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Using a Gaussian filter to reduce the effect of positioning errors when optimizing sawing of CT scanned Scots pine and Norway spruce logs
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.ORCID iD: 0000-0003-4530-0536
Number of Authors: 1
2017 (English)In: International Wood Machining Seminar (IWMS-23), 2017Conference paper, Published paper (Refereed)
Abstract [en]

Computed tomography (CT) scanning of logs is being introduced in sawmills, so there is reason to study how log positioning can be controlled using information from CT. However, positioning errors affect this positioning optimization in a negative way. To reduce this effect, a method was developed using sawing simulation, where logs were sawn in a large number of positions, varying rotation and centering. This resulted in three-dimensional surfaces, with the sawn timber value, rotation and centering on the axes. The surfaces were filtered with a Gaussian filter using a distribution corresponding to that of the positioning error. The filtered values were used for optimization, choosing the global maximum. This resulted in a value recovery that was about two percent higher compared to a simpler optimization without filtering, for a normally distributed rotational error of 5 – 15° standard deviation and a ditto centering error of 3.5 – 10.5 mm standard deviation. This was tested using sawing simulation, using the optimal log position for the two methods, with an added positioning error. Furthermore, the robust method has been tested on a smaller number of rotational positions, starting from horns down, to reduce the number of necessary calculations. The result of this was that at least ± 60 ° in the rotational direction should be evaluated for the robust method to result in a higher recovery than the simpler optimization. The robust method was better than sawing horns down and centered, no matter the positioning error, using only 65 evaluated positions per log.

Place, publisher, year, edition, pages
2017.
National Category
Wood Science Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-59966OAI: oai:DiVA.org:ltu-59966DiVA: diva2:1040095
Conference
23rd International Wood Machining Seminar, Warsaw, Poland, 28-31 May 2017
Funder
ÅForsk (Ångpanneföreningen's Foundation for Research and Development), 239179
Available from: 2016-10-26 Created: 2016-10-26 Last updated: 2017-06-19Bibliographically approved

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fulltext(388 kB)20 downloads
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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
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  • en-US
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More languages
Output format
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