Publication
Estimation of node pressures in water distribution networks by Gaussian process regression
Conference Article
Conference
Conference on Control and Fault Tolerant Systems (SYSTOL)
Edition
4th
Pages
50-55
Doc link
http://dx.doi.org/10.1109/SYSTOL.2019.8864793
File
Authors
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Santos-Ruiz, Ildeberto
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Lopez Estrada, Francisco Ronay
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Puig Cayuela, Vicenç
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Blesa Izquierdo, Joaquim
Abstract
This paper proposes a method to predict pressures in all nodes of a water distribution network (WDN) by Gaussian process regression (GPR) from pressure measurements in a subset of selected nodes. The pressure sensors are placed in the nodes where, together, they capture the maximum pressure variance and also have a minimum sensitivity to measurement noise. As a case study, the proposed method was tested on a dataset obtained from simulations with the hydraulic model of the Hanoi WDN. Using only three pressure sensors, the GPR estimation error in the pressures of the unmeasured nodes are comparable to the error due to measurement noise in physical pressure sensors.
Categories
automation.
Author keywords
water distribution networks; leak localization; Gaussian Process
Scientific reference
I. Santos-Ruiz, F.R. Lopez, V. Puig and J. Blesa. Estimation of node pressures in water distribution networks by Gaussian process regression, 4th Conference on Control and Fault Tolerant Systems, 2019, Casablanca, Morocco, pp. 50-55.
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