Edge effect of optical surfacing process with different data extension algorithms

Yang LIU, Haobo CHENG, Zhichao DONG, Hon-Yuen TAM

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PDF(572 KB)
Front. Optoelectron. ›› 2014, Vol. 7 ›› Issue (1) : 77-83. DOI: 10.1007/s12200-014-0393-7
RESEARCH ARTICLE
RESEARCH ARTICLE

Edge effect of optical surfacing process with different data extension algorithms

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Abstract

This study presents a strategy which integrates extra polishing path (EPP) and error map extension to weaken the edge effect in the ultraprecise optical surfacing process. Different data extension algorithms were presented and analyzed. The neighbor-hood average can be selected as the frequently-used method, as it has not bad precision and time-saving performance for most surface forms through the simulation results and practical experiment. The final error map was obtained, its peak-to-valley (PV) was 0.273λ and root mean square (RMS) was 0.028λ (λ = 632.8 nm). The edge effect was weakened and suppressed well through the experiment.

Keywords

edge effect / convergence rate / extension algorithms

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Yang LIU, Haobo CHENG, Zhichao DONG, Hon-Yuen TAM. Edge effect of optical surfacing process with different data extension algorithms. Front Optoelec, 2014, 7(1): 77‒83 https://doi.org/10.1007/s12200-014-0393-7

References

[1]
Johns M. The giant magellan telescope (GMT). In: Proceedings of SPIE, Extremely Large Telescopes: Which Wavelengths? Lund, Sweden, 2008, 6986: 696803-1-696803-12
[2]
Clampin M. Status of the James Webb space telescope (JWST). In: Proceedings of SPIE, Astronomical Telescopes and Instrumentation: Synergies Between Ground and Space. France, 2008, 7010: 70100L-1-70100L-7
[3]
Kim D W, Park W H, Kim S W, Burge J H. Parametric modeling of edge effects for polishing tool influence functions. Optics Express, 2009, 17(7): 5656-5665
CrossRef Pubmed Google scholar
[4]
Jones R A. Computer-controlled optical surfacing with orbital tool motion. Optical Engineering (Redondo Beach, Calif.), 1986, 25(6): 785-790
CrossRef Google scholar
[5]
Zhang X J, Yu J C, Sun X F. Theoretical method for edge figuring in computer-controlled polishing of optical surface. In: Proceedings of SPIE’s 1993 International Symposium on Optics, Imaging, and Instrumentation. 1994, 239-246
[6]
Luna-Aguilar E, Cordero-Davila A, Gonzalez J, Nunez-Alfonso M, Cabrera V, Robledo-Sanchez C I, Cuautle-Cortez J, Pedrayes M H. Edge effects with Preston equation. In: Procedings of SPIE, Astronomical Telescopes and Instrumentation. 2003, 4840: 598-603
[7]
Cordero-Dávila A, González-García J, Pedrayes-López M, Aguilar-Chiu L A, Cuautle-Cortés J, Robledo-Sánchez C. Edge effects with the Preston equation for a circular tool and workpiece. Applied Optics, 2004, 43(6): 1250-1254
CrossRef Pubmed Google scholar
[8]
Wang T, Cheng H B, Feng Y P, Dong Z C. Simulation analysis of edge effect in typical processing. Transactions of Beijing Institute of Technology, 2011, 31(9): 1100-1103
[9]
Shu L X, Wu F, Shi C Y. Optimization of the edge extension in dwell time algorithm for ion beam figuring. In: Proceedings of 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies (AOMATT). 2012, 8416: 84162M-1-84162M-6
[10]
Jiao C J, Li S Y, Xie X H. Algorithm for ion beam figuring of low-gradient mirrors. Applied Optics, 2009, 48(21): 4090-4096
CrossRef Pubmed Google scholar
[11]
Zhou L. Optical mirror ion beam figuring theory and technology. Dissertation for the Doctoral Degree. Hunan: National University of Defense Technology, 2008, 30-43 (in Chinese)
[12]
Wu J. Research on ion beam figuring technology. Dissertation for the Doctoral Degree. Jilin: Changchun Institute of optics, Fine Mechanics and Physics, Chinese Academy of Science, 2010, 13-38
[13]
MarksII R J, Robert J. Gerchberg’s extrapolation algorithm in two dimensions. Applied Optics, 1981, 20(10): 1815-1820 (in Chinese)
CrossRef Pubmed Google scholar
[14]
Wu J F, Lu Z W, Zhang H X, Wang T S. Dwell time algorithm in ion beam figuring. Applied Optics, 2009, 48(20): 3930-3937
CrossRef Pubmed Google scholar

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61308075, 61128012, 61061160503 and 61222506), Specialized Research Fund for the Doctoral Program of Higher Education (No. 20131101110026), and China Postdoctoral Science Foundation funded project (Nos. 2013M540052).

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2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
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