Characterization of post-consumer polyolefin wastes by hyperspectral imaging for quality control in recycling processes

In this paper new analytical inspection strategies, based on hyperspectral imaging (HSI) in the VIS–NIR and NIR wavelength ranges (400–1000 and 1000–1700 nm, respectively), have been investigated and set up in order to define quality control logics that could be applied at industrial plant level for polyolefins recycling. The research was developed inside the European FP7 Project W2Plastics “Magnetic Sorting and Ultrasound Sensor Technologies for Production of High Purity Secondary Polyolefins from Waste”. The main aim of the project is the separation of pure polyethylene and polypropylene adopting an innovative process, the magnetic density separation (MDS). Spectra of plastic particles and contaminants resulting from post-consumer complex wastes and of virgin polyolefins have been acquired by HSI and by Raman spectroscopy. The classification results obtained applying principal component analysis (PCA) on HSI data have been compared with those obtained by Raman spectroscopy, in order to validate the proposed innovative methodology. Results showed that HSI sensing techniques allow to identify both polyolefins and contaminants. Results also demonstrated that HSI has a great potentiality as a tool for quality control of feed (identification of contaminants in the plastic waste) and of the two different pure polypropylene and polyethylene flow streams resulting from the MDS-based recycling process.

► We apply an innovative technique, hyperspectral imaging, to plastic waste recycling.
► The study was applied to polyolefin quality control in MDS-based recycling plants.
► Polyethylene, polypropylene and contaminants from complex waste are correctly classified.
► Quality certification procedures for the investigated complex plastic waste are discussed.
► On-line quality control architectures based on hyperspectral imaging are proposed.