Wood species identification using terahertz time-domain spectroscopy

Abstract

A new method for wood identification using terahertz (THz) time-domain spectroscopy (TDS) is presented. THz-TDS technology is an emerging method of spectral analysis method that shows great advantages in wood non-destructive testing. Wood is opaque in the optical and near infrared spectrum, and relatively transparent in the THz band. In this experiment, four wood species (Pinus densiflora, Pinus sylvestris, Pseudotsuga menziesii, and Cunninghamia lanceolata) were selected as samples. Optical parameters such as absorption coefficient and refractive index of the measured samples can be extracted from THz time-domain spectra. Principal component analysis was introduced to reduce the dimensionality of the THz spectral data of the wood. The principal component score matrix of the wood was obtained and used as a characteristic matrix. A wood classification model was established using a support vector machine. The experimental results showed that THz-TDS had excellent performance in wood recognition. This research lays a theoretical and application foundation for the application of THz technology in the field of wood detection and recognition. It also provides a new direction and technical scheme in the wood identification field.