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Estimating birch veneer (Betula pendula Roth) moisture content using infrared technology

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Abstract

The potential of infrared (IR) technology in estimating the moisture content (MC) of birch (Betula pendula Roth) veneer was investigated. A total of 56 birch veneer sheets (42 × 130 cm2) were dried with a convective type laboratory-scale veneer dryer at drying times ranging from 1 to 6 min at 1 min intervals. After drying, IR data were recorded and the veneer sheets were sawn into 100 × 100 mm2 pieces. IR data were averaged over the same area and then the true MC and density values were assessed gravimetrically. The dependency between temperature and MC was found to be non-linear and between temperature and density there was no dependency. The relationship between temperature and MC was modeled with a neural network and a Gaussian model. Both model types gave similar results. At a true MC below 10 %, the root mean square error of prediction (RMSE) was 1.5 % for the 100 × 100 mm2 pieces and 1.2 %, for the larger veneer sheets, whereas at higher MC (above 10 %), the RMSE increased to 2.6 % for the 100 × 100 mm2 pieces and 1.9 % for the sheets. It was observed that the IR measurement should be taken within 5 s, since after that the RMSE increased rapidly. Based on the results of this study, it was concluded that veneer MC can be estimated with reasonably good accuracy using IR technology.

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References

  • Adedipe OE, Dawson-Andoh B (2008) Predicting moisture content of yellow-poplar (Liriodendrum tulipifera L.) veneer using near infrared spectroscopy. Forest. Prod J 58(4):28–33

    CAS  Google Scholar 

  • Atkins JW (1983) Using thermography to correct wet streaks. Tappi J 66(8):96

    Google Scholar 

  • Bishop CM (1995) Neural networks for pattern recognition. Department of Computer Science and Applied Mathematics Aston University Birmingham, UK. Clarendon Press, Oxford

  • Bos M, Bos A, van der Linden WE (1993) Data processing by neural networks in quantitative chemical analysis. Analyst 118:323–328

  • Bowyer LJ, Shmulsky R, Haygreen G (2003) Forest products and wood science. An introduction, 4th edn. A Blackwell publishing company, Iowa, p 554

  • Christiansen AW (1990) How overdrying wood reduces its bonding to phenol-formaldehyde adhesives: a critical review of the literature. Part I physical responses. Wood Fiber Sci 22:441–459

    CAS  Google Scholar 

  • Chwif L, Barretto P, Paul RJ (2000) On simulation model complexity. In: Proceedings of the 2000 Winter Simulation Conference, vol 1, pp 449–455

  • Defo M, Taylor MA, Bond B (2007) Determination of moisture content and density of fresh sawn red oak lumber by near infrared spectroscopy. Forest Prod J 57(5):68–72

    CAS  Google Scholar 

  • Fike GM, Abedi J, Benerjee S (2004) Imaging the drying of surfaces by infrared thermography. Ind Eng Chem Res 43(15):4178–4181

    Article  CAS  Google Scholar 

  • Fischer M, Nyfors E, Vainikainen P (1996) On the permittivity of wood and the on-line measurement of veneer sheets. In: Kraszewski A (ed) Microwave aquametry. IEEE Press, New York, pp 347–354

    Google Scholar 

  • Goodacre R, Neal MJ, Kell DB (1996) Quantitative analysis of multivariate data using artificial neural networks: a tutorial review and applications to the deconvolution of pyrolysis mass spectra. Zbl Bakt 284:516–539

    Article  CAS  Google Scholar 

  • Hagan MT, Menhaj MB (1994) Training feed-forward networks with the Marquardt algorithm. IEEE Trans Neural Networks 5(6):989–993

    Article  CAS  PubMed  Google Scholar 

  • Haykin S (1999) Neural networks, a comprehensive foundation, 2nd edn. Prentice-Hall Inc., USA

    Google Scholar 

  • Hellier C (2001) Handbook of nondestructive evaluation. McGraw-Hill, US, p 594

    Google Scholar 

  • Hojjatie B, Abedi J, Coffin DW (2001) Quantitative determination of in-plane moisture distribution in paper by infrared thermography. Tappi J 84(5):71

    CAS  Google Scholar 

  • Honma C (1982) Infrared thermography. An aid to solving paper machine moisture profile problems. JPN Tappi 36(1):109–111

    Article  Google Scholar 

  • James WL (1963) Electric moisture meters for wood. Forest Products Laboratory, USA

    Google Scholar 

  • James WL (1988) Electric moisture meters for wood. In: General Technical report. Madison, WI US Department of Agriculture, Forest Service, Forest Products Laboratory, p 17

  • Jones PD, Schimleck LR, Daniels RF, Clark A, Purnell RC (2008) Comparison of Pinus taeda L. whole-tree wood property calibrations using diffuse reflectance near infrared spectra obtained using a variety of sampling options. Wood Sci Technol 42(5):358–400

    Article  Google Scholar 

  • Kiiskinen HT, Kukkonen HK, Pakarinen PI, Laine AJ (1997) Infrared thermography examination of paper structure. Tappi J 80(4):159–162

    CAS  Google Scholar 

  • López G, Basterra LA, Acuña L (2013) Estimation of wood density using infrared thermography. Constr Build Mater 42:29–32

    Article  Google Scholar 

  • Marra AA (1992) Technology of wood bonding. Springer, Principles in Practice

    Google Scholar 

  • Nyfors E (2000) Industrial microwave sensors–a review. Subsurf Sens Technol Appl 1(1):2000

    Article  Google Scholar 

  • So CL, Via KB, Groom HL, Schimleck RL, Shupe FT, Kelley SS, Rials GT (2004) Near Infrared spectroscopy in the forest products industry. Forest Product J. 54(3):6–17

    Google Scholar 

  • Stuart HB (2004) Infrared spectroscopy: fundamentals and applications. Wiley. Sydney, p 244 (ISBN 0-470-85427-8)

  • Swierenga H, Wülfert F, Noord OE, Weijer AP, Smilde AK, Buydens LMC (2000) Development of robust calibration models in near infra-red spectrometric applications. Anal Chim Acta 411:121–135

    Article  CAS  Google Scholar 

  • Thygesen LG, Lundqvist SO (2000) NIR measurement of moisture content in wood under unstable temperature conditions. Part 1: thermal effects in near infrared spectra of wood. J Near Infrared Spectrosc 8(3):183–189

    Article  CAS  Google Scholar 

  • Tsuchikawa S (2007) A review of recent near infrared research for wood and paper. Appl Spectrosc Rev 42(43–71):2007

    Google Scholar 

  • Vainikainen P, Nyfors E, Fischer M (1987) Radiowave sensor for measuring the properties of dielectric sheets: application to veneer moisture content and mass per unit area measurement. In: IEEE Transactions on instrumentation and measurement. vol 36(4)

  • Vickery DE, Luce JE, Atkins JW (1978) Infrared thermography–an aid to solving paper machine moisture profile problems. Tappi J 61(12):17–20

    Google Scholar 

  • Yan X, Su X (2009) Linear regression analysis: theory and computing. World Scientific Publishing Co

  • Zavarin E, Jones SG, Cool LG (1990) Analysis of solid wood surfaces by diffuse reflectance infrared fourier-transform (DRIFT) spectroscopy. J Wood Chem Technol 10(4):495–513

    Article  CAS  Google Scholar 

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Acknowledgments

The authors would like to acknowledge the financial assistance provided by the Energy Efficient Wood Processing and Machining project. This project forms part of the Multidisciplinary Institute of Digitalisation and Energy (MIDE), a research program on digitalisation and energy technology at Aalto University, that carries out important long-term projects aimed at creating high-level expertise, strengthening teaching and increasing the competitiveness of Finnish business and industry. Special thanks are also extended to Infradex Oy (Vantaa, Finland) for providing infrared camera and valuable advice.

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Antikainen, T., Rohumaa, A., Bulota, M. et al. Estimating birch veneer (Betula pendula Roth) moisture content using infrared technology. Eur. J. Wood Prod. 73, 617–625 (2015). https://doi.org/10.1007/s00107-015-0944-7

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  • DOI: https://doi.org/10.1007/s00107-015-0944-7

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