Enhancing Pipe-Break Early Warning in Smart Water Networks: Distinguishing Leaks from Water Uses

Abstract

This research presents a denoising technique developed for enhancing the identification of newly developed and/or developing leaks by acoustic loggers in smart water networks. The key challenge addressed is the differentiation of leak-induced signals from signals originating from other sources, such as customer water use, pumps operations and environmental noise. A spectral subtraction-based denoising technique is adapted to process the acoustic waves measured daily using wireless accelerometers. A newly captured wave file can be filtered based on a reference wave file, either one with a known nonleak noise source or one measured in the past at the same location, to highlight the differences or the evolution of the signals over time. This technique enhances the robustness of automated alarms in identifying leaks in water networks.