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

Abstract

A nondestructive technique for swiftly measuring the stress level of the surface of wood is proposed, which is important for process control in timber drying. Partial least squares (PLS) regression models for predicting surface-released strain (ε) were developed using NIR spectra obtained from Sugi (Cryptomeria japonica D. Don) samples during drying. The predictive ability of the models was evaluated by PLS analysis and by comparing NIR-predicted ε with laboratory-measured values. The PLS regression model using the NIR spectra pre-processed by MSC and second derivatives with a wavelength range of 2,000–2,220 nm showed good agreement with the measurement (R ² = 0.72). PLS analysis identified the wavelengths around 2,035 nm as making significant contributions to the prediction of ε. Orthogonal signal correction (OSC) was an effective pre-processing technique to reduce the number of factors required for the model using the wavelength range 1,300–2,500 nm. However, the predictive ability of the OSC-corrected model was not improved. Elapsed times to reach the maximum tensile stress (T _max) and the stress reversal point (T _rev) at the wood surface during drying were detected correctly for 75 % of the samples. The results show that NIR spectroscopy has potential to predict the drying stress level of the timber surface and to detect critical periods in drying, such as T _max and T _rev.