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Water 2017, 9(11), 820; https://doi.org/10.3390/w9110820

Robust Meter Network for Water Distribution Pipe Burst Detection

1
Research Center for Disaster Prevention Science and Technology, Korea University, Anam-ro 145, Seongbuk-gu, Seoul 02841, Korea
2
School of Civil, Environmental and Architectural Engineering, Korea University, Anam-ro 145, Seongbuk-gu, Seoul 02841, Korea
*
Author to whom correspondence should be addressed.
Received: 15 September 2017 / Revised: 23 October 2017 / Accepted: 24 October 2017 / Published: 26 October 2017
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Abstract

A meter network is a set of meters installed throughout a water distribution system to measure system variables, such as the pipe flow rate and pressure. In the current hyper-connected world, meter networks are being exposed to meter failure conditions, such as malfunction of the meter’s physical system and communication system failure. Therefore, a meter network’s robustness should be secured for reliable provision of informative meter data. This paper introduces a multi-objective optimal meter placement model that maximizes the detection probability, minimizes false alarms, and maximizes the robustness of a meter network given a predefined number of meters. A meter network’s robustness is defined as its ability to consistently provide quality data in the event of meter failure. Based on a single-meter failure simulation, a robustness indicator for the meter network is introduced and maximized as the third objective of the proposed model. The proposed model was applied to the Austin network to determine the independent placement of pipe flow and pressure meters with three or five available meters. The results showed that the proposed model is a useful tool for determining meter locations to secure high detectability and robustness. View Full-Text
Keywords: water distribution system; pipe burst detection; meter network; robustness water distribution system; pipe burst detection; meter network; robustness
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Jung, D.; Kim, J.H. Robust Meter Network for Water Distribution Pipe Burst Detection. Water 2017, 9, 820.

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