Deep learning assisted real-time and portable refractometer using a π-phase-shifted tilted fiber Bragg grating sensor

In this work, we demonstrate a π -phase-shifted tilted fiber Bragg grating ( π -PSTFBG)-based sensor for measuring the refractive index (RI) of NaCl solutions, achieving a real-time and online measurement system by employing a densely connected convolutional neural network (D-CNN) model to demodulate the full spectrum. The proposed π -PSTFBG sensor is prepared by using the advanced fiber grating inscription system based on a two-beam interferometry method, which could introduce deeper features of dip-splitting for all the lossy dips in the spectrum, giving the possibility of fully measuring the change of RI. This enhanced feature gives relatively higher prediction accuracy ( R 2 of 99.67%) using the well-trained D-CNN model compared with the results achieved by pure TFBG or that with a gold coating. As a further demonstration from a practical view, a prototype integrated with the proposed D-CNN algorithm is developed to conduct RI measurement of NaCl solutions in real time using a π -PSTFBG-based RI sensor. The results show that the proposed real-time demodulation system is capable of measuring RI with an average error of 1.6×10 −4 RIU in a short response time of <1 s. The demonstrated spectral demodulation approach powered by deep learning shows great potential in real-time analysis for chemical solutions and point-of-care medical testing based on RI changes, especially for the portable requirements.