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Journal of Signal Processing Systems

, Volume 72, Issue 1, pp 1–16 | Cite as

Wavelet-based Burst Event Detection and Localization in Water Distribution Systems

  • Seshan SrirangarajanEmail author
  • Michael Allen
  • Ami Preis
  • Mudasser Iqbal
  • Hock Beng Lim
  • Andrew J. Whittle
Article

Abstract

In this paper we present techniques for detecting and locating transient pipe burst events in water distribution systems. The proposed method uses multiscale wavelet analysis of high rate pressure data recorded to detect transient events. Both wavelet coefficients and Lipschitz exponents provide additional information about the nature of the signal feature detected and can be used for feature classification. A local search method is proposed to estimate accurately the arrival time of the pressure transient associated with a pipe burst event. We also propose a graph-based localization algorithm which uses the arrival times of the pressure transient at different measurement points within the water distribution system to determine the actual location (or source) of the pipe burst. The detection and localization performance of these algorithms is validated through leak-off experiments performed on the WaterWiSe@SG wireless sensor network test bed, deployed on the drinking water distribution system in Singapore. Based on these experiments, the average localization error is 37.5 m. We also present a systematic analysis of the sources of localization error and show that even with significant errors in wave speed estimation and time synchronization the localization error is around 56 m.

Keywords

Multiscale wavelet analysis Transient detection Pipe burst Burst localization 

Notes

Acknowledgements

This work is a collaboration between the Center for Environmental Sensing and Modeling (CENSAM) – Singapore-MIT Alliance for Research and Technology (SMART), Intelligent Systems Center (IntelliSys) at Nanyang Technological University (NTU) and Singapore Public Utilities Board (PUB). This research is supported by the Singapore National Research Foundation (NRF) through the Singapore-MIT Alliance for Research and Technology (SMART) Center for Environmental Sensing and Modeling (CENSAM). We would like to acknowledge our colleagues Cheng Fu, Lewis Girod and Kai-Juan Wong for their contributions.

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Seshan Srirangarajan
    • 1
    • 4
    Email author
  • Michael Allen
    • 2
  • Ami Preis
    • 2
  • Mudasser Iqbal
    • 2
  • Hock Beng Lim
    • 1
  • Andrew J. Whittle
    • 3
  1. 1.Intelligent Systems CenterNanyang Technological UniversitySingaporeSingapore
  2. 2.Singapore-MIT Alliance for Research and TechnologySingaporeSingapore
  3. 3.Department of Civil and Environmental EngineeringMassachusetts Institute of TechnologyCambridgeUSA
  4. 4.Nimbus CenterCork Institute of TechnologyCorkIreland

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