Prediction of wood moisture content based on THz time-domain spectroscopy

Abstract

A new method for predicting wood moisture content using terahertz (THz) time-domain spectroscopy (TDS) is presented in this paper. The THz wave is a promising method in measuring wood moisture content due to its sensitivity to water, impressive penetration ability in wood, and no destructive effect on wood interior. In this study, the selected wood, Douglas fir (Pseudotsuga menziesii), with different moisture content was studied. THz-TDS was used to extract the optical parameter of the sample. The THz refractive index and absorption coefficient spectrum of the wood were calculated. The first and second derivatives of the absorption coefficient spectrum were processed to obtain the first and second derivative spectra. The successive projections algorithm (SPA) was used to select the characteristic frequency for the THz absorption coefficient spectrum and its first and second derivative spectrum of the wood. A regression prediction model of wood moisture content was established by partial least squares regression (PLS). The results showed that the proposed model based on the second derivative spectrum had the best prediction effect for the moisture content of wood.