Online force control of large optical grinding machine for brittle materials assisted by force prediction

Author:

Lin Shuo1ORCID,Wang QianRen1ORCID,Jiang ZhenHua1,Yin YueHong1

Affiliation:

1. State Key Laboratory of Mechanism System and Vibration, Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China

Abstract

Trajectory planning of aspherical surfaces with appropriate cutting parameters is always a tedious task, especially on difficult-to-grind materials. Orthogonal experiments are usually designed and conducted first to get a full estimation of forces under different sets of grinding conditions (e.g. depth of cut and feeding velocity). However, all these data will change, as the grinding wheel becomes blunt. To reduce the work on the selection of grinding parameters and keep the grinding process stable, a new force-controlled grinding strategy for large optical grinding machine on brittle material is proposed. The grinding force is controlled by adjusting feeding velocity along the trajectories in real time. The grinding force model is established by analyzing the complex contact area between the arc-shaped wheel and the workpiece. The co-existing of brittle and ductile removal is also considered. For the longtime delay of the system, the controller foresees the grinding force in 0.4 s later based on the model proposed, to prevent the large overshoot of the force (up to 87.5%). The verification of the controller was conducted on silicon carbide ceramics. The force overshoot was reduced to 22.5%, and the motion accuracy was guaranteed by position servo within 5 µm. The subsurface damage along the trajectory was further analyzed and discussed.

Funder

the National Basic Research Program of China

Publisher

SAGE Publications

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. System Identification and Force Estimation of a Grinding Tool;2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM);2023-06-28

2. Static numerical simulation of radial deformation of ultra-thin dicing blade;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2023-02-03

3. Tracking changes in grinding wheel condition using reduced features of acoustic emission signals;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2022-04-07

4. Simulation and experimental study of tool wear in high-speed dry gear hobbing;The International Journal of Advanced Manufacturing Technology;2022-01-06

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