The Dual Model under Pressure
How Robust Is Leak Detection under Uncertainties and Model Mismatches?
Enrique Campbell (Kompetenzzentrum Wasser Berlin)
Edo Abraham (TU Delft - Water Resources)
Johannes Koslowski (Kompetenzzentrum Wasser Berlin)
Olivier Piller (Institut National de Recherche Pour L’Agriculture, L’Alimentation et L’Environnement (INRAE))
David B. Steffelbauer (Kompetenzzentrum Wasser Berlin)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
This paper investigates the robustness of one innovative model-based method for leak detection, namely the Dual Model. We evaluate the algorithm’s performance under various leakage scenarios in the L-Town network, despite uncertainties and model mismatches in (i) base demand, (ii) pipe roughness, (iii) the number of sensors, and (iv) network topology. Our investigation results indicate that the Dual Model is highly sensitive to discrepancies in the first three parameters. However, the impact can be mitigated through sensor-specific calibration, such as adjusting sensor elevations. Moreover, the Dual Model has demonstrated robustness to minor topology mismatches, like those introduced by closed valves.
help_outline