文献类型：期刊文献

英文题名：Spectral Correlation Information Embedded NIR Modeling Method and Its Industrial Applications

作者：Li, Yuqiang[1,2,3];Du, Wenli[1,2,3];Zhao, Yunmeng[1,2,3]

机构：[1]East China Univ Sci & Technol, State Key Lab Ind Control Technol, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[3]Huzhou Inst Ind Control Technol, Huzhou 313099, Peoples R China

年份：2025

卷号：21

期号：8

起止页码：5877

外文期刊名：IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

收录：;EI(收录号：20252018410085);WOS:【SCI-EXPANDED(收录号:WOS:001481870600001)】；

基金：This work was supported in part by the National Key Research and Development Program of China under Grant 2022YFB3305900, in part by the National Natural Science Foundation of China under Grant 62136003, in part by the National Natural Science Foundation of China under Grant 62293501, in part by the Major Science and Technology Projects of Longmen Laboratory under Grant LMZDXM202206, in part by the Programme of Introducing Talents of Discipline to Universities (the 111 Project) under Grant B17017, in part by the State Key Laboratory of Industrial Control Technology under Grant ICT2024A03, and in part by the Fundamental Research Funds for the Central Universities.

语种：英文

外文关键词：Correlation; Data models; Analytical models; Vectors; Vibrations; Knowledge discovery; Bayes methods; Wavelength measurement; Spectral analysis; Predictive models; Industrial application; multivariate modeling; near-infrared (NIR) spectroscopy; spectral correlation analysis; structural information embedding

摘要：Near-infrared (NIR) technology is an essential online measurement and monitoring technology in modern industrial processes. Although various methods have been developed for spectral multivariate analysis, they often ignore the potential correlation and complementary relationship between wavelengths. To this end, this work proposes the spectral correlation information embedded (SCIE) modeling method to improve NIR model performance by incorporating the underlying correlation structure among spectral wavelengths, in which the structural model is developed to integrate the spectral correlation information matrix into NIR regression analysis. Furthermore, the theory-guided initialization and structural correlation constraint are introduced to assist model learning and avoid overfitting. The effectiveness of the proposed SCIE method is demonstrated on the benchmark dataset and real-world NIR datasets from the refining process. Comparative results indicate that the proposed method effectively selects wavelengths associated with functional groups and achieves accurate prediction of petrochemical product properties.