Nondestructive evaluation of drying stress level on wood surface using near-infrared spectroscopy

Watanabe, Ken; Kobayashi, Isao; Saito, Shuetsu; Kuroda, Naohiro; Noshiro, Shuichi

doi:10.1007/s00226-012-0492-9

Cited by 17 publications

(12 citation statements)

References 25 publications

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“…They determined that cooling under relatively high humidity after drying improves the internal stress relief within kiln-dried rubberwood lumber (Hevea brasiliensis) during conditioning [41]. Watanabe et al [42] demonstrated that NIR could be used to predict drying stress levels to detect critical periods in drying [42]. While all the methods described demonstrated being able to measure drying stresses to some degree, no commercial system using these techniques is yet available at the time of writing.…”

Section: Measurement Of Drying Stressesmentioning

confidence: 99%

A Decade of Improved Lumber Drying Technology

Bond

Espinoza

2016

Curr Forestry Rep

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In this paper, we comprehensively review the relevant literature published from 2005 to 2016, focused on lumber drying and provide a summary of where we feel future research will focus. Drying is a critical part of most wood products manufacturing process, and the methods used and proper control are key to achieving the appropriate production level, quality, and costs. While a combination of drying methods may be used, most lumber is dried in a kiln at some point in the process. The most common commercial kilns can be classified as conventional, high temperature, and vacuum; however, there continues to be some interest in solar and compression drying. While no new drying technologies have been proposed, work has continued on improving the existing methods. Control of the drying process varies with the type of kiln used, the species being dried and the temperatures used in the process; however, it usually involves some type of measurement of the moisture content of the wood being dried. The development of new methods for controlling the drying process focuses on new ways to measure moisture content or moisture content variation, temperature drop across the load, and drying stresses. While wood quality can be defined differently by its various users, for example, industrial or end users, certain aspects of quality remain constant across these groups, such as minimizing warp, checks, and splits, and discoloration, and maintaining or enhancing mechanical properties. New schedules have been proposed to increase drying rate and improve drying quality. Methods to reduce drying defects and improve its quality have focused mainly on mechanical restraint to prevent warp, better understanding of defect formation, and pre-treatments to speed up the drying process or reduce final moisture content variation. Finally, concerns regarding the environmental impacts of wood drying, most importantly the high energy demands and emissions, have increased in importance as concerns about sustainability and health issues become more mainstream.

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Section: Measurement Of Drying Stressesmentioning

confidence: 99%

A Decade of Improved Lumber Drying Technology

Bond

Espinoza

2016

Curr Forestry Rep

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“…Even though the surface moisture content during drying is important to the final product quality, there has thus far not been a method to measure surface moisture content industrially. There have been academic examples of measuring surface moisture content measurement on small samples with near infrared (NIR), magnetic resonance and X-ray computed tomography scanning (Baettig et al 2006, Rosenkilde and Glover 2002, Watanabe et al 2011, Watanabe et al 2013, Wiberg and Morén 1999. Electrical resistivity has also been used (Yamamoto et al 2013).…”

Section: Introductionmentioning

confidence: 99%

A method to estimate wood surface moisture content during drying

Scheepers

Wiberg²,

Johansson

2017

Maderas, Cienc. tecnol.

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A method to estimate the surface moisture content below the fibre saturation point that is a function of the surface temperature, wet-and dry bulb temperatures, equilibrium moisture content, and fibre saturation point was evaluated. The method is based on the premise that the surface temperature is solely influenced by the surface moisture content and the climate that the surface is exposed to. The prediction model contends that the surface moisture content is equal to the fibre saturation point when the surface temperature is equal to the wet bulb temperature, and equal to the equilibrium moisture content when the surface temperature is equal to the dry bulb temperature, with a linear interpolation between those two points. The model thus predicts that the average moisture content of a thin piece of veneer can be predicted with fairly good accuracy. Also, when drying boards in a fast changing climate, e.g. fan reversals in industrial kilns, the surface temperature and surface moisture content should change as abruptly as the climate does. Additionally, the surface moisture content should correlate to the known drying phases, with a consistently high surface moisture content during the capillary phase when the wet line is close to the surface, and a quickly decreasing surface moisture content when the wet line moves into the wood during the transition to the diffusion phase. The prediction model was tested in these three scenarios and the results suggest that the basic premise is reasonable, and that the method is useful for surface moisture content estimation.

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“…As a nondestructive detection technology, NIR spectroscopy has been applied for several uses in wood research, for example, wood color (Yang et al 2012), basic density (Santos et al 2012), moisture content (Eom et al 2013), drying stress level (Ken et al 2013), and surface roughness (Zhang et al 2015). In addition, NIR spectroscopy has also been used to detect defects on the surface of veneers according to size (Yang et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Potential of Near-infrared Spectroscopy to Detect Defects on the Surface of Solid Wood Boards

et al. 2016

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Defects on the surface of solid wood boards directly affect their mechanical properties and product grades. This study investigated the use of near-infrared spectroscopy (NIRS) to detect and classify defects on the surface of solid wood boards. Pinus koraiensis was selected as the raw material. The experiments focused on the ability to use the model to sort defects on the surface of wood into four types, namely live knots, dead knots, cracks, and defect-free. The test data consisted of 360 NIR absorption spectra of the defect samples using a portable NIR spectrometer, with the wavelength range of 900 to 1900 nm. Three preprocessing methods were used to compare the effects of noise elimination in the original absorption spectra. The NIR discrimination models were developed based on partial least squares and discriminant analysis (PLS-DA), least squares support vector machine (LS-SVM), and backpropagation neural network (BPNN) from 900 to approximately 1900 nm. The results demonstrated that the BPNN model exhibited the highest classification accuracy of 97.92% for the model calibration and 97.50% for the prediction set. These results suggest that there is potential for the NIR method to detect defects and differentiate between types of defects on the surface of solid wood boards.

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Nondestructive evaluation of drying stress level on wood surface using near-infrared spectroscopy

Cited by 17 publications

References 25 publications

A Decade of Improved Lumber Drying Technology

A Decade of Improved Lumber Drying Technology

A method to estimate wood surface moisture content during drying

Potential of Near-infrared Spectroscopy to Detect Defects on the Surface of Solid Wood Boards

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