Submicron Motion Measurement Based on Nonlinear Identification of Diffractive Optical Features

Abstract

Abstract Precision positioning is a critical technology in precision machinery manufacturing, and precision displacement measurement is the basis of precision positioning. Optical displacement measurement technology currently occupies the dominant position of precision displacement measurement. In contrast, the existing precision optical measurement methods are easily restricted by environmental interference, high cost, complex structure, and difficult integration. A submicron-level accuracy motion measurement method proposed in this paper is based on the nonlinear identification of diffractive optical features with the help of spatial information contained in the phenomenon of Fresnel diffraction. According to this method, the relationship between the aperture position and the diffraction image in Fresnel circular aperture diffraction is used to establish a nonlinear mapping model of the relationship between diffractive optical features and the aperture position by a convolutional neural network to convert the plane displacement measurement into the problem of diffractive optical features recognition, to realize the high-precision motion displacement measurement of two degrees of freedom on the same plane. An experimental setup is developed and experimentally tested to verify the scheme’s feasibility. The experimental results show that the mapping relationship between diffractive optical features and aperture position can be adequately fitted by CNN to achieve motion measurement with submicron-level accuracy. This method of precision measurement based on diffractive optical features provides a new research idea and solution for motion measurement with submicron-level accuracy.