A Fuzzy Approach to LPFG-Based Optical Sensor Processing and Interrogation

In this work, we report on a new interrogation method for long-period fiber-grating (LPFG) sensors. This type of sensor has been gaining increasing attention due its several interesting practical and metrological advantages. However, the LPFG optical signal is complex and could be difficult to process. We present a novel approach to the LPFG resonant wavelength detection and tracking using a multifilter LPFG interrogator. Multifilter LPFG interrogators present a great solution for LPFG sensor interrogation because there is no need for a priori knowledge concerning the LPFG sensor spectrum. We present a novel source-compensating preprocessing and a fuzzy inference system (FIS) to track the LPFG resonant wavelength. Our proposal was compared to two baseline models: a simple linear regression and an artificial neural network. Our results showed the new approach could reduce resonant wavelength uncertainty by almost three times comparing to results found in the literature.

Automated summary

This work reports on a new interrogation method for long-period fiber-grating (LPFG) sensors. The proposed method utilizes a multifilter LPFG interrogator for LPFG resonant wavelength detection and tracking. Results show that the new approach significantly reduces the uncertainty of the resonant wavelength compared to traditional methods.