Raman spectroscopy combined with active hyperspectral sensing for classification of waste plastics containing brominated flame retardants: A sensor fusion approach

Abstract

Discrimination of waste plastics according to brominated flame retardant (BFR) concentration is essential to ensure quality and safety in recycling. We present a sensor fusion approach to classify BFR-containing plastic waste by combining Raman and near-infrared (NIR) spectroscopies. We analysed 210 waste plastic samples sourced from waste electronics and electrical equipment stream and 25 laboratory-made plastics. The Raman spectra were acquired in the range 27–2481 cm−1 using a time-gated Raman and the NIR spectra in the range 4000–5260 cm−1 using a novel active hyperspectral sensor. Total elemental bromine concentrations were determined with X-ray fluorescence spectroscopy and used as reference for training extremely randomized trees classifiers for high- and low-bromine plastics with different thresholds of segmentation. The classifier models were built using Raman and NIR spectral data after reducing dimensions with principal component analysis, both separately and by fusing the data. We achieved over 80% balanced classification accuracies using all models, with significant improvements by data fusion.