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Estimation of shrinkage coefficients in radial and tangential directions from CT images
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering. Faculty of Engineering and Natural Sciences, Norwegian University of Science and Technology (NTNU), Ålesund.ORCID iD: 0000-0002-5869-2236
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.ORCID iD: 0000-0001-7270-1920
Luleå University of Technology, Professional Support, IT-Service.ORCID iD: 0000-0003-0830-1070
Number of Authors: 32017 (English)In: Wood Material Science & Engineering, ISSN 1748-0272, E-ISSN 1748-0280, Vol. 12, no 4, p. 251-256Article in journal (Refereed) Published
Abstract [en]

The aim of the present work was to use the displacement information generated from the spatial alignment in order to compute wood shrinkage in the radial and tangential directions in computed tomography (CT) images, and to compare the results with those obtained with computer-aided design software on the same images. To estimate the shrinkage coefficients from tomography images, wood specimens in the green state, equilibrium moisture content 15% and 8% state and oven dry condition were scanned. Specimens were taken from Norway spruce and Scots pine logs. The root-mean-square-error calculations showed acceptable small differences between the two measuring methods, which means that the algorithm is a useful tool for estimating the shrinkage coefficients in radial and tangential direction from CT images. This provides an image processing tool to monitor the dimensional changes during the drying and heat treatment process. 

Place, publisher, year, edition, pages
Taylor & Francis, 2017. Vol. 12, no 4, p. 251-256
National Category
Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-60142DOI: 10.1080/17480272.2016.1249405ISI: 000402709800009Scopus ID: 2-s2.0-84997272329OAI: oai:DiVA.org:ltu-60142DiVA, id: diva2:1044520
Note

Validerad;2017;Nivå 2;2017-06-07(andbra)

Available from: 2016-11-03 Created: 2016-11-03 Last updated: 2019-05-07Bibliographically approved
In thesis
1. X-ray computed tomography to study moisture distribution in wood
Open this publication in new window or tab >>X-ray computed tomography to study moisture distribution in wood
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

X-ray computed tomography (CT) has been used as an analysing tool for different features in wood research since the beginning of the1980s, but it can also be used to study wood-water interactions in different ways, such as by determining wood moisture content (MC). The determination of wood MC with CT requires two CT images: one at the unknown moisture distribution and a second one at a known reference MC level, usually at oven-dry condition. The two scans are then compared, and the MC is calculated based on the differences between the images. If the goal is to determine the MC in local regions within the wood volume, e.g. when studying moisture gradients in wood drying, wood shrinkage must be taken into account during the data processing of the images. The anisotropy of wood shrinkage creates an obstacle, however, since the shrinkage is not uniform throughout the wood specimen. The technique is thus limited in two ways: it cannot measure MC in local regions and it cannot do it in real time.

The objective of this thesis was to study methods to overcome these two limitations. The work explores up to three different methods to estimate local MC from CT images in real time. The first method determines shrinkage for each pixel using digital image correlation (DIC) and is embedded in a broader method to estimate the MC, which verified against a reference. It involves several steps in different pieces of software, making it time-consuming and creating many sources of possible experimental errors. The determination of shrinkage within this method is further explored to enable the implementation of all steps in a unique piece of software. It is shown that it is possible to calculate MC through this method with a root mean square error of prediction of 1.4 percentage points for MC between 6 and 25%.

The second method studied succeeds in determining the MC distribution in research applied to wood drying, but the calculation of shrinkage differs from the previous method: instead of calculating shrinkage in the radial and tangential directions, it does so by using the displacement information generated from the spatial alignment of the CT images. Results show that the algorithm can provide consistent data of internal MC distribution of wood at the pixel level that entail continuing researching wood drying processes with an improvement in the accuracy of the MC determination. It represents an improvement regarding the first method because the calculation is fast and highly automatized in a single piece of software.

The third method studied is the application of dual energy CT (DECT) to moisture. DECT would provide means for MC calculation at the pixel level and, potentially, in real time, which would mean an important breakthrough in wood drying research. Previous research shows promising results, but its implementation in medical CT, the tool used throughout this work, has shown poor predicting ability. Nevertheless, further research is encouraged.

The work done in this thesis proves that it is possible to measure local distribution of MC in wood using CT with accuracy and precision. It also shows that further research could potentially provide a means for MC estimation in real time.

Place, publisher, year, edition, pages
Luleå tekniska universitet, 2019
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
National Category
Wood Science
Research subject
Wood Science and Engineering
Identifiers
urn:nbn:se:ltu:diva-73860 (URN)978-91-7790-382-6 (ISBN)978-91-7790-383-3 (ISBN)
Public defence
2019-09-12, Hörsal A (A193), Skellefteå, 09:00 (English)
Opponent
Supervisors
Available from: 2019-05-07 Created: 2019-05-07 Last updated: 2019-08-21Bibliographically approved

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Hansson, LarsCouceiro, JoséFjellner, Bengt-Arne

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