Multiple-fault detection in water pipelines using transient-based time-frequency analysis

Author:

Sun Jilong12,Wang Ronghe1,Duan Huan-Feng3

Affiliation:

1. Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong 518055, China

2. School of Environment, Tsinghua University, Beijing 100084, China

3. Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China

Abstract

Pipe faults, such as leakage and blockage, commonly exist in water pipeline systems. It is essential to identify and fix these failures appropriately in order to reduce the risk of water pollution and enhance the security of water supply. Recently, transient-based detection methods have been developed for their advantages of non-intrusion, efficiency and economics compared to traditional methods. However, this method is so far limited mainly to simple pipelines with a single known type of pipe fault in the system. This paper aims to extend the transient-based method to multiple-fault detection in water pipelines. For this purpose, this study introduced an efficient and robust method for transient pressure signal analysis – a combination of the empirical mode decomposition and Hilbert transform – in order to better identify and detect different anomalies (leakage, blockage and junction) in pipelines. To validate the proposed transient-based time-frequency analysis method, laboratory experimental tests were conducted in this study for a simple pipeline system with multiple unknown types of pipe faults including leakages, blockages and junctions. The preliminary test results and analysis indicate that multiple pipe faults in simple pipelines can be efficiently identified and accurately located by the proposed method.

Publisher

IWA Publishing

Subject

Atmospheric Science,Geotechnical Engineering and Engineering Geology,Civil and Structural Engineering,Water Science and Technology

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