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

Download the digital copy of the doc pdf document

Authors

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.