Process Monitoring Based on Improved Principal Component Analysis

被引:0
|
作者
Xiao Yingwang [1 ]
机构
[1] Guangdong Polytech Normal Univ, Sch Automat, Guangzhou 510665, Guangdong, Peoples R China
关键词
Principal component analysis; Process monitoring; Principal-component-related variable; Double-effect evaporator process;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The information provided by T-2 and squared prediction error (SPE) test of principal component analysis (PCA) is not corresponding. An improved PCA is proposed which uses principal-component-related variable residual statistic and common variable residual statistic to replace SPE statistic. Then a simulated double-effect evaporator is monitored by using the proposed method and comparisons with the conventional PCA are made. The simulation result shows that the improved PCA can avoid the conservation of SPE statistical test and provide more explicit information about the process conditions. So the improved PCA has an enhanced fault diagnosing performance.
引用
收藏
页码:42 / 45
页数:4
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