ABSTRACT
Plastics have many unrivaled properties and are thus indispensable materials with an ever-increasing production. Since the plastics recycling rates are still small, the plastic waste that ends up on landfills, in the environment including oceans, and incineration plants also steadily grows. Large-scale automated sorting of waste plastics may help solve the problem. However, most state-of-the-art approaches are limited to a (very) small number of plastic types that can be simultaneously sorted and have severe difficulties with black plastics. The labeling of plastics with fluorescent tracers ("markers") during their production has the potential to enable the fast and highly reliable classification and automated sorting of many different plastic types simultaneously. Unfortunately, the unique marker fluorescence ("optical fingerprint") might be obscured by the autofluorescence (AF) often emitted by plastics. Recently, we have shown that time-gated fluorescence spectroscopy (TGFS) can be successfully applied to eliminate the influences from AF. In this study, we present the prototype of a TGFS measurement system for the classification and sorting of plastics and evaluate its performance in a typical industrial situation. With 150 000 investigated plastics flakes from 10 different plastic types that were labeled with binary combinations of six fluorescent markers, an overall plastics recovery rate (mean true positive rate TPR¯ ) of 99.76%, and a plastics purity (positive predictive value PPV¯ ) of 99.88% were achieved. Additional simulations that were carried out based upon the experiments allow a prediction of the performance as a function of the signal-to-noise (S/N) ratio such that various system parameters can be adapted to the particular situation.
ABSTRACT
For the production of high-quality parts from recycled plastics, a very high purity of the plastic waste to be recycled is mandatory. The incorporation of fluorescent tracers ("markers") into plastics during the manufacturing process helps overcome typical problems of non-tracer based optical classification methods. Despite the unique emission spectra of fluorescent markers, the classification becomes difficult when the host plastics exhibit (strong) autofluorescence that spectrally overlaps the marker fluorescence. Increasing the marker concentration is not an option from an economic perspective and might also adversely affect the properties of the plastics. A measurement approach that suppresses the autofluorescence in the acquired signal is time-gated fluorescence spectroscopy (TGFS). Unfortunately, TGFS is associated with a lower signal-to-noise (S/N) ratio, which results in larger classification errors. In order to optimize the S/N ratio we investigate and validate the best TGFS parameters-derived from a model for the fluorescence signal-for plastics labeled with four specifically designed fluorescent markers. In this study we also demonstrate the implementation of TGFS on a measurement and classification prototype system and determine its performance. Mean values for a sensitivity of [Formula: see text] = 99.93% and precision [Formula: see text] = 99.80% were achieved, proving that a highly reliable classification of plastics can be achieved in practice.
