Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/102646
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Civil and Environmental Engineering | - |
| dc.creator | Sun, J | en_US |
| dc.creator | Wang, R | en_US |
| dc.creator | Duan, HF | en_US |
| dc.date.accessioned | 2023-10-26T07:20:07Z | - |
| dc.date.available | 2023-10-26T07:20:07Z | - |
| dc.identifier.issn | 1464-7141 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/102646 | - |
| dc.language.iso | en | en_US |
| dc.publisher | International Water Association Publishing | en_US |
| dc.rights | © IWA Publishing 2016 | en_US |
| dc.rights | This is the accepted manuscript of the following article: Jilong Sun, Ronghe Wang, Huan-Feng Duan; Multiple-fault detection in water pipelines using transient-based time-frequency analysis. Journal of Hydroinformatics 1 November 2016; 18 (6): 975–989, which has been published in final form at https://doi.org/10.2166/hydro.2016.232. | en_US |
| dc.subject | Empirical mode decomposition (EMD) | en_US |
| dc.subject | Hilbert transform (HT) | en_US |
| dc.subject | Multiple-fault detection | en_US |
| dc.subject | Pipelines | en_US |
| dc.subject | Time-frequency analysis | en_US |
| dc.subject | Transient-based method | en_US |
| dc.title | Multiple-fault detection in water pipelines using transient-based time-frequency analysis | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 975 | en_US |
| dc.identifier.epage | 989 | en_US |
| dc.identifier.volume | 18 | en_US |
| dc.identifier.issue | 6 | en_US |
| dc.identifier.doi | 10.2166/hydro.2016.232 | en_US |
| dcterms.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. | - |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Journal of hydroinformatics, 1 Nov. 2016, v. 18, no. 6, p. 975-989 | en_US |
| dcterms.isPartOf | Journal of hydroinformatics | en_US |
| dcterms.issued | 2016-11-01 | - |
| dc.identifier.scopus | 2-s2.0-85006844267 | - |
| dc.identifier.eissn | 1465-1734 | en_US |
| dc.description.validate | 202310 bcch | - |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | CEE-2599 | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | National Natural Science Foundation of China; Hong Kong Polytechnic University | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 6706702 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Duan_Multiple-Fault_Detection_Water.pdf | Pre-Published version | 1.2 MB | Adobe PDF | View/Open |
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