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Signal monitoring using adaptive theshold classifier in pulp and paper processes

  • Jukka Hiltunen
  • , Manne Tervaskanto
  • , Sauli Kivikunnas
  • , Lauri Pohjanheimo
  • , Janne Haltamo
  • University of Oulu
  • UPM-Kymmene Oyj

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

Abstract

Typically in pulp and paper processes raw material quality variation due to seasonal deviations as well as measurement drifts cause difficulties in setting the tight alarm thresholds for quality and control measurements. By using adaptive thresholds, more sensitive measurement range and thus reduced quality variation can be achieved. In this paper, new adaptive classification algorithm is proposed and validated using simulated and real mill data.
Original languageEnglish
Title of host publicationProceedings of 16th IFAC World Congress 2005
PublisherElsevier
Pages381-386
ISBN (Print)978-3-902661-75-3
DOIs
Publication statusPublished - 2005
MoE publication typeA4 Article in a conference publication
Event16th IFAC World Congress 2005 - Prague, Czech Republic
Duration: 3 Jul 20058 Jul 2005

Publication series

SeriesIFAC Proceedings Volumes
Volume38
ISSN1474-6670

Conference

Conference16th IFAC World Congress 2005
Country/TerritoryCzech Republic
CityPrague
Period3/07/058/07/05

Keywords

  • adaptive systems
  • classification
  • monitoring
  • pulp industry
  • paper industry

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