A neural network identification method for misalignment errors of reflective optical system

The reflective optical system is widely used in the military and civilian fields. Satisfactory assembly is the premise to ensure the performance of the optical system, and the identification of misalignment errors is the pivotal step of assembly. In this paper, the neural network was used to identify the non-ideal misalignment errors in the assembly process. The wave aberration was studied and the assembly model of a two-mirror reflective optical system was established. The misalignment errors of the secondary mirror were randomly generated and combined, and the corresponding Zernike coefficients were obtained through simulation. The misalignment errors identification model of neural network was established. And finally, the validity of this model was verified. The method proposed in this paper can achieve efficient and accurate identification of misalignment errors, which is of great significance for improving assembly efficiency and accuracy.