Analytical modeling of power detection-based interrogation methods for fiber Bragg grating sensors for system optimization
Document Type
Journal Article
Publisher
SPIE
School
School of Engineering / Centre for Communications Engineering Research
RAS ID
20485
Abstract
We present an analytical model to investigate power detection-based interrogation methods for optical fiber Bragg grating (FBG) sensors. This model is used to facilitate the optimization of interrogation systems in terms of sensitivity and dynamic range. In general, power detection methods are passive intensity-based interrogation schemes, where the spectral shift in the FBG due to the applied measurand is converted into a change in optical power due to the spectral properties of the light source. The analytical model developed herein assumes that the FBG and light source are Gaussian shaped. As such, the filtering of the light source by the FBG results in the reflection of a Gaussian spectrum governed by the properties of both the light source and FBG. The further investigation of the model has enabled analytical expressions to be developed for the sensitivity and dynamic range of the different power detection methods considered. The different power detection methods investigated include linear edge source and narrow bandwidth source (utilizing the reflected component, transmitted components, and both the transmitted and reflected components). Results show how the dynamic range and sensitivity of the power detection methods vary for different FBG sensor widths and different light source properties, specifically the width and optical power. This facilitates a direct comparison between the interrogation methods and also enables system optimization based on either a given light source or FBG.
DOI
10.1117/1.OE.54.9.097109
Access Rights
subscription content
Comments
Wild, G., Richardson, S. (2015). Analytical modeling of power detection-based interrogation methods for fiber Bragg grating sensors for system optimization in Optical Engineering, 54(9) 097109. Available here.