| description abstract | Detecting and localizing leakages in underground water pipelines continue to be challenging in large-scale water distribution networks (WDNs) having a low density of acoustic sensors per unit pipeline. Many previous acoustic research analyses have been restricted to either (1) lab-scale WDN setups having simulated leakage conditions, or (2) field-scale WDNs with high densities of acoustic sensors. To address the current challenges, this study develops a generic and practical acoustic data analysis framework to analyze acoustics signals for leakage detection and localization in large-scale WDNs, where the proposed framework encompasses multi-stage systematic analyses, namely: (1) data quality assessment; (2) acoustic features generation and analysis; (3) leakage event detection; and (4) leakage event localization. In collaboration with Public Utility Board (PUB), Singapore’s National Water Agency, our proposed framework has been verified in large-scale WDNs in Singapore having more than 1,100 km of underground water pipelines and 82 permanently installed monitoring stations, each of which is instrumented to measure acoustics, via hydrophone equipment, pressure, and water quality parameters, and by using historical data collected between August 1, 2019 and August 31, 2020, where numerous leakage events were reported to within 1,000 m, or less, connected pipelines from independent hydrophones. | |
