Characterization of Unplasticized Polyvinyl Chloride Windows by Confocal Raman Microspectroscopy and Chemometrics

Abstract

In order to nondestructively and accurately identify unplasticized polyvinyl chloride windows, a classification method based on multi-feature algorithm selection modeling was developed. Confocal Raman microspectroscopy was used to obtain the spectral profiles of 150 samples from five brands. The differences in model recognition accuracy were compared among three preprocessing methods: Savitzky-Golay filtering, Hilbert transform, and wavelet transform. The best preprocessing method was selected, and the competitive adaptive reweighted sampling was used to extract feature wavelengths. Furthermore, a Bayesian classification model was constructed to classify and differentiate each sample. The results showed that confocal Raman microspectroscopy can reflect the differences in physicochemical information among different samples. Preprocessing can improve the model’s recognition accuracy, with wavelet transform (96%) > Hilbert transform (90%) > Savitzky-Golay filtering (76%) > untreated (72%). Wavelet transform can remove noise from spectral data without changing the peak region and its absorbance. Based on wavelet transform processing and competitive adaptive reweighted sampling (CARS) combined with Bayesian discriminant analysis, a 100% accurate classification of 150 samples was successfully achieved.

Keywords:

• Chemometrics
• competitive adaptive reweighted sampling (CARS)
• confocal Raman microspectroscopy
• unplasticized polyvinyl chloride windows

Acknowledgements

We sincerely thank the People’s Public Security University of China for supporting and assisting this project. We are also grateful to the participants who generously gave their time and effort to participate in this study. Finally, we thank our colleagues and friends for their valuable feedback and support.

Authors’ contributions

Ge Qin: Conceptualization, Methodology, Data curation, Software, Writing - original draft, Writing - review & editing. Zhenjun Jia: Formal analysis, Project administration, Supervision, Validation, Writing - review & editing. Haoyu Wang, Huaice Liu: Conceptualization, Data curation, Software, Writing - review & editing. Yijie Sun, Huichao Wang: Methodology, Writing - review & editing, Data curation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by the Double First-Class Discipline Program of Criminal Science and Technology at China People’s Public Security University (2023SYL06).