Hysteresis Compensation in Temperature Response of Fiber Bragg Grating Thermometers Using Dynamic Regression

Published

September 23, 2022

Author(s)

Zeeshan Ahmed

Abstract

In recent years there has been considerable interest in using photonic thermometers such as Fiber Bragg grating (FBG) and silicon ring resonators as an alternative technology to resistance-based legacy thermometers. Although FBG thermometers have been commercially available for decades their metrological performance remains remain poorly understood, hindered in part by complex behavior at elevated temperatures. In this study we systematically examine the temporal evolution of the temperature response of 14 sensors that were repeatedly cycled between 233 K and 393 K. Data exploration and modelling indicates the need to account for serial-correlation in model selection. Utilizing the coupled-mode theory treatment of FBG to guide feature selection we evaluate various calibration models. Our results indicates that a dynamic regression model can effectively reduce measurement uncertainty due to hysteresis by up to $\approx $70 \% .

Citation

Sensors and Actuators A: Physical

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.sna.2022.113872

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Keywords

nist-on-a-chip, nanophotonics, photonic thermometry, arima, time series, AI

Citation

Ahmed, Z. (2022), Hysteresis Compensation in Temperature Response of Fiber Bragg Grating Thermometers Using Dynamic Regression, Sensors and Actuators A: Physical, [online], https://doi.org/10.1016/j.sna.2022.113872, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934728 (Accessed December 5, 2024)