Leakage detection and location in water distribution systems using a fuzzy-based methodology

Abstract

Loss of water due to leakage is a common phenomenon observed practically in all water distribution systems (WDS). However, the leakage volume can be reduced significantly if the occurrence of leakage is detected within minimal time after its occurrence. This paper proposes a novel methodology to detect and diagnose leakage in WDS. In the proposed methodology, a fuzzy-based algorithm has been employed that incorporates various uncertainties into different WDS parameters such as roughness, nodal demands, and water reservoir levels. Monitored pressure in different nodes and flow in different pipes have been used to estimate the degree of membership of leakage and its severity in terms of index of leakage propensity (ILP). Based on the degrees of leakage memberships and the ILPs, the location of the nearest leaky node or leaky pipe has been identified. To demonstrate the effectiveness of the proposed methodology, a small distribution network was investigated which showed very encouraging results. The proposed methodology has a significant potential to help water utility managers to detect and locate leakage in WDS within a minimal time after its occurrence and can help to prioritise leakage management strategies.

Keywords:

• water distribution system (WDS)
• leakage detection and diagnosis
• fuzzy algorithm
• water mains

Acknowledgements

This research has been carried out as a part of NSERC-SPG (Strategic Project Grants) funded by Natural Sciences and Engineering Research Council of Canada (NSERC). The authors would also like to express sincere gratitude to the anonymous reviewers for their critical reviews that has improved the quality of the paper significantly.

Notes

1. A systematic survey technique for listening for leak noises on hydrants, valves, stop taps or at the ground surface above the line of the pipe line. Various types of equipment are available; however, the sounding stick is a basic one, which can be used as a simple acoustic instrument or an electrically amplified instrument (Farley and Trow 2003).

2. It is a ratio of deviation of the monitored flow from the most likely value to deviation of the extreme value from the most likely value. Details have been discussed in Section 2.4.