臺灣博碩士論文加值系統

加工技術的進步帶動產業的發展，對於工具機的加工精度要求也越來越高重要。通常工具機存在三大誤差，幾何、熱和切削力誤差，其中熱變形與切削力穩定性是影響加工精度的關鍵因素。為了改善工具機的誤差，特別針對機台精度優化的方向來做為研究主題，對熱誤差的部分建立智能化的補償方式，切削力的部分則針對顫振穩定性進行分析。本研究主要分為三個部分，包含主軸熱變形補償系統、切削力係數鑑別及顫振穩定曲線分析。首先是主軸熱變形量測系統的建置，參考ASME B5.54的檢測規範，量測工具機主軸系統相對於床台的熱變形量，以倒傳遞類神經網路分析出主軸熱變形與溫度之間的關係，以建立主軸熱變形模型，並於機台上進行實際之智能化補償；第二部分，則是切削力係數鑑別與分析，針對7075鋁合金進行銑削力量測實驗，基於Altintas的平均銑削力模型，得到應用於顫振穩定曲線分析之切削力係數，用於預測不同切削參數下的切削力。第三部分則是對刀具進行動剛性實驗，將實驗數據與切削力係數帶入顫振穩定曲線計算，驗證曲線對於切削狀態預測的準確性。主軸熱變形實際量測結果發現， Z方向伸長量的增加與溫度的上升成正比，則針對軸承端與鑄件端溫度進行倒傳遞類神經建模，應用在三軸加工機上進行實際運轉8小時的進行長時間的智能化補償，由補償結果顯示改善了73.43%的Z方向熱位移。對鋁合金7075-T6的銑削力鑑別切削力係數，用於預測不同切深與每刃進刀的切削力具有相同的趨勢，結合量測的刀具動剛性，將其應用於顫振穩定性預測，初步判定使用對應的切削力係數有助於顫振穩定性預測，預測準確性約78.57%。

Processing technology is the key to driving industrial development. The machining accuracy requirements of the machine tool are also becoming more and more important. There are three major errors of the machine tool, which respectively geometric, thermal and cutting force errors. The key to affecting machining accuracy is thermal deformation and cutting force stability. In order to improve the errors of the machine tool, the precision optimization of the machine is used as the research topic. Build intelligent compensation methods to improve thermal error. The portion of the cutting force is analyzed for chatter stability. This research is mainly divided into three parts, including the spindle thermal deformation compensation system, the identification of the cutting force coefficient and the analysis of the chatter stability curve. The first is the construction of the spindle thermal deformation measurement system. With reference to the ASME B5.54 inspection specification, the thermal deformation of the spindle system of the machine tool is measured relative to the bed, and the thermal deformation and temperature of the spindle are analyzed by the inverse transmission-like neural network. The relationship between the two is to establish the spindle thermal deformation model, and the actual intelligent compensation on the machine; the second part is the identification and analysis of the cutting force coefficient, milling strength test for 7075 aluminum alloy, based on Altintas The average milling force model is obtained for the cutting force coefficient applied to the chatter stability curve analysis to predict the cutting force under different cutting parameters. The third part is to carry out the dynamic rigidity test of the tool, and bring the experimental data and the cutting force coefficient into the chatter stability curve to verify the accuracy of the curve prediction for the cutting state. The actual measurement results of the spindle thermal deformation show that the increase in the Z-direction elongation is proportional to the temperature rise, and the reverse-transfer-like neural modeling is performed on the bearing end and the casting end temperature, and the actual operation is performed on a three-axis machining machine for 8 hours. For a long time of intelligent compensation, the compensation result shows an improvement of 73.43% of the Z-direction thermal displacement. The cutting force coefficient is determined by the milling force of aluminum alloy 7075-T6. It is used to predict the different cutting depths and the cutting force of each cutting edge has the same trend. Combined with the measured tool dynamic rigidity, it is applied to the prediction of chatter stability. The preliminary determination of the corresponding cutting force coefficient is helpful for the prediction of the chatter stability, and the prediction accuracy is about 78.57%.

摘要....i
英文摘要(Abstract)....ii
誌謝....iv
目錄....v
表目錄....vii
圖目錄....viii
符號說明....x
第 一 章 緒論....1
1.1 研究背景與動機....1
1.2 研究目的....2
1.3 論文架構....3
第 二 章 文獻回顧....4
2.1 熱變形補償相關研究....4
2.2 切削力係數鑑別相關研究....8
第 三 章 研究架構與方法....13
3.1 研究架構與流程....13
3.2 硬體及系統架構....14
3.2.1 硬體設備....14
3.2.2 實驗機台介紹....17
3.2.3 實驗刀具與切削材料....18
3.2.4 顫振穩定曲線實驗設備....18
3.3 熱補償的原理與規範....20
3.3.1 主軸熱變形的改善....20
3.3.2 熱變形量測規範....21
3.4 主軸熱變形量測與線上補償....23
3.4.1 主軸熱變形量測....23
3.4.2 熱變形數學模型建立....24
3.4.3 熱變形智能化補償....27
3.5 銑削系統與切削力模型分析....27
3.5.1 正交與斜交切削....28
3.5.2 局部切削力....28
3.5.3 銑削力模式解析....30
3.5.4 直齒切削力模型解析....30
3.5.5 端銑刀切削力模型....32
3.5.6 平均銑削力模型....34
3.6 切削力係數鑑別....36
3.6.1 基於平均銑削力模型之切削力係數估測....36
3.6.2 平均切削力量測實驗....37
3.6.3 切削力的特性....38
3.7 切削力係數與顫振穩定預測....40
3.7.1 顫振穩定曲線與切削力係數的關係....40
3.7.2 顫振穩定曲線計算實驗....43
3.7.3 振動相位差量測與顫振判別....44
第 四 章 實驗結果....46
4.1 熱變形量測實驗....46
4.1.1 熱變形量測實驗....46
4.1.2 倒傳遞類神經分析之熱變形建模....49
4.1.3 線上熱變形補償系統建置....50
4.1.4 線上熱變形補償結果....50
4.2 切削力係數鑑別....51
4.2.1 切削力係數鑑別實驗....51
4.2.2 測力計之切削力訊號擷取功能....52
4.2.3 切削實驗與回歸分析....53
4.2.4 切削力係數驗證....56
4.3 顫振曲線預測實驗與實際切削結果....58
4.3.1 刀具動剛性實驗....58
4.3.2 顫振穩定曲線圖計算....60
4.3.3 切削實驗規劃與顫振穩定切削結果....61
第 五 章 結論與未來展望....69
參考文獻....70
Extended Abstract....73

[1]財團法人精密機械發展中心,”工具機熱變位補償應用技術”,2015.
[2]陳忠誠,張文陽,2017,“基於零階包絡法進行刀具銑削穩定性預測及顫振分析”,國立虎尾科技大學,碩士學位論文
[3]Josef Mayr, Jerzy Jedrzejewski, Eckart Uhlmann,M.Alkan Donmez,Wolfgang Knapp,Frank Härtig,Klaus Wendt, Toshimichi Moriwaki, Paul Shore, Robert Schmitt, Christian Brecher, Timo Würz, Konrad Wegener, ” Thermal issues in machine tools”, CIRP Annals,Vol.61, Issue 2, 2012, Pages 771-791.
[4]Walter AG,” Walter machining calculator”.
[5]Manufacturing Automation Laboratories Inc,”Cutpro- fundamentals of machining”.
[6]蘇春維,”工具機熱變位補償應用技術”, 財團法人精密機械發展中心,2016.
[7]ISO230-3,Test code for machine tools part3 “Determination of thermal effects”, page:44, 2007.
[8]Moshe, Barash,” Thermal Effects on the Accuracy of Numerically Controlled Machine Tools”, Annals of the CIRP, Vol.35/1/1968, page 255-258.
[9]Okushima, k. ,“Compensation of Thermal Displacement by Coordinate System Correction”, Annals of the CIRP, Vol.24/1/1975, page 327-331.
[10]Juliane Weber , Linart Shabi and Jürgen Weber, “Thermal Impact Of Different Cooling Sleeve’S Flow Geometries In Motorized High-Speed Spindles Of Machine Tools”, Proceedings of the 9th FPNI Ph.D. Symposium on Fluid Power, 2016.
[11]Philip Blaser, Florentina Pavlicek, Kotaro Mori, Josef Mayr, Sascha Weikert,” Adaptive Learning Control For Thermal Error Compensation Of 5-Axis Machine Tools”, Journal of Manufacturing Systems Volume 44, Part 2, July 2017, Pages 302-309
[12]Josef Mayr, Michael Müller, Sascha Weikert, ” Automated thermal main spindle & B-axis error compensation of 5-axis machine tools”, Annals of the CIRP, Vol.65/1/2016, page 479-482.
[13]Ali M.Abdulshahed, Andrew P. Longstaff, Simon Fletcher, “The application of ANFIS prediction models for thermal error compensation on CNC machine tools”, Applied Soft Computing, Volume 27, February 2015, Pages 158-168
[14]張文鴻, 王圳木, 2011 “工具機主軸溫升熱變位補償技術研究”, 國立勤益科技大學, 碩士學位論文
[15]陳俊榮, 陳政雄, 2000 “高速主軸之熱變形分析及量測”, 國立中正大學, 碩士學位論文
[16]謝榮泰, 李榮顯, “虛擬多軸銑床導入靜態切削力預估之研究”, 國立成功大學,碩士學位論文
[17]E.Budak, Y. Altintas, “Analytical Prediction of Chatter Stability in Milling—Part I: General Formulation”, Journal of Dynamic Systems, Measurement, and Control, March 1998.
[18]Qi Yao, Baohai Wu, Ming Luo, Dinghua Zhang, “On-line cutting force coefficients identification for bull-end milling process with vibration”, Measurement, September 2018.
[19]Kistler Instrument Corp.,” Data sheets-Multi-Component Dynamometer Type 9257B”, Page2/4.
[20]黃條嵩, 簡文通,” 建立SKD61模具鋼之切削力預測及車削參數最佳化模式之探討”, 國立屏東科技大學,碩士學位論文.
[21]陳羿銘,康耀鴻, “微銑削加工之切削厚度與切削力模式之研究”, 國立高雄應用科技大學,碩士學位論文.
[22]TaeguTec Member IMC Group : http://tw.taegutec.com
[23]陳威辰, 王俊志,“端銑刀刃口幾何對系統穩定性影響之研究”, 國立成功大學,碩士學位論文.
[24]PCB Piezotronics,” Model 086C03 Impact Hammer Installation and Operating Manual”, Page3 .
[25]Dr Stan Zurek,”aNETka version 2.0 Operation Manual”, Wolfson Centre for Magnetics School of Engineering Cardiff University.
[26]周國華, “工具機切削技術研究”,翰蘆圖書,2017
[27]Y. Altintas,”Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, And CNC Design”, page 44, Cambridge University Press, 2012.
[28]Manufacturing Automation Lab” CUTPRO fundamentals of machining ,Start to Finish Guide”,Page12,2013.
[29]聶強,黃凱,畢慶貞,朱利民, ”微銑削中考慮刀具跳動的瞬時切厚解析計算方法”,機械工程學報,Vol.52,No.3,2016.
[30]ChangfuLiu, LidaZhu, ChenbingNi, ” Chatter detection in milling process based on VMD and energy entropy”, Mechanical Systems and Signal Processing,Volume 105, 15 May 2018, Pages 169-182.
[31]Yang Fu,Yun Zhanga,Huamin Zhou, DequnLi, Hongqi Liu, Haiyu Qiao, Xiaoqiang Wang, ”Timely online chatter detection in end milling process”, Mechanical Systems and Signal Processing Volume 75, 15 June 2016, Pages 668-688
[32]M.Y.Tsai, S.Y.Chang, J.P.Hung, C.C.Wang, ” Investigation of milling cutting forces and cutting coefficient for aluminum 6060-T6”, Computers & Electrical Engineering Volume 51, April 2016, Pages 320-330
[33]R.P.H Faassen, “Chatter prediction and control for high-speed milling: modelling and experiments”, Technische Universiteit Eindhoven, 2007.