Evaluating the Effect on Demodulation With a Comprehensive Model of Distortions of Fiber Bragg Grating Sensing Signals

Abstract

Spectral distortions are complex and unpredictable in fiber Bragg grating (FBG) sensing applications. An inappropriate choice of FBG demodulation algorithm will lead to unacceptable results in practice. Although many demodulation algorithms have been developed for distorted spectra, they may be limited for some types of spectral distortion. Until now, no model of FBG spectral distortion has been proposed to test different demodulation algorithms. Here, we fulfill this aim by introducing a comprehensive model with asymmetrical distortion, multi-peaks distortion, interferometric noise, background noise, and random noise. Using numerical simulations, we evaluate the performance of eight most typical demodulation algorithms with this model. We show that different algorithms should be used within specific ranges of spectral distortions. Altogether, this study provides a guide map as useful reference for selecting an appropriate FBG demodulation algorithm for practical applications. Furthermore, our proposed model paves the way for developing more reliable FBG demodulation algorithms for different spectral distortions.