The use of Kohonen self-organizing maps in process monitoring

被引：0

作者：

Vermasvuori, M ^{[1
]}

Endén, P ^{[1
]}

Haavisto, S ^{[1
]}

Jämsä-Jounela, SL ^{[1
]}

机构：

[1] Helsinki Univ Technol, Dept Proc Control & Automat, FIN-02150 Espoo, Finland

来源：

2002 FIRST INTERNATIONAL IEEE SYMPOSIUM INTELLIGENT SYSTEMS, VOL III, STUDENT SESSION, PROCEEDINGS | 2002年

关键词：

process control; fault diagnosis; fault detection; neural networks; rule-based systems;

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：

Process monitoring and fault diagnosis have been studied widely in recent years, and the number of industrial applications with encouraging results has grown rapidly. In the case of complex processes a computer aided monitoring enhances operators possibilities to run the process economically. In this paper a fault diagnosis system will be described and some application results from the Outokumpu Harjavalta smelter will be discussed. The system monitors process states. using neural networks (Kohonen Self-Organizing Maps, SOM) in conjunction with heuristic rules, which are also used to detect equipment malfunctions.

引用

页码：2 / 7

页数：6

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