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AuthorEl-Abbasy, Mohammed S.
AuthorMosleh, Fadi
AuthorSenouci, Ahmed
AuthorZayed, Tarek
AuthorAl-Derham, Hassan
Available date2016-09-26T11:04:17Z
Publication Date2016-09
Publication NameJournal of Infrastructure Systems
CitationEl-Abbasy, M., Mosleh, F., Senouci, A., Zayed, T., and Al-Derham, H. (2016). "Locating Leaks in Water Mains Using Noise Loggers." J. Infrastruct. Syst., Article ID 04016012.
ISSN1076-0342
URIhttp://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000305
URIhttp://hdl.handle.net/10576/4771
AbstractBecause of their potential danger to public health, economic loss, environmental damage, and energy waste, underground water pipelines leaks have received more attention globally. Researchers have proposed active leakage control approaches to localize, locate, and pinpoint leaks. Noise loggers have usually been used only for localizing leaks while other tools were used for locating and pinpointing. These approaches have resulted in additional cost and time. Thus, regression and artificial neural network (ANN) models were developed in this study to localize and locate leaks in water pipelines using noise loggers. Several lab experiments have been conducted to simulate actual leaks in a sample ductile iron pipeline distribution network with valves. The noise loggers were used to detect these leaks and record their noise readings. The recorded noise readings were then used as input data for the developed models. The ANN models outperformed regression models during testing. Moreover, ANN models were successfully validated using an actual case study.
SponsorQatar National Research Fund (QNRF) for this research project under Award No. QNRF-NPRP 4-529-2-193.
Languageen
PublisherAmerican Society of Civil Engineers (ASCE)
SubjectWater mains
SubjectLeak locating
SubjectNoise loggers
SubjectRegression analysis
SubjectArtificial neural network
TitleLocating leaks in water mains using noise loggers
TypeArticle
Issue Number3
Volume Number22


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