Leakage Zone Identification in Large-Scale Water Distribution Systems Using Multiclass Support Vector Machines
Publication: Journal of Water Resources Planning and Management
Volume 142, Issue 11
Abstract
This paper presents a new method for identifying leakage zones of water distribution systems. A large water network is first divided into a number of zones. The zone number is used as the category label of the multiclass support vector machine (M-SVM), which is trained with the data set generated by simulation of the possible leakages using a hydraulic model. The trained M-SVM is used as the leakage zone identification model and applied to determine the likely leakage zones with the observed field data. Two case studies are presented in this paper to demonstrate the effectiveness of the method. The results indicate that this method has many unique advantages in solving the nonlinear and high-dimensional pattern recognition problem with a small sample data set. Together with the method of pressure-dependent leakage detection (PDLD), the proposed approach enables engineers to improve the effectiveness and efficiency of leakage detection for large water distribution systems.
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Acknowledgments
This work is financially supported by the National Science and Technology Major Project (2014ZX07406003). The authors would like to thank the local water utility for providing the leakage data.
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Information & Authors
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Published In
Journal of Water Resources Planning and Management
Volume 142 • Issue 11 • November 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Sep 22, 2015
Accepted: Jan 24, 2016
Published online: Jun 14, 2016
Published in print: Nov 1, 2016
Discussion open until: Nov 14, 2016
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