Acoustic Data Analysis Framework for Near Real-Time Leakage Detection and Localization for Smart Water Grid

Abstract

[EN] Acoustic sensors are widely used for monitoring urbanized water distribution networks (WDNs) to detect and localize pipe leakages. Since their inception, few research studies have focused on developing a generic, effective, and practical methodology to analyse complex acoustics signals for leakage detection and localization in large-scale WDNs. In collaboration with PUB, Singapore’s National Water Agency, a generic acoustic data analysis approach has been developed to facilitate PUB’s present Smart Water Grid (SWG) management. The proposed approach encompasses multi-stage systematic analyses, namely: (1) data quality assessment; (2) data pre-processing; (3) near real-time leakage event detection and classification; and finally (4) near real-time leakage localization. Our proposed approach is then tested in major WDNs in Singapore having more than 1100km of underground water pipelines and 82 permanently installed hydrophone acoustic sensors between 1 Aug 2019 and 31 Aug 2020, where multiple historical leakage events were reported to within 600m, or less, from neighbouring hydrophones across the large complex networks. By emulating the near real-time detection and localization analyses daily, our proposed methodology could localize reported leakage events to an error range of around 150m on average, while demonstrating significant and stable acoustic leakage power rate over the temporal size of the leakage event cluster(s).