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PET and PVC Separation with Hyperspectral Imaging
* 1 , 2 , 3 , 1 , 3
1  DICEA-Sapienza University of Rome, via Eudossiana 18 00184 Rome, Italy
2  CNR - IIA, Via Salaria km 29,300, 00016 Monterotondo Stazione (RM), Italy
3  DICMA-Sapienza University of Rome, via Eudossiana 18 00184 Rome, Italy

Abstract: The proper design of a product life cycle may contribute both to the optimization of primary raw material uses and to the reduction of waste environmental impacts. Recycling may enter the life cycle of materials in the contexts of production of secondary raw materials and in the reduction of waste extensive disposal in landfills. Tradition plants for plastic separation in homogeneous products employ material physical properties (for instance density). Due to the variability of the properties of various polymers in reduced intervals, the output quality may not be adequate enough. Sensing technologies based on hyperspectral imaging enter this framework being suitable to separate materials and increase the quality of recycled products, which have to comply with specific standards determined by industrial applications. This paper presents the results of the characterization of two different typologies of plastics, namely PET and PVC, in some phases of their life cycle (raw materials, waste and regenerate conditions) to show the contribution of hyperspectral methods in the field of material recycling. This is accomplished via near-infrared (900-1700 nm) reflectance spectra acquired with a linear spectrometer. Though reflectance values depend on many factors such as the characteristics and the thickness of the materials, the lighting conditions, the characteristics of the instrumentation used, and the background, characteristic spectral profiles of PET and PVC samples have been obtained allowing a robust statistical analysis to be developed. Wavelengths 1200 nm and 1650 nm result to be the most suitable for sample classification.
Keywords: Hyperspectral imaging, PET, PVC, classification, statistical analysis, recycling