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Publicação:
Adaptive phase transform method for pipeline leakage detection

dc.contributor.authorMa, Yifan
dc.contributor.authorGao, Yan
dc.contributor.authorCui, Xiwang
dc.contributor.authorBrennan, Michael J. [UNESP]
dc.contributor.authorAlmeida, Fabricio C. L. [UNESP]
dc.contributor.authorYang, Jun
dc.contributor.institutionChinese Academy of Sciences
dc.contributor.institutionUniversity of Chinese Academy of Sciences
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2019-10-06T15:30:57Z
dc.date.available2019-10-06T15:30:57Z
dc.date.issued2019-01-02
dc.description.abstractIn leak noise correlation surveys, time delay estimation (TDE) is of great importance in pinpointing a suspected leak. Conventional TDE methods involve pre-filtering processes prior to performing cross-correlation, based on a priori knowledge of the leak and background noise spectra, to achieve the desired performance. Despite advances in recent decades, they have not proven to be capable of tracking changes in sensor signals as yet. This paper presents an adaptive phase transform method based on least mean square (LMS) algorithms for the determination of the leak location to overcome this limitation. Simulation results on plastic water pipes show that, compared to the conventional LMS method, the proposed adaptive method is more robust to a low signal-to-noise ratio. To further verify the effectiveness of the proposed adaptive method, an analysis is carried out on field tests of real networks. Moreover, it has been shown that by using the actual measured data, improved performance of the proposed method for pipeline leakage detection is achieved. Hence, this paper presents a promising method, which has the advantages of simple implementation and ability to track changes in practice, as an alternative technique to the existing correlation-based leak detection methods.en
dc.description.affiliationKey Laboratory of Noise and Vibration Research Institute of Acoustics Chinese Academy of Sciences
dc.description.affiliationUniversity of Chinese Academy of Sciences
dc.description.affiliationDepartment of Mechanical Engineering UNESP
dc.description.affiliationFaculty of Science and Engineering UNESP
dc.description.affiliationUnespDepartment of Mechanical Engineering UNESP
dc.description.affiliationUnespFaculty of Science and Engineering UNESP
dc.description.sponsorshipNational Natural Science Foundation of China
dc.description.sponsorshipIdNational Natural Science Foundation of China: 11774378
dc.identifierhttp://dx.doi.org/10.3390/s19020310
dc.identifier.citationSensors (Switzerland), v. 19, n. 2, 2019.
dc.identifier.doi10.3390/s19020310
dc.identifier.issn1424-8220
dc.identifier.scopus2-s2.0-85060038004
dc.identifier.urihttp://hdl.handle.net/11449/187269
dc.language.isoeng
dc.relation.ispartofSensors (Switzerland)
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectLMS adaptive algorithm
dc.subjectPhase spectrum
dc.subjectPipeline leakage detection
dc.subjectTime delay estimation
dc.titleAdaptive phase transform method for pipeline leakage detectionen
dc.typeArtigo
dspace.entity.typePublication

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