Due to the increasing complexity of operating conditions and performance requirements, improvements in the precision of mirror systems have been actively sought. However, these developments have complicated the design of structural optimization and real-time performance monitoring. A high-dimensional parametric model of the mirror system has been developed that enables fast multi-parameter, multi-constraint, and multi-objective optimization for mirror systems. With only 100 finite element analyses, collaborative optimization with three objectives and three constraints was effectively achieved by the constraint surrogate assisted evolutionary algorithm CNSGAIII-EHVI. This method provided Pareto solutions with greater accuracy, comprehensiveness, and diversity than other algorithms. A digital twin platform was also created to facilitate real-time online monitoring and performance visualization of the mirror system. By combining the RBF-G model with optical fitting data, fast wavefront reconstruction and real-time visualization of full-field deformation with synchronized changes in deflection angles and steady-state temperatures were enabled. With an R2 value of 0.999, the wavefront calculation and visualization were completed in 2 s, while the response time for the full-field deformation was about 50 ms. This paper presents an idea for data-fused modeling, optimization, and visualization in optomechanical systems.
Guo et al. (Sun,) studied this question.
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