导引头光学系统装配不确定性建模分析与工艺参数鲁棒性优化

薛奋琪; 贺芳; 巩浩; 刘检华; 朱荣全; 王彩锋; 胡丙阳

doi:10.12382/bgxb.2025.0053

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导引头光学系统装配不确定性建模分析与工艺参数鲁棒性优化

更新时间：2026-04-24

- 导引头光学系统装配不确定性建模分析与工艺参数鲁棒性优化
- Modeling and Analysis of Uncertainty in Seeker Optical System Assembly and Robust Optimization of Assembly Process Parameters
- 兵工学报 2026年47卷第2期页码：250053
- 作者机构：
  
  北京理工大学机械与车辆学院，北京 100081
  北京遥感信息研究所，北京 100193
  北京理工大学唐山研究院，河北唐山 063015
  河北省智能装配与检测技术重点实验室，河北唐山 063015
  北京遥感设备研究所，北京 100854
- 作者简介：
  
  通信作者邮箱：gongh0220@bit.edu.cn
- 基金信息：
  
  国家重点研发计划项目(2022YFB3403800;2022YFB3304200)
- DOI：10.12382/bgxb.2025.0053
  中图分类号： TJ765.4
- 收稿：2025-01-14，
  
  网络首发：2025-12-25，
  
  纸质出版：2026-02-28
- 稿件说明：
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薛奋琪, 贺芳, 巩浩, 等. 导引头光学系统装配不确定性建模分析与工艺参数鲁棒性优化[J]. 兵工学报, 2026,47(2):250053.

XUE Fenqi, HE Fang, GONG Hao, et al. Modeling and Analysis of Uncertainty in Seeker Optical System Assembly and Robust Optimization of Assembly Process Parameters[J]. Acta Armamentarii, 2026, 47(2): 250053.
薛奋琪, 贺芳, 巩浩, 等. 导引头光学系统装配不确定性建模分析与工艺参数鲁棒性优化[J]. 兵工学报, 2026,47(2):250053. DOI： 10.12382/bgxb.2025.0053.

XUE Fenqi, HE Fang, GONG Hao, et al. Modeling and Analysis of Uncertainty in Seeker Optical System Assembly and Robust Optimization of Assembly Process Parameters[J]. Acta Armamentarii, 2026, 47(2): 250053. DOI： 10.12382/bgxb.2025.0053.

摘要

两反式光学系统广泛应用于空间遥感、探测制导等领域，其成像质量是光学系统的核心指标，不仅依赖光学器件的制造精度，而且很大程度上受装配精度的影响。在实际工程中，光学系统装配后的成像质量很容易受到界面条件、装配位姿偏差等多源不确定性因素的影响，即使相同的装配工艺参数也可能导致成像质量出现偏差。为此，提出一种两反式光学系统装配与成像的联合仿真方法，以能量集中度作为成像质量定量评价指标，辨识光学系统装配过程中的不确定性参数并进行不确定性度量，根据参数特点选择合理的采样方法，通过联合仿真方法得到不同装配误差条件下的光学系统成像质量数据。建立基于Matern5/2核函数的高斯过程回归（Gaussian Process Re-gression，GPR）拧紧力矩指向性代理模型，以及结合贝叶斯优化和蒙特卡洛模拟（Bayesian Optimiza-tion-Monte Carlo Simulation，BO-MCS）的不确定性优化算法，基于构建的原始数据集，实现光学系统装配不确定性建模分析与装配工艺参数鲁棒性优化。研究结果表明：与其他代理模型相比，所建立的GPR代理模型具有最小的成像质量预测误差（平均预测误差仅有1.95%）；优化后的光学系统成像质量平均提升6.13%，波动半径平均减少14.05%，有效提高了光学系统装配后的成像质量一致性。

Abstract

The two-mirror optical system is widely used in fields such as space remote sensing

detection and guidance. The imaging quality

as a core performance indicator of optical systems

depends not only on the manufacturing accuracy of optical components but also significantly on the assembly precision. In practical engineering applications

the imaging quality of optical system after assembly is highly susceptible to multi-source uncertainty factors

such as interface conditions and assembly pose deviations. These factors can result in imaging quality deviations even when the identical assembly process parameters are applied. To address this issue

a joint simulation method for the assembly and imaging of two-mirror optical system is proposed

with energy concentration being used as a quantitative evaluation index for imaging quality. This method is used to identify and quantify the uncertainty parameters in the process of optical system assembly

and the appropriate sampling methods are chosen based on parameter characteristics. The imaging quality data under various assembly error conditions is generated through joint simulations. A Gaussian process regression(GPR)torque-directionality surrogate model based on the Matern 5/2 kernel function is constructed

and a Bayesian optimization-Monte Carlo simulation(BO-MCS)uncertainty optimization algorithm is presented. The uncertainty modeling of optical system assembly and the robust optimization of assembly process parameters are achieved by leveraging the developed dataset. The results show that the proposed GPR surrogate model outperforms other models with the lowest imaging quality prediction error(an average prediction error of only 1.95%). Additionally

the optimized assembly process parameters improve the average imaging quality of the optical system by 6.13% and reduce the fluctuation radius by 14.05%

significantly enhancing the consistency of imaging quality after assembly.

关键词

Keywords

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