Title | Compressed-domain Data Classification for Distributed Acoustic Sensing System |
Author | |
DOI | |
Publication Years | 2022
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Conference Name | Asia Communications and Photonics Conference (ACP) / International Conference on Information Photonics and Optical Communications (IPOC)
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ISSN | 2162-108X
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ISBN | 978-1-6654-8156-4
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Source Title | |
Pages | 108-110
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Conference Date | 5-8 Nov. 2022
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Conference Place | Shenzhen, China
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Publication Place | 345 E 47TH ST, NEW YORK, NY 10017 USA
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Publisher | |
Abstract | One of the challenges in distributed acoustic sensing (DAS) system is how to transmit, store, and process massive streams of data. In this work, we propose a novel classification method in compressed-domain for DAS system Our method compresses the signal to reduce the data size and classify the different vibration events using compressed signal directly. We experimentally verified that 90% classification accuracy can be achieved on a four-class classification task with only 30% of original data size. Classification accuracy under different SNRs and measurement ratios are also investigated in this work. |
Keywords | |
SUSTech Authorship | First
|
Language | English
|
URL | [Source Record] |
Indexed By | |
Funding Project | Stable Support Program for Higher Education Institutions from Shenzhen Science, Technology Innovation Commission[20200925162216001]
; Special Funds for the Major Fields of Colleges and Universities by the Department of Education of Guangdong Province[2021ZDZX1023]
; Guangdong Basic and Applied Basic Research Foundation[2021B1515120013]
; Open Fund of State Key Laboratory of Information Photonics and Optical Communications (Beijing University of Posts and Telecommunications)[IPOC2020A002]
; Natural Science Foundation of Guangdong Province[2022A1515011434]
; Open Projects Foundation of State Key Laboratory of Optical Fiber and Cable Manufacture Technology[SKLD2105]
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WOS Research Area | Engineering
; Optics
; Telecommunications
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WOS Subject | Engineering, Electrical & Electronic
; Optics
; Telecommunications
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WOS Accession No | WOS:001000552100030
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Data Source | IEEE
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PDF url | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10088818 |
Citation statistics |
Cited Times [WOS]:0
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Document Type | Conference paper |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/527448 |
Department | College of Engineering 工学院_电子与电气工程系 |
Affiliation | 1.Department of Electrical and Electronic Engineering, College of Engineering, Southern University of Science and Technology, Shenzhen, China 2.Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China |
First Author Affilication | College of Engineering; Department of Electrical and Electronic Engineering |
First Author's First Affilication | College of Engineering; Department of Electrical and Electronic Engineering |
Recommended Citation GB/T 7714 |
Xingliang Shen,Jialong Li,Zhengting Wu,et al. Compressed-domain Data Classification for Distributed Acoustic Sensing System[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2022:108-110.
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