自动模板印刷机精密对位系统的设计与研究
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摘要
随着自动模板印刷机在消费电子、汽车电子等产品的自动化生产线上的广泛应用,以及电子产品的小型化、薄型化、轻量化和便携化的发展趋势,都要求自动模板印刷机具有高精度,高效率,高稳定性,智能化等性能。
本文立足于自动模板印刷机更好的满足未来高精度小尺寸元件的生产需求,以机器视觉、图像处理、模式识别等人工智能理论和现代控制理论为基础,对自动模板印刷机的视觉对位系统、印刷后检测系统和位置控制系统分析与研究,并通过实验验证设计方案的可行性。论文的研究内容包括:
首先,精密对位系统的设计与研究,首先介绍精密对位系统工作原理,针对自动模板印刷机所特有的电路板图像,进行分析比较几种传统的图像匹配算法,并根据实际情况对其算法进行改进,提出针对印刷机的精密视觉对位算法,试验证实了改进后算法的优越性。
其次,印刷后检测系统的设计与研究,本文利用图像分割和图像特征提取技术对特征区域进行分割和特征提取的研究。针对各种印刷缺陷情况,本文提出了相应的图像检测算法,并经过实验验证取得了良好的检测效果。
最后,调整平台的运动学和动力学分析与研究,对工作平台的机械结构的介绍,分析平台的自由度,并对平台进行运动反解、动力学分析,平台建模,最后对工作平台进行可控性与可观性分析。
Intelligent printer is widely used in automatic production line of surface mounted technology, such as consumer electronics and automotive electronics. However, future requirements of electronics components are small, thin and portable. Intelligent printer must be required to be of higher precision, efficiency and stability.
In order to meet the requirements of high-precision for small size electronics, the Para-position system is mainly studied in this thesis. The detection system and position control system based on modern control theory and artificial intelligence theory are designed. Experiments show that the design for intelligent printer is feasible. The research works of the thesis is given in the following.
Firstly, the basic theory of Para-position system is introduced. Then several traditional image matching algorithms are analyzed and realized. According to the actual tests, a precise image matching algorithm for intelligent printer is obtained. Finally, the advantage of this algorithm is shown by the precise pare-position software.
Secondly, segmenting and extracting features of PCB based on image segmentation and feature extraction theories are studied. For variety defects of printing boards, several image detection algorithms are carried out. Experiments show that the algrithems achieve good test results.
Finally, the mechanical structure is introduced and the degrees of freedom of planar parallel working stage are analyzed. Then anti-movement solution, dynamic analysis and modeling platform are completed. And controllability and observability of parallel micro-motion stage are analyzed for further study of closed loop control system.
本文立足于自动模板印刷机更好的满足未来高精度小尺寸元件的生产需求,以机器视觉、图像处理、模式识别等人工智能理论和现代控制理论为基础,对自动模板印刷机的视觉对位系统、印刷后检测系统和位置控制系统分析与研究,并通过实验验证设计方案的可行性。论文的研究内容包括:
首先,精密对位系统的设计与研究,首先介绍精密对位系统工作原理,针对自动模板印刷机所特有的电路板图像,进行分析比较几种传统的图像匹配算法,并根据实际情况对其算法进行改进,提出针对印刷机的精密视觉对位算法,试验证实了改进后算法的优越性。
其次,印刷后检测系统的设计与研究,本文利用图像分割和图像特征提取技术对特征区域进行分割和特征提取的研究。针对各种印刷缺陷情况,本文提出了相应的图像检测算法,并经过实验验证取得了良好的检测效果。
最后,调整平台的运动学和动力学分析与研究,对工作平台的机械结构的介绍,分析平台的自由度,并对平台进行运动反解、动力学分析,平台建模,最后对工作平台进行可控性与可观性分析。
Intelligent printer is widely used in automatic production line of surface mounted technology, such as consumer electronics and automotive electronics. However, future requirements of electronics components are small, thin and portable. Intelligent printer must be required to be of higher precision, efficiency and stability.
In order to meet the requirements of high-precision for small size electronics, the Para-position system is mainly studied in this thesis. The detection system and position control system based on modern control theory and artificial intelligence theory are designed. Experiments show that the design for intelligent printer is feasible. The research works of the thesis is given in the following.
Firstly, the basic theory of Para-position system is introduced. Then several traditional image matching algorithms are analyzed and realized. According to the actual tests, a precise image matching algorithm for intelligent printer is obtained. Finally, the advantage of this algorithm is shown by the precise pare-position software.
Secondly, segmenting and extracting features of PCB based on image segmentation and feature extraction theories are studied. For variety defects of printing boards, several image detection algorithms are carried out. Experiments show that the algrithems achieve good test results.
Finally, the mechanical structure is introduced and the degrees of freedom of planar parallel working stage are analyzed. Then anti-movement solution, dynamic analysis and modeling platform are completed. And controllability and observability of parallel micro-motion stage are analyzed for further study of closed loop control system.
引文
1熊祥玉.丝网印刷对SMT质量的影响及对策.电子工艺技术. 1999,20(4): 157~160
2 P. E. Anuta. Spatial registration of multispectral and multitemporal digital imagery using Fast Fourier Transformation techniques. IEEE Trans. on Geosci.Electron. 1970,8:355-368
3 D. I. Barnea, H. F. Silverman. A Class of Algorithms for Fast Digital Image Registration. IEEE Trans. on Computer. 1972,21:186~192
4 C. D. MacGillen et al. Image Registration on Variance as a Measure of Overlay Quality. IEEE Trans. 1976,14:44~49
5 Katsuyuki Tanimizu. High-speed Defect Detection Method for Color Printed Matter. IEEE. 1990:653~658
6 Shan X M, Kuo S K, et al. Ultra precision motion control of a multiple degrees of freedom magnetic suspension stage. IEEE Trans. on Mechatronics. 2002,7(1):67~78
7王延风.磁悬浮精密定位工作台机电一体化CAD/CAE集成研究.中国科学院博士论文. 2004:8~13
8李强,张钹.一种基于图像灰度的快速匹配算法.软件学报. 2006,17(2): 186~192
9石绘,余文勇.基于多目视觉的高速印刷质量在线检测系统.武汉理工大学学报. 2007,29(6):65~68
10姜会亮,郭振民,胡学龙.数字图像处理中几种平滑技术的研究比较.现代电子技术. 2004,27(8):185~187
11顾茂松,杨小冈,缪栋,刘云峰.基于机器视觉的印刷条码质量检测系统研究. 2007,33(5):20~26
12王岩松.基于最小二乘影像匹配的畸变图像校正算法.北方交通大学学报. 2002,26(1):15~16
13罗钟铉,刘成明.灰度图像匹配的快速算法.计算机辅助设计与图像学学报. 2005,17(5):966~969
14钟志光,卢君. Visual C++.NET数字图像处理实例与解析.清华大学出版社, 2003:383~387
15巩娟,李庆祥,李玉和.精密工作台的设计与研究.光学技术. 2005,31(4): 636~638
16薛实福,李庆祥.精密仪器设计.清华大学出版社, 1991:34~65
17谢传钵.分步重复投影光刻机精密快速定位工作台研究.光电工程. 1996,23(4):65~72
18 Awabdy B A, ShihW C, DavidM Auslander. Nanometer positioning of a linear motion stage under static bads. IEEE Trans.on Mechatronics. 1998,2(3):113~120
19 A. Goshtasby, G. C. Stockman. Point pattern matching using convex hull edges. IEEE Trans.Systems, Man and Cybemetics. 1985,15:631~637
20 G. Stockman, S. Kopstein, S. Benett. Matching images to models for registration and object detection via clustering. IEEE Trans. Pattern Analysis and Machine Intelligence. 1982,4:229~241
21 R. S. Mitra, N. N. Murthy. Elastic maximal matching. Pattern Recognition. 1991,24:747~753
22 G. Medioni, R. Nevatia. Matching images using linear features. IEEE Trans. Pattern Analysis and Machine Intelligence. 1984,6:675~685
23 W. H. Wang, Y. C. Chen. Image registration by control points pairing using the invariant properties of line segments. pattern Registration Letters. 1997,18:269~281
24 J. Ton, A. K. Jain. Registering Lands at images by point matching. IEEE Trans. Geoscience and Remote Sensing. 1989,27:642~651
25 A. Noble. Finding comers. Image and Vision Computing. 1988,6:121~128
26 S. M. Smith, J. M. Brady. SUSAN-A new approach to low level image processing. Int’l. Journal of Computer Vision. 1997,23:45~78
27 D. Skea, I. Barrodale, R.Kuwahara, R. Poeckert, A control point matching algorithm. Pattern Recognition. 1993,26:269~276
28 T. Suk, J. Flusser. Point-based projective invariants. Pattern Recognition. 2000,33:251~261
29 Ostu N A. Tresthold Selection Method from Gray-Level Histograms.IEEE Trans. on System. 1979,9(1):62~66
30梁萧颖等.基于Hough变换的多适应性圆检测.机械与电子. 2007,9: 74~75
31 Truchetet F, Laligant O. Subpixle edge detection for dimensional control by artificial vision. Journal of Electronic Imaging. 2001,10(1):234~239
32张永宏等.基于灰度矩的CCD图像亚像素边缘检测算法研究.光学技术. 2004,30(6):693~698
33 KRIS J, DIMITRIS A. Subpixel edge localization and the interpolation of still images. IEEE Trans. on Image Processing,1995,4(3):285~295
34孙家广.计算机图形学(第三版).清华大学出版社. 1999:35~41
35和青芳.计算机图形学原理及算法教程(Visual C++版).清华大学出版社, 2006:45~53
36 Lee K M. Kinematic Analysis of a Three Degree of Freedom In-Parallel Actuated Manipulators. IEEE Trans. on Robotics Automation. 1998,4(2): 354~360
37朱红光,周云飞,胡建兵,胡科峰.一种两层复合式微驱动平台的运动分析.机床与液压. 2004,6:11~12
38武建新,李强,赵卫国,孙燕.并联机构机电耦合动力学计算.中国工程机械学报. 2006,4(4):415~418
39 Bhaskar Dasgupta, Mruthyunjaya. A Newton-Euler formulation for the inverse dynamics of Stewart platform manipulator. Mechanism and Machine theory. 1998,33(8):1135~1152
40郭祖华,陈五一,陈鼎昌. 6-UPS并联机构的刚体动力学模型.机械工程学报. 2002,38(11):53~57
41 Y. Nakamura, M. Ghodoussi. Dynamics computation of Structure: Varying Kinematics Chains and its Application to Human Figures. IEEE Trans. on Robotics Automation. 1989,5(3):254~261
2 P. E. Anuta. Spatial registration of multispectral and multitemporal digital imagery using Fast Fourier Transformation techniques. IEEE Trans. on Geosci.Electron. 1970,8:355-368
3 D. I. Barnea, H. F. Silverman. A Class of Algorithms for Fast Digital Image Registration. IEEE Trans. on Computer. 1972,21:186~192
4 C. D. MacGillen et al. Image Registration on Variance as a Measure of Overlay Quality. IEEE Trans. 1976,14:44~49
5 Katsuyuki Tanimizu. High-speed Defect Detection Method for Color Printed Matter. IEEE. 1990:653~658
6 Shan X M, Kuo S K, et al. Ultra precision motion control of a multiple degrees of freedom magnetic suspension stage. IEEE Trans. on Mechatronics. 2002,7(1):67~78
7王延风.磁悬浮精密定位工作台机电一体化CAD/CAE集成研究.中国科学院博士论文. 2004:8~13
8李强,张钹.一种基于图像灰度的快速匹配算法.软件学报. 2006,17(2): 186~192
9石绘,余文勇.基于多目视觉的高速印刷质量在线检测系统.武汉理工大学学报. 2007,29(6):65~68
10姜会亮,郭振民,胡学龙.数字图像处理中几种平滑技术的研究比较.现代电子技术. 2004,27(8):185~187
11顾茂松,杨小冈,缪栋,刘云峰.基于机器视觉的印刷条码质量检测系统研究. 2007,33(5):20~26
12王岩松.基于最小二乘影像匹配的畸变图像校正算法.北方交通大学学报. 2002,26(1):15~16
13罗钟铉,刘成明.灰度图像匹配的快速算法.计算机辅助设计与图像学学报. 2005,17(5):966~969
14钟志光,卢君. Visual C++.NET数字图像处理实例与解析.清华大学出版社, 2003:383~387
15巩娟,李庆祥,李玉和.精密工作台的设计与研究.光学技术. 2005,31(4): 636~638
16薛实福,李庆祥.精密仪器设计.清华大学出版社, 1991:34~65
17谢传钵.分步重复投影光刻机精密快速定位工作台研究.光电工程. 1996,23(4):65~72
18 Awabdy B A, ShihW C, DavidM Auslander. Nanometer positioning of a linear motion stage under static bads. IEEE Trans.on Mechatronics. 1998,2(3):113~120
19 A. Goshtasby, G. C. Stockman. Point pattern matching using convex hull edges. IEEE Trans.Systems, Man and Cybemetics. 1985,15:631~637
20 G. Stockman, S. Kopstein, S. Benett. Matching images to models for registration and object detection via clustering. IEEE Trans. Pattern Analysis and Machine Intelligence. 1982,4:229~241
21 R. S. Mitra, N. N. Murthy. Elastic maximal matching. Pattern Recognition. 1991,24:747~753
22 G. Medioni, R. Nevatia. Matching images using linear features. IEEE Trans. Pattern Analysis and Machine Intelligence. 1984,6:675~685
23 W. H. Wang, Y. C. Chen. Image registration by control points pairing using the invariant properties of line segments. pattern Registration Letters. 1997,18:269~281
24 J. Ton, A. K. Jain. Registering Lands at images by point matching. IEEE Trans. Geoscience and Remote Sensing. 1989,27:642~651
25 A. Noble. Finding comers. Image and Vision Computing. 1988,6:121~128
26 S. M. Smith, J. M. Brady. SUSAN-A new approach to low level image processing. Int’l. Journal of Computer Vision. 1997,23:45~78
27 D. Skea, I. Barrodale, R.Kuwahara, R. Poeckert, A control point matching algorithm. Pattern Recognition. 1993,26:269~276
28 T. Suk, J. Flusser. Point-based projective invariants. Pattern Recognition. 2000,33:251~261
29 Ostu N A. Tresthold Selection Method from Gray-Level Histograms.IEEE Trans. on System. 1979,9(1):62~66
30梁萧颖等.基于Hough变换的多适应性圆检测.机械与电子. 2007,9: 74~75
31 Truchetet F, Laligant O. Subpixle edge detection for dimensional control by artificial vision. Journal of Electronic Imaging. 2001,10(1):234~239
32张永宏等.基于灰度矩的CCD图像亚像素边缘检测算法研究.光学技术. 2004,30(6):693~698
33 KRIS J, DIMITRIS A. Subpixel edge localization and the interpolation of still images. IEEE Trans. on Image Processing,1995,4(3):285~295
34孙家广.计算机图形学(第三版).清华大学出版社. 1999:35~41
35和青芳.计算机图形学原理及算法教程(Visual C++版).清华大学出版社, 2006:45~53
36 Lee K M. Kinematic Analysis of a Three Degree of Freedom In-Parallel Actuated Manipulators. IEEE Trans. on Robotics Automation. 1998,4(2): 354~360
37朱红光,周云飞,胡建兵,胡科峰.一种两层复合式微驱动平台的运动分析.机床与液压. 2004,6:11~12
38武建新,李强,赵卫国,孙燕.并联机构机电耦合动力学计算.中国工程机械学报. 2006,4(4):415~418
39 Bhaskar Dasgupta, Mruthyunjaya. A Newton-Euler formulation for the inverse dynamics of Stewart platform manipulator. Mechanism and Machine theory. 1998,33(8):1135~1152
40郭祖华,陈五一,陈鼎昌. 6-UPS并联机构的刚体动力学模型.机械工程学报. 2002,38(11):53~57
41 Y. Nakamura, M. Ghodoussi. Dynamics computation of Structure: Varying Kinematics Chains and its Application to Human Figures. IEEE Trans. on Robotics Automation. 1989,5(3):254~261