A Zero-Cross Detection Algorithm for Cavity-Length Interrogation of Fiber-Optic Fabry–Perot Sensors

Abstract

A zero-cross detection algorithm was proposed for the cavity-length interrogation of fiber-optic Fabry–Perot (FP) sensors. The method can avoid the inaccuracy of peak determination in the conventional peak-to-peak method for the cavity-length interrogation of fiber-optic FP sensors caused by the slow variation of the spectral power density in peak neighboring regions. Both simulations and experiments were carried out to investigate the feasibility and performance of the zero-cross detection algorithm. Fiber-optic FP sensors with cavity lengths in the range of 150–1000 μm were successfully interrogated with a maximum error of 0.083 μm.

A Review of Wearable Optical Fiber Sensors for Rehabilitation Monitoring

“…Integrating artificial intelligence and big data analysis allows for in-depth sensor data analysis, facilitating accurate diagnoses and personalized treatment plans [ 108 , 109 , 110 ]. Third, through the optimization and refinement of query algorithms, sensor performance can be enhanced while simultaneously reducing complexity and cost [ 111 , 112 , 113 , 114 ]. A notable advantage of wavelength-modulated optical fiber sensors is their capability to measure multiple parameters using a single optical fiber.…”