|
The alignment of optical components is one of the fundamental tasks faced in the optical manufacturing industry. If the task is extended to miniaturized aspheric glass lenses, or multi-lens systems, the complexity is further increased. Wavefront sensors are commonly used in the precision alignment of optical components, and they provide an elegant and efficient tool for systems with high complexity. We have implemented an alignment simulation environment which is based on Zemax optics studio (ZOS) and related application interface (API). This tool is used to create a set of linear equations or a neural network which are used to solve the relation between wavefront and optical element alignment. In our first alignment approach, the optical system description is linearized by simulating a set of linear dependencies connecting the known perturbation values and corresponding aberrations in the resulting wavefront described as a set of Zernike coefficients. Based on the simulated perturbation and the resulting Zernike coefficients, the alignment correction action can be determined by solving the resulting set of linear equations in MATLAB. To get more equations to describe shallow dependencies on the on-axis solution, we added options for additional fields and an iterative solution which mimics the real alignment system by minimizing the perturbations through successive corrections in lens position estimation. As a non-linear alternative to computationally expensive equation solving approach, we have also evaluated AI-based neural networks for which the training data was automatically generated in the optical simulator via the ZOS-API. In preliminary evaluations the neural network approach has shown promising performance when compared to the approach with linearized equations.
|
