Improving Detection of Events at Water Treatment Works: A UK Case Study

6 pages•Published: September 20, 2018

Gerald Riss, Michele Romano, Kevin Woodward, Zoran Kapelan and Fayyaz Ali Memon

Abstract

This paper presents a study aimed at improving the event detection capabilities of the existing, threshold-based detection system at a selected Water Treatment Works operated by United Utilities. The study shows that improvements can be achieved by using optimised threshold and persistence values identified by performing a sensitivity type analysis. The main findings from this study show that, although an overall increase in the true detection rate and decrease in the number of false alarms can be achieved, the high number of false alarms remains an issue. To address this problem a new event detection system based on suitable relations across multiple signals will be developed as part of future work.

Keyphrases: confusion matrices, event recognition, online monitoring, water treatment works

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 1766-1771.

Links:	https://easychair.org/publications/paper/6MwG
	https://doi.org/10.29007/grgj

BibTeX entry

@inproceedings{HIC2018:Improving_Detection_Events_at,
  author    = {Gerald Riss and Michele Romano and Kevin Woodward and Zoran Kapelan and Fayyaz Ali Memon},
  title     = {Improving Detection of Events at Water Treatment Works: A UK Case Study},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/6MwG},
  doi       = {10.29007/grgj},
  pages     = {1766-1771},
  year      = {2018}}

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