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.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China [grant number U1509208, 61573313]; the Key Technology Research and Development Program of Zhejiang Province [grant number 2015C03G2010034]; and the Fundamental Research Funds for the Central Universities [grant number 2017FZA5011].
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Xie, X., Hou, D., Tang, X. et al. Leakage Identification in Water Distribution Networks with Error Tolerance Capability. Water Resour Manage 33, 1233–1247 (2019). https://doi.org/10.1007/s11269-018-2179-y
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DOI: https://doi.org/10.1007/s11269-018-2179-y