Method of smoothing an aspheric surface with mm-scale departure

Jian Zhang

doi:10.1117/12.2245102

28 October 2016 Method of smoothing an aspheric surface with mm-scale departure

Jian Zhang

Proceedings Volume 9683, 8th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies; 96830D (2016) https://doi.org/10.1117/12.2245102
Event: Eighth International Symposium on Advanced Optical Manufacturing and Testing Technology (AOMATT2016), 2016, Suzhou, China

Abstract

Method of smoothing an aspheric surface was studied and discussed in this paper, and a new design of smoothing tool called bonnet-like polishing tool was used to smooth out Mid-Spatial-Frequency (MSF) errors. A concave surface with F# 0.8 and a huge departure of 1mm from best fit radius was polished by this new bonnet-like polishing tool in this paper. The tool can be well matched to the changing radius of the aspheric surface and can effectively restrain MSF errors on the surface. After pre-polishing, the surface was first smoothed by the tool and then was corrected by the bonnet polishing method. This iteration was continued until the MSF errors were nearly gone. In this process, the aspheric surface was first tested by Luphoscan and then tested by CGH when the surface was good enough, which can ensure the accuracy of the surface. This new tool was successfully used to polish a 240mm aperture asphere. Finally, after two iterations between surface smoothing and figure correction, the surface accuracy converged to 5.7nm RMS as well as the period between 1mm to 10 mm converged to around 4nm RMS. The result shows that this method can realize the valid polishing of high-accuracy aspheric surface with mm-scale departure.

Citation Download Citation

Jian Zhang "Method of smoothing an aspheric surface with mm-scale departure", Proc. SPIE 9683, 8th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies, 96830D (28 October 2016); https://doi.org/10.1117/12.2245102

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