Work

Fast and effective classification of plastic waste by pushbroom hyperspectral sensor coupled with hierarchical modelling and variable selection

Year: 2023

Type: article

Abstract: Plastic waste management represents a global challenge in the framework of sustainable production and consumption of resources. One of the most critical issues in plastic recycling is polymer separation, necessary to obtain high-quality secondary raw material flow streams. The aim of this work was to build a classification strategy, based on pushbroom hyperspectral imaging, able to recognize the most common polymers found in mixed plastic waste to be applied at recycling plant scale. After exploring polymer spectral differences by principal component analysis, a hierarchical partial least squares-discriminant analysis, based on the acquired full spectra, and a hierarchical interval partial least squares-discriminant analysis, based on selected variables, were tested and their performances were evaluated and compared. High quality classification results were obtained in both cases, demonstrating that the developed multi-class models can be utilized in a flexible way for quality control and/or for on-line sorting actions in recycling plants.

Source: Resources Conservation and Recycling

DOI: 10.1016/j.resconrec.2023.107068

Authors: Giuseppe Bonifazi, Giuseppe Capobianco, Silvia Serranti

Institution: Sapienza University of Rome

Language: English

Topic: Spectroscopy and Chemometric Analyses

Subfield: Analytical Chemistry

Field: Chemistry

Domain: Physical Sciences

SDG: Responsible consumption and production

Open Access status: hybrid

Estimated APC paid: $4,350