Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/65795
Title: Multiple-fault detection in water pipelines using transient-based time-frequency analysis
Authors: Sun, J
Wang, R
Duan, HF 
Keywords: Empirical mode decomposition (EMD)
Hilbert transform (HT)
Multiple-fault detection
Pipelines
Time-frequency analysis
Transient-based method
Issue Date: 2016
Publisher: International Water Association Publishing
Source: Journal of hydroinformatics, 2016, v. 18, no. 6, p. 975-989 How to cite?
Journal: Journal of hydroinformatics 
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.
URI: http://hdl.handle.net/10397/65795
ISSN: 1464-7141
DOI: 10.2166/hydro.2016.232
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

14
Last Week
1
Last month
Checked on Aug 13, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.