Water Distribution

Oral

394265 - Leakage detection in water distribution systems using routine measurements under model and data uncertainty

Wednesday, June 6
10:30 AM - 12:00 PM
Location: Lakeshore C
Co-Authors: Mohd Anwer, Greensboro – NC A&T University; May Almousa, Greensboro, NC – NC A&T University

In most modern water networks, pressure and flow measurements are routinely collected at various points in the network for operational reasons. Since leaks typically induce a signature on these measurements, they can be used in non-intrusive leak detection approaches that rely on a hydraulic model such as EPANET. This research extends previously developed iterative linear approximation methods (based on linear and mixed integer linear programming) for detecting leaks by incorporating a number of new enhancements. These include the following: (a) change in model formulation to use flow measurements in addition to pressure, (b) algorithmic changes to handle measurement and model uncertainties, and (c) a more realistic leakage representation in the hydraulic model. The performance of the linear approximation methods will be compared against a machine learning approach that uses only sensor observations (pressure, flow) to detect leaks. The methods are validated using simulated leakage scenarios for representative networks in North Carolina and South Africa.

Kumar Mahinthakumar

Professor
North Carolina University

Dr. Mahinthakumar is a professor in the Department of Civil, Construction, and Environmental Engineering at North Carolina State University. He obtained his PhD in Civil Engineering from University of Illinois at Urbana Champaign in 1995 with a focus on hydrosystems. His research interests are in large scale modeling of subsurface flow and transport, parallel and distributed computing, optimization and inverse problems, water distribution system analysis

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Kobus Van Zyl

Professor
University of Cape Town

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Asaph Kabaasha

Post-doctoral Associate
University of Cape Town

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