Rapid Detection of Knot Defects on Wood Surface by Near Infrared Spectroscopy Coupled with Partial Least Squares Discriminant Analysis

Zhong Yang, Maomao Zhang, Kang Li, Ling Chen

Abstract


Natural defects, especially knots, on the surface of veneers have a great influence on the sorting and degradation of veneers. To realize rapid and accurate knot detection, a study on the possibility of detecting knots was carried out. Samples of poplar, eucalypt, and masson pine were used. The experiments mainly focused on the ability of using the models built with samples from one type of knot and normal wood to predict samples from a different type of knot and normal wood within the same wood species; and when only the samples from middle-sized knots and normal wood were used, whether or not the model based on one species could predict the samples from another species. The results showed that using the model built with small knots and normal wood to predict the larger knots and normal wood was not satisfactory, but the model based on large knots and normal wood can predict the samples from smaller knots and normal wood under a certain condition. When only the middle-sized knots and normal wood from the three species were used, the model built with eucalypt samples could predict the samples from poplar, and vice versa; however, the model built with masson pine samples could not predict the other two sample species, and vice versa.

Keywords


Rapid detection; Knot defects; Wood surface; Near infrared spectroscopy; Partial least squares discriminant analysis (PLS-DA)

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