Carbon Dioxide Optical Sensing using Tapered and Coated LPGs and Neural Networks

Abstract

This work presents the development of a refractive index sensing methodology for measuring carbon dioxide concentrations, considering the effect of temperature environment. We propose and demonstrate, using simulations, the use of tapered and coated Long Period Gratings as a way to enhance the refractive index sensitivity. In addition, artificial neural networks were used to improve the estimation of carbon dioxide concentration, considering the crosssensitivity effect with temperature.

Index Terms
Artificial Neural Networks; Carbon Dioxide; LPG; Optical Fiber Sensors.