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Discriminant Analyzing System for Wood Wastes Using A Visible–Near-Infrared Chemometric Imaging Technique

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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.

Keywords: CHEMOMETRIC IMAGING; NEAR-INFRARED SPECTROSCOPY; NIR SPECTROSCOPY; SEPARATION; SIMCA; SOFT INDEPENDENT MODELING OF CLASS ANALOGY; VISIBLE-NEAR-INFRARED CHEMOMETRIC IMAGING; WOOD WASTE

Document Type: Research Article

DOI: http://dx.doi.org/10.1366/000370208785284295

Affiliations: 1: Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya 464-8601, Japan 2: Naruto University of Education, Naruto 772-8502, Japan 3: Nagoya Port Lumber Warehouse INC., Tobishima 490-1447, Japan

Publication date: August 1, 2008

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