Discriminant analyzing system for wood wastes using a visible-near-infrared chemometric imaging technique.
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.
Kobori
Hikaru
H
Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, Japan.
Yonenobu
Hitoshi
H
Noma
Junichi
J
Tsuchikawa
Satoru
S
D001331:Automation; D003247:Conservation of Natural Resources / Q000379:methods; D016002:Discriminant Analysis; D005240:Feasibility Studies; D007091:Image Processing, Computer-Assisted; D007220:Industrial Waste; D012037:Refuse Disposal / Q000379:methods* / Q000706:statistics & numerical data; D013055:Spectrophotometry, Infrared / Q000379:methods; D014934:Wood
D007220:Industrial Waste