Publication
Leak localization in water distribution networks using Bayesian classifiers
Journal Article (2017)
Journal
Journal of Process Control
Pages
1-9
Volume
55
Doc link
http://doi.org/10.1016/j.jprocont.2017.03.015
File
Authors
-
Soldevila, Adrià
-
Fernandez-Cantí, Rosa M.
-
Blesa Izquierdo, Joaquim
-
Tornil Sin, Sebastian
-
Puig Cayuela, Vicenç
Projects associated
Abstract
This paper presents a method for leak localization in water distribution networks (WDNs) based on Bayesian classifiers. Probability density functions for pressure residuals are calibrated off-line for all the possible leak scenarios by using a hydraulic simulator, and considering the leak size uncertainty, demand uncertainty and sensor noise. A Bayesian classifier is applied on-line to the computed residuals to determine the location of leaks in the WDN. A time horizon based reasoning combined with the Bayesian classifier is also proposed to improve the localization accuracy. Two case studies based on the Hanoi and the Nova Icària networks are used to illustrate the performance of the proposed approach. Simulation results are presented for the Hanoi case study, whereas results for a real leak scenario are shown for the Nova Icària case study.
Categories
automation.
Author keywords
Fault diagnosis; Bayesian classifier; Water distribution networks; Leak localization
Scientific reference
A. Soldevila, R.M. Fernandez-Cantí, J. Blesa, S. Tornil-Sin and V. Puig. Leak localization in water distribution networks using Bayesian classifiers. Journal of Process Control, 55: 1-9, 2017.
Follow us!