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Environmental Technology Volume 44, 2023 - Issue 25
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Articles

Leak detection in real water distribution networks based on acoustic emission and machine learning

Ali FaresDepartment of Building and Real Estate, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong KongView further author information
,
I. A. TijaniDepartment of Building and Real Estate, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong KongORCID Iconhttps://orcid.org/0000-0002-9423-1074View further author information
ORCID Icon,
Zhang RuiDepartment of Building and Real Estate, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong KongCorrespondence[email protected]
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Tarek ZayedDepartment of Building and Real Estate, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong KongView further author information
Pages 3850-3866 | Received 25 Jan 2022, Accepted 22 Apr 2022, Published online: 15 May 2022

Citations (7)

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Read on this site (1)

M. Saravanabalaji, N. Sivakumaran, S. Ranganthan & V. Athappan. (2023) Acoustic signal based water leakage detection system using hybrid machine learning model. Urban Water Journal 0:0, pages 1-17.
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Articles from other publishers (6)

Alvin Wei Ze Chew, Zheng Yi Wu, Rony Kalfarisi, Xue MengJocelyn Pok. (2023) Generalized Acoustic Data Analysis Framework for Leakage Detection and Localization in Field Operational Water Distribution Networks. Journal of Water Resources Planning and Management 149:11.
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Beenish Bakhtawar & Tarek Zayed. (2023) State‐of‐the‐art review of leak diagnostic experiments: Toward a smart water network. WIREs Water 10:5.
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David Barrientos-Torres, Erick Axel Martinez-Ríos, Sergio A. Navarro-Tuch, Jose Luis Pablos-Hach & Rogelio Bustamante-Bello. (2023) Water Flow Modeling and Forecast in a Water Branch of Mexico City through ARIMA and Transfer Function Models for Anomaly Detection. Water 15:15, pages 2792.
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Vineet Tyagi, Prerna Pandey, Shashi Jain & Parthasarathy Ramachandran. (2023) A Two-Stage Model for Data-Driven Leakage Detection and Localization in Water Distribution Networks. Water 15:15, pages 2710.
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Oscar Scussel, Michael J. Brennan, Fabrício Cézar L. de Almeida, Mauricio K. Iwanaga, Jennifer M. Muggleton, Phillip F. Joseph & Yan Gao. (2023) Key Factors That Influence the Frequency Range of Measured Leak Noise in Buried Plastic Water Pipes: Theory and Experiment. Acoustics 5:2, pages 490-508.
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K.R. Aravind Britto, Dvsssv Prasad, S D Prabu Ragavendiran, Sarange Shreepad, Nishant Kumar Singh, Avijit Bhowmick & M Siva Ramkumar. (2022) Supervised Learning Algorithm for Water Leakage Detection through the Pipelines. Supervised Learning Algorithm for Water Leakage Detection through the Pipelines.

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