Detecting bursts in water distribution system via penalized functional decomposition

Yinwei Zhang, Kevin Lansey, Jian Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Detecting bursts in water distribution systems, as anomalies from normal daily usage, is of critical importance for urban infrastructure maintenance. Existing methods based on conventional statistical process control fall short of accurate estimations of burst magnitude and starting time. This research combines a functional basis expansion of water flow data stream and a penalized decomposition to parameterize and estimate the normal water usage profile and detect spars burst with a comparatively small magnitude. The effectiveness of the proposed method is demonstrated by a high-fidelity simulation case study.

Original languageEnglish (US)
Title of host publication2020 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2020
PublisherIEEE Computer Society
Pages205-209
Number of pages5
ISBN (Electronic)9781538672204
DOIs
StatePublished - Dec 14 2020
Event2020 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2020 - Virtual, Singapore, Singapore
Duration: Dec 14 2020Dec 17 2020

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
Volume2020-December
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

Conference2020 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2020
Country/TerritorySingapore
CityVirtual, Singapore
Period12/14/2012/17/20

Keywords

  • Basis expansion
  • Hydraulics
  • Optimization
  • Profile monitoring
  • Regularization

ASJC Scopus subject areas

  • Business, Management and Accounting (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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