Multivision demodulation of the FBG based on a thermal-induced chirp and a shallow neural network

We present a high-precision, low-cost demodulation method for the fiber Bragg grating (FBG) using a thermal-induced, chirp and a shallow neural network. The thermal-induced chirp of a semiconductor laser generates the different wavelength components in a single pulse, which will form an exponential function echo signal after being reflected by the FBG. By learning the shape of the reflected light, the back-propagation neural network can simultaneously demodulate the sensing temperature and laser power. The whole detection system has only a few basic detection devices, which makes it low cost. The experimental results show that the multivision demodulation (MVD) method can reach a high demodulation precision of 0.35 degrees C. We believe these results indicate the MVD method is an outstanding scheme in the field of FBG interrogation. (C) 2021 Optical Society of America

Automated summary

A high-precision, low-cost demodulation method for fiber Bragg gratings (FBG) is presented, utilizing thermal-induced chirp and a shallow neural network to simultaneously demodulate sensing temperature and laser power. Experimental results show a high demodulation precision of 0.35 degrees C, indicating the potential of the multivision demodulation (MVD) method in the field of FBG interrogation.