Artificial intelligence-driven distributed acoustic sensing technology and engineering application

Liyang Shao; Jingming Zhang; Xingwei Chen; Deyu Xu; Huaxin Gu; Qi Mu; Feihong Yu; Shuaiqi Liu; Xiaobing Shi; Jiayao Sun; Zixing Huang; Xiongji Yang; Haifeng Zhang; Yunbin Ma; Han Lu; Chuanqing Liu; Changyuan Yu

doi:10.1186/s43074-025-00160-z

Artificial intelligence-driven distributed acoustic sensing technology and engineering application

doi: 10.1186/s43074-025-00160-z

1 Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China;
2 Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong (SAR), China;
3 Energy Advanced Measurement and Control and Equipment R&D Center, Research Institute of Tsinghua University, Pearl River Delta, Guangzhou, Guangdong, China;
4 PipeChina Institute of Science and Technology, Langfang, Hebei, China;
5 Shenzhen Gas Corporation Ltd, Shenzhen, Guangdong, China

基金项目:

Science, Technology and Innovation Commission of Shenzhen Municipality, grant number 20220815121807001

Hong Kong Research Grants Council(RGC) under General Research Fund 15224521.

This work was supported in part by Department of Natural Resources of Guangdong Province, grant number GDNRC [2022] No. 22

Intelligent Laser Basic Research Laboratory, grant number PCL2021A14-B1. Key Basic Research Scheme of Shenzhen Natural Science Foundation (JCYJ20200109142010888)

详细信息

通讯作者:
Liyang Shao, E-mail:shaoly@sustech.edu.cn

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出版历程
- 收稿日期: 2024-05-30
- 录用日期: 2025-01-13
- 修回日期: 2025-01-08
- 网络出版日期: 2025-03-05

Artificial intelligence-driven distributed acoustic sensing technology and engineering application

1 Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China;
2 Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong (SAR), China;
3 Energy Advanced Measurement and Control and Equipment R&D Center, Research Institute of Tsinghua University, Pearl River Delta, Guangzhou, Guangdong, China;
4 PipeChina Institute of Science and Technology, Langfang, Hebei, China;
5 Shenzhen Gas Corporation Ltd, Shenzhen, Guangdong, China

Funds:

Science, Technology and Innovation Commission of Shenzhen Municipality, grant number 20220815121807001

Hong Kong Research Grants Council(RGC) under General Research Fund 15224521.

This work was supported in part by Department of Natural Resources of Guangdong Province, grant number GDNRC [2022] No. 22

Intelligent Laser Basic Research Laboratory, grant number PCL2021A14-B1. Key Basic Research Scheme of Shenzhen Natural Science Foundation (JCYJ20200109142010888)

摘要

摘要: Distributed acoustic sensing (DAS) technology is a fiber-optic based distributed sensing technology. It achieves real-time monitoring of acoustic signals by detecting weak disturbances along the fiber. It has advantages such as long measurement distance, high spatial resolution and large dynamic range. Artificial intelligence (AI) has great application potential in DAS technology, including data augmentation, preprocessing and classification and recognition of acoustic events. By introducing AI algorithms, DAS system can process massive data more automatically and intelligently. Through data analysis and prediction, AI-enabled DAS technology has wide applications in fields such as transportation, energy and security due to its accuracy of monitoring data and reliability of intelligent decision-making. In the future, the continuous advancement of AI technology will bring greater breakthroughs and innovations for the engineering application of DAS technology, play a more important role in various fields, and promote the innovation and development of the industry.
- Distributed acoustic sensing(DAS) /
- Artificial intelligence(AI) /
- Engineering application
Abstract: Distributed acoustic sensing (DAS) technology is a fiber-optic based distributed sensing technology. It achieves real-time monitoring of acoustic signals by detecting weak disturbances along the fiber. It has advantages such as long measurement distance, high spatial resolution and large dynamic range. Artificial intelligence (AI) has great application potential in DAS technology, including data augmentation, preprocessing and classification and recognition of acoustic events. By introducing AI algorithms, DAS system can process massive data more automatically and intelligently. Through data analysis and prediction, AI-enabled DAS technology has wide applications in fields such as transportation, energy and security due to its accuracy of monitoring data and reliability of intelligent decision-making. In the future, the continuous advancement of AI technology will bring greater breakthroughs and innovations for the engineering application of DAS technology, play a more important role in various fields, and promote the innovation and development of the industry.
- Distributed acoustic sensing(DAS) /
- Artificial intelligence(AI) /
- Engineering application