Abstract

Nowadays, there is growing interest in controlling and reducing the amount of water lost through leakage in water supply systems (WSSs). Leakage is, in fact, one of the biggest problems faced by the managers of these utilities. This work addresses the problem of leakage in WSSs by using GPR (Ground Penetrating Radar) as a non-destructive method. The main objective is to identify and extract features from GPR images such as leaks and components in a controlled laboratory condition by a methodology based on second order statistical parameters and, using the obtained features, to create 3D models that allows quick visualization of components and leaks in WSSs from GPR image analysis and subsequent interpretation. This methodology has been used before in other fields and provided promising results. The results obtained with the proposed methodology are presented, analyzed, interpreted and compared with the results obtained by using a well-established multi-agent based methodology. These results show that the variance filter is capable of highlighting the characteristics of components and anomalies, in an intuitive manner, which can be identified by non-highly qualified personnel, using the 3D models we develop. This research intends to pave the way towards future intelligent detection systems that enable the automatic detection of leaks in WSSs.

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