Simultaneous Measurement of Salinity and Temperature Based on Hybrid-Interferometer

A compact hybrid-interferometer-based fiber sensor integrating the C-shaped Fabry–Perot interferometer (FPI) and Mach–Zehnder interferometer (MZI) is put forward and verified. The C-shaped FPI formed by a section of hollow core fiber (HCF) spliced between a single-mode fiber (SMF) and a few-mode fiber (FMF) and opened up by femtosecond laser inscribing technology is sensitive to salinity and temperature. While the MZI constructed by a single stress-applying fiber (SSAF) between two FMFs with a large lateral offset and covered by Polydimethylsiloxane (PDMS) is for temperature measurement only. Combined with the properties of the two interferometers, the quadratic polynomial surface fitting algorithm is adopted to solve the nonlinear response and cross-sensitivity of temperature and salinity to figure out a more precise result. According to the experimental results, the proposed sensor could achieve a high sensitivity of 12.05 nm/‰ in the salinity range of 0‰–40‰ by cavity length demodulation, and −3.33 nm/°C in the temperature range of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5~^{\circ }$ </tex-math></inline-formula>C<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 40~^{\circ }$ </tex-math></inline-formula>C by wavelength demodulation, respectively. After the processing of the quadratic polynomial surface fitting algorithm, the indication errors of salinity and temperature are 1.44% and 2.6%, respectively.

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Publication Details

Journal
IEEE Sensors Journal
Published
2025-08-11
DOI
https://doi.org/10.1109/jsen.2025.3595709
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00

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article

Simultaneous Measurement of Salinity and Temperature Based on Hybrid-Interferometer

Hong-kun Zheng, Ruijie Liu, Ri-Qing Lv, R. S. Gao et al.
IEEE Sensors Journal
Soil Moisture and Remote Sensing
article

Simultaneous Measurement of Salinity and Temperature Based on Hybrid-Interferometer

Hong-kun Zheng, Ruijie Liu, Ri-Qing Lv, R. S. Gao, Yong Zhao
article en

Abstract

A compact hybrid-interferometer-based fiber sensor integrating the C-shaped Fabry–Perot interferometer (FPI) and Mach–Zehnder interferometer (MZI) is put forward and verified. The C-shaped FPI formed by a section of hollow core fiber (HCF) spliced between a single-mode fiber (SMF) and a few-mode fiber (FMF) and opened up by femtosecond laser inscribing technology is sensitive to salinity and temperature. While the MZI constructed by a single stress-applying fiber (SSAF) between two FMFs with a large lateral offset and covered by Polydimethylsiloxane (PDMS) is for temperature measurement only. Combined with the properties of the two interferometers, the quadratic polynomial surface fitting algorithm is adopted to solve the nonlinear response and cross-sensitivity of temperature and salinity to figure out a more precise result. According to the experimental results, the proposed sensor could achieve a high sensitivity of 12.05 nm/‰ in the salinity range of 0‰–40‰ by cavity length demodulation, and −3.33 nm/°C in the temperature range of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5~^{\circ }$ </tex-math></inline-formula>C<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 40~^{\circ }$ </tex-math></inline-formula>C by wavelength demodulation, respectively. After the processing of the quadratic polynomial surface fitting algorithm, the indication errors of salinity and temperature are 1.44% and 2.6%, respectively.

IEEE Sensors JournalVol. 25(18)
Northeastern University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hebei Province, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 81%
Soil Moisture and Remote Sensing
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