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Innovative shunt measurement for residential water micro-leakage detection

Alarefi, SAS and Walker, S (2017) Innovative shunt measurement for residential water micro-leakage detection. In: UNSPECIFIED, ? - ?.

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Abstract

© 2017 IEEE. In the U.K., between 7.6 m 3 to 76m 3 of water is lost annually in each residence through leaks. In contrast to the ongoing improvement on water distribution network leakage detection technologies, research on water leakage at the domestic level has been limited. Identification of large flow rate leaks (i.e. L/min. with floods or bursts) through the analysis of the household water consumption is highly feasible. However, micro-flow rate leaks (i.e. mL/min.) tend to be overlooked and can therefore waste hundreds of liters of water before detection. This, alongside increasing awareness of water quality and resource protection, mandates further investigation of micro-leak detection systems. An innovative micro-leak detection system for domestic applications that utilizes an ultrasonic flowmeter in a new shunt configuration is proposed. Unlike conventional water leakage detection systems, the proposed automated system is highly sensitive (detected leaks of 1 mL/min.) and does not impede the main flow. The micro-leak detection system is completely automated as it employs a: USB-powered voltmeter, USB-powered flowmeter and USB-powered switches. An elegant feature is that the system is remotely controlled across the Globe; thus, allowing large-scale data collection and system control. This system circumvents water leaks on any scale, anywhere in the world. This latter feature is beyond the reach of the complex conventional detection methods. The de-noising property of Wavelet transform is carried out on the remotely collected data from the ultrasonic flowmeter to remove unwanted noise.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2017 8th International Renewable Energy Congress, IREC 2017
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 03 Aug 2017 14:57
Last Modified: 16 Oct 2017 13:15
URI: http://repository.essex.ac.uk/id/eprint/20017

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