A better estimation of wave arrival time in water distribution networks using WAvelet kNEe (WANE) |
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| Affiliation: | 1. Faculty of Science, Agriculture, and Engineering, Newcastle University, Singapore 599493, Singapore;2. Xylem Inc, USA;3. Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, TX 78712, USA;1. Department of Civil & Environmental Engineering, National University of Singapore, Block E1A, #07-03, No.1 Engineering Drive 2, Singapore 117576, Singapore;2. Future Cities Laboratory, Singapore-ETH Centre, 1 CREATE Way, CREATE Tower, #06-01, Singapore 138602, Singapore;3. Applied Computing and Mechanics Laboratory (IMAC), School of Architecture, Civil and Environmental Engineering (ENAC), Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland;1. Applied Mechanics and Construction, University of Vigo, Spain;2. Chair of Computational Modelling and Simulation, Technical University of Munich, Germany;1. Department of Information Science, Faculty of Sciences, Toho University, 2-2-1 Miyama, 274-8510 Funabashi, Japan;2. Department of Applied Mathematics and Computational Sciences, E.T.S.I. Caminos, Canales y Puertos, University of Cantabria, Avda. de los Castros, s/n, 39005 Santander, Spain;3. School of Civil Engineering, Universidad de Cantabria, Avda. de los Castros 44, E-39005 Santander, Spain;4. Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor SI-2000, Slovenia;5. R&D EgiCAD, School of Civil Engineering, Universidad de Cantabria, Avda. de los Castros 44, 39005 Santander, Spain |
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| Abstract: | A transient pressure wave is a sudden pressure change that occurs in a short time, which can be induced by sudden changes in valve and pump operation, and pipe bursts in a Water Distribution Network (WDN). An accurate estimation of a transient wave arrival time is crucial because it facilitates pipe condition assessment, hydraulic model calibration, and accurate localization of pipe burst events. Due to the noisy and highly fluctuating nature of the pressure signals, estimating an accurate transient pressure wave arrival time is not a trivial task. Among many methodologies proposed for detecting abrupt pressure changes, Discrete Wavelet Transform (DWT) and Cumulative Sum (CUSUM) were the two most popular approaches. However, several limitations involved with these two approaches can easily lead to unsatisfactory results. Moreover, some of the existing methodologies were only tested on either a single pipeline, engineered events, or a small sample size of events, making these methodologies suitable and accurate only for a limited number of scenarios. Driven by these limitations, a novel approach is proposed to estimate the wave arrival time in water distribution networks (WDNs). The backbone of this approach is the integration of wavelet decomposition and a knee point detection algorithm, thus gaining the name WAvelet kNEe (WANE). Through a comparative study against the other methodologies using 90 recorded transient events detected in a real WDN, WANE is found to provide the best wave arrival time estimation, with a Root Mean Square Error (RMSE) of 0.4 s. Based on the result, our estimation error is at least 15 s lesser than the other methodologies. With an improved wave arrival time estimation, WANE has the potential to minimize the response time of repair crews, service disruption time, as well as the associated water losses due to a pipe break. |
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| Keywords: | Water distribution network Transient pressure wave Transient analysis Discrete wavelet transform Cumulative sum Knee point detection |
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