Fuzzy clustering and classification for automated leak detection systems

Nathalie Taillefond, Olaf Wolkenhauer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

A methodology for pipeline integrity monitoring systems using a mixture of clustering and classification tools for fault detection is presented here. The approach is used to classify more readily faults or changes in the context of on-line leak detection with initially off-line training. The methodology is applied to a small-scale pipeline monitoring case where portability, robustness and reliability are amongst the most important criteria. The results are encouraging as relatively low levels of false alarms and increased fault detection are obtained.

Original languageEnglish
Title of host publicationIFAC Proceedings Volumes (IFAC-PapersOnline)
EditorsGabriel Ferrate, Eduardo F. Camacho, Luis Basanez, Juan. A. de la Puente
PublisherIFAC Secretariat
Pages407-411
Number of pages5
Edition1
ISBN (Print)9783902661746
DOIs
StatePublished - 2002
Externally publishedYes
Event15th World Congress of the International Federation of Automatic Control, 2002 - Barcelona, Spain
Duration: 21 Jul 200226 Jul 2002

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1
Volume15
ISSN (Print)1474-6670

Conference

Conference15th World Congress of the International Federation of Automatic Control, 2002
Country/TerritorySpain
CityBarcelona
Period21/07/0226/07/02

Keywords

  • Classifiers
  • Fault detection
  • Fault diagnosis
  • Methodology
  • Pattern recognition

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