Predictive Analysis on Apodized FBG for Quasi-Distributed Temperature-Strain Sensing

Abstract

An apodized fiber Bragg grating (FBG) is designed for quasi-distributed sensing of temperature and strain due its various advantages particularly in hazardous environment. The main purpose of apodized FBG is to attain maximum reflectivity, narrow bandwidth and low level of side lobes, which are crucial for quasi-distributed sensing applications. Relationship between FBG properties and grating length have been explored to enhance and optimize the FBG. K Nearest Neighbors (KNN) algorithm is introduced for predictive analysis of FBG properties with different K values for the reliability of apodized FBG particularly for sensing applications. The optimal value of K has been identified for KNN by using various statistical techniques such as Mean Squared Error and Mean Absolute Error. Strong linearity has been obtained for both temperature and strain sensitivity of the designed apodized FBG. The optimized apodized FBG is utilized on wavelength division multiplexing (WDM) based quasi-distributed sensing system of four FBG signifying high reliability. High temperature and strain sensitivity ranges have been achieved in quasi-distributed sensing. The obtained ranges can be imposed in FBG-based sensing applications for monitoring of civil structure in hazardous environment.