Rapid and Nondestructive On-Site Classification Method for Consumer-Grade Plastics Based on Portable NIR Spectrometer and Machine Learning
Joint Authors
Yang, Yinglin
Zhang, Xin
Yin, Jianwei
Yu, Xiangyang
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-10
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
The classification of plastic waste before recycling is of great significance to achieve effective recycling.
In order to achieve rapid, nondestructive, and on-site detection, a portable near-infrared spectrometer was used in this study to obtain the diffuse reflectance spectrum for both standard and commercial plastics made by ABS, PC, PE, PET, PP, PS, and PVC.
After applying a series of pretreatments, the principal component analysis (PCA) was used to analyze the cluster trend.
K-nearest neighbor (KNN), support vector machine (SVM), and back propagation neural network (BPNN) classification models were developed and evaluated, respectively.
The result showed that different plastics could be well separated in top three principal components space after pretreatment, and the classification models performed excellent classification results and high generalization capability.
This study indicated that the portable NIR spectrometer, integrated with chemometrics, could achieve excellent performance and has great potential in the field of commercial plastic identification.
American Psychological Association (APA)
Yang, Yinglin& Zhang, Xin& Yin, Jianwei& Yu, Xiangyang. 2020. Rapid and Nondestructive On-Site Classification Method for Consumer-Grade Plastics Based on Portable NIR Spectrometer and Machine Learning. Journal of Spectroscopy،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1190819
Modern Language Association (MLA)
Yang, Yinglin…[et al.]. Rapid and Nondestructive On-Site Classification Method for Consumer-Grade Plastics Based on Portable NIR Spectrometer and Machine Learning. Journal of Spectroscopy No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1190819
American Medical Association (AMA)
Yang, Yinglin& Zhang, Xin& Yin, Jianwei& Yu, Xiangyang. Rapid and Nondestructive On-Site Classification Method for Consumer-Grade Plastics Based on Portable NIR Spectrometer and Machine Learning. Journal of Spectroscopy. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1190819
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190819