The Dual Model under pressure: how robust is leak detection under uncertainties and model-mismatches - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Journal Articles Engineering Proceedings Year : 2024

The Dual Model under pressure: how robust is leak detection under uncertainties and model-mismatches

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) 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.
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hal-04646743 , version 1 (12-07-2024)

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Enrique Campbell, Edo Abraham, Johannes Koslowski, Olivier Piller, David B Steffelbauer. The Dual Model under pressure: how robust is leak detection under uncertainties and model-mismatches. Engineering Proceedings, 2024, 69 (1), pp.89. ⟨10.3390/engproc2024069089⟩. ⟨hal-04646743⟩
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