A sub-aperture stitching algorithm for cylindrical surfaces

Feng Zhu; Pei-ji Guo; Xi Chen

doi:10.1117/12.2504781

16 January 2019 A sub-aperture stitching algorithm for cylindrical surfaces

Feng Zhu, Pei-ji Guo, Xi Chen

Proceedings Volume 10838, 9th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies; 1083805 (2019) https://doi.org/10.1117/12.2504781
Event: Ninth International Symposium on Advanced Optical Manufacturing and Testing Technologies (AOMATT2018), 2018, Chengdu, China

Abstract

Sub-aperture stitching algorithm is an attractive method for measuring the figure errors of large aperture optics. Measuring large aperture cylindrical surfaces by this method can effectively improve the problems of lacking sampling points, the results of evaluation are not uniform and so on. In this method, several sub-apertures of cylindrical optics will be measured one by one. Then, the relative spatial location relationship is established by the information of overlapping areas, and the sub-apertures are unified under the same coordinate system through coordinate transformation so as to achieve the stitched measurement result of the whole surface. In this process, we need to compensate for the alignment errors of each sub-aperture, but it is easy to fall into local optimum solutions when mechanical position errors are large. Therefore, a sub-aperture stitching algorithm based on particle swarm optimization (PSO) algorithm is proposed in this paper, which uses PSO to optimize the relative position errors. Particle swarm optimization is less likely to become trapped at a locally optimal solution, thus we utilized this method to develop a more robust algorithm. Computer simulation and experiment demonstrate the feasibility and validity of the proposed method.

Citation Download Citation

Feng Zhu, Pei-ji Guo, and Xi Chen "A sub-aperture stitching algorithm for cylindrical surfaces", Proc. SPIE 10838, 9th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies, 1083805 (16 January 2019); https://doi.org/10.1117/12.2504781

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KEYWORDS

Particle swarm optimization

Optics manufacturing

Computer simulations

Wavefronts

Algorithm development

Mirrors

Optical components

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