Hyperspectral Imaging Detection Architectures for Polyethilene (PE) and Polypropylene (PP) Identification Inside Plastic Waste Streams

Since polymers are continuously replacing other materials in major consumer products, the consumption of plastic increases faster than the economy as a whole. One of the weakest points in the recycling system is the reuse of waste plastic. There are many kinds of plastics utilised in every day life: polyethylene (PE), polystyrene (PS), polypro-pylene (PP), polyvinyl chloride (PVC) and polyethylene terephthalate (PET). The most important polymers in the consumer goods and the least recycled plastics materials are the polyolefin’s. The reason can be mainly attributed to the complexity of these wastes according to different polymers (rubber, foam, etc.) and polluting (not polymers) materi-als (wood, aluminium, copper, stones, glass, etc.) commonly present in plastic waste streams. In this paper an innovative sensing technology, based on an hyperspectral imaging (HSI) approach, is presented and discussed: i) to determine the quality of waste plastic feed and ii) to set up new sorting strategies for pure PP and PE recovery.