Highly Dense FBG Temperature Sensor Assisted with Deep Learning Algorithms

Abstract

In this paper, we demonstrate the application of deep neural networks (DNNs) for processing the reflectance spectrum from a fiberoptic temperature sensor composed of densely inscribed fiber Bragg gratings (FBG). Such sensors are commonly avoided in practice since close arrangement of short FBGs results in distortion of the spectrum caused by mutual interference between gratings. In our work the temperature sensor contained 50 FBGs with the length of 0.95 mm, edge-to-edge distance of 0.05 mm and arranged in the 1500–1600 nm spectral range. Instead of solving the direct peak detection problem for distorted signal, we applied DNNs to predict temperature distribution from entire reflectance spectrum registered by the sensor. We propose an experimental calibration setup where the dense FBG sensor is located close to an array of sparse FBG sensors. The goal of DNNs is to predict the positions of the reflectance peaks of the reference sparse FBG sensors from the reflectance spectrum of the dense FBG sensor. We show that a convolution neural network is able to predict the positions of FBG reflectance peaks of sparse sensors with mean absolute error of 7.8 pm that is slightly higher than the hardware reused interrogator equal to 5 pm. We believe that dense FBG sensors assisted with DNNs have a high potential to increase spatial resolution and also extend the length of a fiber optical sensors.

FBG-Based Accelerometer for Buried Pipeline Natural Frequency Monitoring and Corrosion Detection

“…Fiber Bragg gratings (FBGs) have relevant characteristics in the context of monitoring the integrity of structures, such as the possibility of multiplexing several gratings along a single fiber cable, as well as allowing the collection of signals with reduced noise [36]. In this scenario, the use of these sensors has gained interest also due to their easy monitoring and the different parameters that can be measured, such as deformation, frequency, acceleration, temperature, and pressure, among others [37][38][39][40][41][42]. There are a variety of applications for these sensors to identify damage in pipelines, such as leak detection, as Sun et al reported, in which the authors proposed a method based on the psychrometer principle with FBG temperature sensors to assess the manifestation of this damage [43].…”

Hot Spot Detection of Photovoltaic Module Based on Distributed Fiber Bragg Grating Sensor

“…The above methods have low detection efficiency and low accuracy, and they cannot be applied to detect distributed hot spots. The FBG sensor can achieve distributed monitoring with small-volume, anti-electromagnetic interference, and corrosion resistance [21][22][23][24]. It has been widely studied in distributed temperature measurement [25][26][27][28].…”

Temperature Field Measurement of Photovoltaic Module Based on Fiber Bragg Grating Sensor Array

“…This is especially suitable for distributed measurement. In recent years, researchers have carried out extensive research on temperature measurement with FBG sensor arrays [ 17 , 18 , 19 , 20 , 21 , 22 ].…”