An effective temperature monitoring scheme using ANN-based fiber Bragg grating sensor

Abstract

In this paper, a fiber Bragg grating (FBG) based temperature sensor is designed and implemented using a conventional laser source. It is observed that the sensitivity of FBG temperature sensor is low and not effective in sensing temperature of critical applications. Hence, FBG temperature sensitization encapsulation technique is introduced to increase the sensitivity of the sensor. The sensitivity is improved by a factor of 44 with temperature sensitization encapsulation technique, but the linearity error is ±15% full scale reading. In order to retain the high sensitivity without compromising the linearity of the system, multilayer perceptron (MLP) artificial neural network (ANN) is introduced to estimate and reduce the linearity error of FBG sensor. The Levenberg-Marquardt (LM) algorithm is used for training and learning mechanism of MLP-ANN. A linearity error of approximately ±2.8% is achieved without affecting the sensitivity of the system.