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- W4247440760 abstract "In this paper, identification system of plastic solid waste (PSW) based on near-infrared (NIR) reflectance spectroscopy in combination with Support Vector Machine (SVM) was presented. A device applied to obtain NIR spectra of plastics in the detection platform was developed. After pre-processing (normalized, 1st derivative and smooth), the repeatability of spectral absorption features was improved, which would assist the identification. A “principal component analysis (PCA)SVM” identification method was proposed to identify polypropylene (PP), polystyrene (PS), polyethylene (PE), poly(methyl methacrylate) (PMMA), acrylonitrile butadiene styrene (ABS) and polyethylene terephthalate (PET) among plastics, and its identification accuracy can reach 97.5%. The type of samples could clearly be identified and the shape of samples could also be roughly discerned. It is clearly shown that this system can achieve good identification results while reducing costs considerably, which has great potential in industrial recycling." @default.
- W4247440760 created "2022-05-12" @default.
- W4247440760 date "1991-05-01" @default.
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- W4247440760 title "New pigments for the coatings industry" @default.
- W4247440760 doi "https://doi.org/10.1016/0306-3747(91)90478-5" @default.
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