Single-shot multi-sensitivity distributed acoustic sensing with hardware envelope retrieving acceleration

Author:

Wang Yixuan12,Jiang Junfeng12ORCID,Liu Kun12ORCID,Zhang Mingjiang3,Wang Shuang12,Liu Yize12,Ma Zhe3ORCID,Xu Tianhua124,Zhang Xuezhi12,Ding Zhenyang12ORCID,Liu Tiegen12

Affiliation:

1. Tianjin University

2. Institute of Optical Fiber Sensing

3. Taiyuan University of Technology

4. University of Warwick

Abstract

Distributed acoustic sensing (DAS) can virtualize a fiber optic cable into an ultra-dense seismic network, offering long-term seismic wave observing capability and high-fidelity waveform recording performance. In practical applications, DAS systems still face two main challenges. Firstly, the large amount of raw data brings a burden on storage and demodulation speed. Secondly, the fixed strain sensitivity of DAS limits the dynamic measurement range of the actual seismic signal. In this work, we present a single-shot multi-sensitivity distributed acoustic sensing method with hardware assistance. A hardware filtering module is utilized to achieve equivalent sampling results at a lower sampling rate, thereby reducing the volume of raw data and accelerating the acquisition and demodulation process. The average processing time for a single-sideband pulse detection can be reduced from 214.79 s to 9.83 s, resulting in approximately a 20-time reduction. Meanwhile, multiple sidebands pulse with different bandwidths is generated to enable multi-sensitivity detection under hardware filtering. The different ranges of strain events can be recovered through a modulated pulse with 20 MHz, 40 MHz, and 80 MHz bandwidths. The hardware-assistance multi-sensitivity DAS method offers a potential solution to complex environments and real-time detection applications.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Optica Publishing Group

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3