Clustering algorithm for burst detection in water distribution systems

doi:10.16511/j.cnki.qhdxxb.2017.25.051

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Abstract Pipe bursts are a universal problem in water supply systems, which can severely disrupt daily life and urban development. This study correlates flow measurements collected from inlets and outlets of a district metering area (DMA) to quickly identify bursts. The analysis uses a clustering algorithm to detect abnormal flow data i.e., outliers. Then, some outliers are identified as bursts according to the inlet and outlet flow fluctuation characteristics. The results indicate that the number and locations of the inlets and outlets affect the detection performance. The system can accurately detect bursts and insure a low false positive rate when there are a relatively small number of inlets and outlets and the locations are well placed.

Keywords burst detection clustering algorithm district metering area (DMA) water distribution system

ZTFLH:

TU991.33

Issue Date: 15 October 2017

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	LIU Shuming
	WU Yipeng
	WANG Xiaoting
	LIU Youfei
	LI Jiajie

Cite this article:

LIU Shuming,WU Yipeng,WANG Xiaoting, et al. Clustering algorithm for burst detection in water distribution systems[J]. Journal of Tsinghua University(Science and Technology), 2017, 57(10): 1096-1101.

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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2017.25.051 OR http://jst.tsinghuajournals.com/EN/Y2017/V57/I10/1096

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