Genetic-optimised aperiodic code for distributed optical fibre sensors

Sun, Xizi; Yang, Zhisheng; Hong, Xiaobin; Zaslawski, Simon; Wang, Sheng; Soto, Marcelo A.; Gao, Xia; Wu, Jian; Thevenaz, Luc

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. Performance of distributed optical fiber sensing is partially limited by the need for hardware changes. Here, the authors introduce a coding algorithm that enables enhanced performance through faster processing using only software-based methods.

Más información

Título según WOS: Genetic-optimised aperiodic code for distributed optical fibre sensors
Título de la Revista: NATURE COMMUNICATIONS
Volumen: 11
Número: 1
Editorial: NATURE PORTFOLIO
Fecha de publicación: 2020
DOI:

10.1038/S41467-020-19201-1

Notas: ISI