hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Screening paper Formation variations on production line
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).ORCID iD: 0000-0003-2185-8973
2007 (English)In: New Trends in Applied Artificial Intelligence, Proceedings / [ed] Okuno, HG and Ali, M, Berlin: Springer Berlin/Heidelberg, 2007, p. 511-520Conference paper, Published paper (Other academic)
Abstract [en]

This paper is concerned with a multi–resolution tool for screening paper formation variations in various frequency regions on production line. A paper web is illuminated by two red diode lasers and the reflected light recorded as two time series of high resolution measurements constitute the input signal to the papermaking process monitoring system. The time series are divided into blocks and each block is analyzed separately. The task is treated as kernel based novelty detection applied to a multi–resolution time series representation obtained from the band-pass filtering of the Fourier power spectrum of the series. The frequency content of each frequency region is characterized by a feature vector, which is transformed using the canonical correlation analysis and then categorized into the inlier or outlier class by the novelty detector. The ratio of outlying data points, significantly exceeding the predetermined value, indicates abnormalities in the paper formation. The tools developed are used for online paper formation monitoring in a paper mill.

Place, publisher, year, edition, pages
Berlin: Springer Berlin/Heidelberg, 2007. p. 511-520
Series
Lecture Notes in Artificial Intelligence, ISSN 0302-9743 ; 4570
Keywords [en]
Screening, Paper
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-2103DOI: 10.1007/978-3-540-73325-6_51ISI: 000248621400051Scopus ID: 2-s2.0-34948896581Local ID: 2082/2498ISBN: 978-3-540-73322-5 OAI: oai:DiVA.org:hh-2103DiVA, id: diva2:239321
Conference
20th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems Location, Kyoto, JAPAN, JUN 26-29, 2007
Available from: 2008-11-04 Created: 2008-11-04 Last updated: 2018-03-23Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Ejnarsson, MarcusNilsson, Carl-MagnusVerikas, Antanas

Search in DiVA

By author/editor
Ejnarsson, MarcusNilsson, Carl-MagnusVerikas, Antanas
By organisation
Intelligent systems (IS-lab)
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 184 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf