Sorting of black plastics using statistical pattern recognition on terahertz frequency domain data

The sorting of used plastics is an ever-growing market field which is further pushed by new EU regulations in, e.g., car recycling. Modern recycling techniques require pure or almost pure fractions of polymers. These pure fractions can be generated from waste using modern sorting technologies based on specific mechanical, electrical and chemical material properties such as density, conductivity and melting point. The thermal recycling of plastics is no longer seasonable. More modern recycling techniques require pure fractions containing only a single variety of polymer. A large portion of the plastic waste contains black or multilayer materials that are not sortable with todays' sorting technologies. To overcome this challenge, three Fraunhofer institutes are working together to develop a new type of sorting system. As a first step, we have developed a frequency domain line-scan camera working in the terahertz range with frequencies below 300 GHz. Since the entropy in terahertz signals below 300 GHz is not as high as needed for simple classification, more complex statistical pattern recognition methods are needed. The application of those methods to the problem of sorting black plastics as the second step in this joint project is presented in this paper. These methods have to be integrated into a real sorting system, which is the third part of our joint project. The modular approach gives the ability to integrate our sensors and algorithms into existing sorting systems.