Detail publikace
Classification of diverse plastic samples by LIBS and Raman data fusion
HOLUB, D. PALÁSTI, D. FINTOR, K. POŘÍZKA, P. GALBÁCS, G. KAISER, J.
Anglický název
Classification of diverse plastic samples by LIBS and Raman data fusion
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
en
Originální abstrakt
The plastic production and usage in the world is steadily increasing. This leads to increased amounts of plastic waste. Most of the waste could be potentially recycled, but only 14 % of plastic waste is recycled. In order to increase the share of recycling in plastic waste management, the recycling process should be completely automated. The problematic part of sorting is being solved by either manual (labor-intensive) or spectroscopy-based (still in development) methods. In this work, we propose the data fusion of Laser-Induced Breakdown Spectroscopy (LIBS) and Raman spectroscopy as a fast, robust, and reliable way to sort/classify any potential polymer material. The sample set of this work consists of several types of polymers in clear, colored, and even mixture versions. So far, no LIBS/Raman classification works involved all these categories in one experiment. Additionally, the low and medium level of data fusion is discussed, and the performance is compared. By using LIBS and Raman data fusion method and both linear and nonlinear chemometric techniques, increased accuracy reaching more than 98 % in the classification of investigated plastic samples was achieved, which was a significant improvement when compared with singular methods classification accuracy.
Anglický abstrakt
The plastic production and usage in the world is steadily increasing. This leads to increased amounts of plastic waste. Most of the waste could be potentially recycled, but only 14 % of plastic waste is recycled. In order to increase the share of recycling in plastic waste management, the recycling process should be completely automated. The problematic part of sorting is being solved by either manual (labor-intensive) or spectroscopy-based (still in development) methods. In this work, we propose the data fusion of Laser-Induced Breakdown Spectroscopy (LIBS) and Raman spectroscopy as a fast, robust, and reliable way to sort/classify any potential polymer material. The sample set of this work consists of several types of polymers in clear, colored, and even mixture versions. So far, no LIBS/Raman classification works involved all these categories in one experiment. Additionally, the low and medium level of data fusion is discussed, and the performance is compared. By using LIBS and Raman data fusion method and both linear and nonlinear chemometric techniques, increased accuracy reaching more than 98 % in the classification of investigated plastic samples was achieved, which was a significant improvement when compared with singular methods classification accuracy.
Klíčová slova anglicky
Laser-Induced Breakdown Spectroscopy, Raman spectroscopy, polymers, data fusion, data analysis, chemometric techniques, classification
Vydáno
15.04.2024
Nakladatel
Elsevier
Místo
Amsterdam, Nizozemsko
ISSN
0142-9418
Ročník
134
Číslo
5
Počet stran
17
BIBTEX
@article{BUT188559,
author="Daniel {Holub} and Dávid Jenő {Palásti} and Krisztian {Fintor} and Pavel {Pořízka} and Gábor {Galbács} and Jozef {Kaiser},
title="Classification of diverse plastic samples by LIBS and Raman data fusion",
year="2024",
volume="134",
number="5",
month="April",
publisher="Elsevier",
address="Amsterdam, Nizozemsko",
issn="0142-9418"
}