平面喷涂漆膜厚度分布规律研究与搭接参数优化
|
摘要
目的实现大型船舶外板表面喷涂的自动化作业,开展表面漆膜厚度分布规律研究,优化平面喷涂轨迹,求出最佳喷涂搭接参数。方法以喷嘴雾幅宽度、距离、喷枪移动速度三个喷涂工艺参数为因素进行正交实验,获得漆膜厚度分布数据,使用b分布函数进行实验数据表征,运用遗传算法优化拟合b分布模型的三个关键参数。基于BP神经网络算法建立漆膜厚度分布预测模型,并对预测结果进行合理性分析。在此基础上,研究每道漆膜之间的搭接规律,运用NSGA-Ⅱ算法求解最优漆膜搭接宽度。结果计算得到15组实验数据对应b分布模型的T_(max)、w及β,构建的漆膜厚度分布预测模型能准确预测在不同喷涂工艺参数下的漆膜厚度分布。以第16组实验为例,计算得到了最优的漆膜搭接宽度为41.76 cm。结论建立了喷涂工艺参数和膜厚分布规律之间的映射模型,该模型可以准确预测不同工艺参数下的涂层厚度分布,应用该模型计算出的最优漆膜搭接宽度能获得厚度均匀的涂层,为实现船舶外板的自动化喷涂做好了前期准备。
The work aims to study the thickness distribution of paint film so as to achieve automatic spray painting on huge ship outer panel, optimize surface spraying trajectory and find out the best lap width of paint film. The orthogonal experiment was designed with 3 factors, including width of spray nozzle, distance and speed of spray gun to obtain the thickness distribution data of paint film. β distribution function was used to characterize experimental data, and Genetic Algorithm(GA) was applied to optimize 3 key parameters of the β distribution model. The thickness distribution prediction model of paint film was established based on BP(Back Propagation) neural network, and the prediction results were analyzed reasonably. The overlap rules of each paint film were studied and NSGA-Ⅱ algorithm was used to solve the best lap width of paint film. The corresponding T_(max), w and β of the β distribution model were obtained for the 15 groups of painting experimental data. The prediction model could accurately predict the thickness distribution of paint film under different spraying parameters. For example, in the 16~(th) group of painting experiment, the best lap width of paint film was 41.76 cm. The mapping model between the spraying process parameters and the paint film thickness distribution is obtained. The mapping model can accurately predict the coating thickness distribution under different process parameters. The best lap width of paint film calculated based on this model can obtain the coating with uniform thickness, thus making good preparations for the automatic spraying of ship outer panel.
The work aims to study the thickness distribution of paint film so as to achieve automatic spray painting on huge ship outer panel, optimize surface spraying trajectory and find out the best lap width of paint film. The orthogonal experiment was designed with 3 factors, including width of spray nozzle, distance and speed of spray gun to obtain the thickness distribution data of paint film. β distribution function was used to characterize experimental data, and Genetic Algorithm(GA) was applied to optimize 3 key parameters of the β distribution model. The thickness distribution prediction model of paint film was established based on BP(Back Propagation) neural network, and the prediction results were analyzed reasonably. The overlap rules of each paint film were studied and NSGA-Ⅱ algorithm was used to solve the best lap width of paint film. The corresponding T_(max), w and β of the β distribution model were obtained for the 15 groups of painting experimental data. The prediction model could accurately predict the thickness distribution of paint film under different spraying parameters. For example, in the 16~(th) group of painting experiment, the best lap width of paint film was 41.76 cm. The mapping model between the spraying process parameters and the paint film thickness distribution is obtained. The mapping model can accurately predict the coating thickness distribution under different process parameters. The best lap width of paint film calculated based on this model can obtain the coating with uniform thickness, thus making good preparations for the automatic spraying of ship outer panel.
引文
[1]陈雁,邵君奕,张传清,等.喷涂机器人自动轨迹规划研究进展与展望[J].机械设计与制造,2010(2):149-151.CHEN Yan,SHAO Jun-yi,ZHANG Chuan-qing,et al.Developments and prospects of research on automatic trajectory planning for painting robot[J].Machinery design&manufacture,2010(2):149-151.
[2]ANTONIO K J,RAMABHADRAN R,LING L T.A Framework for trajectory planning for automated spray coating[J].International journal of robotics and automation,1997,12(4):124-134.
[3]FREUND E,ROKOSSA D,ROSSMANN J.Processoriented approach to an efficient off-line programming of industrial robots[C]//Proceedings of the 24th annual conference of the IEEE industrial electronics society.New York,USA:IEEE,1998.
[4]AR?KAN M A S,BALKAN T.Process modeling,simulation,and paint thickness measurement for robotic spray painting[J].Journal of robotic systems,2000,17(9):479-494.
[5]SUH S H,WOO I K,NOH S K.Development of an automatic trajectory planning system(ATPS)for spray painting robots[C]//Proceedings of the 1991 IEEE international conference on robotics and automation.Sacramento,CA:IEEE,1991.
[6]张永贵,黄玉美,高峰,等.喷漆机器人空气喷枪的新模型[J].机械工程学报,2007,42(11):226-233.ZHANG Yong-gui,HUANG Yu-mei,GAO Feng,et al.New model for air spray gun of robotic spray-painting[J].Chinese journal of mechanical engineering,2007,42(11):226-233.
[7]王国磊,伊强,缪东晶,等.面向机器人喷涂的多变量涂层厚度分布模型[J].清华大学学报(自然科学版),2017,57(3):324-330.WANG Guo-lei,YI Qiang,MIAO Dong-jing,et al.Multivariable coating thickness distribution model for robotic spray painting[J].Journal of Tsinghua University(science&technology),2017,57(3):324-330.
[8]杨连生,李爱平,祁国栋,等.基于优化BP算法的涂装机器人喷涂漆膜厚度成长模型的研究[J].中国造船,2016,57(1):193-199.YANG Lian-sheng,LI Ai-ping,QI Guo-dong,et al.Amodified BP based model of thickness growth of film sprayed with painting robot[J].Ship building of China,2016,57(1):193-199.
[9]潘玉龙,王国磊,朱丽,等.管道喷涂机器人喷枪运动速度优化[J].清华大学学报(自然科学版),2014,54(2):212-216.PAN Yu-long,WANG Guo-lei,ZHU Li,et al.Optimization of spray gun speed for pipe painting robot[J].Journal of Tsinghua University(science&technology),2014,54(2):212-216.
[10]吴洪键,刘敏,邓思豪,等.涂层厚度数学模型的建立及喷涂轨迹间距优化[J].热机加工工艺,2017,46(16):127-132.WU Hong-jian,LIU Min,DENG Si-hao.et al.Establishment of coating thickness mathematic model and optimization of spacing of spray track[J].Hot working technology,2017,46(16):127-132.
[11]汤养,陈伟.喷涂机器人喷枪轨迹规划的优化算法研究[J].机械设计与制造,2007(10):144-146.TANG Yang,CHEN Wei.A study on optimization algorithm of the trajectory planning for painting robots[J].Machinery design&manufacture,2007(10):144-146.
[12]龚俊,陆保印,曾勇.喷炬新模型在平面喷涂轨迹优化中的应用研究[J].机械设计与制造,2010(8):63-65.GONG Jun,LU Bao-yin,ZENG Yong.Application research of the spraying trajectory optimization in-plane for the new model of spray gun[J].Machinery design&manufacture,2010(8):63-65.
[13]孟慧杰,尹志新.喷漆机器人喷漆工艺分析及优化研究[J].机械与电子,2009(4):3-6.MENG Hui-jie,YIN Zhi-xin.Study on technology and optimization of robotic spray painting[J].Machinery&electronics,2009(4):3-6.
[14]王国磊,陈恳,陈雁,等.变参数下的空气喷枪涂层厚度分布建模[J].吉林大学学报(工学版),2012,42(1):188-192.WANG Guo-lei,CHEN Ken,CHEN Yan,et al.Film thickness distribution model with variable parameters for air spray gun[J].Journal of Jilin University(engineering and technology edition),2012,42(1):188-192.
[15]SCHAFFER J D.Multiple objective optimization with vector evaluated genetic algorithms[C]//International Conference on Genetic Algorithms.Pittsburgh,PA,USA:[s.n.],1985:93-100.
[2]ANTONIO K J,RAMABHADRAN R,LING L T.A Framework for trajectory planning for automated spray coating[J].International journal of robotics and automation,1997,12(4):124-134.
[3]FREUND E,ROKOSSA D,ROSSMANN J.Processoriented approach to an efficient off-line programming of industrial robots[C]//Proceedings of the 24th annual conference of the IEEE industrial electronics society.New York,USA:IEEE,1998.
[4]AR?KAN M A S,BALKAN T.Process modeling,simulation,and paint thickness measurement for robotic spray painting[J].Journal of robotic systems,2000,17(9):479-494.
[5]SUH S H,WOO I K,NOH S K.Development of an automatic trajectory planning system(ATPS)for spray painting robots[C]//Proceedings of the 1991 IEEE international conference on robotics and automation.Sacramento,CA:IEEE,1991.
[6]张永贵,黄玉美,高峰,等.喷漆机器人空气喷枪的新模型[J].机械工程学报,2007,42(11):226-233.ZHANG Yong-gui,HUANG Yu-mei,GAO Feng,et al.New model for air spray gun of robotic spray-painting[J].Chinese journal of mechanical engineering,2007,42(11):226-233.
[7]王国磊,伊强,缪东晶,等.面向机器人喷涂的多变量涂层厚度分布模型[J].清华大学学报(自然科学版),2017,57(3):324-330.WANG Guo-lei,YI Qiang,MIAO Dong-jing,et al.Multivariable coating thickness distribution model for robotic spray painting[J].Journal of Tsinghua University(science&technology),2017,57(3):324-330.
[8]杨连生,李爱平,祁国栋,等.基于优化BP算法的涂装机器人喷涂漆膜厚度成长模型的研究[J].中国造船,2016,57(1):193-199.YANG Lian-sheng,LI Ai-ping,QI Guo-dong,et al.Amodified BP based model of thickness growth of film sprayed with painting robot[J].Ship building of China,2016,57(1):193-199.
[9]潘玉龙,王国磊,朱丽,等.管道喷涂机器人喷枪运动速度优化[J].清华大学学报(自然科学版),2014,54(2):212-216.PAN Yu-long,WANG Guo-lei,ZHU Li,et al.Optimization of spray gun speed for pipe painting robot[J].Journal of Tsinghua University(science&technology),2014,54(2):212-216.
[10]吴洪键,刘敏,邓思豪,等.涂层厚度数学模型的建立及喷涂轨迹间距优化[J].热机加工工艺,2017,46(16):127-132.WU Hong-jian,LIU Min,DENG Si-hao.et al.Establishment of coating thickness mathematic model and optimization of spacing of spray track[J].Hot working technology,2017,46(16):127-132.
[11]汤养,陈伟.喷涂机器人喷枪轨迹规划的优化算法研究[J].机械设计与制造,2007(10):144-146.TANG Yang,CHEN Wei.A study on optimization algorithm of the trajectory planning for painting robots[J].Machinery design&manufacture,2007(10):144-146.
[12]龚俊,陆保印,曾勇.喷炬新模型在平面喷涂轨迹优化中的应用研究[J].机械设计与制造,2010(8):63-65.GONG Jun,LU Bao-yin,ZENG Yong.Application research of the spraying trajectory optimization in-plane for the new model of spray gun[J].Machinery design&manufacture,2010(8):63-65.
[13]孟慧杰,尹志新.喷漆机器人喷漆工艺分析及优化研究[J].机械与电子,2009(4):3-6.MENG Hui-jie,YIN Zhi-xin.Study on technology and optimization of robotic spray painting[J].Machinery&electronics,2009(4):3-6.
[14]王国磊,陈恳,陈雁,等.变参数下的空气喷枪涂层厚度分布建模[J].吉林大学学报(工学版),2012,42(1):188-192.WANG Guo-lei,CHEN Ken,CHEN Yan,et al.Film thickness distribution model with variable parameters for air spray gun[J].Journal of Jilin University(engineering and technology edition),2012,42(1):188-192.
[15]SCHAFFER J D.Multiple objective optimization with vector evaluated genetic algorithms[C]//International Conference on Genetic Algorithms.Pittsburgh,PA,USA:[s.n.],1985:93-100.