Xiao, Dongrui, Shao, Liyang, Wang, Chao, Lin, Weihao, Yu, Feihong, Wang, Guoqing, Ye, Tao, Wang, Weizhi, Vai, Mang I (2021) Optical sensor network interrogation system based on nonuniform microwave photonic filters. Optics Express, 29 (2). p. 2564. ISSN 1094-4087. (doi:10.1364/OE.413990) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:92169)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication) | |
Official URL: https://doi.org/10.1364/OE.413990 |
Abstract
Based on the nonuniformly spaced microwave photonic delay-line filter technology, a new design of a generic optical fiber sensor network interrogation platform is proposed and demonstrated. Sensing information from different types of optical sensors embedded in filter taps is converted into the variations of delay time and amplitude of each filter tap individually. Information to be measured can be decoded from the complex temporal impulse response of the microwave photonic filter. As proof-of-concept, our proposed approach is verified by simulations and experimental demonstrations successfully. Four optical sensors of different types are simultaneously interrogated via inverse Fourier transform of the filter frequency response. The experiment results show good linearity between the variation of temporal impulse response and the variations of the twist, the lateral pressure, the transversal loading and the temperature. The sensitivity of the sensors in the proposed platform is −2.130×10−5 a.u/degree, 6.1039 ps/kPa, −1.9146×10−5 a.u/gram, and 5.1497 ps/°C, respectively. Compared to the conventional optical sensors interrogation system, the presented approach provides a centralized solution that works for different types of optical sensors and can be easily expanded to cover larger optical sensor networks.
Item Type: | Article |
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DOI/Identification number: | 10.1364/OE.413990 |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Chao Wang |
Date Deposited: | 06 Dec 2021 10:05 UTC |
Last Modified: | 06 Dec 2021 10:05 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/92169 (The current URI for this page, for reference purposes) |
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