Advertisement

European Journal of Wood and Wood Products

, Volume 77, Issue 2, pp 235–247 | Cite as

Potential of microwave scanning for determining density and tension strength of four European hardwood species

  • Andreas WeidenhillerEmail author
  • Peter Linsenmann
  • Christian Lux
  • Franka Brüchert
Original
  • 24 Downloads

Abstract

As an effect of changing forest management—away from softwood monocultures to more robust mixed stands—the availability of hardwood on the European timber market increases. Thus, a more diversified spectrum of hardwood products is required between the established uses in furniture and energy production. Glued timber products are a promising option in this respect. One important prerequisite for efficiently producing glued hardwood products is to establish hardwood strength grading. To this end, the current paper explored the potential of microwave scanning, stand-alone or combined with the measurement of dynamic stiffness, to estimate the tension strength of ash, beech, sweet chestnut and oak lamellas. In this preliminary study, combining microwave and dynamic stiffness measurement showed much potential for hardwood strength grading for all four species; for beech and sweet chestnut, coefficients of determination (\({r}^{2}\)) beyond 60% could be achieved, which is on a level with established softwood grading principles. For ash and oak, \({r}^{2}\approx 45\%\) was observed, which is acceptable for machine strength grading. The paper also considered measuring density using microwaves. Such a density measurement was found to be as accurate for hardwoods as for softwoods.

Notes

Acknowledgements

This study was conducted in the scope of the WoodWisdom-Net project European hardwoods for the building sector (EU Hardwoods) which was financed by Fachagentur Nachwachsende Rohstoffe e.V. (FNR) under grant number 22004114 in Germany and Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft (BMLFUW) under grant number 101003 in Austria.

References

  1. Aichholzer A, Arthaber H, Schuberth C, Mayer H (2013) Non-destructive evaluation of grain angle, moisture content and density of spruce with microwaves. Eur J Wood Prod 71(6):779–786.  https://doi.org/10.1007/s00107-013-0740-1 CrossRefGoogle Scholar
  2. Bacher M (2008) Comparison of different machine strength grading principles. In: Gard WF, van de Kuilen JG (eds) End user’s needs for wood material and products. In: Proceedings of the conference in COST E53 quality control for wood and wood products, pp 183–193 http://www.coste53.net/downloads/Delft/Presentations/COSTE53-Conference_Delft_Bacher.pdf. Accessed 25 Jan 2019
  3. BMEL (2016) Ergebnisse der Bundeswaldinventur 2012 (Results of the federal forest inventory 2012) (In German), Berlin. https://www.bmel.de/SharedDocs/Downloads/Broschueren/Wald-Rohholzpotential-40Jahre.pdf. Accessed 21 Jan 2019
  4. BMEL (2017) Wald und Rohholzpotenzial der nächsten 40 Jahre: Ausgewählte Ergebnisse der Waldentwicklungs- und Holzaufkommensmodellierung 2013 bis 2052 (Forest and raw material potential for the next 40 years: selected results of modelling forest development and timber production 2013–2052) (In German), Berlin. https://www.bmel.de/SharedDocs/Downloads/Broschueren/ErgebnisseBWI2012.pdf. Accessed 21 Jan 2019
  5. Boström L (1994) Machine strength grading. Comparison of four different systems. SP Report nr. (1994:49). http://www.diva-portal.org/smash/get/diva2:961864/FULLTEXT01.pdf. Accessed 25 Jan 2019
  6. Canty A, Ripley BD (2017) boot: Bootstrap R (S-Plus) Functions. R package version 1.3–20. https://cran.r-project.org/web/packages/boot/. Accessed 25 Jan 2019
  7. Daval V, Pot G, Belkacemi M, Meriaudeau F, Collet R (2015) Automatic measurement of wood fiber orientation and knot detection using an optical system based on heating conduction. Opt Express 23(26):33529–33539.  https://doi.org/10.1364/OE.23.033529 CrossRefGoogle Scholar
  8. Denzler JK, Weidenhiller A (2014) New perspectives in machine strength grading: or how to identify a top rupture. In: Aicher S, Reinhardt H, Garrecht H (eds) Materials and joints in timber structures, vol 9. Springer, Netherlands, pp 761–771CrossRefGoogle Scholar
  9. Denzler JK, Weidenhiller A (2015) Microwave scanning as an additional grading principle for sawn timber. Eur J Wood Prod 73(4):423–431.  https://doi.org/10.1007/s00107-015-0906-0 CrossRefGoogle Scholar
  10. Denzler JK, Koppensteiner J, Arthaber H (2013) Grain angle detection on local scale using microwave transmission. Int Wood Prod J 4(2):68–74.  https://doi.org/10.1179/2042645313Y.0000000030 CrossRefGoogle Scholar
  11. Denzler JK, Lux C, Arthaber H (2014) Contactless moisture content and density evaluation of sawn timber using microwave transmission. Int Wood Prod J 5(4):200–206.  https://doi.org/10.1179/2042645314Y.0000000066 CrossRefGoogle Scholar
  12. Diebold R, Schleifer A, Glos P (2000) Machine grading of structural sawn timber from various softwood and hardwood species. In: Proceedings of the 12th International Symposium on Nondestructive Testing of Wood University of Western Hungary, Sopron, 13–15 September 2000Google Scholar
  13. Ehrhart T, Fink G, Steiger R, Frangi A (2016) Experimental investigation of tensile strength and stiffness indicators regarding European Beech timber. In: Eberhardsteiner J, Winter W, Fadai A (eds) WCTE 2016 e-book (Proceedings of the 2016 world conference on timber engineering, 22–25 August 2016, Vienna, Austria), pp 600–607 (ISBN 9783903024359)Google Scholar
  14. Ehrhart T, Steiger R, Frangi A (2018) A non-contact method for the determination of fibre direction of European beech wood (Fagus sylvatica L.). Eur J Wood Prod 76(3):925–935.  https://doi.org/10.1007/s00107-017-1279-3 CrossRefGoogle Scholar
  15. EN 14081-2 (2012) Timber structures—strength graded structural timber with rectangular cross section. Part 2: machine grading—additional requirements for initial type testing (EN 14081-2:2010 + A1:2012-11). https://shop.austrian-standards.at/action/en/public/details/462133/OENORM_EN_14081-2_2013_01_15. Accessed 25 Jan 2019
  16. EN 384 (2010) Structural timber—determination of characteristic values of mechanical properties and density. https://shop.austrian-standards.at/action/en/public/details/362300/OENORM_EN_384_2010_05_15. Accessed 25 Jan 2019
  17. EN 408 (2012) Timber structures—structural timber and glued laminated timber—determination of some physical and mechanical properties (EN 408:2010 + A1:2012-07). https://shop.austrian-standards.at/action/en/public/details/448783/DIN_EN_408_2012_10. Accessed 25 Jan 2019
  18. Firmanti A, Bachtiar ET, Surjokusumo S, Komatsu K, Kawai S (2005) Mechanical stress grading of tropical timbers without regard to species. J Wood Sci 51(4):339–347.  https://doi.org/10.1007/s10086-004-0661-z CrossRefGoogle Scholar
  19. Gil-Moreno D, Ridley-Ellis DJ (2015) Comparing usefulness of acoustic measurements on standing trees for segregation by timber stiffness. In: Ross RJ, Gonçalves R, Wang X (eds) Proceedings: 19th international nondestructive testing and evaluation of wood symposium, pp 378–385. https://www.napier.ac.uk/research-and-innovation/research-search/outputs/comparing-usefulness-of-acoustic-measurements-on-standing-trees-for-segregation-by-timber-1. Accessed 25 Jan 2019
  20. Hanhijärvi A, Ranta-Maunus A (2008) Development of strength grading of timber using combined measurement techniques. Report of the Combigrade-project—phase 2. https://www.vtt.fi/inf/pdf/publications/2008/P686.pdf. Accessed 25 Jan 2019 (ISBN 978-951-38-7106-2)
  21. Hunger F, van de Kuilen JG (2018) Slope of grain measurement: a tool to improve machine strength grading by detecting top ruptures. Wood Sci Technol 52(3):821–838.  https://doi.org/10.1007/s00226-018-1000-7 CrossRefGoogle Scholar
  22. IGN (2014) Résultats d’inventaire forestier—Résultats standards (campagnes 2009 à 2013) (standardized results of the forest inventory (campaigns 2009–2013)): Tome national version régions administratives, Saint-Mandé, France (In French). https://inventaire-forestier.ign.fr/IMG/pdf/RS_0913_FR_RA.pdf. Accessed 25 Jan 2019
  23. Kandler G, Lukacevic M, Füssl J (2016) An algorithm for the geometric reconstruction of knots within timber boards based on fibre angle measurements. Constr Build Mater 124:945–960.  https://doi.org/10.1016/j.conbuildmat.2016.08.001 CrossRefGoogle Scholar
  24. Kollmann F, Cote WA Jr (1984) Principles of wood science and technology, reprint. Springer, BerlinGoogle Scholar
  25. Koppensteiner J, Denzler JK, Weidenhiller A, Arthaber H, Leder N (2017) Method and apparatus for estimating the projection on a reference plane of the direction of extension of the fibres of a portion of a wooden plank (EP2829876 (B1))Google Scholar
  26. Kretschmann DE, Green DW (1999) Mechanical grading of oak timbers. J Mater Civ Eng 11(2):91–97.  https://doi.org/10.1061/(ASCE)0899-1561(1999)11:2(91) CrossRefGoogle Scholar
  27. Lukacevic M, Füssl J, Eberhardsteiner J (2015) Discussion of common and new indicating properties for the strength grading of wooden boards. Wood Sci Technol 49(3):551–576.  https://doi.org/10.1007/s00226-015-0712-1 CrossRefGoogle Scholar
  28. Lundgren N, Brännström M, Hagman O, Oja J (2007) Predicting the strength of norway spruce by microwave scanning: a comparison with other scanning techniques. Wood Fiber Sci 39(1):167–172Google Scholar
  29. Nocetti M, Brunetti M, Bacher M (2016) Efficiency of the machine grading of chestnut structural timber: prediction of strength classes by dry and wet measurements. Mater Struct 49(11):4439–4450.  https://doi.org/10.1617/s11527-016-0799-3 CrossRefGoogle Scholar
  30. Nyström J (2003) Automatic measurement of fiber orientation in softwoods by using the tracheid effect. Comput Electron Agric 41(1–3):91–99.  https://doi.org/10.1016/S0168-1699(03)00045-0 CrossRefGoogle Scholar
  31. Olsson A, Oscarsson J, Serrano E, Källsner B, Johansson M, Enquist B (2013) Prediction of timber bending strength and in-member cross-sectional stiffness variation on the basis of local wood fibre orientation. Eur J Wood Prod 71(3):319–333.  https://doi.org/10.1007/s00107-013-0684-5 CrossRefGoogle Scholar
  32. R Core Team (2018) R: A Language and Environment for Statistical Computing. https://www.R-project.org/. Accessed 25 Jan 2019
  33. Ravenshorst GJP (2015) Species independent strength grading of structural timber. Dissertation Thesis, Technische Universiteit DelftGoogle Scholar
  34. Şahin Kol H, Yalçın İ (2015) Predicting wood strength using dielectric parameters. BioResour.  https://doi.org/10.15376/biores.10.4.6496-6511 Google Scholar
  35. Schajer GS, Orhan FB (2005) Microwave non-destructive testing of wood and similar orthotropic materials. Subsurf Sens Technol Appl 6(4):293–313.  https://doi.org/10.1007/s11220-005-0014-z CrossRefGoogle Scholar
  36. Schajer GS, Orhan FB (2006) Measurement of wood grain angle, moisture content and density using microwaves. Holz Roh Werkst 64(6):483–490.  https://doi.org/10.1007/s00107-006-0109-9 CrossRefGoogle Scholar
  37. Schlotzhauer P, Wilhelms F, Lux C, Bollmus S (2018) Comparison of three systems for automatic grain angle determination on European hardwood for construction use. Eur J Wood Prod 76(3):911–923.  https://doi.org/10.1007/s00107-018-1286-z CrossRefGoogle Scholar
  38. Torgovnikov GI (1993) Dielectric properties of wood and wood-based materials. Springer series in wood science. Springer-Verlag, BerlinCrossRefGoogle Scholar
  39. van de Kuilen JG, Torno S (2014) Materialkennwerte von Eschenholz für den Einsatz in Brettschichtholz: Schlussbericht zum Vorhaben [Material characteristics of ash timber for use in glue laminated timber: final report], MunichGoogle Scholar
  40. Vega A, Dieste A, Guaita M, Majada J, Baño V (2012) Modelling of the mechanical properties of Castanea sativa Mill. structural timber by a combination of non-destructive variables and visual grading parameters. Eur J Wood Prod 70(6):839–844.  https://doi.org/10.1007/s00107-012-0626-7 CrossRefGoogle Scholar
  41. Viguier J, Jehl A, Collet R, Bleron L, Meriaudeau F (2015) Improving strength grading of timber by grain angle measurement and mechanical modeling. Wood Mater Sci Eng 10(1):145–156.  https://doi.org/10.1080/17480272.2014.951071 CrossRefGoogle Scholar
  42. Wang X (2013) Acoustic measurements on trees and logs: a review and analysis. Wood Sci Technol 47(5):965–975.  https://doi.org/10.1007/s00226-013-0552-9 CrossRefGoogle Scholar
  43. Zhou J, Shen J (2003) Ellipse detection and phase demodulation for wood grain orientation measurement based on the tracheid effect. Opt Lasers Eng 39(1):73–89.  https://doi.org/10.1016/S0143-8166(02)00041-6 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Holzforschung AustriaViennaAustria
  2. 2.Forstliche Versuchs-und Forschungsanstalt Baden-WürttembergFreiburgGermany

Personalised recommendations