Towards sustainable water networks: automated fault detection and diagnosis
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Perfido, D.; Raciti, M.; Zanotti, C.; Chambers, N.; Hannon, L.; Keane, M.; Clifford, E.; Costa, A. 2017. Towards sustainable water networks: automated fault detection and diagnosis, Entrepreneurship and Sustainability Issues 4(3): 339-350. https://doi.org/10.9770/jesi.2017.4.3S(9)
The paper will present an overview of one of the Fault Detection and Diagnosis (FDD) systems developed within the Waternomics project. The FDD system has been developed basing on the hydraulic modeling of the water network, the real time values of flow and pressure obtained from installation of innovative ICT and commercial smart meters and the application of the Anomaly Detection with fast Incremental ClustEring (ADWICE) algorithm adapted for the drinking water network. The FDD system developed is useful when we have to consider more than one parameter at the same time to determine if an anomaly or fault is in place in a complex water network and the system is designed on purpose to cope with a larger features set. The new FDD system will be implemented in an Italian demo site, the Linate Airport Water network in Milan, where a large water distribution network is in place and where, due the many variables coming into play, it could be very difficult to detect anomalies with a low false alarm rate.