Publicação: Adaptive phase transform method for pipeline leakage detection
dc.contributor.author | Ma, Yifan | |
dc.contributor.author | Gao, Yan | |
dc.contributor.author | Cui, Xiwang | |
dc.contributor.author | Brennan, Michael J. [UNESP] | |
dc.contributor.author | Almeida, Fabricio C. L. [UNESP] | |
dc.contributor.author | Yang, Jun | |
dc.contributor.institution | Chinese Academy of Sciences | |
dc.contributor.institution | University of Chinese Academy of Sciences | |
dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2019-10-06T15:30:57Z | |
dc.date.available | 2019-10-06T15:30:57Z | |
dc.date.issued | 2019-01-02 | |
dc.description.abstract | In 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.affiliation | Key Laboratory of Noise and Vibration Research Institute of Acoustics Chinese Academy of Sciences | |
dc.description.affiliation | University of Chinese Academy of Sciences | |
dc.description.affiliation | Department of Mechanical Engineering UNESP | |
dc.description.affiliation | Faculty of Science and Engineering UNESP | |
dc.description.affiliationUnesp | Department of Mechanical Engineering UNESP | |
dc.description.affiliationUnesp | Faculty of Science and Engineering UNESP | |
dc.description.sponsorship | National Natural Science Foundation of China | |
dc.description.sponsorshipId | National Natural Science Foundation of China: 11774378 | |
dc.identifier | http://dx.doi.org/10.3390/s19020310 | |
dc.identifier.citation | Sensors (Switzerland), v. 19, n. 2, 2019. | |
dc.identifier.doi | 10.3390/s19020310 | |
dc.identifier.issn | 1424-8220 | |
dc.identifier.scopus | 2-s2.0-85060038004 | |
dc.identifier.uri | http://hdl.handle.net/11449/187269 | |
dc.language.iso | eng | |
dc.relation.ispartof | Sensors (Switzerland) | |
dc.rights.accessRights | Acesso aberto | |
dc.source | Scopus | |
dc.subject | LMS adaptive algorithm | |
dc.subject | Phase spectrum | |
dc.subject | Pipeline leakage detection | |
dc.subject | Time delay estimation | |
dc.title | Adaptive phase transform method for pipeline leakage detection | en |
dc.type | Artigo | |
dspace.entity.type | Publication |