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机器人磨抛氧化锆涂层工艺研究 被引量:2

Research on Robotic Automatic Grinding for Zirconia Coating
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摘要 使用搭建的机器人自动磨抛平台系统,针对氧化锆热障涂层磨抛工艺开展了研究,旨在通过机器人磨抛加工对涂层厚度及表面粗糙度进行合理控制,提高涂层表面质量。基于Preston理论建立了氧化锆涂层材料的去除模型;通过单因素试验研究了主要磨抛参数对材料去除深度的影响规律,基于正交试验确立了氧化锆涂层材料磨抛最优工艺参数组合和工艺步骤,对航空发动机喉道密封片氧化锆涂层进行了磨抛加工。试验结果表明,在一定范围内,材料去除深度随着磨抛压力及磨抛盘转速的增大而增大,随着进给速度的增大而减小;磨抛压力对材料去除深度的影响较大,磨抛倾角对去除深度的影响较小。机器人磨抛系统采用力控方式实现了定量均匀去除,涂层厚度和表面质量一致性良好,加工效率显著提高,同时也验证了本机器人自动磨抛系统的实用性和优越性。 Based on the robot automatic grinding platform, the experimental study on the grinding process of zirconia coating was carried out in order to control the coating thickness and surface roughness properly and improve coating surface quality. Based on Preston removal equation, the material removal model was established. The effect of main parameters on the removal depth was studied by single factor experiments. The optimum process parameters and process steps were determined by orthogonal experiment and utilized on the zirconia coating of throat seal of aero-engine. The experimental results show that the removal depth of the material increases with the increasing of grinding force and speed of grinding tool, and decreases with the increasing of feed speed in a certain range. The grinding force has the more influence and the grinding angle has less influence on the removal depth. The force control method is adopted to achieve the quantitative and uniform removal, the coating thickness and surface quality are consistent, the processing efficiency is improved significantly, which verifies the practicability and advantages of the robot automatic grinding system.
作者 田凤杰 安宏伟 李小龙 李论 TIAN Fengjie;AN Hongwei;LI Xiaolong;LI Lun(School of Mechanical Engineering, Shenyang Ligong University, Shenyang 110159, China;Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China)
出处 《航空制造技术》 2019年第10期38-43,50,共7页 Aeronautical Manufacturing Technology
基金 辽宁省自然科学基金指导计划项目(20180550648) 国家自然科学基金资助项目(51775542)
关键词 机器人自动磨抛 氧化锆涂层 正交试验 参数优化 Robotic automation grinding Zirconium oxide coating Orthogonal test Parameter optimization
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