Distributed Fiber-Optic Sensing with Low Bending Loss based on Thin-Core Fiber

Abstract

This paper presents a thin-core high-numerical aperture (TC-HNA) optical fiber with low macrobending loss for Rayleigh backscattering-based (RBS-based) temperature and strain measurements. The standard single-mode optical fiber (SMF), commonly used in RBS-based sensing, has low macrobending loss-resistance, making the fiber less suited for sensing applications that require sharp bending of the fiber under test. The TC-HNA fiber, on the other hand, offers high macrobending loss-resistance. Experiments were designed and conducted to demonstrate the reliability of a TC-HNA fiber for RBS-based temperature and strain measurements. The macrobending losses in a standard SMF and a TC-HNA fiber were compared in many experiments conducted with different bending radii ranging from 12.5 mm down to 0.9 mm. The RBS signal for a standard SMF, with a single turn of a 5 mm bending radius, degraded severely, exhibiting a 75% drop (6 dB) in signal power. Notably, the RBS signal for a similar test configuration of a TC-HNA fiber did not exhibit any observable loss. We demonstrated that a TC-HNA fiber could be used for RBS-based measurements with a single turn of ~1 mm bending radius. Moreover, an experiment was conducted to demonstrate the spatial thermal mapping capability of the TC-HNA fiber configured with multiple tight bends with radii in the range ~2–3 mm. The high macrobending loss-resistance of the TC-HNA fiber could extend the range of applications for RBS-based measurements to compact structures, such as batteries, robotic fingers, and printed circuit boards, where sharp bending of the test optical fiber is unavoidable.

Department(s)

Materials Science and Engineering

Second Department

Electrical and Computer Engineering

Research Center/Lab(s)

Peaslee Steel Manufacturing Research Center

Second Research Center/Lab

Intelligent Systems Center

International Standard Serial Number (ISSN)

1530-437X; 1558-1748

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2021 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

11 Jan 2021

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