上的精確性與表面品質。一般磨削加工中,磨削力過大會讓工件表面粗糙度較差且需要等待磨削加工後才能經由量測得知,為了能夠即時的判斷工件磨削力與表面粗糙度的趨勢及品質的優劣,因此本研究將配合SkyMars軟體建立遠距監測磨削力與表面粗糙度的數值來評估工件品質的好壞。
本研究將使用不同輪磨深度、工件速度、砂輪切線速度、砂輪粒度、磨粒種類對磨削力與表面粗糙度的關係,以瞭解輪磨的加工範圍是否發生犁切或燒傷等加工異常現象,接著再進行輪磨驗證預測磨削力模型與預測表面粗糙度Ra值模型的誤差值。
觀察磨削力實驗結果發現,磨削力隨著輪磨深度、工件速度、砂輪粒度增加而上升,隨著砂輪切線速度增加而下降,但輪磨深度對磨削力的影響程度大於工件速度、砂輪切線速度、砂輪粒度、砂輪磨粒種類。然而在觀察表面粗糙度Ra值實驗結果發現,表面粗糙度Ra值成與磨削力成正比,其中砂輪粒度對表面粗糙度Ra值則是影響最大。
經由實驗結果得知,降低輪磨深度與工件速度或增加砂輪切線速度可以減少磨削力的產生與表面粗糙度Ra值,但若輪磨深度與工件速度乘積遠小於砂輪切線速度,則磨削力較不可預測且表面粗糙度Ra值會隨著工件速度增加而減少。
本實驗由此實驗結果推論可預測加工區為磨削條件在砂輪號數#60~#120、輪磨深度5μm~10μm、砂輪切線速度450m/min~1800m/min、砂輪切線速度與工件速度比值在100以內,在可預測加工區內磨削力與表面粗糙度Ra值可以經由公式求得,預測磨削力最大誤差為19%,預測表面粗糙度Ra值最大誤差為8.86%且磨削力與表面粗糙度Ra值成正比關係。在加工過程中亦可透過遠距的方式可以快速的將可能會發生犁切、燒傷等異常的區域讓操作員得知以告知是否繼續加工。


Grinding processing is the common processing method in the precision processing, which plays the most important part in the final stage of the processing because it relates to surface accuracy and scale quality. In general grinding, excess grinding force will rough workpiece'' surface, and which has to be measured after grinding. In order to judge the trends of grinding force and surface roughness efficiently, this study will cooperate with SkyMars, establishing the model of grinding force and surface roughness to estimate the quality of workpiece.
This study applies different grinding depth, workpiece''s speed, wheel''s tangential velocity, wheel abrasive size, and abrasive type to explore the relationship between the grinding force and surface roughness. Further, this study investigates whether the range of grinding process leads abnormal phenomena such as plowing force or burning. Eventually, applying grinding verification to predict error value on grinding force model and surface roughness Ra value model is needed.
According to the consequence of grinding force experiment, grinding force increases depend on increasing grinding depth, workpiece''s speed and wheel abrasive; while decreasing when grinding wheel''s tangential speed increases. However, grinding depth has an effect on grinding force more than workpiece''s speed, wheel''s tangential velocity, wheel abrasive size, and abrasive type. Based on the consequence of surface roughness Ra value experiment, surface roughness Ra value and grinding force are in direct proportion, and wheel abrasive size has great effect on surface roughness Ra value.
The result shows that reducing grinding depth and workpiece''s speed or gaining wheel''s tangential velocity speed decrease grinding force and surface roughness Ra value. However, if the product of grinding depth and workpiece''s speed are much less than wheel''s tangential velocity, grinding force is hard to be predicted, and surface roughness Ra value decreases depend on increasing workpiece''s speed.
According to the result, the study predicts that is working region in grinding grain grit number #60~#120, depth of cut is between 5μm~10μm in grinding, wheel''s tangential velocity speed is between 450m/min~1800m/min, the ratio of wheel''s tangential velocity speed and workpiece''s speed are less than 100. Grinding force and surface roughness Ra value can be measured in predicable processing area through formula. The result shows that the maximal error of predicable grinding force is 19%, and the maximal error of predicable surface roughness Ra value is 8.86%. Further, grinding force and surface roughness Ra value are in direct proportion. During processing, distance method is the efficient way to inform operators whether keeping processing if they are aware of abnormal phenomena such as plowing force or burning.


口試委員會審定書 II
致謝 II
摘要 III
Abstract V
目錄 VII
圖目錄 XI
表目錄 XV
第一章 緒論 1
1.1 研究背景 1
1.2 文獻回顧 2
1.3 研究動機與目的 9
1.4 論文大綱 10
第二章 相關背景知識與技術理論 11
2.1 磨削理論 11
2.2 磨削力 12
2.2.1 切削階段之磨削力 12
2.2.2 摩擦階段之磨削力 13
2.2.3 犁切階段之磨削力 15
2.2.4 總和之磨削力 18
2.3 SkyMars 18
2.3.1 SkyMars架構 18
2.3.2 SkyMars設置 20
2.3.3 SkyMars擷取 20
2.4砂輪 21
2.4.1 磨粒種類 23
2.4.2 粒度 24
2.4.3 結合度 24
2.4.4 組織 25
2.4.5 結合劑 25
2.5 表面粗糙度理論 26
2.5.1 表面組織定義 26
2.5.2 表面量測相關術語 27
2.5.3 表面粗糙度表示方式 28
第三章 實驗步驟與方法 33
3.1 實驗規劃與流程 33
3.2 實驗系統架構 35
3.3 實驗設備與儀器 36
3.3.1 超精密平面磨床GS-45PFNC 36
3.3.2 砂輪選用 37
3.3.3 工件材料 37
3.3.4 動平衡檢測儀SB-8800 38
3.3.5 加工音檢出裝置 39
3.3.6 三軸動力計Kistler 9257A 40
3.3.7 電荷放大器 41
3.3.8 USB資料擷取模組 42
3.3.9 TESATAST槓桿表 43
3.3.10 網路交換器DGS-1005D 44
3.3.11 Mitutoyo SJ400表面粗度儀 45
3.3.12 3D雷射共軛焦顯微鏡 46
第四章 實驗結果與討論 49
4.1 磨削參數對磨削力之影響 49
4.1.1 輪磨深度對磨削力之影響 49
4.1.2 砂輪切線速度對磨削力之影響 51
4.1.3 工件速度對磨削力之影響 53
4.1.4 磨粒種類對磨削力之影響 58
4.2 磨削力模型建立與驗證 60
4.2.1輪磨深度對磨削力之驗證 62
4.2.2砂輪切線速度對磨削力之驗證 65
4.2.3工件速度對磨削力之驗證 67
4.2.4多變數驗證磨削力模型實驗 70
4.3 磨削參數對表面粗糙度之影響 73
4.3.1 輪磨深度對表面粗糙度之影響 73
4.3.2 砂輪切線速度對表面粗糙度之影響 75
4.3.3 工件速度對表面粗糙度之影響 77
4.3.4 磨粒種類對表面粗糙度之影響 80
4.4 表面粗糙度Ra模型建立與驗證 82
4.4.1 輪磨深度對表面粗糙度Ra值之驗證 82
4.4.2 砂輪切線速度對表面粗糙度Ra值之驗證 84
4.4.3 工件速度對表面粗糙度Ra值之驗證 85
4.4.4 多變數驗證表面粗糙度Ra模型實驗 87
4.5 預測區建立與分析 88
4.5.1 磨削力可預測區 88
4.5.2 表面粗糙度Ra可預測區 91
4.5.3即時更新可預測區 92
第五章 結論與未來展望 95
5.1 結論 95
5.2 未來展望 96
參考文獻 97
附錄A各個參數之磨削力與表面粗糙Ra圖 100


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