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Towards sustainable water networks: automated fault detection and diagnosis

Author

Listed:
  • Domenico Perfido

    (R2M Solution Srl, Italy)

  • Massimiliano Raciti

    (R2M Solution Srl, Italy)

  • Chiara Zanotti

    (University of Milano-Bicocca, Italy)

  • Niall Chambers

    (Informatics Research Unit for Sustainable Engineering, Ireland)

  • Niall Chambers

    (National University of Ireland Galway, Ireland)

  • Louise Hannon

    (Informatics Research Unit for Sustainable Engineering, Ireland)

  • Louise Hannon

    (National University of Ireland Galway, Ireland)

  • Marcus Keane

    (Informatics Research Unit for Sustainable Engineering, Ireland)

  • Marcus Keane

    (National University of Ireland Galway, Ireland)

  • Eoghan Clifford

    (Informatics Research Unit for Sustainable Engineering, Ireland)

  • Eoghan Clifford

    (National University of Ireland Galway, Ireland)

  • Andrea Costa

    (R2M Solution Srl, Italy)

Abstract

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.

Suggested Citation

  • Domenico Perfido & Massimiliano Raciti & Chiara Zanotti & Niall Chambers & Niall Chambers & Louise Hannon & Louise Hannon & Marcus Keane & Marcus Keane & Eoghan Clifford & Eoghan Clifford & Andrea Cos, 2017. "Towards sustainable water networks: automated fault detection and diagnosis," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 4(3), pages 339-350, March.
    • Handle: RePEc:ssi:jouesi:v:4:y:2017:i:3:p:339-350
    DOI: 10.9770/jesi.2017.4.3S(9)
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    More about this item

    Keywords

    FDD; water network; anomalies detection; leakages; ADWICE;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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