两镜反射系统自适应装调技术研究

Adaptive alignment technology of two-mirror reflection system

  • 摘要: 为了满足两镜反射系统对光学元件高精度的装调、定位要求,以及系统工程化应用对可靠性与装调效率的要求,提出了一种基于人工神经网络(ANN)的自适应装调技术。基于矢量波像差理论分析两镜系统波像差与失调量的映射关系,在Keras框架下搭建ANN,并以非解析思路构建了自适应装调模型,开发了自适应装调装置,使失调次镜的平移调校精度优于2 μm,倾斜调校精度优于2″,解决了算法设计与精度优化、反射镜组微应力固联等技术难题,并对某双抛无焦系统完成了自适应装调验证。试验结果表明:运用该装调技术,两镜反射系统装调后波像差优于λ/16、装调周期大幅缩短、装配可靠性通过环境试验考核,为该技术的工程化应用打下了基础。

     

    Abstract: In order to meet the requirements of high-precision alignment and positioning of optical elements for two-mirror reflection system, as well as the requirements of reliability and efficiency for system engineering applications, an adaptive alignment technology based on artificial neural network (ANN) was proposed. Based on the vector wave aberration theory, the mapping relationship between the wave aberration and the offset of the two-mirror system was analyzed. The ANN was built under the framework of Keras, and the adaptive alignment model was constructed with non-analytic ideas. An adaptive alignment device was developed to make the alignment accuracy of the secondary mirror better than 2 μm, and the tilt alignment accuracy is better than 2″, which solved the technical problems such as algorithm design and precision optimization, micro-stress connection of mirror group, and completed the adaptive alignment verification of a double parabolic defocusing system. The test results show that by using this technology, the wave aberration after alignment of system is better than λ/16, the alignment cycle is greatly shortened, and the assembly reliability passes the environmental test assessment, which lays a foundation for the engineering application of the technology.

     

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