Raman Spectroscopy Combined with Active Hyperspectral Sensing for Classification of Waste Plastics Containing Brominated Flame Retardants: A Sensor Fusion Approach
Tuomas Sormunen,Ilkka Rytöluoto,Anna Tenhunen,Francisco Senna Vieira
出处
期刊:Social Science Research Network [Social Science Electronic Publishing] 日期:2022-01-01
标识
DOI:10.2139/ssrn.4264557
摘要
Detection of brominated flame retardants (BFRs) in waste plastics 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 NIR spectroscopies. We analyzed 210 real waste plastic samples sourced from WEEE 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 values 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 PCA, both separately and by fusing the data. We achieved over 80% balanced classification accuracies using all models, with significant improvements by data fusion.