Theoretical and Experimental Analysis of the Directional RI Sensing Property of Tilted Fiber Grating

Abstract

In this paper, we have theoretically and experimentally investigated the unique vector refractive index (RI) sensing property of tilted fiber grating (TFG). Due to the orthogonal symmetric grating structure, TFGs would mainly achieve the coupling between the fiber core mode and the two orthogonal polarization LP1m of cladding mode. And the numerical simulation results showed that the coupling coefficient between fundamental core mode to the LP1m cladding mode is higher than the others. In the experiment, we have furthermore observed the cladding mode field distribution of excessively TFG (Ex-TFG) and long period fiber grating (LPFG), which indicated that the evanescent field distribution of cladding mode of TFG shows an asymmetric near field distribution with two lobes oriented along the fast axis of TFG, and the one of LPFG has a circularly symmetric cladding mode field distribution. In addition, by employing side-immersion method, we have measured the azimuth RI sensitivities of Ex-TFG, tilted fiber Bragg grating (TFBG) and LPFG, which exhibited that both Ex-TFG and TFBG have shown a direction-dependency RI sensitivity, and the RI sensitivity with side-immersion along fast axis is almost half of the one along slow axis, and the RI sensitivity of LPFG is azimuth independent. Overall, the experiment results show that the TFGs inherently show unique directional RI sensing property, which could be potentially applied in vector sensing area.

Publication DOI: https://doi.org/10.1109/JLT.2020.3027947
Divisions: Engineering & Applied Sciences > Aston Institute of Photonics Technology
Engineering & Applied Sciences
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Related URLs: https://ieeexpl ... cument/9210176/ (Publisher URL)
PURE Output Type: Article
Published Date: 2020-09-30
Published Online Date: 2020-09-30
Accepted Date: 2020-09-01
Authors: Sun, Yuezhen
Lu, Tean
Moreno, Yarien
Li, Liangye
Wang, Hushan
Zhou, Kaiming ( 0000-0002-6011-1912)
Sun, Qizhen
Yan, Zhijun
Liu, Deming
Zhang, Lin

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