期刊
TRAC-TRENDS IN ANALYTICAL CHEMISTRY
卷 22, 期 9, 页码 634-640出版社
ELSEVIER SCI LTD
DOI: 10.1016/S0165-9936(03)01005-7
关键词
multivariate statistical process control (MSPC) near infrared spectroscopy (NIR); petrochemical industry; robust model; standardisation
Analytical methods based on near infrared spectroscopy (NIR) and multivariate calibration techniques have important characteristics for industrial applications because they are quick and can be used to make direct determinations and extract information from several parameters from one single measurement. They can also be used in on-line applications. However, they have not been used in industry as much as one might expect because the validity of the calibration model must be assured when the signal is transformed. There are chemometric techniques for tackling every problem, but there are no specific guidelines about which procedure to use. In this article, we describe a practical strategy for introducing these methods. We discuss the relative merits of the various univariate and multivariate control techniques and describe how they might be used. We also discuss the standardisation of the calibration models and describe how to obtain robust models at low experimental cost. Finally, we illustrate our strategy with a practical case study from the petrochemical industry. (C) 2003 Published by Elsevier B.V.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据