On the topological modeling and analysis of industrial process data using the SOM

被引：26

作者：

Corona, Francesco ^{[1
]}

Mulas, Michela ^{[2
]}

Baratti, Roberto ^{[3
]}

Romagnoli, Jose A. ^{[3
]}

机构：

[1] Aalto Univ, Dept Informat & Comp Sci, FI-02015 Espoo, Hut, Finland

[2] Aalto Univ, Dept Biotechnol & Chem Technol, FI-02015 Espoo, Hut, Finland

[3] Univ Cagliari, Dept Chem Engn & Mat, I-09123 Cagliari, Pzza Darmi, Italy

来源：

COMPUTERS & CHEMICAL ENGINEERING | 2010年 / 34卷 / 12期

关键词：

Process monitoring; Process supervision; Self-organizing maps; NETWORK;

D O I：

10.1016/j.compchemeng.2010.07.002

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, we overview and discuss the implementation of topology-based approaches to modeling and analyzing industrial process data. Emphasis is given to the representation of the data obtained with the self-organizing map (SOM). The methods are used in visualizing process measurements and extracting relevant information by exploiting the topological structure of the observations. Benefits of the SOM with industrial data are presented for a set of process measurements measured in an industrial gas treatment plant. The practical goal is to identify significant operational modes and most sensitive process variables before developing an alternative control strategy. The results confirmed that the SOM-based approach is capable of providing valuable information and offers possibilities for direct application to other process monitoring tasks. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：2022 / 2032

页数：11