文献类型：期刊文献

英文题名：Rapid Coal Quality Detection Based on Near-Infrared Diffuse Reflectance Spectroscopy

作者：Wang, Yaning[1]; Li, Yuqiang[1]; Li, Jia[1]; Wang, Zixiang[1]; Gu, Hanshun[1]; Chen, Feidi[1]; Zhao, Yunmeng[1,2]

机构：[1] East China University of Science and Technology, School of Information Science and Engineering, Shanghai, 200030, China; [2] Qingyuan Innovation Laboratory, Quanzhou, 362801, China

年份：2024

起止页码：6740

外文期刊名：Chinese Control Conference, CCC

收录：EI(收录号：20244117154930)

语种：英文

外文关键词：Atomic spectroscopy - Coal ash - Coal dust - Regression analysis - Sulfur determination

摘要：This study investigated the application of near-infrared (NIR) diffuse reflectance spectroscopy for rapid and non-destructive detection of ash and sulfur content in coal powder. Partial least squares (PLS) regression models were established using NIR diffuse reflectance spectroscopy. Preprocessing methods included standard normal variate, first derivative, second derivative, and multiplicative scatter correction were discussed. The ash and sulfur content models processed with standard normal variate transformation outperformed. The experimental results demonstrate that the established models for ash and sulfur content have achieved satisfactory performance, with coefficients of determination ( R 2) of 0.95 and 0.96, respectively, and root mean square error of prediction (RMSEP) of 0.68 and 0.18, respectively. The confirmation of NIR spectroscopy modeling for rapid detection of coal powder properties compared to traditional methods indicates faster speed and satisfactory precision, demonstrating its significant applicability in industrial process analysis. It has been confirmed that NIR spectroscopy modeling enables rapid detection of coal powder properties. Compared to traditional methods, it offers faster speed while meeting the required precision standards, demonstrating higher application value. ? 2024 Technical Committee on Control Theory, Chinese Association of Automation.