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  • Regression-based Age Prediction of Plastic Waste using Hyperspectral Imaging

    Felix Kronenwett, Pia Klingenberg, Georg Maier, Thomas Längle, Elke Metzsch-Zilligen, Jürgen Beyerer

    Kapitel/Beitrag aus dem Buch: Beyerer, J et al. 2023. OCM 2023 - 6th International Conference on Optical Characterization of Materials, March 22nd – 23rd, 2023, Karlsruhe, Germany : Conference Proceedings.

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    In order to enable high quality recycling of polypropylene (PP) plastic, additional classification and separation into the degree of degradation is necessary. In this study, different PP plastic samples were produced and degraded by multiple extrusion and thermal treatment. Using near infrared spectroscopy, the samples were examined and regression models were trained to predict the degree of aging. The models of the multiple extruded samples showed high accuracy, despite only minor spectral changes. The accuracy of the models of the thermally aged samples varied with the design of the training set due to the non-linear aging process, but showed sufficient accuracy in prediction.

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    Empfohlene Zitierweise für das Kapitel/den Beitrag
    Kronenwett, F et al. 2023. Regression-based Age Prediction of Plastic Waste using Hyperspectral Imaging. In: Beyerer, J et al (eds.), OCM 2023 - 6th International Conference on Optical Characterization of Materials, March 22nd – 23rd, 2023, Karlsruhe, Germany : Conference Proceedings. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.58895/ksp/1000155014-5
    Lizenz

    This is an Open Access chapter distributed under the terms of the Creative Commons Attribution 4.0 license (unless stated otherwise), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. Copyright is retained by the author(s).

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    Dieses Buch ist Peer reviewed. Informationen dazu Hier finden Sie mehr Informationen zur wissenschaftlichen Qualitätssicherung der MAP-Publikationen.

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    Veröffentlicht am 25. Mai 2023

    DOI
    https://doi.org/10.58895/ksp/1000155014-5