Abstract

Optical sensors using fiber Bragg gratings (FBGs) have become an alternative to traditional electronic sensors thanks to their immunity against electromagnetic interference, their applicability in harsh environments, and other advantages. However, the complexity and high cost of the FBG interrogation systems pose a challenge for the wide deployment of such sensors. Herein, we present a clean and cost-effective method for interrogating an FBG temperature sensor using a micro-chip called the waveguide spectral lens (WSL) and a standard CMOS camera. This interrogation system can project the FBG transmission spectrum onto the camera without any free-space optical components. Based on this system, an FBG temperature sensor is developed, and the results show good agreement with a commercial optical spectrum analyzer (OSA), with the respective wavelength-temperature sensitivity measured as 6.33 pm/°C for the WSL camera system and 6.32 pm/°C for the commercial OSA. Direct data processing on the WSL camera system translates this sensitivity to 0.44 μm/°C in relation to the absolute spatial shift of the FBG spectra on the camera. Furthermore, a deep neural network is developed to train the spectral dataset, achieving a temperature resolution of 0.1 °C from 60 °C to 120 °C, while direct processing on the valley/dark line detection yields a resolution of 7.84 °C. The proposed hardware and the data processing method may lead to the development of a compact, practical, and low-cost FBG interrogator.

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