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.
The recycling of plastic products becomes increasingly attractive not only from an environmental point of view, but also economically. For recycled (engineering) plastic products with the highest possible quality, plastic sorting technologies must provide clean and virtually mono-fractional compositions from a mixture of many different types of (shredded) plastics. In order to put this high quality sorting into practice, the labeling of virgin plastics with specific fluorescent markers at very low concentrations (ppm level or less) during their manufacturing process is proposed. The emitted fluorescence spectra represent "optical fingerprints" -each being unique for a particular plastic -which we use for plastic identification and classification purposes. In this study we quantify the classification performance using our prototype measurement system and 15 different plastic types when various influence factors most relevant in practice cause disturbances of the fluorescence spectra emitted from the labeled plastics. The results of these investigations help optimize the development and incorporation of appropriate fluorescent markers as well as the classification algorithms and overall measurement system in order to achieve the lowest possible classification error rates.
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