Optimization Design for the Supporting System of 2m Telescope Primary Mirror

This paper describes the optimization solution improving the total quality of the primary mirror supporting type. With the methods of Finite element analysis(FEA), Orthogonal experiment and BP Neural Network, the relationship between the structure parameters in primary mirror supporting type and the deformation of the primary mirror is built. With this relationship and Genetic Algorithm(GA) optimization design, a group of reasonable technology parameters is found that can improve the static stiffness of the primary mirror supporting type so as to reduce the gravity deformation of the primary mirror. The modal analysis and random vibration analysis are also discussed in detail, and the results indicate that the dynamic stiffness of the primary mirror supporting type is also improved.