Modeling of the nonlinearity in nano-displacement measuring system based on the neural network approaches

Saeed Olyaee; Reza Ebrahimpour; Samaneh Hamedi; Farzad M. Jafarlou

doi:10.1117/12.846348

21 October 2009 Modeling of the nonlinearity in nano-displacement measuring system based on the neural network approaches

Saeed Olyaee, Reza Ebrahimpour, Samaneh Hamedi, Farzad M. Jafarlou

Author Affiliations +

Proceedings Volume 7515, Photonics and Optoelectronics Meetings (POEM) 2009: Industry Lasers and Applications; 75150H (2009) https://doi.org/10.1117/12.846348
Event: Photonics and Optoelectronics Meetings 2009, 2009, Wuhan, China

Abstract

Periodic nonlinearity is the main limitation on the accuracy of the nano-displacement measurements in the heterodyne interferometers. It is mainly produced by non-ideal polarized beams of the leaser and imperfect alignment of the optical components. In this paper, we model the periodic nonlinearity resulting from non-orthogonality and ellipticity of the laser beam by using combination of neural networks such as stacked generalization method and mixture of experts. The ensemble neural networks used for nonlinearity modeling are compared with single neural networks such as multi layer percepterons and radial basis function.

Citation Download Citation

Saeed Olyaee, Reza Ebrahimpour, Samaneh Hamedi, and Farzad M. Jafarlou "Modeling of the nonlinearity in nano-displacement measuring system based on the neural network approaches", Proc. SPIE 7515, Photonics and Optoelectronics Meetings (POEM) 2009: Industry Lasers and Applications, 75150H (21 October 2009); https://doi.org/10.1117/12.846348

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