Optimization of spraying trajectory based on elliptical double β spraying gun model
Received date: 2019-09-03
Online published: 2020-10-14
喷涂轨迹优化是保证最终涂层高质量的重要环节,直接作用于涂层的成形过程。该文针对平面喷涂提出一种轨迹优化方法,通过互补喷枪模型的优化求解,实现高效、高质量的平面喷涂,并在此基础上针对NURBS(non-uniform rational B-spline)自由曲面喷涂,受启发于绘画时人们采用不同尺寸的画笔描绘不同精细程度的物体,提出可变尺寸画笔的喷涂概念,利用喷涂距离的变化实现喷幅尺寸大小的变化,同时利用变速喷涂,增强喷涂优化方法对各种复杂曲面的处理能力。通过仿真与实验验证,该文提出的方法喷涂平面时,膜厚均匀度损失了1.64%,而漆料利用率提升了13.54%;喷涂自由曲面时,膜厚均匀度由31.68%提升到4.79%。实验结果验证了该文提出方法的有效性。
华霄桐 , 张思敏 , 刘兴杰 , 陈志良 , 王国磊 , 陈恳 . 基于椭圆双β喷枪模型的喷涂轨迹优化[J]. 清华大学学报(自然科学版), 2020 , 60(12) : 985 -992 . DOI: 10.16511/j.cnki.qhdxxb.2020.25.020
Spraying trajectory optimization is important for ensuring high quality coatings because the trajectory directly affects the coating formation. This paper describes a trajectory optimization method for planar spraying. Efficient, high quality planar spraying is realized by solving a complementary spraying gun model. As for NURBS free-form surfaces, artists use different size brushes to create finer features on some objects than on others. This concept of variable size brushes is implemented here by changing the distance from the spray gun to the surface for free-form surfaces. The spraying is further optimized on complex surfaces by varying the spraying speed. Simulations and tests show that the film thickness uniformity is 1.64% worse and the paint utilization rate is 13.54% higher when spraying flat surfaces but that the film thickness uniformity is improved from 31.68% to 4.79% when spraying free-form surfaces. The results verify the effectiveness of this method for free-form surfaces.
| 2 | BALKAN T , ARIKAN M A S . Surface and process modeling and off-line programming for robotic spray painting of curved surfaces[J]. Journal of Robotic Systems, 2000. 17 (9): 479- 494. |
| 3 | BALKAN T , ARIKAN M A S . Modeling of paint flow rate flux for circular paint sprays by using experimental paint thickness distribution[J]. Mechanics Research Communications, 1999. 26 (5): 609- 617. |
| 4 | CONNER D C , GREENFIELD A , ATKAR P N , et al. Paint deposition modeling for trajectory planning on automotive surfaces[J]. IEEE Transactions on Automation Science and Engineering, 2005. 2 (4): 381- 392. |
| 7 | 邵振华.基于表面分割的复杂曲面喷涂路径规划与离线编程系统实现[D].南京:东南大学, 2015. |
| 7 | SHAO Z H. Spraying trajectory planning based on segmentation of complex free surfaces and development of off-line programming system[D]. Nanjing: Southeast University, 2015. (in Chinese) |
| 8 | 曾勇.大型复杂自由曲面的喷涂机器人喷枪轨迹优化研究[D].兰州:兰州理工大学, 2011. |
| 8 | ZENG Y. The research on spray tool trajectory optimization of painting robot for large and complex free-form curved surface[D]. Lanzhou: Lanzhou University of Technology, 2011. (in Chinese) |
| 9 | 张鹏.面向大曲率复杂曲面的喷涂机器人喷枪轨迹优化方法研究[D].兰州:兰州理工大学, 2017. |
| 9 | ZHANG P. Study on spray too trajectory optimization method of spray-painting robot for large curvature and complex surface[D]. Lanzhou: Lanzhou University of Technology, 2017. (in Chinese) |
| 11 | 熊浩.面向小曲率曲面的喷涂机器人喷涂轨迹规划[D].重庆:重庆大学, 2016. |
| 11 | XIONG H. Spraying trajectory planning of spraying robot on small curvature surface[D]. Chongqing: Chongqing University, 2016. (in Chinese) |
| 13 | 陈伟.喷涂机器人轨迹优化关键技术研究[D].镇江:江苏大学, 2013. |
| 13 | CHEN W. Research on key techniques of robotic spray painting trajectory optimization robot[D]. Zhenjiang: Jiangsu University, 2013.(in Chinese) |
| 14 | SHENG W H, XI N, CHEN H P, et al. Part geometric understanding for tool path planning in additive manufacturing[C]//IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium. Kobe, Japan: IEEE, 2003: 1515-1520. |
| 17 | ATKAR P N, CHOSET H, RIZZI A A. Towards optimal coverage of 2-dimensional surfaces embedded in IR3: Choice of start curve[C]//Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems. Las Vegas, USA: IEEE, 2003: 3581-3587. |
| 18 | 邢悦.异形曲面快速重构优化技术研究[D].长春:长春理工大学, 2018. |
| 18 | XING Y. Research on rapid reconstruction and optimization of special-shaped surface[D]. Changchun: Changchun University of Science and Technology, 2018. (in Chinese) |
/
| 〈 |
|
〉 |