Burst in brief
Self-learning technologies now enable us to make demand, flow and pressure predictions. These deliver major advantages in identifying when leaks and bursts occur within the water supply network. Leaks can be quickly located to reduce the time for repair.
Comparing network predictions with real-time data highlights anomalies that may be the result of leaks. Learning the variance at each node is used to develop a very accurate alarm threshold variance. The real-time flow is compared instantaneously to nodal prediction, and to historical flow data, to identify smaller leaks and bursts.
Meeting the growing demand for water relies on a robust and well-maintained water network. Managing water assets, particularly underground pipelines, is essential. Early detection of issues and preventative maintenance are the key to protecting these vital assets. Aqua Suite’s sophisticated prediction and detection capabilities ensure that assets can be managed in the most cost efficient, least disruptive way.