Research on subaperture stitching optimization algorithm for large flat mirror testing

被引：0

作者：

Zhou, Zhixuan ^{[1
]}

Han, Sen ^{[1
]}

Xu, Chunfeng ^{[1
]}

Wang, Quanquan ^{[1
]}

机构：

[1] Univ Shanghai Sci & Technol, Shanghai 200093, Peoples R China

来源：

OPTICAL METROLOGY AND INSPECTION FOR INDUSTRIAL APPLICATIONS IX | 2022年 / 12319卷

基金：

国家重点研发计划;

关键词：

flat mirror testing; subaperture stitching; stitching error; immune optimization algorithm;

D O I：

10.1117/12.2643395

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

To address the problem of high-precision detection of large flat aperture mirror shapes, the current subaperture stitching methods are analyzed. The results show that the full aperture surface shape stitching errors due to subaperture adjustment errors and localization errors are the main reasons affecting the high precision detection. To improve the detection accuracy of subaperture stitching, we propose an immune optimization algorithm for subaperture stitching. The algorithm reduces the influence of subaperture adjustment errors and positioning errors, so that the PV value of reconstructed shape reaches lambda/100. It is shown that the proposed method can effectively control the stitching errors and improve the stitching accuracy.

引用

页数：8

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