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分布式布里渊光纤传感中光谱特性工程的优势

Benefits of Spectral Property Engineering in Distributed Brillouin Fiber Sensing.

作者信息

Feng Cheng, Schneider Thomas

机构信息

THz Photonics Group, Institut für Hochfrequenztechnik, Technische Universität Braunschweig, Schleinitzstr. 22, 38106 Braunschweig, Germany.

出版信息

Sensors (Basel). 2021 Mar 8;21(5):1881. doi: 10.3390/s21051881.

DOI:10.3390/s21051881
PMID:33800206
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7962463/
Abstract

As one of the most consolidated distributed fiber sensors based on stimulated Brillouin scattering, the Brillouin optical time-domain analyzer (BOTDA) has been developed for decades. Despite the commercial availability and outstanding progresses which has been achieved, the intrinsic Lorentzian gain spectrum restricts the sensing performance from possible further enhancements and hence limits the field of validity of the technique. In this paper, the novel method of engineering the gain spectral properties of the Brillouin scattering and its application on static and dynamic BOTDA sensors will be reviewed. Such a spectral property engineering has not only provided improvements to BOTDA, but also might open a new way to enhance the performance of all kinds of distributed Brillouin fiber sensors.

摘要

作为基于受激布里渊散射的最成熟的分布式光纤传感器之一,布里渊光时域分析仪(BOTDA)已经发展了数十年。尽管已经实现了商业可用性并取得了显著进展,但固有的洛伦兹增益谱限制了传感性能的进一步提升,从而限制了该技术的有效应用范围。本文将综述对布里渊散射增益谱特性进行工程设计的新方法及其在静态和动态BOTDA传感器中的应用。这种谱特性工程不仅改进了BOTDA,还可能为提高各类分布式布里渊光纤传感器的性能开辟一条新途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/48f0d8800dcb/sensors-21-01881-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/2a73741d8f76/sensors-21-01881-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/f3aa9f7a1347/sensors-21-01881-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/ab474c187613/sensors-21-01881-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/2d4a4f9dcb05/sensors-21-01881-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/c1f0bfdb652e/sensors-21-01881-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/84e04eca18b5/sensors-21-01881-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/dbe8ffbbb736/sensors-21-01881-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/1dec81c2edf6/sensors-21-01881-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/4ac253f411d6/sensors-21-01881-g009a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/a267eb685913/sensors-21-01881-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/06f7ad2d0a2a/sensors-21-01881-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/417b30a0dae8/sensors-21-01881-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/5170e0ff5a81/sensors-21-01881-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/48f0d8800dcb/sensors-21-01881-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/2a73741d8f76/sensors-21-01881-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/f3aa9f7a1347/sensors-21-01881-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/ab474c187613/sensors-21-01881-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/2d4a4f9dcb05/sensors-21-01881-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/c1f0bfdb652e/sensors-21-01881-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/84e04eca18b5/sensors-21-01881-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/dbe8ffbbb736/sensors-21-01881-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/1dec81c2edf6/sensors-21-01881-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/4ac253f411d6/sensors-21-01881-g009a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/a267eb685913/sensors-21-01881-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/06f7ad2d0a2a/sensors-21-01881-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/417b30a0dae8/sensors-21-01881-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/5170e0ff5a81/sensors-21-01881-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bc/7962463/48f0d8800dcb/sensors-21-01881-g014.jpg

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本文引用的文献

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Study on the signal-to-noise ratio of Brillouin optical-time domain analyzers.布里渊光时域分析仪的信噪比研究。
Opt Express. 2020 Jul 6;28(14):19864-19876. doi: 10.1364/OE.393928.
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Measurement Accuracy Enhancement via Radio Frequency Filtering in Distributed Brillouin Sensing.分布式布里渊传感中通过射频滤波提高测量精度
Sensors (Basel). 2019 Jun 28;19(13):2878. doi: 10.3390/s19132878.
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Enhancing strain dynamic range of slope-assisted BOTDA by manipulating Brillouin gain spectrum shape.通过操纵布里渊增益谱形状提高斜率辅助布里渊光时域分析的应变动态范围
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