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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74933完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 李貫銘 | |
| dc.contributor.author | Cheng-Yi Cheng | en |
| dc.contributor.author | 鄭呈毅 | zh_TW |
| dc.date.accessioned | 2021-06-17T09:10:38Z | - |
| dc.date.available | 2029-10-29 | |
| dc.date.copyright | 2019-12-03 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-09-11 | |
| dc.identifier.citation | [ 1 ] Ulsoy, A.G., Y. Koren, and F. Rasmussen, Principal developments in the adaptive control of machine tools. ASME Journal of Dynamic Systems, Measurement, and Control, 1983, p. 107-112.
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Altintas, CAD Assisted Adaptive Control for Milling. Journal of Dynamic Systems, Measurement, and Control, 1991, p. 444-450. [ 15 ] Tomizuka, M., J. Oh, and D. Dornfeld, Model reference adaptive control of the milling process. Control of Manufacturing Processes and Robotic Systems, 1983, p. 55-63. [ 16 ] Zuperl, U., F. Cus, and M. Reibenschuh, Neural control strategy of constant cutting force system in end milling. Robotics and Computer-Integrated Manufacturing, 2011, p. 485-493. [ 17 ] Saikumar, S. and M.S. Shunmugam, Development of a feed rate adaption control system for high-speed rough and finish end-milling of hardened EN24 steel. The International Journal of Advanced Manufacturing Technology, 2012, p. 869-884. [ 18 ] Liu, Y. and C. Wang, Neural Network based Adaptive Control and Optimisation in the Milling Process. The International Journal of Advanced Manufacturing Technology, 1999, p. 791-795. [ 19 ] Yang, M.Y., T.M. Lee, and J.G. Choi, A New Spindle Current Regulation Algorithm for the CNC End Milling Process. The International Journal of Advanced Manufacturing Technology, 2002, p. 473-481. [ 20 ] P.Y.Pien, M. Tomizuka, Adaptive Force Control of Two Dimensional Milling, American Control Conference, 1992, p. 399-403. [ 21 ] Rehorn, A.G. , J. Jiang, and P.E. Orban, State-of-the-art methods and results in tool condition monitoring: a review. The International Journal of Advanced Manufacturing Technology, 2005, p. 693-710. [ 22 ] Hidayah, M., et al., A Review of Utilisation of Cutting Force Analysis In cutting tool condition monitoring. Int. J. Eng. Tech, 2015, p. 28-35. [ 23 ] Gloth, G. and M. Sinapius, Analysis of swept-sine runs during modal identification. Mechanical Systems and Signal Processing, 2004, p. 1421-1441. [ 24 ]邱雅琳,等切切削力控制系統動態特性建立之研究, in 機械工程研究所.國立台灣大學, 2017, p.71 [ 25 ] Adams, O., et al., Model-based Predictive Force Control in Milling – System Identification. Procedia Technology, 2016. 26(Supplement C): p. 214-220. [ 26 ] Torsten, Söderström; Stoica. P. System identification. New York: Prentice Hall, 1989. [ 27 ] Pintelon, R. and J. Schoukens, System identification: a frequency domain approach, 2012. [ 28 ] Ewins, D.J. and Ewins, Modal testing : theory, practice, and application. New York , 1984 [ 29 ] Rober, S.J. and Y.C. Shin, Control of Cutting Force for End Milling Processes Using an Extended Model Reference Adaptive Control Schemes,” ASME J. of Manufacturing Science and Engineering, Vol.118, 1996, p. 339-347 [ 30 ] Ljung, L. Experiments With Identification of Continuous-Time Models. Proceedings of the 15th IFAC Symposium on System Identification, 2009 [ 31 ] Ziegler, J.G and Nichols, N. B. Optimum settings for automatic controllers. Transactions of the ASME 64, 1942, p. 759–768. [ 32 ] ISO, Tool Life Testing with Single-Point Turning Tools, ISO, 5th draft proposal, ISO/TC 29/ WG 22 (secretariat 37), 1972. [ 33 ] W. R. DeVries, Analysis of material removal processes, Springer, New York; Berlin, 1992. [ 34 ] Khan, M. E., & Khan, F. A comparative study of white box, black box and grey box testing techniques. International Journal of Advanced Computer Sciences and Applications, 2012, 12-1. [ 35 ] M.H.Hayato Yoshioka, and Hidenori Shinno, Status Monitoring of Ultraprecision Machining Using Micro Thermo Sensor and AE Sensor, 2009 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74933 | - |
| dc.description.abstract | 傳統的工具機加工方法中，通常採固定進給率進行加工，而為了避免損害刀具或機台，通常會設定較保守的加工條件，因此加工效率仍然有改善的空間，而適應性控制器透過即時調控進給率來達成穩定主軸負載，並適時地提高進給率，能夠提升加工效率。
雖然目前已有許多適應性切削的研究，但在建立系統的動態特性時，通常只基於單一軸向的直線路徑。本研究嘗試於雙軸向的直線路徑與弧形路徑進行系統鑑別實驗，以取得不同軸向的系統動態特性。並且透過實驗探討弧線路徑以及直角轉彎適應性切削的可行性。 本研究中亦提出一套設定主軸負載參考值的流程，配合進給率下限的設定，不但能夠使保持工件表面粗糙度小於設定值，同時還可以透過進給率控制訊號變化估算更換刀具的時機。實驗結果表示，當可接受之工件表面粗糙度為1.3µm，適應性切削之加工效率較固定進給率切削高出65%，且當可接受之工件表面粗糙度越大，適應性切削於加工效率上之優勢將更為明顯。 | zh_TW |
| dc.description.abstract | Constant feed force milling is considered as high performance machining in the literatures. However, it is difficult to implement this technology in the industry because there is not any method to set proper parameters in this control system. In this study, an adaptive control system with constraint (ACC) is first developed based on cutting dynamics. The cutting dynamics is obtained by system identification under various tool paths, including straight path in x-direction, straight path in y- direction and curve path. Result shows that cutting dynamics obtained under different path are almost the same, which makes developing the controller of the cutting system easy. Also force signal is replaced by spindle current signal because it is easier to collect spindle current signal in machine tools. Impact of tool wear on the control system is investigated with experiments. It is found that the ACC system can remain stable even if the open-loop gain remains below a certain value even if tool wears. A procedure to determine tool life is proposed in this work based on establishing the reference of the spindle current signal and the corresponded lower limit of the feedrate. It turns out that with this procedure, surface roughness, an index of tool life, can be kept under a predetermined level. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T09:10:38Z (GMT). No. of bitstreams: 1 ntu-108-R06522709-1.pdf: 8110972 bytes, checksum: 16e5a4d9857bf92b70bb639c2732b131 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 目錄
Abstract II 圖目錄 VIII 表目錄 XIII 第一章 緒論 1 1.1 研究背景 1 1.2 研究動機與目的 3 1.3 研究架構 4 第二章 文獻回顧 5 2.1 適應性控制技術 5 2.1.1 Adaptive Control with Optimization 5 2.1.2 Adaptive Control with constraints 5 2.1.3 Geometric Adaptive control 6 2.2 等切削力技術 6 2.2.1 動態系統建立 6 2.2.2 控制器設計 7 2.2.3 二維路徑之適應性控制 7 2.3 刀具磨耗診斷 8 2.4 系統識別 8 第三章 研究方法 9 3.1 研究流程 9 3.2 系統設備規格 10 3.2.1 立式加工機 10 3.2.2 訊號擷取卡 11 3.2.3 數位類比轉換器 13 3.2.4 電流鉤表 15 3.2.5 數位顯微鏡 16 3.2.6 麥克風 17 3.2.7 表面粗度計 17 3.3 控制系統架構 18 3.4 建立系統動態特性 21 3.4.1 系統鑑別之輸入訊號與系統輸出 22 3.4.2 訊號前處理 23 3.4.3 系統鑑別 24 3.5 控制器設計 26 3.5.1 PI控制器 27 3.5.2 控制器參數 28 3.5.3 根軌跡法 29 3.5.4 Labview 31 3.6 主軸負載參考值之選定流程 32 3.6.1 常見之換刀時機 32 3.6.2 可預測換刀時機之主軸負載參考值設定方案 34 3.7 刀具磨耗 38 3.8 工件表面粗糙度 38 3.8.1 銑削理論與表面粗糙度之關係 39 3.8.2 表面粗糙度量測 41 第四章 實驗規劃 42 4.1 系統識別實驗 43 4.2 控制效果驗證 45 4.3 主軸負載參考值設定實驗 46 4.3.1 設定主軸負載參考值 46 4.3.2 固定進給率切削實驗 48 4.4 驗證實驗 48 第五章 實驗結果與討論 49 5.1 掃頻實驗 49 5.2 系統動態 55 5.2.1 小結 59 5.3 控制器設計 60 5.3.1 開迴路增益之最大容許值 60 5.3.2 暫態響應分析 62 5.3.3 控制器設計結果 64 5.4 控制器規格驗證 66 5.4.1 進刀過程中之進給率反應實驗 66 5.4.2 開迴路增益之最大容許值實驗 67 5.4.3 小結 72 5.5 控制效果實驗 73 5.5.1 變動切深之控制實驗 73 5.5.2 小結 76 5.5.3 圓型路徑與方形路徑控制實驗 76 5.5.4 小結 82 5.6 等進給率切削實驗 83 5.6.1 步驟(a)、步驟(b) 83 5.6.2 步驟(c) 83 5.6.3 步驟(d) 87 5.6.4 步驟(e) 88 5.7 實驗驗證 89 5.7.1 主軸負載參考值4.8A 89 5.7.2 主軸負載參考值5.4A 93 5.8 討論 95 第六章 總結與未來展望 101 6.1 總結 101 6.2 未來展望 101 參考文獻 103 | |
| dc.language.iso | zh-TW | |
| dc.subject | 二維路徑系統鑑別 | zh_TW |
| dc.subject | 適應性切削 | zh_TW |
| dc.subject | 表面粗糙度 | zh_TW |
| dc.subject | 主軸負載參考值 | zh_TW |
| dc.subject | adaptive control | en |
| dc.subject | system identification in 2-dimensional milling | en |
| dc.subject | surface roughness | en |
| dc.subject | reference of spindle load | en |
| dc.title | 等負載銑削加工之主軸負載參考值設定流程 | zh_TW |
| dc.title | Method of setting the reference current of spindle load for constant cutter load in milling | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 蔡曜陽,王富正 | |
| dc.subject.keyword | 適應性切削,二維路徑系統鑑別,主軸負載參考值,表面粗糙度, | zh_TW |
| dc.subject.keyword | adaptive control,system identification in 2-dimensional milling,reference of spindle load,surface roughness, | en |
| dc.relation.page | 106 | |
| dc.identifier.doi | 10.6342/NTU201904126 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-09-12 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 機械工程學研究所 | zh_TW |
| 顯示於系所單位： | 機械工程學系 | |
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