Classification of commercial plastics using hyperspectral long wave infrared emission imaging

The long wave infrared regime of the electromagnetic spectrum has been used to identify and classify different types of plastics. This work presents an early-stage version of an industrial hyperspectral camera, which is based on a low-order scanning Fabry-Pérot interferometer and is sensitive to radiation with wavelengths from 8 µm to 15 µm. As a demonstration, the setup is used to record interferograms and distinguish between twelve types of common plastics heated to 60 °C. The plastic identification is based on a nine-component principal component analysis model combined with k-nearest neighbors. The resulting model shows a micro precision of 90 % and a macro specificity of 99 %, being able to classify all tested plastic types except ABS.

Authors

Institutions

Publication Details

Journal
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy
Published
2024-11-27
DOI
https://doi.org/10.1016/j.saa.2024.125501
Citations
3
Primary Topic
Microplastics and Plastic Pollution
Type
article
Field-Weighted Citation Impact
0.40

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Classification of commercial plastics using hyperspectral long wave infrared emission imaging

Bjarke Jørgensen, Jakob Kjelstrup‐Hansen, Mogens Hinge, Victor Petrunin et al.
3 citations
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy
Microplastics and Plastic Pollution
0.40
article

Classification of commercial plastics using hyperspectral long wave infrared emission imaging

Bjarke Jørgensen, Jakob Kjelstrup‐Hansen, Mogens Hinge, Victor Petrunin, Anders Løchte Jørgensen, Martin Lahn Henriksen
article en
3 citations

Abstract

The long wave infrared regime of the electromagnetic spectrum has been used to identify and classify different types of plastics. This work presents an early-stage version of an industrial hyperspectral camera, which is based on a low-order scanning Fabry-Pérot interferometer and is sensitive to radiation with wavelengths from 8 µm to 15 µm. As a demonstration, the setup is used to record interferograms and distinguish between twelve types of common plastics heated to 60 °C. The plastic identification is based on a nine-component principal component analysis model combined with k-nearest neighbors. The resulting model shows a micro precision of 90 % and a macro specificity of 99 %, being able to classify all tested plastic types except ABS.

Spectrochimica Acta Part A Molecular and Biomolecular SpectroscopyVol. 329
University of Southern Denmark (DK), Aarhus University (DK), Bruhn NewTech (Denmark) (DK)
Aarhus Universitet, Innovationsfonden
Openalex Percentile: Top 46%
Microplastics and Plastic Pollution
0.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Classification of commercial plastics using hyperspectral long wave infrared emission imaging — Bjarke Jørgensen, Jakob Kjelstrup‐Hansen, et al. · Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2024) | TGRS Research Map | TGRS