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Published on: June 10, 2017
Discriminant analyzing system for wood wastes using a visible-near-infrared chemometric imaging technique
Hikaru Kobori1, Hitoshi Yonenobu, Junichi Noma
1Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, Japan.
Abstract:
A new optical system was developed and applied to automated separation of wood wastes, using a combined technique of visible-near-infrared (Vis-NIR) imaging analysis and chemometrics. Three kinds of typical wood wastes were used, i.e., non-treated, impregnated, and plastic-film overlaid wood. The classification model based on soft independent modeling of class analogy (SIMCA) was examined using the difference luminance brightness of a sample. Our newly developed system showed a good/promising performance in separation of wood wastes, with an average rate of correct separation of 89%. Hence, it is concluded that the system is efficiently feasible for online monitoring and separation of wood wastes in recycling mills.
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