• Ei tuloksia

Two wavelengths from the IR range used were found to be respon-sive to the layer thickness of water–dilutable compounds. The IR range of the EM spectrum also offered reference wavelengths for data normalization. These discovered wavelengths were then used to develop a practical method for layer thickness measurement.

Even though the method was developed with image data, it can also be scaled down for a line or a spot.

The Lambert–Beer law was found to be limited to layer thickness measurement within the thickness recommendations of compound manufacturers. Thus, an empirical third–order polynomial model was developed to obtain the required dynamic range for the mea-surement. The Lambert–Beer law could probably also have been customized using external terms to obtain a greater thickness range, but this was not tested because the empirical model was already seen to be appropriate.

Discussion

The method was also successfully extended from adhesives to other compounds due to their common diluter, water. This in-creases the number of possible applications in the wood industry, from glued wood production to all–over surface finishing. Further-more, the method could be applied for other background materials than wood, if the determined requirements for a background mate-rial are fulfilled.

The main advantage of the method from a practical point of view is that it requires only two wavelengths to be observed. Hence, the sensors used could be simple and low–cost compared to hyper–

spectral ones and computation would be simple due to the small dimensional data, which is a solid basis for real–time processing.

These are important features when searching for a high–throughput production line implementation.

The ability to measure wet compounds is a great benefit com-pared to the techniques employed for dry ones. Wet measurement allows the repair of faulty parts or their rejection from the pro-cess, which could save production resources. The method was also found to be applicable to drying process monitoring because dry-ing is the loss of water in the compounds used and this affects to the absorption of near–infrared radiation. On the other hand, this sets a constant water concentration requirement for the compounds used.

8 Conclusion

In this work a wide spectral range imaging system with photolu-minescence imaging ability has been introduced. The developed setup can be widely customized for different measuring geometries and spatial resolutions. The system was benchmarked with dif-ferent tests in order to obtain knowledge about performance and the appropriate operational range. The most significant challenges were found in the UV region of the EM spectrum due to several reasons. However, the UV region could hold a great deal of in-formation about the samples under examination, which suggests directing more effort towards the challenges of UV range imaging in the future.

The wide spectral range imaging system was applied to two re-search cases in the context of the wood industry. The first rere-search case was the acquisition of a public spectral image database of sawn timber for research purposes. Sample handling and selection were to be performed so that the final database would correspond to data from real sawmill conditions and be as versatile as possible. As a result, the final database contains approximately 44 million spec-tra, which connect spectral information over the UV–VIS–IR range pixel–wise. According to the performed analysis it was confirmed that the database provides possibility to access the spatial distribu-tions of wood properties and compounds.

The second research case was the development of a practical method for adhesive layer thickness measurement. Key wavelengths associated with layer thickness were determined and used to derive a model which requires the monitoring of only two wavelengths.

Furthermore, the key wavelengths were the absorption peaks of water, which allowed the extension of the method to other water–

diluted compounds as well. This feature offers considerable possi-bilities for the method because nowadays water is a common diluter in industrial and surface finishing compounds.

Bibliography

[1] J. Antikainen, T. Hirvonen, J. Kinnunen, and M. Hauta-Kasari, “Heartwood detection for Scotch pine by fluorescence image analysis,”Holzforschung66,877–881 (2012).

[2] M. Vilaseca, B. Schael, X. Delpueyo, E. Chorro, E. Perales, T. Hirvonen, and J. Pujol, “Repeatability, reproducibility, and accuracy of a novel pushbroom hyperspectral system,”Color Research & Application(2013).

[3] S. Tsuchikawa, “A review of recent near infrared research for wood and paper,” Applied Spectroscopy Reviews42, 43–71 (2007).

[4] B. Leblon, O. Adedipe, G. Hans, A. Haddadi, S. Tsuchikawa, J. Burger, R. Stirling, Z. Pirouz, K. Groves, J. Nader, and A. LaRocque, “A review of near-infrared spectroscopy for monitoring moisture content and density of solid wood,”The Forestry Chronicle89,595–606 (2013).

[5] O. Hagman, On reflections of wood: wood quality features mod-elled by means of multivariate image projections to latent structures in multispectral images, PhD thesis (Lule˚a University of Tech-nology, Skellefte˚a, Sweden, 1996).

[6] H. Kauppinen, Development of a color machine vision method for wood surface inspection, PhD thesis (University of Oulu, Oulu, Finland, 1999).

[7] P. Duncker and H. Spiecker, “Detection and classification of Norway spruce compression wood in reflected light by means of hyperspectral image analysis,”IAWA Journal30,59–

70 (2009).

[8] P. K. Lebow, C. C. Brunner, A. G. Maristany, and D. A. But-ler, “Classification of wood surface features by spectral re-flectance,”Wood and Fiber Science28,74–90 (1996).

[9] S. Tsuchikawa, K. Inoue, J. Noma, and K. Hayashi, “Applica-tion of near-infrared spectroscopy to wood discrimina“Applica-tion,”

Journal of Wood Science49,29–35 (2003).

[10] K. Pandey and A. Pitman, “FTIR studies of the changes in wood chemistry following decay by brown-rot and white-rot fungi,” International Biodeterioration & Biodegradation 52,151–

160 (2003).

[11] B. Mohebby, “Attenuated total reflection infrared spec-troscopy of white-rot decayed beech wood,” International Biodeterioration & Biodegradation55,247–251 (2005).

[12] A. Naumann, M. Navarro-Gonz´alez, S. Peddireddi, U. K ¨ues, and A. Polle, “Fourier transform infrared microscopy and imaging: Detection of fungi in wood,” Fungal Genetics and Biology42,829–835 (2005).

[13] B. K. Via, C.-L. So, L. G. Eckhardt, T. F. Shupe, L. H. Groom, and M. Stine, “Response of near infrared diffuse reflectance spectra to blue stain and wood age,” Journal of Near Infrared Spectroscopy16,71–74 (2008).

[14] J. B. Hauksson, G. Bergqvist, U. Bergsten, M. Sj ¨ostr ¨om, and U. Edlund, “Prediction of basic wood properties for Nor-way spruce. Interpretation of near infrared spectroscopy data using partial least squares regression,”Wood Science and Tech-nology35,475–485 (2001).

[15] S. S. Kelley, T. G. Rials, R. Snell, L. H. Groom, and A. Sluiter,

“Use of near infrared spectroscopy to measure the chemical and mechanical properties of solid wood,” Wood Science and Technology38,257–276 (2004).

Bibliography

[16] T. Fujimoto, Y. Kurata, K. Matsumoto, and S. Tsuchikawa,

“Feasibility of near-infrared spectroscopy for on-line grading of sawn lumber,”Applied Spectroscopy64,92–99 (2010).

[17] T.-F. Yeh, H.-M. Chang, and J. F. Kadla, “Rapid prediction of solid wood lignin content using transmittance near-infrared spectroscopy,” Journal of Agricultural and Food Chemistry 52, 1435–1439 (2004).

[18] F. S. Poke, J. K. Wright, and C. A. Raymond, “Predicting extractives and lignin contents in Eucalyptus globulus using near infrared reflectance analysis,” Journal of Wood Chemistry and Technology24,55–67 (2004).

[19] A. Terdwongworakul, V. Punsuwan, W. Thanapase, and S. Tsuchikawa, “Rapid assessment of wood chemical proper-ties and pulp yield of Eucalyptus camaldulensis in Thailand tree plantations by near infrared spectroscopy for improving wood selection for high quality pulp,”Journal of Wood Science 51,167–171 (2005).

[20] P. D. Jones, L. R. Schimleck, G. F. Peter, R. F. Daniels, and A. Clark III, “Nondestructive estimation of wood chemical composition of sections of radial wood strips by diffuse re-flectance near infrared spectroscopy,” Wood Science and Tech-nology40,709–720 (2006).

[21] L. Donaldson, K. Radoti´c, A. Kalauzi, D. Djikanovi´c, and M. Jeremi´c, “Quantification of compression wood severity in tracheids of Pinus radiata D. Don using confocal fluorescence imaging and spectral deconvolution,”Journal of Structural Bi-ology169,106–115 (2010).

[22] V. Piuri and F. Scotti, “Design of an automatic wood types classification system by using fluorescence spectra,”Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on40,358–366 (2010).

[23] S.-Y. Yang, Y. Han, Y.-S. Chang, K.-M. Kim, I.-G. Choi, and H. Yeo, “Moisture Content Prediction Below and Above Fiber Saturation Point by Partial Least Squares Regression Analysis on Near Infrared Absorption Spectra of Korean Pine,” Wood and Fiber Science45,415–422 (2013).

[24] L. Thygesen and S. Lundqvist, “NIR measurement of mois-ture content in wood under unstable temperamois-ture conditions.

Part 1. Thermal effects in near infrared spectra of wood,” Jour-nal of Near Infrared Spectroscopy8,183–189 (2000).

[25] M. L. Selbo,Adhesive bonding of wood(US Department of Agri-culture, Washington DC, USA, 1975).

[26] R. A. Mbachu and T. G. Congleton, “Spectroscopic monitor-ing of resin-application prior to assembly of composite wood veneer product,” (2005), US Patent 6,942,826.

[27] J. Larsson, K. Thavelin, S. R ¨onnb¨ack, T. Lagerb¨ack, and T. Sandin, “Apparatus, method and system for detecting the width and position of adhesives applied to a substrate,”

(2005), WO Patent 2,005,087,460.

[28] W. F. Huck, “Electro–optical devide for measuring thick-nesses,” (1956), US Patent 2,773,412.

[29] N. K. Edwards and M. W. Gorden, “Glue detection system,”

(1987), US Patent 4,704,603.

[30] J. T. May and E. A. Casacia, “Measurement of the thickness of thin films,” (1989), US Patent 4,841,156.

[31] O. Hagman, “Multivariate prediction of wood surface fea-tures using an imaging spectrograph,”Holz als Roh-und Werk-stoff55,377–382 (1997).

[32] J. Nystr ¨om and O. Hagman, “Real-time spectral classification of compression wood inPicea abies,” Journal of Wood Science 45,30–37 (1999).

Bibliography

[33] C. M. Pieters, J. Boardman, B. Buratti, A. Chatterjee, R. Clark, T. Glavich, R. Green, J. Head, P. Isaacson, E. Malaret, T. Mc-Cord, J. Mustard, N. Petro, C. Runyon, M. Staid, J. Sunshine, L. Taylor, S. Tompkins, P. Varanasi, and M. White, “The Moon mineralogy mapper (M3) on Chandrayaan-1,”Current Science 96,500–505 (2009).

[34] R. L. Easton Jr, K. T. Knox, and W. A. Christens-Barry, “Mul-tispectral imaging of the Archimedes palimpsest,” inApplied Imagery Pattern Recognition Workshop, 2003. Proceedings. 32nd (IEEE, 2003), pp. 111–116.

[35] M. Kim, Y. Chen, and P. Mehl, “Hyperspectral reflectance and fluorescence imaging system for food quality and safety,”

Transactions of the American Society of Agricultural Engineers44, 721–730 (2001).

[36] K. Heia, A. H. Sivertsen, S. K. Stormo, E. Elvevoll, J. P.

Wold, and H. Nilsen, “Detection of nematodes in cod (Gadus morhua) fillets by imaging spectroscopy,”Journal of Food Sci-ence72,E011–E015 (2007).

[37] G. Vane, R. O. Green, T. G. Chrien, H. T. Enmark, E. G.

Hansen, and W. M. Porter, “The airborne visible/infrared imaging spectrometer (AVIRIS),” Remote Sensing of Environ-ment44,127–143 (1993).

[38] J. Antikainen, M. Hauta-Kasari, J. Parkkinen, and T. Jaaske-lainen, “Using two line scanning based spectral cameras si-multaneously in one measurement process to create wider spectral area from the measured target,” inIEEE International Workshop on Imaging Systems and Techniques - IST 2007.(IEEE, 2007), pp. 1–5.

[39] M. E. Klein, B. J. Aalderink, R. Padoan, G. De Bruin, and T. A.

Steemers, “Quantitative hyperspectral reflectance imaging,”

Sensors8,5576–5618 (2008).

[40] Spectral Imaging Ltd., “Datasheet: AisaFENIX hyperspectral sensor,” (2012).

[41] International Standard, “ISO 21348: Space environment (nat-ural and artificial) – Process for determining solar irradi-ances,” (2007).

[42] H.-C. Lee, Introduction to Color Imaging Science (Cambridge University Press, Cambridge, UK, 2005).

[43] M. Bass, Handbook of optics. Vol. 2, Devices, measurements, and properties(McGraw-Hill, New York, USA, 1995).

[44] J. W. Robinson, E. M. S. Frame, and G. M. Frame II, Un-dergraduate instrumental analysis (Marcel Dekker, New York, USA, 2005).

[45] N. Hagen and M. W. Kudenov, “Review of snapshot spectral imaging technologies,” Optical Engineering 52, 90901–90901 (2013).

[46] T. S. Hyvarinen, E. Herrala, and A. Dall’Ava, “Direct sight imaging spectrograph: a unique add-on component brings spectral imaging to industrial applications,” in Photonics West’98 Electronic Imaging (International Society for Optics and Photonics, 1998), pp. 165–175.

[47] G. Blasse and B. Grabmaier, Luminescent materials, Vol. 44, (Springer, Berlin, Germany, 1994).

[48] J. Mutanen, Fluorescent Colors, PhD thesis (University of Joen-suu, JoenJoen-suu, Finland, 2004).

[49] M. Ruiz-Urbieta, E. M. Sparrow, and E. R. G. Eckert, “Meth-ods for Determining Film Thickness and Optical Constants of Films and Substrates,” Journal of Optical Society of America61, 351 (1971).

[50] R. M. A. Azzam, A.-R. M. Zaghloul, and N. M.

Bashara, “Polarizer–surface–analyzer null ellipsometry for

Bibliography

film–substrate systems,” Journal of Optical Society of America 65,1464 (1975).

[51] K. Matsuda and T. Eiju, “Interferometric determination of film thickness and absolute fringe order: a new method,” Ap-plied Optics25,2641 (1986).

[52] K. F. McCarty, “Raman scattering as a technique of measur-ing film thickness: interference effects in thin growmeasur-ing films,”

Applied Optics26,4482 (1987).

[53] E. J. Hutchinson, D. Shu, F. LaPlant, and D. Ben-Amotz,

“Measurement of Fluid Film Thickness on Curved Surfaces by Raman Spectroscopy,”Applied Spectroscopy49,1275 (1995).

[54] M. A. Gaon, “Detection and measurement of cold emulsion adhesives applied to a substrate,” (2001), US Patent 6,281,500.

[55] J. I. Amalvya, C. A. Lasquibara, R. Arizagab, H. Rabalb, and M. Trivib, “Application of dynamic speckle interferometry to the drying of coatings.,”Progress in Organic Coatings42,89–99 (2001).

[56] B. F. Taylor, “System and method for the on-line measurement of glue application rate on a corrugator,” (2002), US Patent 6,470,294 B1.

[57] R. A. Mbachu and T. G. Congleton, “Methods for monitoring resin-loading of wood materials and engineered wood prod-ucts,” (2005), US Patent 6,846,447 B2.

[58] S. Otsuki, K. Tamada, and S.-I. Wakida, “Two–dimensional thickness measurements based on internal reflection ellip-sometry,”Applied Optics44,1410 (2005).

[59] D. Pristinski, V. Kozlovslaya, and S. A. Sukhishvili, “Deter-mination of film thickness and refractive index in one mea-surement of phase–modulated ellipsometry,” Journal of Opti-cal Society of America23,2639 (2006).

[60] J. J. Cowan and A. G. Landers, “Method using NIR spec-troscopy to monitor components of engineered wood prod-ucts,” (2007), US Patent 7,279,684.

[61] G. Scarel, J.-S. Na, B. Gong, and G. N. Parsons, “Phonon Response in the Infrared Region to Thickness of Oxide Films Formed by Atomic Layer Deposition,”Applied Spectroscopy64, 120–126 (2010).

[62] V. Lauria, J. Gillen, and R. McKinley, “Adhesive detection methods,” (2012), US Patent 8,313,799.

[63] Fraunhofer-Gesellschaft, “Research news 3: Effective thermal insulation with wood foam,” (2014).

[64] F. Carvalheiro, L. C. Duarte, and F. M. G´ırio, “Hemicellulose biorefineries: a review on biomass pretreatments,” Journal of Scientific & Industrial Research67,849–864 (2008).

[65] S. Liu, T. E. Amidon, R. C. Francis, B. V. Ramarao, Y.-Z. Lai, and G. M. Scott, “From forest biomass to chemicals and energy; Biorefinery initiative in New York State,” Industrial Biotechnology2, 113–120 (2006).

[66] M. Schwanninger, J. C. Rodrigues, and K. Fackler, “A review of band assignments in near infrared spectra of wood and wood components,” Journal of Near Infrared Spectroscopy 19, 287 (2011).

[67] C. D. Elvidge, “Visible and near infrared reflectance charac-teristics of dry plant materials,”Remote Sensing11,1775–1795 (1990).

[68] J. Soukupova, B. Rock, and J. Albrechtova, “Spectral charac-teristics of lignin and soluble phenolics in the near infrared – a comparative study,”International Journal of Remote Sensing 23,3039–3055 (2002).

Bibliography

[69] J. Nystr ¨om, L. Axrup, and E. Dahlquist, “Long-term eval-uation of on-line sensors for determination of moisture in biomass,” (2002), V¨armeforsk, Sweden.

[70] L. Axrup, K. Markides, and T. Nilsson, “Using miniature diode array NIR spectrometers for analysing wood chips and bark samples in motion,”Journal of Chemometrics14,561–572 (2000).

[71] C.-L. So, B. K. Via, L. H. Groom, L. R. Schimleck, T. F. Shupe, S. S. Kelley, and T. G. Rials, “Near infrared spectroscopy in the forest products industry,”Forest Products Journal54,6–16 (2004).

[72] A. Thumm, M. Riddell, B. Nanayakkara, J. Harrington, and R. Meder, “Near infrared hyperspectral imaging applied to mapping chemical composition in wood samples,”Journal of Near Infrared Spectroscopy18,507 (2010).

[73] T. Fujimoto, T. Numa, H. Kobori, and S. Tsuchikawa, “Visual-isation of spatial distribution of moisture content and basic density using near-infrared hyperspectral imaging method in sugi (Cryptomeria japonica),” International Wood Products Journal(2014).

[74] S. Tsuchikawa, K. Hayashi, and S. Tsutsumi, “Nondestructive measurement of the subsurface structure of biological ma-terial having cellular structure by using near-infrared spec-troscopy,”Applied Spectroscopy50,1117–1124 (1996).

[75] S. Tsuchikawa and S. Tsutsumi, “Directional characteristics model and light-path model for biological material having cellular structure,”Applied Spectroscopy53,233–240 (1999).

[76] S. Tsuchikawa and S. Tsutsumi, “Analytical characterization of reflected and transmitted light from cellular structural ma-terial for the parallel beam of NIR incident light,” Applied Spectroscopy53,1033–1039 (1999).

[77] P. Kubelka and F. Munk, “Ein Beitrag zur Optik der Far-banstriche,” in Zeitschrift f ¨ur technische Physik, Vol. 12 (1931), pp. 593–601.

[78] S. Tsuchikawa, M. Torii, and S. Tsutsumi, “Directional char-acteristics of near infrared light reflected from wood,” Holz-forschung55,534–540 (2001).

[79] S. Tsuchikawa, “Non-traditional application of time-of-flight near-infrared spectroscopy to biological material having cel-lular structure,”Analytical Sciences17,1463–1466 (2001).

[80] Spectral Imaging Ltd., “Datasheet: Imspector VIS & VNIR,”

(2013).

[81] Spectral Imaging Ltd., “Datasheet: Imspector NIR & SWIR,”

(2013).

[82] Spectral Imaging Ltd., “Datasheet: Imspector UV,” (2009).

[83] Spectral Imaging Ltd., “Test Report: Imspector V10E,” (2006).

[84] Spectral Imaging Ltd., “Test Report: Imspector N25E,” (2009).

[85] Spectral Imaging Ltd., “Test Report: Imspector UV4E,”

(2009).

[86] L. Karlman, T. M ¨orling, and O. Martinsson, “Wood Den-sity, Annual Ring Width and Latewood Content in Larch and Scots Pine,”Eurasian Journal of Forest Research8,91–96 (2005).

[87] W. T. Simpson, Chap 12 Drying and control of moisture content and dimensional changes in The Encyclopedia of Wood (Skyhorse Publishing Inc., New York, USA, 2013).

[88] A. Field, Discovering statistics using SPSS (and sex and drugs and rock n roll)(SAGE Publications Ltd, London, UK, 2009).

[89] A. Buades, B. Coll, and J.-M. Morel, “A review of image denoising algorithms, with a new one,”Multiscale Modeling &

Simulation4,490–530 (2005).

Bibliography

[90] R. R. Shannon and J. C. Wyant, Applied Optics and Optical Engineering(Academic Press Inc., New York, USA, 1983).

[91] H. H. Willard, L. L. Merritt, J. A. Dean, and F. A. Settle, Instru-mental methods of analysis(Wadsworth, Belmont, USA, 1988).

[92] R. J. Marks, Handbook of Fourier analysis & its applications (Ox-ford University Press, London, UK, 2009).

[93] G. Yang, C. V. Stewart, M. Sofka, and C.-L. Tsai, “Registration of challenging image pairs: Initialization, estimation, and de-cision,” Pattern Analysis and Machine Intelligence, IEEE Trans-actions on29,1973–1989 (2007).

[94] C. V. Stewart, C.-L. Tsai, and B. Roysam, “The dual-bootstrap iterative closest point algorithm with application to retinal image registration,”Medical Imaging, IEEE Transactions on22, 1379–1394 (2003).

[95] ˚A. Rinnan, F. V. D. Berg, and S. B. Engelsen, “Review of the most common pre-processing techniques for near-infrared spectra,” TrAC Trends in Analytical Chemistry 28, 1201–1222 (2009).

[96] J. X. Wu, S. Rehder, F. van den Berg, J. M. Amigo, J. M.

Carstensen, T. Rades, C. S. Leopold, and J. Rantanen, “Chemi-cal imaging and solid state analysis at compact surfaces using UV imaging,” International Journal of Pharmaceutics 477, 527–

535 (2014).

[97] K. H. Norris and A. M. C. Davies, “Examining diffuse re-flection and transmission spectra more thoroughly: Part 1.

Instrument noise,”Spectroscopy Europe23,24–27 (2011).

[98] M. F. Modest, Radiative heat transfer(Academic Press, Oxford, UK, 2013).

[99] R. Kane and H. Sell, Revolution in lamps: a chronicle of 50 years of progress(The Fairmont Press Inc., Lilburn, USA, 2001).

[100] Z. Al-Ameen, G. Sulong, and M. G. M. Johar, “A comprehen-sive study on fast image deblurring techniques,”International Journal of Advanced Science and Technology44(2012).

Publications of the University of Eastern Finland Dissertations in Forestry and Natural Sciences

Publications of the University of Eastern Finland Dissertations in Forestry and Natural Sciences

Tapani Hirvonen

A Wide Spectral Range Imaging System

- Applications in Wood Industry

This study introduces a new wide spectral range imaging system with photoluminescence imaging capabil-ity. The system is benchmarked and applied to two research cases in the context of the wood industry. The first research case is the acquisition of a public spectral image database of sawn timber which potential is demonstrated with an analysis examples. The second research case is the development of a non-de-structive method for layer thickness measurement of freshly applied water-dilutable compounds.

dissertations| No 173 | Tapani Hirvonen | A Wide Spectral Range Imaging System - Applications in Wood Industry

Tapani Hirvonen A Wide Spectral Range

Imaging System

- Applications in Wood Industry