Multivariate analysis and monitoring of sequencing batch reactor using multiway independent component analysis

被引：0

作者：

Yoo, C ^{[1
]}

Vanrolleghem, PA ^{[1
]}

机构：

[1] State Univ Ghent, BIOMATH, B-9000 Ghent, Belgium

来源：

EUROPEAN SYMPOSIUM ON COMPUTER-AIDED PROCESS ENGINEERING - 14 | 2004年 / 18卷

关键词：

batch monitoring; multivariate statistical process monitoring (MSPM); multiway independent component analysis (MICA); sequencing batch reactor (SBR);

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This contribution describes the monitoring on a pilot-scale sequencing batch reactor (SBR) using a batchwise multiway independent component analysis method (MICA) which can extract meaningful hidden information from non-Gaussian data. Given that independent component analysis (ICA) is superior to principal component analysis (PCA) to extract features from non-Gaussian data sets, the use of ICA may improve monitoring performance. The monitoring results of a pilot-scale SBR for biological wastewater treatment showed the power and advantages of MICA monitoring in comparison to conventional monitoring methods.

引用

页码：859 / 864

页数：6

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