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
Minimizing profile error when estimating the sieve-size distribution of iron ore pellets using ordinal logistic regression
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-6186-7116
2011 (English)In: Powder Technology, ISSN 0032-5910, E-ISSN 1873-328X, Vol. 206, no 3, p. 218-226Article in journal (Refereed) Published
Abstract [en]

Size measurement of pellets in industry is usually performed by manual sampling and sieving techniques. Automatic on-line analysis of pellet size based on image analysis techniques would allow non-invasive, frequent and consistent measurement. We evaluate the statistical significance of the ability of commonly used size and shape measurement methods to discriminate among different sieve-size classes using multivariate techniques. Literature review indicates that earlier works did not perform this analysis and selected a sizing method without evaluating its statistical significance. Backward elimination and forward selection of features are used to select two feature sets that are statistically significant for discriminating among different sieve-size classes of pellets. The diameter of a circle of equivalent area is shown to be the most effective feature based on the forward selection strategy, but an unexpected five-feature classifier is the result using the backward elimination strategy. The discrepancy between the two selected feature sets can be explained by how the selection procedures calculate a feature's significance and that the property of the 3D data provides an orientational bias that favours combination of Feret-box measurements. Size estimates of the surface of a pellet pile using the two feature sets show that the estimated sieve-size distribution follows the known sieve-size distribution.

Place, publisher, year, edition, pages
2011. Vol. 206, no 3, p. 218-226
National Category
Signal Processing Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Signal Processing; Industrial Electronics
Identifiers
URN: urn:nbn:se:ltu:diva-11427DOI: 10.1016/j.powtec.2010.09.021ISI: 000286299200003Scopus ID: 2-s2.0-78649714204Local ID: a6330560-c6eb-11df-a707-000ea68e967bOAI: oai:DiVA.org:ltu-11427DiVA, id: diva2:984377
Projects
Vision Systems Research Platform
Note
Validerad; 2011; 20100923 (tobiasa)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Andersson, TobiasThurley, Matthew

Search in DiVA

By author/editor
Andersson, TobiasThurley, Matthew
By organisation
Signals and Systems
In the same journal
Powder Technology
Signal ProcessingOther Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 333 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