The process chemometrics approach to process monitoring and fault detection

被引:672
作者
Wise, BM
Gallagher, NB
机构
[1] Eigenvector Research, Manson, WA 98831
关键词
fault detection; multivariable systems; multivariate quality control; statistical analysis;
D O I
10.1016/0959-1524(96)00009-1
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Chemometrics, the application of mathematical and statistical methods to the analysis of chemical data, is finding ever widening applications in the chemical process environment. This article reviews the chemometrics approach to chemical process monitoring and fault detection. These approaches rely on the formation of a mathematical/statistical model that is based on historical process data. New process data can then be compared with models of normal operation in order to detect a change in the system. Typical modelling approaches rely on principal components analysis, partial least squares and a variety of other chemometric methods. Applications where the ordered nature of the data is taken into account explicitly are also beginning to see use. This article reviews the state-of-the-art of process chemometrics and current trends in research and applications. Copyright (C) 1996 Published by Elsevier Science Ltd
引用
收藏
页码:329 / 348
页数:20
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