Leakage Detection in Water Distribution Systems Based on Time–Frequency Convolutional Neural Network-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Leakage Detection in Water Distribution Systems Based on Time–Frequency Convolutional Neural Network

Published:2021-02 Issue:2 Volume:147 Page:04020101
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Guo Guancheng¹,Yu Xipeng¹,Liu Shuming²^ORCID,Ma Ziqing³,Wu Yipeng¹,Xu Xiyan⁴,Wang Xiaoting¹,Smith Kate⁴,Wu Xue⁵

Affiliation:

1. Ph.D. Student, School of Environment, Tsinghua Univ., Beijing 100084, China.

2. Professor, School of Environment, Tsinghua Univ., Beijing 100084, China (corresponding author). ORCID: .

3. M.Sc. Student, School of Environment, Tsinghua Univ., Beijing 100084, China.

4. Postdoctoral Fellow, School of Environment, Tsinghua Univ., Beijing 100084, China.

5. Research Assistant, School of Environment, Tsinghua Univ., Beijing 100084, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29WR.1943-5452.0001317

Reference47 articles.

1. Towards Achieving a Reliable Leakage Detection and Localization Algorithm for Application in Water Piping Networks: An Overview

2. Leak detection in water-filled plastic pipes through the application of tuned wavelet transforms to Acoustic Emission signals

3. On the Acoustic Filtering of the Pipe and Sensor in a Buried Plastic Water Pipe and its Effect on Leak Detection: An Experimental Investigation

4. Amran T. S. T. M. P. Ismail M. R. Ahmad M. S. M. Amin S. Sani N. A. Masenwat M. A. Ismail and S. H. A. Hamid. 2017. “Detection of underground water distribution piping system and leakages using ground penetrating radar (GPR).” In Vol. 1799 of Proc. AIP Conf. 030004. Melville NY: American Institute of Physics. https://doi.org/10.1063/1.4972914.

5. Boaz L. S. Kaijage and R. Sinde. 2014. “An overview of pipeline leak detection and location systems.” In Proc. 2014 Pan African Conf. on Science Computing and Telecommunications 133–137. New York: IEEE. https://doi.org/10.1109/SCAT.2014.7055147.

Cited by 54 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Leak detection and localization of fluid-filled pipeline using accelerometer pairs and mode separation method;Measurement;2025-01

2. Feature selection of acoustic signals for leak detection in water pipelines;Tunnelling and Underground Space Technology;2024-10

3. Advancing deep learning-based acoustic leak detection methods towards application for water distribution systems from a data-centric perspective;Water Research;2024-09

4. Time-Transformer for acoustic leak detection in water distribution network;Journal of Civil Structural Health Monitoring;2024-08-27

5. Leak detection in water distribution networks based on deep learning and kriging interpolation method;AQUA — Water Infrastructure, Ecosystems and Society;2024-08-01

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