UM
Data-Driven Distributed Optical Vibration Sensors: A Review
Shao,Li Yang1; Liu,Shuaiqi1; Bandyopadhyay,Sankhyabrata1; Yu,Feihong1; Xu,Weijie1; Wang,Chao2; Li,Hengchao3; Vai,Mang I.4; Du,Linlin5; Zhang,Jinsheng5
2020-06-15
Source PublicationIEEE Sensors Journal
ISSN1530-437X
Volume20Issue:12Pages:6224-6239
AbstractDistributed optical vibration sensors (DOVS) have attracted much attention recently since it can be used to monitor mechanical vibrations or acoustic waves with long reach and high sensitivity. Phase-sensitive optical time domain reflectometry ( $\Phi $ -OTDR) is one of the most commonly used DOVS schemes. For $\Phi $ -OTDR, the whole length of fiber under test (FUT) works as the sensing instrument and continuously generates sensing data during measurement. Researchers have made great efforts to try to extract external intrusions from the redundant data. High signal-to-noise ratio (SNR) is necessary in order to accurately locate and identify external intrusions in $\Phi $ -OTDR systems. Improvement in SNR is normally limited by the properties of light source, photodetector and FUT. But this limitation can also be overcome by post-processing of the received optical signals. In this context, detailed methodologies of SNR enhancement post-processing algorithms in $\Phi $ -OTDR systems have been described in this paper. Furthermore, after successfully locating the external vibrations, it is also important to identify the types of source of the vibrations. Pattern classification is a powerful tool in recognizing the intrusion types from the vibration signals in practical applications. Recent reports of $\Phi $ -OTDR systems employed with pattern classification algorithms are subsequently reviewed and discussed. This thorough review will provide a design pathway for improving the performance of $\Phi $ -OTDR while maintaining the cost of the system as no additional hardware is required.
KeywordFiber optics sensors optical time domain reflectometry phase-sensitive optical time domain reflectometry scattering measurement
DOI10.1109/JSEN.2019.2939486
URLView the original
Language英语
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Cited Times [WOS]:6   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Department of Electrical and Electronic Engineering,Southern University of Science and Technology,Shenzhen,518005,China
2.School of Engineering and Digital Arts,University of Kent,Canterbury,United Kingdom
3.School of Information Science and Technology,Southwest Jiaotong University,Chengdu,China
4.Department of Electrical and Computer Engineering,Faculty of Science and Technology,University of Macau,Macao
5.Shenzhen Gas Corporation Ltd.,Shenzhen,China
Recommended Citation
GB/T 7714
Shao,Li Yang,Liu,Shuaiqi,Bandyopadhyay,Sankhyabrata,et al. Data-Driven Distributed Optical Vibration Sensors: A Review[J]. IEEE Sensors Journal,2020,20(12):6224-6239.
APA Shao,Li Yang,Liu,Shuaiqi,Bandyopadhyay,Sankhyabrata,Yu,Feihong,Xu,Weijie,Wang,Chao,Li,Hengchao,Vai,Mang I.,Du,Linlin,&Zhang,Jinsheng.(2020).Data-Driven Distributed Optical Vibration Sensors: A Review.IEEE Sensors Journal,20(12),6224-6239.
MLA Shao,Li Yang,et al."Data-Driven Distributed Optical Vibration Sensors: A Review".IEEE Sensors Journal 20.12(2020):6224-6239.
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