Publication

Fault handling in large water networks with online dictionary learning

Journal Article (2020)

Journal

Journal of Process Control

Pages

46-57

Volume

94

Doc link

https://doi.org/10.1016/j.jprocont.2020.08.003

File

Download the digital copy of the doc pdf document

Authors

Abstract

Fault detection and isolation in water distribution networks is an active topic due to the nonlinearities of flow propagation and recent increases in data availability due to sensor deployment. Here, we propose an efficient two-step data driven alternative: first, we perform sensor placement taking the network topology into account; second, we use incoming sensor data to build a network model through online dictionary learning. Online learning is fast and allows tackling large networks as it processes small batches of signals at a time. This brings the benefit of continuous integration of new data into the existing network model, either in the beginning for training or in production when new data samples are gathered. The proposed algorithms show good performance in our simulations on both small and large-scale networks.

Categories

control theory.

Scientific reference

P. Irofti, F. Stoican and V. Puig. Fault handling in large water networks with online dictionary learning. Journal of Process Control, 94: 46-57, 2020.