SBS-based fiber sensors

Zadok, Avi; Bao, Xiaoyi; Yang, Zhisheng; Thévenaz, Luc

doi:10.1016/bs.semsem.2022.05.001

Cited by 4 publications

(3 citation statements)

References 133 publications

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“…IBER optic distributed sensing based on Brillouin scattering [1], [2] has experienced a huge development in the last decade thanks to its capability to perform spatially resolved sensing of environmental variables, like temperature and strain. Compared to other distributed sensing technologies, Brillouin sensors allow the monitoring of several tens of kilometers of optical fiber (even more than 100 km with advanced methods [1], [3]) with a typical spatial resolution of a few meters.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Performance of Compressive Sensing in Fiber-Optic Distributed Brillouin Sensors

Díaz,

Soto

2024

J. Lightwave Technol.

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With the aim of speeding up the measurement time of Brillouin distributed sensors, the use of compressive sensing (CS) has been recently proposed to reconstruct the Brillouin gain spectral shape based on a reduced number of spectral samples. However, the real benefits of using CS are still unclear in terms of the achieved sensing performance, especially when compared to the performance of a conventional Brillouin sensor operating with the same reduced number of spectral samples and with no use of CS. Here, a thorough analysis of the performance of compressive sensing applied to distributed Brillouin sensors is presented. Based on experimental and theoretical results, the usefulness of CS for Brillouin spectral reconstruction is analyzed by investigating its impact on the tradeoff between sensing performance parameters, such as measurement time, signal-tonoise ratio (SNR), and frequency estimation errors. For this, the sensing performance achieved by CS under uniform and random sampling scenarios is compared to the performance obtained by a classical interrogation scheme, under similar SNR and spectral sampling conditions (i.e., under the same measurement time, fiber length and spatial resolution). Results point out that both classical and CS-based Brillouin sensing approaches lead to the same figure of merit, verifying that the use of CS for Brillouin spectral reconstruction provides no real benefits to improve the overall performance of the sensor.

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Section: Introductionmentioning

confidence: 99%

Evaluating the Performance of Compressive Sensing in Fiber-Optic Distributed Brillouin Sensors

Díaz,

Soto

2024

J. Lightwave Technol.

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“…As both the manipulation and post-processing procedures of FS-BOTDR are in total similarity with those of standard Brillouin optical time-domain analysis (BOTDA) [13]- [15], these two techniques share a similar methodology in terms of evaluating the performance of sensing system. This means that any relevant know-how developed for one of these two techniques may directly benefit the other.…”

Section: Introductionmentioning

confidence: 99%

Analytical Signal-to-Noise Ratio Model on Frequency-Scanned Brillouin Optical Time-Domain Reflectometry

Jin,

Yang,

Hong

et al. 2024

J. Lightwave Technol.

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An analytical signal-to-noise ratio (SNR) model of standard frequency-scanned Brillouin optical time-domain reflectometry (FS-BOTDR) is established, by comprehensively taking into account nearly all non-negligible signal and noise terms with substantial impact on the sensing performance. The accuracy and generality of the proposed model are experimentally validated, supported by the fact that under various experimental conditions all experimental results are in good quantitative agreement with theoretical calculations. Serving as a theoretical tool, the established model makes it possible to accurately anticipate and comprehensively interpret the SNR behavior of the FS-BOTDR under any given measurement condition, without the need to construct an experimental system or carry out experiments. It also enables theoretically quantifying the SNR difference between FS-BOTDR and other distributed optical fiber sensors that already have mature SNR models. Furthermore, the proposed model provides guidelines on optimizing system parameters towards the highest possible SNR with minimized energy consumption.

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“…Distributed Brillouin sensors, relying on acoustic phonon-induced light scattering, demonstrate distinct sensitivity to variations in both strain and temperature 7 . Over the years, Brillouin sensors have been developed across various platforms, including time-domain 8 , 9 , correlation-domain 10 , 11 , and frequency-domain 12 , 13 systems utilizing spontaneous and stimulated scattering processes.…”

Section: Introductionmentioning

confidence: 99%

Brillouin expanded time-domain analysis based on dual optical frequency combs

Youn,

Song,

Martin-Lopez

et al. 2024

Light Sci Appl

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Brillouin Optical Time-Domain Analysis (BOTDA) is a widely-used distributed optical fiber sensing technology employing pulse-modulated pump waves for local information retrieval of the Brillouin gain or loss spectra. The spatial resolution of BOTDA systems is intrinsically linked to pulse duration, so high-resolution measurements demand high electronic bandwidths inversely proportional to the resolution. This paper introduces Brillouin Expanded Time-Domain Analysis (BETDA) as a modified BOTDA system, simultaneously achieving high spatial resolution and low detection bandwidth. Utilizing two optical frequency combs (OFCs) with different frequency intervals as pump and probe, local Brillouin gain spectra are recorded by their spectral beating traces in an expanded time domain. A 2-cm-long hotspot located in a 230 m single-mode fiber is successfully measured in the time domain with a detection bandwidth of less than 100 kHz using dual OFCs with tailored spectral phase, line spacing, and bandwidth.

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SBS-based fiber sensors

Cited by 4 publications

References 133 publications

Evaluating the Performance of Compressive Sensing in Fiber-Optic Distributed Brillouin Sensors

Evaluating the Performance of Compressive Sensing in Fiber-Optic Distributed Brillouin Sensors

Analytical Signal-to-Noise Ratio Model on Frequency-Scanned Brillouin Optical Time-Domain Reflectometry

Brillouin expanded time-domain analysis based on dual optical frequency combs

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