Experimental research on in-pipe leaks detection of acoustic signature in gas pipelines based on the artificial neural network-Reference-Cited by-同舟云学术

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Experimental research on in-pipe leaks detection of acoustic signature in gas pipelines based on the artificial neural network

Published:2021-10 Issue: Volume:183 Page:109875
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Wang Wenming,Mao Xingxiang,Liang Haiguan,Yang Dashan,Zhang Jifeng,Liu Shuhai

Funder

China University of Petroleum Beijing

Science Foundation of China University of Petroleum, Beijing

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference31 articles.

1. Acoustic detection and tracking of a pipeline inspection gauge;Bernasconi;J. Petrol. Sci. Eng.,2020

2. Application of robotics in onshore oil and gas industry-A review Part I;Shukla;Rob. Auton. Syst.,2016

3. Differential-drive in-pipe robot for moving inside urban gas pipelines;Roh;IEEE Trans. Rob.,2005

4. Natural-gas pipeline leak location using variational mode decomposition analysis and cross-time–frequency spectrum;Xiao;Measurement,2018

5. A novel hybrid technique for leak detection and location in straight pipelines;Zhang;J. Loss Prev. Process Ind.,2015

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