A Model of Spray Tool and a Parameter Optimization Method for Spraying Path Planning
Ruxiang Hua1,2; Wei Zou1,2;  Guodong Chen3; Hongxuan Ma1,2; Wei Zhang4
发表期刊International Journal of Automation and Computing
2021-09
卷号18期号:6页码:1017-1031
摘要

The digital camouflage spraying of special vehicles carried out by robots can greatly improve the spraying
efficiency, spraying quality, and rapid adaptability to personalized
patterns. The selection of spray tool and the accuracy of the adopted mathematical spray tool model has a great impact on the effectiveness of spray path planning and spraying quality. Since traditional conical spray tool models are not suitable for spraying rectangular digital camouflage, according to the characteristics of digital camouflage, the coating thickness cumulative distribution model of strip nozzle spray tool for 2D plane spraying and 3D surface spraying is derived, and its validity is verified by simulation. Based on the accumulation velocity model of the coating thickness on the curved surface (ASCT) and aiming at spraying path planning within the same surface and different surfaces, a path parameter optimization method based on coating uniformity evaluation of adjacent path overlapping area is proposed. Combined with the vehicle surface model, parameters such as path interval, spray tool angle and spray tool motion velocity can be calculated in real-time to ensure uniform coating. Based on the known local three-dimensional model of vehicle surface and the comprehensive spraying simulation, the validity of the purposed models: the coating thickness on the adjacent path area (APCT), the coating thickness on the intersection of two surfaces (CCCT), the coating thickness on the intersection of a plane and a surface (PSCT), and the optimization method of path parameters are verified. The results show that compared with the traditional spray tool, the strip nozzle can better ensure the uniformity of the coating thickness of digital camouflage spray. Finally, according to a practical spraying experiment, the results prove that the proposed models not only are effective but also meet the practical industrial requirements and are of great practical value.

关键词Digital camouflage spraying robot path optimization parameter setting coating thickness uniformity
收录类别EI
语种英语
七大方向——子方向分类模式识别基础
国重实验室规划方向分类复杂系统建模与推演
是否有论文关联数据集需要存交
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/52315
专题中科院工业视觉智能装备工程实验室_精密感知与控制
通讯作者Ruxiang Hua
作者单位1.School of Artificial intelligence, University of Chinese Academy of science
2.Institute of Automation, Chinese Academy of Science
3.Shandong Jonkin Intelligent Technology Co., Ltd
4.Inner Mongolia First Machinery Group of Co., Ltd
推荐引用方式
GB/T 7714
Ruxiang Hua,Wei Zou, Guodong Chen,et al. A Model of Spray Tool and a Parameter Optimization Method for Spraying Path Planning[J]. International Journal of Automation and Computing,2021,18(6):1017-1031.
APA Ruxiang Hua,Wei Zou, Guodong Chen,Hongxuan Ma,&Wei Zhang.(2021).A Model of Spray Tool and a Parameter Optimization Method for Spraying Path Planning.International Journal of Automation and Computing,18(6),1017-1031.
MLA Ruxiang Hua,et al."A Model of Spray Tool and a Parameter Optimization Method for Spraying Path Planning".International Journal of Automation and Computing 18.6(2021):1017-1031.
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