Leakage Diagnosis Framework for Water Distribution Networks using ABC

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Abstract

In this work, we present a novel approach for leakage localization and Identification in water distribution networks using Approximate Bayesian Computation(ABC). A reduced pressure graph theory-based model is derived for the water networks. A leakage is considered an unknown parameter of the model which is to be estimated. Consumer demands are considered stochastic in nature and owing to that the model output, which is pressure, is also stochastic. The first moment of the model and the pressure measurements are compared to estimate probable leakages. Further, the probability distribution for the estimated leakages is computed using ABC. Results from an experimental test on a small-scale water network are also presented to demonstrate the approach.
Original languageEnglish
Book seriesIFAC-PapersOnLine
Volume56
Issue number2
Pages (from-to)8067-8072
Number of pages6
ISSN1474-6670
DOIs
Publication statusPublished - 22 Nov 2023
Event22nd IFAC World Congress 2023 - Yokohama, Japan
Duration: 9 Jul 202314 Jul 2023
https://www.ifac2023.org/

Conference

Conference22nd IFAC World Congress 2023
Country/TerritoryJapan
CityYokohama
Period09/07/202314/07/2023
Internet address

Keywords

  • Leakage localization and identification
  • Approximate Bayesian Computation
  • water resources
  • graph theory

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