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Open AccessArticle

PET and PVC Separation with Hyperspectral Imagery

1
DICEA-Sapienza University of Rome, via Eudossiana 18, 00184 Rome, Italy
2
CNR—Institute of Atmospheric Pollution Research, Area della Ricerca di Roma1, Via Salaria Km 29,300 Monterotondo, I-00015 Rome, Italy
3
DICMA-Sapienza University of Rome, via Eudossiana 18, 00184 Rome, Italy
*
Author to whom correspondence should be addressed.
Sensors 2015, 15(1), 2205-2227; https://doi.org/10.3390/s150102205
Received: 12 October 2014 / Revised: 18 November 2014 / Accepted: 22 December 2014 / Published: 20 January 2015
Traditional plants for plastic separation in homogeneous products employ material physical properties (for instance density). Due to the small intervals of variability of different polymer properties, the output quality may not be adequate. Sensing technologies based on hyperspectral imaging have been introduced in order to classify materials and to 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 plastic polymers—polyethylene terephthalate (PET) and polyvinyl chloride (PVC)—in different phases of their life cycle (primary raw materials, urban and urban-assimilated waste and secondary raw materials) to show the contribution of hyperspectral sensors in the field of material recycling. This is accomplished via near-infrared (900–1700 nm) reflectance spectra extracted from hyperspectral images acquired with a two-linear-spectrometer apparatus. Results have shown that a rapid and reliable identification of PET and PVC can be achieved by using a simple two near-infrared wavelength operator coupled to an analysis of reflectance spectra. This resulted in 100% classification accuracy. A sensor based on this identification method appears suitable and inexpensive to build and provides the necessary speed and performance required by the recycling industry. View Full-Text
Keywords: recycling; plastic polymers; hyperspectral imaging; NIR; PET; PVC recycling; plastic polymers; hyperspectral imaging; NIR; PET; PVC
MDPI and ACS Style

Moroni, M.; Mei, A.; Leonardi, A.; Lupo, E.; Marca, F.L. PET and PVC Separation with Hyperspectral Imagery. Sensors 2015, 15, 2205-2227.

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