簡易檢索 / 詳目顯示

研究生: 周梓軒
Chao, Chi-Hin
論文名稱: 自行車輪圈標籤黏貼及品質標籤檢測系統之開發
Development of Bicycle Rim Labeling and Quality Inspection System
指導教授: 劉彥辰
Liu, Yen-Chen
學位類別: 碩士
Master
系所名稱: 工學院 - 機械工程學系
Department of Mechanical Engineering
論文出版年: 2018
畢業學年度: 106
語文別: 中文
論文頁數: 105
中文關鍵詞: 系統整合自動化系統輪圈標籤作業系統網宇實體系統
外文關鍵詞: Cyber-Physical System, System Integration, Automated System
相關次數: 點閱:37下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 本論文基於網宇實體系統之五層式架構,開發、設計並實現一輪圈標籤黏貼及黏貼後品質檢測之自動化整合系統。此整合系統由三個子系統組成:標籤操作系統、輪圈操作平台、品質檢測及資訊回饋系統。旨在達成從提取標籤原料到把標籤黏貼於輪圈表面,及對已經完成黏貼程序的產品進行品質檢測之自動化程序。標籤作業系統包含兩個裝置:原料取料固定裝置、標籤撕黏裝置,此系統針對含有多張待撕取標籤之標籤原枓進行操作。單張標籤原料由安置多張標籤原料之原料匣中,透過挫屈機構及驅動滾輪對最表層之標籤原料產生磨擦力差異,從而帶出最表層之單張標籤原料,單張標籤原料接續被捲帶到平台上進行固定。被固定之標籤原料由標籤撕黏裝置對待撕取之標籤進行撕取及移動到輪圈之目標位置進行黏貼。輪圈操作平台針對輪形物體進行運送、夾持及轉動之操作。輪圈由運送裝置運送到平台之作業區域,並對其進行夾持,輪圈被穩固夾持後,經由資訊回饋系統回傳輪圈狀態資訊進行轉動控制,以配合黏貼程序及品質檢測程序。品質檢測及資訊回饋系統利用工業攝影機針對進行操作中之輪圈進行全域及局部之資訊回饋,同時針對已完成黏貼之標籤進行檢測。在即時資訊回饋及控制中,對於影像進行複雜的計算造成的處理速度下降可能會導致時間延遲問題,無疑對實時控制是一大障礙。本論文整合一基於高斯混合模型之前景偵測技術,以降低操作中不必要之計算量,提高即時狀態回饋之準確性,並以模板比對法對已完成黏貼之標籤進行檢測。最後透過整合各系統,提高系統之連通性及強建性,達成標籤黏貼及檢測自動化之工序,以實體實驗驗證自動化對製程時間控制之成果,並進行延伸之討論。

    In manufacturing of bicycle rims, stickers or labels are always pasted on the products as decoration or identification. The process mentioned above is completed by workers, human operation takes the advantage of giving a high yield rate of products since workers can always make a correction when fault operation happened, but human operation increases the cost of the products due to the salary of employing workers, also the poor management issue occured due to the non-uniform processing time of each worker. In this thesis, the design and hardware realization of wheel-shape objects labeling and quality inspection cyber physical system is presented. The proposed cyber physical system consists of three systems, the label operation system, the operation platform, and the visual based quality inspection system. The proposed system is designed to have the ability to extrect labels with different sizes of arc, the operation platform is designed to have the ability to hold and rotate wheel-shaped object, the visual based quality inspection system is designed to capture the global and local information of operation region as feedback of real time control and execute the quality inspection process. The designed cyber physical system is realized to validate the proposed system. In the emperiments, the results showed that the processing time is garanteeed and the desired motions of labeling process is completed.

    圖目錄 xxii 表目錄 xxv 第一章 緒論 P.1 1.1 研究背景 P.1 1.1.1 工業4.0 P.1 1.1.2 網宇實體系統 P.4 1.2 研究動機與目的 P.5 1.3 研究方法與研究目標 P.7 1.4 論文架構 P.7 第二章 系統設計 P.9 2.1 設計目標 P.9 2.2 標籤操作系統 P.11 2.2.1 取料固定裝置之設計 P.11 2.2.2 標籤撕黏裝置之設計 P.13 2.3 輪圈操作平台 P.17 2.3.1 運送操作 P.18 2.3.2 夾持與轉動操作 P.18 2.4 基於影像之資訊回饋及標籤品質檢測系統 P.22 2.4.1 前景偵測 P.22 2.4.2 高斯混合模型之前景偵測 P.23 2.4.3 前景偵測對於資訊回饋及品質檢測之應用 P.25 2.5 各系統之整合 P.26 第三章 系統之硬體實現 P.29 3.1 標籤操作系統之硬體實現 P.29 3.1.1 取料固定裝置 P.32 3.1.2 標籤撕黏裝置 P.35 3.2 輪圈操作平台之硬體實現 P.44 3.2.1 夾持與轉動機構 P.46 3.3 基於影像之資訊回饋及標籤品質檢測系統之基本測試 P.50 3.3.1 前置作業-建立計算遮罩 P.51 3.3.2 資訊回饋 P.52 3.3.3 樣板比對檢測 P.52 第四章 運動控制 P.56 4.1 循跡控制 P.56 4.1.1 NURBS 非均勻有理基底雲形線 P.56 4.1.2 參數式插值器 P.59 4.1.3 加減速規劃 P.61 第五章 系統整合及實驗架設與測試 P.66 5.1 實驗架設 P.66 5.1.1 標籤操作系統實驗架設 P.66 5.1.2 輪圈操作平台實驗架設 P.70 5.2 實驗結果與討論 P.71 5.2.1 標籤操作系統實驗 P.71 5.2.2 輪圈操作平台實驗 P.78 第六章 結論與未來展望 P.82 6.1 結論 P.82 6.2 未來展望 P.83 參考文獻 P.85 Appendix - Experiment Codes P.88 A.1 Label Operation System P.88

    [1] Rainer Drath and Alexander Horch. Industrie 4.0: Hit or Hype?[Industry Forum]. Industrial Electronics Eagazine, 8(2):56–58, 2014.

    [2] Jay Lee, Behrad Bagheri, and Hung-An Kao. A Cyber-Physical Systems Architecture for Industry 4.0-Based Manufacturing Systems. Manufacturing Letters, 3:18–23, 2015.

    [3] Nasser Jazdi. Cyber Physical Systems in the Context of Industry 4.0. In International Conference on Automation, Quality and Testing, Robotics, pages 1–4. IEEE, 2014.

    [4] Keliang Zhou, Taigang Liu, and Lifeng Zhou. Industry 4.0: Towards Future Industrial Opportunities and Challenges. In 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pages 2147–2152. IEEE, 2015.

    [5] Jay Lee. Smart Factory Systems. Informatik-Spektrum, 38(3):230–235, 2015.

    [6] 劉廷翰. 基於高斯混合模型之前景偵測應用於視覺監視之研究, 碩士論文.國立成功大學電機工程學系, 2017.

    [7] José Barbosa, Paulo Leitão, Damien Trentesaux, Armando W Colombo, and Stamatis Karnouskos. Cross Benefits from Cyber-Physical Systems and Intelligent Products for Future Smart Industries. In 14th International Conference on Industrial Informatics (INDIN), pages 504–509. IEEE, 2016.

    [8] Lihui Wang, Martin T¨¨orngren, and Mauro Onori. Current Status and Advancement of Cyber-Physical Systems in Manufacturing. Journal of Manufacturing Systems, 37:517 – 527, 2015.

    [9] Edward A. Lee. Cyber Physical Systems: Design Challenges. In International Symposium on Object Oriented Real-Time Distributed Computing (ISORC), pages 363–369. IEEE, 2008.

    [10] Mario Hermann, Tobias Pentek, and Boris Otto. Design Principles for Industrie 4.0 Scenarios. In 49th Hawaii International Conference on System Sciences (HICSS), pages 3928–3937. IEEE, 2016.

    [11] R. V. Rao, V. J. Savsani, and D. P. Vakharia. Teaching–Learning-Based Optimization: An Optimization Method for Continuous Non-Linear Large Scale Problems. The International Journal of Information Sciences, 183(1):1– 15, 2012.

    [12] R. V. Rao, V. J. Savsani, and D. P. Vakharia. Teaching–Learning-Based Optimization: A Novel Method for Constrained Mechanical Design Optimization Problems. The International Journal of Computer-Aided Design, 43(3):303– 315, 2011.

    [13] Les Piegl. On NURBS: A Survey. IEEE Computer Graphics and Applications, 11(1):55–71, 1991.

    [14] Les Piegl and Wayne Tiller. The NURBS Book. Springer Science & Business Media, 2012.

    [15] C.-W. Cheng and M.-C. Tsai. Real-Time Variable Feed Rate NURBS Curve Interpolator for CNC Machining. The International Journal of Advanced Manufacturing Technology, 23(11-12):865–873, 2004.

    [16] M.-Y. Cheng, M.-C. Tsai, and J.-C. Kuo. Real-time NURBS Command Generators for CNC Servo Controllers. International Journal of Machine Tools and Manufacture, 42(7):801–813, 2002.

    [17] 鄭銘揚. Introduction to Motion Control System, 講義. 國立成功大學電機工程學系研究所, 2017.

    [18] Tsehaw Yong and Ranga Narayanaswami. A Parametric Interpolator with Confined Chord Errors, Acceleration and Deceleration for NC Machining. Computer-Aided Design, 35(13):1249–1259, 2003.

    [19] Mi-Ching. Tsai, Ming-Yang. Cheng, Kung-Feng. Lin, and Nan-Chyuan Tsai. On Acceleration/Deceleration Before Interpolation for CNC Motion Control. In International Conference on Mechatronics, 2005. ICM’05., pages 382–387. IEEE, 2005.

    [20] Henning Kagermann, Johannes Helbig, Ariane Hellinger, and Wolfgang Wahlster. Recommendations for implementing the strategic initiative INDUS- TRIE 4.0, final report of the Industrie 4.0 Working Group. Forschungsunion, 2013.

    [21] Jian Qin, Ying Liu, and Roger Grosvenor. A Categorical Framework of Manufacturing for Industry 4.0 and Beyond. Procedia Cirp, 52:173–178, 2016.

    [22] Marco Annunziata and Peter C Evans. Industrial Internet: Pushing the Boundaries of Minds and Machines. General Electric, 2012.

    [23] Michael Wiesmu¨ller. Industrie 4.0: Surfing the Wave? Elektrotechnik & Informationstechnik,
    131(7):197–197, 2014.

    [24] Kevin Ashton et al. That 'Internet of Things' Thing. RFID journal, 22(7):97– 114, 2009.

    [25] 紀偉祥. 新型分紙機構之設計與分析, 碩士論文. 國立清華大學動力機械工程學系, 2000.

    [26] Herbert Bay, Tinne Tuytelaars, and Luc Van Gool. SURF: Speeded up robust features. In European Conference on Computer Vision, pages 404–417. Springer, 2006.

    [27] Herbert Bay, Andreas Ess, Tinne Tuytelaars, and Luc Van Gool. Speeded- up robust features (SURF). Computer Vision and Image Understanding, 110(3):346–359, 2008.

    [28] Saeed B Niku. Introduction to Robotics. Prentice Hall Professional Technical Reference, 2001.

    [29] Athulan Vijayaraghavan, Will Sobel, Armando Fox, David Dornfeld, and Paul Warndorf. Improving Machine Tool Interoperability Using Standardized Interface Protocols: MtConnect. 2008.

    [30] Tianyi Wang, Jianbo Yu, David Siegel, and Jay Lee. A similarity-based prognostics approach for remaining useful life estimation of engineered systems. In International Conference on Prognostics and Health Management (ICPHM), pages 1–6. IEEE, 2008.

    [31] P. J. Pawar and R. V. Rao. Parameter Optimization of Machining Processes Using Teaching–Learning-Based Optimization Algorithm. The International Journal of Advanced Manufacturing Technology, 67(5-8):995–1006, 2013.

    無法下載圖示 校內:2023-08-31公開
    校外:不公開
    電子論文尚未授權公開,紙本請查館藏目錄
    QR CODE