Leakage Identification in Water Distribution Networks with Error Tolerance Capability

Xiang Xie (), Dibo Hou (), Xiaoyu Tang () and Hongjian Zhang ()
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Xiang Xie: Zhejiang University
Dibo Hou: Zhejiang University
Xiaoyu Tang: Zhejiang University
Hongjian Zhang: Zhejiang University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2019, vol. 33, issue 3, No 20, 1233-1247

Abstract: Abstract Leakages in water distribution networks have caused considerable waste of water resources. Thus, this study proposes a novel method for hydraulically monitoring and identifying regions where leakages occur in near-real time. A large network is first divided into several identification regions. To exploit a strong constructive and discriminative power, sparse coding is used, thereby adaptively coding the information embedded in observed pressures efficiently and succinctly. And a linear classifier is trained to determine the most likely leakage regions. A benchmark case is presented in this study to demonstrate the effectiveness of the proposed method. Results indicate that the proposed method can identify leakage events with enhanced tolerance capability for measurement errors. The method is also partially effective for identifying two simultaneous leakages. Certain practical advice in balancing the number of sensors and regions is also discussed to enhance the application potential of this method.

Keywords: Water distribution network; Leakage identification; Pressure residual; Sparse coding; Dictionary learning (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11269-018-2179-y

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