喷涂机器人风机叶片分片喷涂轨迹优化  

Spraying Robot Trajectory Optimization for Fan Blade Fragment

作　　者：曾勇[1] 陈洪博 赵雪雅 颜斌 ZENG Yong;CHEN Hongbo;ZHAO Xueya;YAN Bin(School of Mechanical Engineering,Yancheng Institute of Technology,Yancheng Jiangsu 224051,China)

机构地区：[1]盐城工学院机械工程学院,江苏盐城224051

出　　处：《机床与液压》2024年第21期64-70,共7页Machine Tool & Hydraulics

基　　金：国家自然科学基金项目(51405418);江苏省高校自然科学基金重大项目(18KJA460009);江苏省“青蓝工程”人才项目(2021);江苏省高校自然科学基金项目(22KJD460009)。

摘　　要：针对风机叶片机器人喷涂的涂层均匀性和喷涂效率优化问题,基于风机叶片的STL模型,提出一种风机叶片分片喷涂轨迹优化方法。首先,根据机器人运动空间和喷涂表面曲率对涂层厚度误差的影响规律,建立叶片表面的分片算法。然后,以涂层厚度方差最小和喷涂时间最短为目标,建立涂层均匀性和喷涂效率的多目标优化模型,并采用改进的多目标袋獾算法对喷涂轨迹参数进行求解。试验结果表明:提出的分片算法获得的分片数比传统方法至少减少45%,改进的多目标袋獾算法的搜索成功率比改进前提升了9.4%,经优化,涂层均匀性提升33.2%,喷涂效率提升16.4%。Aiming at the optimization of coating uniformity and spraying efficiency of fan blade robot spraying,an optimization method of fan blade fragment spraying trajectory was proposed based on STL model of fan blade.According to the influence rule of robot movement space and spraying surface curvature on coating thickness error,the blade surface segmentation algorithm was established.Then,a multi-objective optimization model for coating uniformity and spraying efficiency was established with the minimum coating thickness variance and the shortest spraying time as goal,and an improved multi-objective Tasmanian devil optimization(IMOTDO)algorithm was used to solve the spraying trajectory parameters.The experimental results show that the number of fragments obtained by the proposed algorithm is at least 45%less than that obtained by the traditional method,and the search success rate of the improved multi-objective Tasmanian devil algorithm is 9.4%higher than that before improvement.After optimization,the coating uniformity is increased by 33.2%,and the spraying efficiency is increased by 16.4%.

关 键 词：风机叶片 喷涂机器人 曲面分片 轨迹优化 仿真试验 

分 类 号：TK221[动力工程及工程热物理—动力机械及工程]