Functional Data Analytics for Detecting Bursts in Water Distribution Systems
Date:
It is crucial to develop effective and efficient algorithms to detect bursts in water distribution systems from spatially and temporally correlated hydraulic measurements. Traditional anomaly detection methods based on basis expansion may be applicable, falling short of accurate estimations of burst magnitude and starting time. This research proposes a spatio-temporal decomposition based burst detection method, which estimates the ST profile parameters according to the expected magnitude of spars burst. The effectiveness of the proposed method is demonstrated by a simulation case study.