High-sensitivity optical fiber seawater temperature and pressure sensor with a low-error demodulation method

Area of Science:

• Optoelectronics
• Sensor Technology
• Machine Learning

Background:

• Single optical microfiber (OM) sensors face demodulation errors in multi-parameter sensing due to matrix issues and nonlinearities.
• Accurate environmental monitoring requires precise measurement of parameters like temperature and pressure.

Purpose of the Study:

• To develop a novel optical microfiber coupler with a silver mirror (OMCM) for enhanced temperature and pressure sensing.
• To create a hybrid demodulation method combining machine learning and wavelength tracking for reduced error.
• To validate the sensor's performance for aquatic environment monitoring.

Main Methods:

• Fabrication of a specially packaged OMCM combined with a mechanically enhanced sensitivity fiber Bragg grating (FBG).
• Implementation of a hybrid demodulation technique integrating machine learning with wavelength tracking.
• Experimental characterization of temperature and pressure sensitivity and depth resolution.

Main Results:

• Achieved high temperature sensitivity (> -1.7 nm/°C) and pressure sensitivity (53.435 nm/MPa).
• Demonstrated a depth resolution of 0.935 cm.
• Attained low mean absolute percentage errors of 0.04% for temperature and 1.31% for pressure.

Conclusions:

• The novel OMCM sensor combined with the hybrid demodulation method effectively minimizes errors in multi-parameter sensing.
• The sensor's high sensitivity and resolution are suitable for detecting subtle changes in aquatic habitats.
• This technology offers significant potential for applications in underwater aquaculture and marine monitoring.