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Acta Armamentarii ›› 2025, Vol. 46 ›› Issue (3): 240278-.doi: 10.12382/bgxb.2024.0278

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Integrated Optomechanical Simulation and Surrogate Model Construction for Imaging Quality Prediction of Two-mirror Optical System

XUE Fenqi1,2, GONG Hao1,2,3,*(), LIU Jianhua1,2,3, ZHU Rongquan4, XIE Weichu1, LEI Jingting1   

  1. 1 School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
    2 Tangshan Research Institute, Beijing Institute of Technology, Tangshan 063015, Hebei, China
    3 Hebei Key Laboratory of Intelligent Assembly and Detection technology, Tangshan 063015, Hebei, China
    4 Beijing Institute of Remote Sensing Equipment, Beijing 100854, China
  • Received:2024-04-12 Online:2025-03-26
  • Contact: GONG Hao

Abstract:

The two-mirror optical system is widely used in the fields and space remote sensing,detection,guidance and so on.Assembly is a key step that impacts the imaging quality of optical system.Currently,there is a lack of systematic research on the correlation between various assembly errors and imaging quality of optical system,which hinders real-time adjustment of optical system.In this study,a joint simulation method is proposed for the assembly and imaging of two-mirror optical system.This method involves using finite element simulation to obtain mirror surface figure errors,followed by precise fitting using Zernike polynomials.Subsequently,optical design and analysis software is employed to conduct the light path imaging simulations for the mirror surface figure errors fitted by Zernike polynomials and the assembly position deviations.The energy concentration degree serves as a quantitative evaluation index for assessing the imaging quality of optical system under different assembling error conditions.Furthermore,a support vector regression (SVR) surrogate model that incorporates both local and global mixed kernel functions is established to accurately capture the correlation between assembly errors and imaging quality.Research results indicate that the mixed kernel function SVR surrogate model proposed in the paper exhibits the smallest imaging quality prediction error with an average prediction error of only 6.51% compared to single kernel function or no kernel function SVR models.The proposed joint simulation method for assembly and imaging,along with the mixed kernel function SVR surrogate model,provides auxiliary support for real-time adjustment of optical systems under varying assembly error conditions.

Key words: optical system, assembly error, energy concentration, support vector regression surrogate model, mixed kernel function

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