Leak localization in water distribution networks using classifiers with cosenoidal features
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Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/342267
Tipus de documentText en actes de congrés
Data publicació2020
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
This paper presents a leak localization approach for water distribution networks using classifiers with pressure residuals as input features. This approach is based on applying a non-linear transformation to the residuals of the node pressures to increase the separability of the leak classes. The transformed features can be interpreted as the direction cosines in the subspace spanned by the residuals of the measured pressures. In order to illustrate the method, different tests were performed with MATLAB® applying four different classification algorithms on a synthetic dataset obtained from an EPANET model of the Hanoi network. Then, by considering the cosenoidal features, a significant improvement in the leak location
error was achieved. In this way, the leak location error decreases by more than 97% compared to the use of residual features when accurate measurements are used, and about 50% when noisy measurements with 60 dB SNR are used.
CitacióSantos-Ruiz, I. [et al.]. Leak localization in water distribution networks using classifiers with cosenoidal features. A: World Congress of the International Federation of Automatic Control. "IFAC 2020 - 21th World Congress of the International Federation of Automatic Control: Berlin, Germany". 2020, p. 3664:1-3664:6.
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3664.pdf | postprint | 773,1Kb | Visualitza/Obre |