Litcius/Paper detail

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, Luc Thévenaz

2020Nature Communications142 citationsDOIOpen Access PDF

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.

Topics & Concepts

Aperiodic graphComputer scienceOverhead (engineering)Code (set theory)Encoding (memory)Optical fiberUpgradeComputer hardwareReal-time computingElectronic engineeringTelecommunicationsEngineeringArtificial intelligenceOperating systemMathematicsSet (abstract data type)Programming languageCombinatoricsAdvanced Fiber Optic SensorsPhotonic and Optical DevicesNeural Networks and Reservoir Computing
Genetic-optimised aperiodic code for distributed optical fibre sensors | Litcius