Sensor Placement for Leak Localization in Water Distribution Networks Based on Graph Convolutional Network

Nowadays, the research on optimal sensor placement (OSP) is very active in the field of leak detection and localization in the water distribution network (WDN). Considering that most of the WDNs are irregular networks, this article proposes a new method for OSP applied to irregular network system conditions. From the initial set of a limited number of sensors placed by node data features, the proposed method makes a completely new change to the limited number of sensor layouts. The solution is based on a graph convolutional network (GCN) algorithm, which combines node features and graph structure features. In order to verify the effectiveness of the algorithm, the nodes selected by the algorithm in this article are used to locate the leakage of the pipeline network. By simulating real leakage scenarios, the method is applied to a small WDN (Anytown) and a large WDN (Net3). The results show that the method proposed in this article outperforms other comparison algorithms to a certain extent.