Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
Real-time wood moisture-content determination using dual-energy X-ray computed tomography scanning
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.ORCID iD: 0000-0001-7270-1920
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.
Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology (NTNU), Ålesund, Norway.ORCID iD: 0000-0002-5869-2236
c Professor Emeritus of Building Materials, Stockholm, Sweden.
Show others and affiliations
2019 (English)In: Wood Material Science & Engineering, ISSN 1748-0272, E-ISSN 1748-0280Article in journal (Refereed) Epub ahead of print
Abstract [en]

The estimation of the pixel-wise distribution of the moisture content (MC) in wood using X-ray computed tomography (CT) requires two scans of the same wood specimen at different MCs, one of which is known. Image-processing algorithms are needed to compensate for the anisotropic distortion that wood undergoes as it dries. An alternative technique based on dual-energy CT (DECT) to determine MC in wood has been suggested by several authors. The purpose of the present study was to evaluate the hypothesis that DECT can be used for the determination of MC in real time. A method based on the use of the quotient between the linear attenuation coefficients (μ) at different acceleration voltages (the so-called quotient method) was used. A statistical model was created to estimate the MC in solid sapwood of Scots pine, Norway spruce and brittle willow. The results show a regression model with R2 > 0.97 that can predict the MC in these species with a RMSE of prediction of 0.07, 0.04 and 0.11 (MC in decimal format) respectively and at MC levels ranging from the green to the totally dry condition. Individual measurements of MC show an uncertainty of up to ±0.4. It is concluded that under the conditions prevailing in this study, and in studies referred to in this paper, it is not possible to measure MC with DECT.

Place, publisher, year, edition, pages
Taylor & Francis, 2019.
Keywords [en]
CT-scanning, dual-energy X-ray absorptiometry, wood drying, attenuation coefficient
National Category
Wood Science Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-75497DOI: 10.1080/17480272.2019.1650828ISI: 000480865200001OAI: oai:DiVA.org:ltu-75497DiVA, id: diva2:1342441
Available from: 2019-08-13 Created: 2019-08-13 Last updated: 2019-08-30
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

Open Access in DiVA

fulltext(1675 kB)9 downloads
File information
File name FULLTEXT01.pdfFile size 1675 kBChecksum SHA-512
e5dc5818f16641583dca54e3d4db5198c044c47856d9d9b20c71985aefc0c72f4142378d6c6563f0c68671bfb69d7ad0d1b308a64c5072fee07501e93b5c1bd0
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Couceiro, JoséLindgren, OweHansson, LarsSandberg, Dick
By organisation
Wood Science and Engineering
In the same journal
Wood Material Science & Engineering
Wood ScienceOther Mechanical Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 9 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 27 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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