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handle: 2117/10371
In this paper, a leak detection, isolation and estimation methodology in pressurized water pipe networks is proposed. The methodology is based on computing residuals which are obtained comparing measured pressures (heads) in selected points of the network with their estimated values by means of a Linear Parameter Varying (LPV) model and zonotopes. The structure of the LPV model is obtained from the non-linear mathematical model of the network. The proposed detection method takes into account modelling uncertainty using zonotopes. The isolation and estimation task employs an algorithm based on the residual fault sensitivity analysis. Finally, a typical water pipe network is employed to validate the proposed methodology. This network is simulated using EPANET software. Parameters of LPV model and their uncertainty bounded by zonotopes are estimated from data coming from this simulator. A leak scenario allows to assess the effectiveness of the proposed approach.
Control automàtic -- Models matemàtics, Aigua -- Canonades, :Informàtica::Automàtica i control [Àrees temàtiques de la UPC], Àrees temàtiques de la UPC::Informàtica::Automàtica i control, :Nàutica [Àrees temàtiques de la UPC], Water leakage, Leak detectors, Àrees temàtiques de la UPC::Nàutica
Control automàtic -- Models matemàtics, Aigua -- Canonades, :Informàtica::Automàtica i control [Àrees temàtiques de la UPC], Àrees temàtiques de la UPC::Informàtica::Automàtica i control, :Nàutica [Àrees temàtiques de la UPC], Water leakage, Leak detectors, Àrees temàtiques de la UPC::Nàutica
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 14 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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