近红外光谱检测技术在精细化工生产过程中的应用
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  • 英文篇名:The application of near infrared spectroscopy(NIR) detection technology to fine chemical production processes
  • 作者:邹志云 ; 孟磊 ; 刘英莉 ; 刘燕军 ; 管臣
  • 英文作者:ZOU Zhiyun;MENG Lei;LIU Yingli;LIU Yanjun;GUAN Chen;Research Institute of Chemical Defence,Military Academy of Sciences;
  • 关键词:精细化工 ; 近红外光谱 ; 定量检测建模 ; 定性判别分析
  • 英文关键词:fine chemical process;;near infrared spectroscopy(NIR);;spectral correction modeling;;discriminant analysis
  • 中文刊名:JSYH
  • 英文刊名:Computers and Applied Chemistry
  • 机构:军事科学院防化研究院;
  • 出版日期:2018-10-28
  • 出版单位:计算机与应用化学
  • 年:2018
  • 期:v.35
  • 基金:国家自然科学基金资助项目(61503204,61773225);; 浙江省自然科学基金(LY16F030001)
  • 语种:中文;
  • 页:JSYH201810004
  • 页数:12
  • CN:10
  • ISSN:11-3763/TP
  • 分类号:29-40
摘要
针对精细化学品D3生产过程中酸碱原料浓度检测和D2生产过程中粗品/精品快速检测鉴定需求,论述了近红外光谱检测的基本原理,给出了偏最小二乘定量建模和马氏距离分类判别等化学计量学算法,构建了Antaris II傅里叶变换近红外光谱检测系统。通过配制样品,采集光谱数据,并经求导、滤波和标准化数据处理,应用偏最小二乘法建立了D3生产过程HCl水溶液摩尔浓度、NaOH水溶液质量百分数和摩尔浓度的近红外光谱检测模型,应用马氏距离结合主元分析法建立了D2生产过程中粗品/精品判别分析模型,给出了详细的检测实验数据。生产现场样品检测结果表明,D3酸碱浓度的定量检测模型具有很高的检测精度,D2粗品/精品判别分析模型判别结果准确,可在相关精细化工生产过程中推广应用,提高生产过程检测鉴定效率。
        According to the detection requirements of fine chemical production processes including D3 acidbase concentration and discriminant analysis of crude and fine D2,the detection technology of near infrared spectroscopy(NIR) was studied,the related spectral correction modeling algorithms including partial least squares(PLS) and Mahalanobis distance were presented,and the relevant testing system Antaris II Fourier transformer NIR analyzer was constructed. By collecting a large number of samples,testing with Antaris II near infrared spectrometer,and processing of the spectral data with derivation,filtering and standardization technique,the establishment of NIR calibration models for the molar concentration detection of HCl,the mass percentage and molar concentration detection of NaOH aqueous solution was completed using PLS,the discriminant analysis model of crude and fine D2 was built combining Mahalanobis distance and Principal Component Analysis(PCA),and detailed experimental detection results were achieved and presented in this paper. The NIR calibration models and discriminant analysis models were successfully used in D3 and D2 fine chemical production processes respectively,and the efficiency of detection of acid-base materials and identification of crude and fine D2 was much improved.
引文
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