The optical-mechanical system of a space camera is composed of several complex components, and the effects of several factors (weight, gravity, modal frequency, temperature, etc.) on its system performance need to be considered during ground tests, launch, and in-orbit operation. In order to meet the system specifications of the optical camera system, the dimensional parameters of the optical camera structure need to be optimized. There is a highly nonlinear functional relationship between the dimensional parameters of the optical machine structure and the design indexes. The traditional method takes a significant amount of time for finite element calculation and is less efficient. In order to improve the optimization efficiency, a recurrent neural network prediction model based on the Bayesian regularization algorithm is proposed in this paper, and the NSGA-II is used to globally optimize multiple prediction objectives of the prediction model. The reflector of the space camera is used as an example to predict the weight, first-order modal frequency, and gravitational mirror deformation root mean square of the reflector, and to complete the lightweight design. The results show that the prediction model established by BR-RNN-NSGA-II offers high prediction accuracy for the design indexes of the reflector, which all reach over 99.6%, and BR-RNN-NSGA-II can complete the multi-objective optimization search efficiently and accurately. This paper provides a new idea of optimization of optical machine structure, which enriches the theory of complex structure design.

Fit of the highly nonlinear functional relationship between input variables and output response is important and challenging for the optical machine structure optimization design process. The backpropagation neural network method based on particle swarm optimization and Bayesian regularization algorithms (called BMPB) is proposed to solve this problem. A prediction model of the mass and first-order modal frequency of the supporting structure is developed using the supporting structure as an example. The first-order modal frequency is used as the constraint condition to optimize the lightweight design of the supporting structure’s mass. Results show that the prediction model has more than 99% accuracy in predicting the mass and the first-order modal frequency of the supporting structure, and converges quickly in the supporting structure’s mass-optimization process. The supporting structure results demonstrate the advantages of the method proposed in the article in terms of high accuracy and efficiency. The study in this paper provides an effective method for the optimized design of optical machine structures.

The temperature state of outer space devices is influenced by the heat flow outside the space. Although traditional numerical simulation analysis methods are highly accurate, they are time-consuming and not conducive for researchers to quickly assess the effects of external heat flow variations and are difficult to apply to program optimization codes that require large-scale iterative calculations or to codes for on-board temperature control chips. This paper presents an analytical algorithm for heat transfer problems: The transfer function method is applied to the thermal control analysis of outer space equipment with a small computational effort and a simple and straightforward computational procedure. Although this analytical approach only considers a limited set of influencing parameters and the precision of the calculation cannot be compared with numerical methods, it can be applied to the early prediction of internal temperature changes caused by heat flow changes outside the modification of outer space devices, embedded in the optimization code of a design solution, or integrated into the code of an on-board temperature control chip with minimum computational effort. In general, the transfer function method is not suitable for solving the radiation term, whereas this paper excludes the radiation term from the time delay calculation based on the small time scale of the radiation term and solves the time delay of the internal temperature relative to the external surface temperature directly, whereas the amplitude decay of the internal temperature change relative to the external surface temperature fluctuation is solved by the steady-state method based on the long period of the external heat flow change. The practicality of the transfer function method in the design of thermal control of external space devices is evidenced by comparing the computational results with those of commercial software and experimental results.