Review of model-based and data-driven approaches for leak detection and location in water distribution systems

被引:89
作者
Hu, Zukang [1 ]
Chen, Beiqing [2 ,3 ]
Chen, Wenlong [2 ,3 ]
Tan, Debao [1 ,2 ,3 ]
Shen, Dingtao [2 ,3 ]
机构
[1] Hohai Univ, Coll Comp & Informat, Nanjing 210098, Peoples R China
[2] Changjiang River Sci Res Inst, Hubei Prov Key Lab River Basin Water Resources &, Wuhan 430310, Peoples R China
[3] Changjiang River Sci Res Inst, Spatial Informat Technol Applicat Dept, Wuhan 430310, Peoples R China
基金
国家重点研发计划;
关键词
data-driven approaches; leak detection and location; model-based approaches; water distribution systems; INVERSE TRANSIENT ANALYSIS; DISTRIBUTION NETWORKS; BURST DETECTION; PRESSURE SENSORS; FAULT-DETECTION; ACOUSTIC-EMISSION; NEURAL-NETWORKS; PIPE BURSTS; SMART WATER; LOCALIZATION;
D O I
10.2166/ws.2021.101
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Leak detection and location in water distribution systems (WDSs) is of utmost importance for reducing water loss, which is, however, a major challenge for water utility companies. To this end, researchers have proposed a multitude of methods to detect such leaks in WDSs. Model-based and data-driven approaches, in particular, have found widespread uses in this area. In this paper, we reviewed both these approaches and classified the techniques used by them according to their leak detection methods. It is seen that model-based approaches require highly calibrated hydraulic models, and their accuracies are sensitive to modeling and measurement uncertainties. On the contrary, data-driven approaches do not require an in-depth understanding of the WDS. However, they tend to result in high false positive rates. Furthermore, neither of these approaches can handle anomalous variations caused by unexpected water demands.
引用
收藏
页码:3282 / 3306
页数:25
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