SIA OpenIR  > 工艺装备与智能机器人研究室
Alternative TitleResearch on Intelligent Power Control Method of Robot Grinding and Polishing
Thesis Advisor李论
Keyword机器人研磨抛光 重力补偿 恒力控制 模糊PID控制 RBF神经网络PID控制
Degree Discipline检测技术与自动化装置
Degree Name硕士
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Other AbstractIn the field of workpieces grinding and polishing. At present, our country relies mainly on manual operation. Manual grinding inevitably faces many problems such as grinding quality, production efficiency, workers' working environment and controllability of production pollutants. Shortage of skilled workers and expensive hiring puts businesses under pressure for significantly higher labor costs. Against the backdrop of production contradictions and along with the continuous development of robotics and computer technology, the research and application of robots in the basic work of polishing and grinding is increasingly receiving attention from industry and academia. However, during the robot's grinding of the workpieces, factors such as the mounting position of the workpieces, the robot's vibration with the grinding tool and the robot's own accuracy can cause the ideal grinding trajectory generated by the 3D model of the workpieces to deviate from the robot's actual motion trajectory. This will cause problems with the grinding tool idling or over- grinding of the workpieces. So there is a need to maintain a constant perception during the grinding process to achieve uniform grinding of the workpieces surface. Based on this, this topic investigates the robot's force control technique in the automated polishing of complex surfaces using the aero-engine casing as a research vehicle. This paper briefly describes the current research status and main research methods of robotic grinding constant force control at home and abroad. Based on the complex curved surface experimental workpieces of aero-engine casing, a robotic grinding compliance control platform based on KUKA industrial robot and ATI six-dimensional force sensor is built. Machines, robots, and force sensors form a local area network to realize real-time data communication. The key of the robot grinding and polishing technology is to keep the contact force between the grinding tool and the workpieces to be processed constant. The gravity compensation algorithm of the robot end load is established through mathematical analysis to eliminate the influence of the load gravity factor on the solution of the robot's end contact force. Based on the robot's multi-pose motion, the effectiveness of the gravity compensation algorithm is verified. On this basis, two solutions for contact force based on the base coordinate system and the tool coordinate system are proposed. The vibration of the grinding tool in contact with the workpieces to be polished during high-speed rotation produces a strong interference signal, which makes the data collected by the sensor fluctuate seriously and directly affects the contact force calculation. Therefore, it is necessary to filter the sensor data before solving the contact force, so that the sensor value is stable and reflects the true value of contact force to a greater extent. The first-order low-pass filter algorithm is used to filter the sensor signal, and a reasonable filter frequency is obtained through experimental comparison and analysis. The design of the controller is the core of the robot grinding and polishing constant force control. The fuzzy PID control algorithm and the RBF neural network PID control algorithm are used to optimize the basic PID controller. Based on the existing mathematical model, the MATLAB simulation platform is used to analyze and optimize the control algorithm to assist in the actual grinding and polishing of the complex curved surface of the aero-engine casing. And the effectiveness of the control algorithm is proved by experiments, which can keep the contact force constant during the grinding and polishing of the robot.
Contribution Rank1
Document Type学位论文
Recommended Citation
GB/T 7714
刘速杰. 机器人研磨抛光智能力控制方法研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2020.
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