Performance comparison of reduced models for leak detection in water distribution networks

This paper presents a methodology for comparing the performance of model-reduction strategies to be used with a diagnostic methodology for leak detection in water distribution networks. The goal is to find reduction strategies that are suitable for error-domain model falsification, a model based data interpretation methodology. Twelve reduction strategies are derived from five strategy categories. Categories differ according to the manner in which nodes are selected for deletion. A node is selected for deletion according to: (1) the diameter of the pipes; (2) the number of pipes linked to a node; (3) the angle of the pipes in the case of two two-pipe nodes; (4) the distribution of the water demand; and, (5) a pair-wise combination of some categories. The methodology is illustrated using part of a real network. Performance is evaluated first by judging the equivalency of the reduced network with the initial network (before the application of any reduction procedure) and secondly, by as...

• Type: Journal
• Year: 2015
• Where: AEI
• Authors: Gaudenz Moser, Stephanie German Paal, Ian F. C. Smith
• Keywords: AEI 2015, Artificial Intelligence