臺灣博碩士論文加值系統

樹木在生長過程常受到外界各種因素影響，造成木材組織結構異常，出現一些瑕疵，常見的缺陷包括孔洞、節子、變色、裂紋等。現今生產木製地板流程中，大多數切割和等級分類都是由工作人員手動完成。針對木板表面上的缺陷，透過自動光學檢測(AOI, Automated Optical Inspection)找出瑕疵，以利後續切割、等級分類，是一個可行的方案。本文使用3D量測技術的雷射三角量測法(Laser Triangulation)，再經過影像處理技術，能順利檢測出木板表面瑕疵，取代原先以人工檢查的方式，能大大提升檢測速度和準確性，並改善產線的生產品質。

Trees in the growth process are often affected by a variety of external factors, resulting in anomalous wood structure, there are some defects, common defects include holes, knots, discoloration, cracks and so on. From now, the production of wooden floor in processes, most cutting and grade classifications are done manually by the staff. For wood board surface defects, it is a feasible solution to find defect through automatic optical inspection (AOI) for subsequent cutting and classifying. This article uses the laser triangulation measurement method in 3D measurement technology, through the image processing technology, can detect successfully the wood board surface defects, replacing the original way of manual inspection, can improve greatly the detection speed and accuracy, and improve the production quality.

摘要 i
ABSTRACT ii
誌謝 iii
目錄 iv
表目錄 vii
圖目錄 viii
第1章 緒論 1
1.1 研究背景 1
1.2 研究動機與目的 3
1.3 文獻探討 4
1.4 論文架構 5
第2章 基礎理論介紹 6
2.1 木製地板製程 6
2.2 自動化光學檢測技術 7
2.3 3D測量技術 8
2.3.1 雷射三角量測法 8
2.3.2 直接校正 9
2.4 通訊協定模型 10
2.5 影像處理演算法 11
2.5.1 影像分割 11
2.5.2 形態學 12
2.5.3 邊緣檢測 13
第3章 硬體架構 15
3.1 木板瑕疵介紹 15
3.1.1 皮料標準檢驗書 16
3.2 工業相機 17
3.3 鏡頭 18
3.4 雷射光源 18
3.5 Motionnet 20
3.6 旋轉編碼器 22
3.7 數位IO模組 23
3.8 光電感測器 25
3.9 木板等級自動化分類整體硬體架構 26
第4章 軟體架構 27
4.1 軟體流程 27
4.1.1 初始設備設定 28
4.1.2 校正設定 31
4.1.3 2.5D灰階影像處理 32
4.1.4 瑕疵分類以及定位切割點 33
第5章 實驗結果 42
5.1 系統環境與架構 42
5.2 實驗結果 44
5.2.1 檢測速率 44
5.2.2 檢測木板瑕疵區塊結果 45
5.2.3 檢測孔洞直徑比對 48
5.2.4 檢測長度比對 50
第6章 結論與未來展望 52
6.1 結論 52
6.2 未來展望 52
參考文獻 53

[1]華泰證券研究所. (2016). 深度報告 - 輕工製造 | 木地板產業：平穩發展中尋找新機遇. Available: https://wallstreetcn.com/articles/264940
[2]J. Wan, H. Cai, and K. Zhou, "Industrie 4.0: Enabling technologies," in Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things, 2015, pp. 135-140.
[3]D. W. Raymond and D. F. Haigh, "Why automate optical inspection?," in Proceedings International Test Conference 1997, 1997, p. 1033.
[4]L. Fu, Y. Zhang, Q. Huang, and X. Chen, "Research and application of machine vision in intelligent manufacturing," in 2016 Chinese Control and Decision Conference (CCDC), 2016, pp. 1126-1131.
[5]K. K. Rathan, A. Ajith, S. Aswathi, and V. M. Silpa, "Survey of robotic arm controlling techniques," in 2017 International Conference on Intelligent Sustainable Systems (ICISS), 2017, pp. 759-763.
[6]L. Sun and L. Fang, "Research on a novel robotic arm with non-backlash driving for industrial applications," in 2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), 2017, pp. 70-75.
[7]S. R. Aghdam, E. Amid, and M. F. Imani, "A fast method of steel surface defect detection using decision trees applied to LBP based features," in 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2012, pp. 1447-1452.
[8]C. Karunasena and N. Wickramarachchi, "Vision based cross sectional area estimator for industrial rubber profile extrusion process controlling," in 2010 Fifth International Conference on Information and Automation for Sustainability, 2010, p. 1.
[9]H. H. P. Wu and H. Y. Guo, "Automatic Optical Inspection for steel golf club," in 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2015, pp. 2332-2336.
[10]H. G. d. Silva, T. G. Amaral, and O. P. Dias, "Automatic optical inspection for detecting defective solders on printed circuit boards," in IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society, 2010, pp. 1087-1091.
[11]M. A. Selver and O. Akay, "Evaluating clustering methods for classification of marble slabs in an automated industrial marble inspection system," in 2009 International Conference on Electrical and Electronics Engineering - ELECO 2009, 2009, pp. II-115-II-119.
[12]Y. Wang, Z. Cheng, J. Hou, D. Cai, and B. Chen, "Quality inspection improvement for cheese packaging using machine vision," in 2012 IEEE International Conference on Electro/Information Technology, 2012, pp. 1-5.
[13]C. S. Nandi, B. Tudu, and C. Koley, "An automated machine vision based system for fruit sorting and grading," in 2012 Sixth International Conference on Sensing Technology (ICST), 2012, pp. 195-200.
[14]V. Ahanathapillai and J. J. Soraghan, "Myocardial Ischemia Detection Algorithm (MIDA): Automated echocardiography sequence analysis for diagnosis of heart muscle damage," in 2010 Computing in Cardiology, 2010, pp. 405-408.
[15]J. Duan, L. Luo, J. Li, X. Gao, and W. Zhang, "Measuring of train wheel surface defect based on linear CCD imaging," in 2016 18th International Wheelset Congress (IWC), 2016, pp. 65-70.
[16]R. W. Conners, D. E. Kline, P. A. Araman, X. Xiao, and T. H. Drayer, "Defect detection system for lumber," ed: Google Patents, 1999.
[17]S. M. Lee, P. A. Araman, A. L. Abbott, and M. Winn, "Automated Grading, Upgrading, and Cuttings Prediction of surfaced dry hardwood lumber," in 2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis, 2009, pp. 371-376.
[18]Y. Jin, L. Zhang, C. Wu, and Z. Zhu, "Detection of 3D curve for shoe sole spraying based on laser triangulation measurement," in 2009 IEEE International Conference on Automation and Logistics, 2009, pp. 865-868.
[19]R. Marani, G. Roselli, M. Nitti, G. Cicirelli, T. D. Orazio, and E. Stella, "A 3D vision system for high resolution surface reconstruction," in 2013 Seventh International Conference on Sensing Technology (ICST), 2013, pp. 157-162.
[20]I. Besic and Z. Avdagic, "Automated test environment for image processing in laser triangulation 3D scanning," in 2016 International Symposium ELMAR, 2016, pp. 161-164.
[21]誌懋股份有限公司. 先進製程. Available: http://www.uafloors.com.tw/about3.html
[22]高彩齡. (2016). 借力結構光技術　3D測量系統簡化機器視覺設計. Available: http://www.2cm.com.tw/technologyshow_content.asp?sn=1609050013
[23]C. Steger, M. Ulrich, and C. Wiedemann, 機器視覺演算法與應用, 2011.
[24]木材圈整理. (2016). 木材缺陷的定義及分類特點分析. Available: http://anywood.com/news/detail/47711.html