中国造纸2025，Vol.44Issue(11)：172-176,5.DOI:10.11980/j.issn.0254-508X.2025.11.023
差分拉曼光谱结合PCA-RCSC-Transformer对快递面单的检验研究
Differential Raman Spectroscopy Combined with PCA-RCSC and Improved Transformer for Courier Face Sheets Inspection Research
摘要
Abstract
Addressing the challenges of easily fading handwriting and stable filler components in thermal paper-based courier face sheets,this study collected data from 173 express delivery label samples from various brands and printing dates through differential Raman spectros-copy,and proposed a novel method integrating modified orthogonally constrained principal component analysis(PCA),and element ratio-cosine similarity clustering(RCSC),combined with a Transformer model incorporating a sparse attention mechanism for data classification prediction.The results showed that orthogonally constrained PCA reduced the dimension of differential Raman spectral data and resulted in a compression rate of 95.6%,while RCSC supplemented by manual validation,categorized the samples into four classes.Further classifica-tion using the sparse attention-based Transformer model achieved an forecast accuracy of 90.0%,significantly outperforming traditional meth-ods such as random forest and support vector machines.关键词
差分拉曼光谱/快递面单/正交约束主成分分析/元素比例-余弦相似度聚类Key words
Differential Raman spectroscopy/courier face sheets/orthogonally constrained principal component analysis/elemental ratio-cosine similarity clustering分类
轻工业引用本文复制引用
姜红,马星煜..差分拉曼光谱结合PCA-RCSC-Transformer对快递面单的检验研究[J].中国造纸,2025,44(11):172-176,5.基金项目
安徽公安学院校级科研项目(2024xjkyyb08). （2024xjkyyb08）
