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Genetic-optimised aperiodic code for distributed optical fibre sensors.

Xizi Sun1, Zhisheng Yang2, Xiaobin Hong3

  • 1State Key Laboratory of Information Photonics & Optical Communications, Beijing University of Posts and Telecommunications, Beijing, 100876, China.

Nature Communications
|November 14, 2020
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Summary
This summary is machine-generated.

A novel technique enhances distributed optical fibre sensing performance without hardware changes. This method uses aperiodic codes and genetic algorithms for improved health monitoring of structures.

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Area of Science:

  • Physics
  • Engineering
  • Materials Science

Background:

  • Distributed optical fibre sensors offer unique structural health monitoring capabilities.
  • Conventional sensors face performance limits, requiring significant hardware for improvements.

Purpose of the Study:

  • To introduce a software-based technique for enhancing distributed optical fibre sensor performance.
  • To demonstrate a cost-effective upgrade for existing sensing instruments.

Main Methods:

  • Encoding interrogating light signals with a single-sequence aperiodic code.
  • Utilizing a genetic algorithm to compute the code sequence.
  • Employing fast post-processing for spatial information resolution.
  • Experimental validation in Brillouin and Raman based sensors.

Main Results:

  • The proposed method achieved performance exceeding the state-of-the-art in both Brillouin and Raman distributed fibre sensors.
  • The technique enables enhanced sensing without modifying the conventional sensor hardware configuration.
  • The approach relies on a specifically developed genetic algorithm for code sequence computation.

Conclusions:

  • This methodological breakthrough offers a simple and cost-effective software upgrade for distributed fibre sensing instruments.
  • The aperiodic coding and genetic algorithm approach significantly boosts sensor performance.
  • The technique is readily implementable in existing systems, enhancing structural health monitoring capabilities.