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

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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.

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Notes

  1. Cost figures from [2] have been adjusted for inflation.

  2. During the initial phase of the WaterWiSe@SG deployment, pressure was sampled at 2 kHz. Wavelet analysis of the burst transients revealed that the detail coefficients above 125 Hz did not aid in identifying the burst events. Thus, sampling frequency for pressure was reduced to 250 Hz.

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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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  1. Seshan Srirangarajan

    Present address: Nimbus Center, Cork Institute of Technology, Cork, Ireland

Authors and Affiliations

  1. Intelligent Systems Center, Nanyang Technological University, Singapore, 637553, Singapore

    Seshan Srirangarajan & Hock Beng Lim

  2. Singapore-MIT Alliance for Research and Technology, Singapore, 138602, Singapore

    Michael Allen, Ami Preis & Mudasser Iqbal

  3. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139-4307, USA

    Andrew J. Whittle

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  1. Seshan Srirangarajan
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  2. Michael Allen
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  4. Mudasser Iqbal
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Correspondence to Seshan Srirangarajan.

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Srirangarajan, S., Allen, M., Preis, A. et al. Wavelet-based Burst Event Detection and Localization in Water Distribution Systems. J Sign Process Syst 72, 1–16 (2013). https://doi.org/10.1007/s11265-012-0690-6

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