Fault detection, identification and diagnosis using CUSUM based PCA

被引：81
|
作者：
Bin Shams, M. A. [1 ]
Budman, H. M. [1 ]
Duever, T. A. [1 ]
机构：
[1] Univ Waterloo, Dept Chem Engn, Waterloo, ON N2L 3G1, Canada
来源：
CHEMICAL ENGINEERING SCIENCE | 2011年 / 66卷 / 20期
关键词：
Parameter identification; Process control; Safety; Systems engineering; Fault detection and diagnosis; PCA; DISTURBANCES; KPCA;
D O I：
10.1016/j.ces.2011.05.028
中图分类号：
TQ [化学工业];
学科分类号：
0817 ;
摘要：
In this paper, a cumulative sum based statistical monitoring scheme is used to monitor a particular set of the Tennessee Eastman Process (TEP) faults that could not be properly detected or diagnosed with other fault detection and diagnosis methodologies previously reported. T-2 and Q statistics based on the cumulative sums of all available measurements were successful in observing these three faults. For the purpose of fault isolation, contribution plots were found to be inadequate when similar variable responses are associated with different faults. Fault historical data is then used in combination with proposed CUSUM based PCA model to unambiguously characterize the different fault signatures. The proposed CUSUM based PCA was successful in detecting, identifying and diagnosing both individual as well as simultaneous occurrences of these faults. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：4488 / 4498
页数：11
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