Genetic-optimised aperiodic code for distributed optical fibre sensors

Xizi Sun, Zhisheng Yang (), Xiaobin Hong (), Simon Zaslawski, Sheng Wang, Marcelo A. Soto, Xia Gao, Jian Wu and Luc Thévenaz
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Xizi Sun: Beijing University of Posts and Telecommunications
Zhisheng Yang: Institute of Electrical Engineering, SCI STI LT
Xiaobin Hong: Beijing University of Posts and Telecommunications
Simon Zaslawski: Institute of Electrical Engineering, SCI STI LT
Sheng Wang: Beijing University of Posts and Telecommunications
Marcelo A. Soto: Universidad Técnica Federico Santa María
Xia Gao: Beijing University of Posts and Telecommunications
Jian Wu: Beijing University of Posts and Telecommunications
Luc Thévenaz: Institute of Electrical Engineering, SCI STI LT

Nature Communications, 2020, vol. 11, issue 1, 1-11

Abstract: Abstract Distributed optical fibre sensors deliver a map of a physical quantity along an optical fibre, providing a unique solution for health monitoring of targeted structures. Considerable developments over recent years have pushed conventional distributed sensors towards their ultimate performance, while any significant improvement demands a substantial hardware overhead. Here, a technique is proposed, encoding the interrogating light signal by a single-sequence aperiodic code and spatially resolving the fibre information through a fast post-processing. The code sequence is once forever computed by a specifically developed genetic algorithm, enabling a performance enhancement using an unmodified conventional configuration for the sensor. The proposed approach is experimentally demonstrated in Brillouin and Raman based sensors, both outperforming the state-of-the-art. This methodological breakthrough can be readily implemented in existing instruments by only modifying the software, offering a simple and cost-effective upgrade towards higher performance for distributed fibre sensing.

Date: 2020
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DOI: 10.1038/s41467-020-19201-1

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