Compressed-domain Data Classification for Distributed Acoustic Sensing System

Xingliang Shen1; Jialong Li1; Zhengting Wu1; Hong Dang1; Jinna Chen1; Liyang Shao1; Huanhuan Liu1; Perry Ping Shum1; Huan Wu2; Kun Zhu2; Yujia Li2; Hua Zheng2; Chao Lu2

10.1109/ACP55869.2022.10088818

2022

Asia Communications and Photonics Conference (ACP) / International Conference on Information Photonics and Optical Communications (IPOC)

2162-108X

978-1-6654-8156-4

2022 Asia Communications and Photonics Conference (ACP)

108-110

5-8 Nov. 2022

Shenzhen, China

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

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.

DAS Compressive Sensing Distributed Fibre sensing Distributed Acoustic Sensing

First

English

CPCI-S

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]

Engineering ; Optics ; Telecommunications

Engineering, Electrical & Electronic ; Optics ; Telecommunications

WOS:001000552100030

IEEE

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

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.