The Development of a Data-Based Leakage Pinpoint Detection Technique for Water Distribution Systems

Article Environmental Sciences

Development of Methods for Diagnosing the Operating Conditions of Water Supply Networks over the Last Two Decades

Justyna Stanczyk et al.

Summary: This article presents a comprehensive overview of the previously used methods for diagnosing the operating conditions of water supply networks and evaluates their usefulness in specific operating conditions. The authors highlight the need for further research on detecting the operating conditions of water supply networks in real systems and summarize the global trends in the development of methods for leak diagnosis and detection in water distribution networks.

WATER (2022)

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Article Engineering, Civil

Detecting and Localizing Leakages in Water Distribution Systems Using a Two-Phase Model

Kyoung Won Min et al.

Summary: This study presents a novel approach to leakage detection and localization, utilizing data classification and an optimization process for accurate identification of leakage locations. However, in the testing, no real leakage events were successfully detected or localized.

JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2022)

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Article Engineering, Civil

Comparison of Imputation Methods for End-User Demands in Water Distribution Systems

Sanghoon Jun et al.

Summary: This study develops a burst detection algorithm and evaluates the effectiveness of different imputation methods for missing AMI data. The historical mean (HM) imputation method is found to be the most effective in replacing missing data, resulting in low prediction errors and high burst detection probability.

JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2021)

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Article Green & Sustainable Science & Technology

Development of Leakage Detection Model and Its Application for Water Distribution Networks Using RNN-LSTM

Chan-Wook Lee et al.

Summary: With the advancement of the 4th Industrial Revolution, advanced measurement infrastructure and utilization technologies have been introduced into the water supply system. A data-driven leak detection model using deep learning technology based on inflow meter data was developed, with high accuracy in performance evaluation on actual leakage accident data. The model can be used as critical software technology for proactive identification of various issues in smart water infrastructure.

SUSTAINABILITY (2021)

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Article Engineering, Civil