Research on Plastic Packaging Foam Classification Based on a Differential Raman Spectroscopy-chemometrics Integrated Framework

JIANG Hong; ZHANG Xiancheng

doi:10.19554/j.cnki.1001-3563.2026.07.022

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Packaging Engineering ›› 2026, Vol. 47 ›› Issue (7) : 186-192. DOI: 10.19554/j.cnki.1001-3563.2026.07.022

Research on Plastic Packaging Foam Classification Based on a Differential Raman Spectroscopy-chemometrics Integrated Framework

JIANG Hong^1,2,*, ZHANG Xiancheng³

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Abstract

The work aims to establish an efficient, non-destructive systematic classification method for plastic packaging foams. Spectral data from 63 plastic packaging foam samples were acquired by differential Raman spectroscopy. Feature dimension reduction and extraction were performed via principal component analysis and linear discriminant analysis. An ensemble classification model was constructed incorporating k-Nearest Neighbors (k-NN), Support Vector Machines (SVM), Lightweight Gradient Boosting Machine (LightGBM), and Extreme Random Forest (ERT). The classification potential of the data was evaluated based on the theoretical separability threshold. The model's generalization capability was independently validated using a Multi-Layer Perceptron (MLP). Results showed that the architecture classified samples into five major categories based on characteristic peaks. After PCA-LDA dimension reduction, the ensemble model achieved a classification accuracy of 93.33% on the test set. The MLP-validated training and test set accuracy rates were 95.45% and 89.47%, respectively. In conclusion, the constructed ensemble classification architecture integrates theoretical evaluation with multi-model ensemble strategies, achieving near-limit classification performance. This method provides a reliable and comprehensive solution for rapid identification of plastic packaging foams.

Key words

plastic packaging foam / differential Raman spectroscopy / chemometrics / ensemble learning / forensic evidence classification

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JIANG Hong, ZHANG Xiancheng. Research on Plastic Packaging Foam Classification Based on a Differential Raman Spectroscopy-chemometrics Integrated Framework[J]. Packaging Engineering. 2026, 47(7): 186-192 https://doi.org/10.19554/j.cnki.1001-3563.2026.07.022

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