RESUMEN
Scratches on optical components induce laser damage and limit the increase in laser power. Magnetorheological finishing (MRF) is a highly deterministic optical manufacturing technology that can improve the surface roughness of optical components. Although MRF has exhibited significant potential for reducing subsurface damage and removing scratches, the principle and mechanism behind the scratch removal are not sufficiently understood. In this study, the theory of fluid mechanics is used to analyze the pressure, velocity, and particle trajectory distribution near a scratch. A physical model was developed for the differential removal of scratches at the bottom and surface of the optical components. The morphological evolution of the scratch was predicted during removal, and detailed experiments were performed to verify the effectiveness of the proposed model. The results indicate that scratches expand laterally rather than being completely removed. Furthermore, scratch removal efficiency is greater when the removal direction is perpendicular to the scratch rather than being parallel. This study offers an intrinsic perspective for a comprehensive understanding of the MRF technique used for scratch removal, which can be beneficial for removing scratches from aspherical optical systems.
RESUMEN
Industrial robots with six degrees-of-freedom have significant potential for use in optical manufacturing owing to their flexibility, low cost, and high space utilisation. However, the low trajectory accuracy of robots affects the manufacturing accuracy of optical components when combined with magnetorheological finishing (MRF). Moreover, general robot trajectory-error compensation methods cannot compensate for the running errors of large robots with high precision. To address this problem, a three-dimensional (3D) tool influence function (TIF) model based on inverse distance interpolation is developed in this study to accurately predict the TIF of different polishing gaps. A high-precision robot-MRF polishing strategy based on variable TIFs and surface shape accuracy of polished optics is proposed to achieve high-precision manufacturing without compensating for trajectory errors. Subsequently, the accuracy of a Ï420 mm fused silica mirror is experimentally verified to be from 0.11 λ RMS to 0.013 λ RMS. This validates that the robot-MRF can achieve high-precision polishing without compensating for trajectory errors. Furthermore, the proposed model will promote the applications of industrial robots in optical manufacturing and will serve as a reference in the field of intelligent optical manufacturing.
RESUMEN
The 6-DOF industrial robot has wide application prospects in the field of optical manufacturing because of its high degrees of freedom, low cost, and high space utilisation. However, the low trajectory accuracy of robots will affect the manufacturing accuracy of optical components when the robots and magnetorheological finishing (MRF) are combined. In this study, aiming at the problem of the diversity of trajectory error sources of robot-MRF, a continuous high-precision spatial dynamic trajectory error measurement system was established to measure the trajectory error accurately, and a step-by-step and multistage iterations trajectory error compensation method based on spatial similarity was established to obtain a high-precision trajectory. The experimental results show that compared with the common model calibration method and general non-model calibration method, this trajectory error compensation method can achieve accurate compensation of the trajectory error of the robot-MRF, and the trajectory accuracy of the Z-axis is improved from PV > 0.2 mm to PV < 0.1 mm. Furthermore, the finishing accuracy of the plane mirror from 0.066λ to 0.016λ RMS and the finishing accuracy of the spherical mirror from 0.184λ RMS to 0.013λ RMS using the compensated robot-MRF prove that the robot-MRF has the ability of high-precision polishing. This promotes the application of industrial robots in the field of optical manufacturing and lays the foundation for intelligent optical manufacturing.