Efficiency enhancement of leakage detection and localisation methods using leakage gradient and most affected sensors

Abstract

Leaks cause substantial economic and water losses for water distribution networks (WDNs). Thus, it is imperative to detect and localize leaks. This paper proposes an efficient set of methods for detecting and localizing leaks, with three main steps: model calibration, leak detection, and leak localization. First, demands, pipe diameter, and pipe roughness in the hydraulic model are calibrated with a genetic algorithm (GA). The X-bar method and cumulative sum control chart are then implemented to detect pipe bursts and incipient leaks, respectively. Lastly, a reduced search space is defined and searched with a GA to locate leaks. The proposed strategy was tested on the hypothetical WDN of L-Town from the Battle of the Leakage Detection and Isolation Methods. Results show that 12 of 19 leaks were detected, and 8 of the 12 leakages were accurately located. Compared with other approaches, the proposed approach is more efficient and equally effective.