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This article presents a leak localization methodology based on stateestimation and learning. The first is handled by an interpolation scheme,whereas dictionary learning is considered for the second stage. The novelproposed interpolation technique exploits the physics of the interconnectionsbetween hydraulic heads of neighboring nodes in water distribution networks.Additionally, residuals are directly interpolated instead of hydraulic headvalues. The results of applying the proposed method to a well-known case study(Modena) demonstrated the improvements of the new interpolation method withrespect to a state-of-the-art approach, both in terms of interpolation error(considering state and residual estimation) and posterior localization.

Learning Dictionaries from Physical-Based Interpolation for Water Network Leak Localization