Online burst detection in a water distribution system using the Kalman filter and hydraulic modelling

Abstract

This paper presents a burst detection methodology that utilizes distributed real time sensor data in a district metered area using a data assimilation method and a hydraulic model. A sensitivity analysis was applied to evaluate the performance of various burst detection metrics under different conditions, and to identify appropriate thresholds for online burst detection using artificial generated burst events. It was found that the best performing metrics are the corrected flow residual and normalized corrected flow residual. This metric can be effective to detect bursts in a timely and reliable manner within a district metering area under assumed test conditions.