Online monitoring of steel casting processes using multivariate statistical technologies: From continuous to transitional operations

被引：31

作者：

Zhang, Yale ^{[1
]}

Dudzic, Michael S. ^{[1
]}

机构：

[1] Dofasco Ltd, Proc Automat, Hamilton, ON L8N 3J5, Canada

来源：

JOURNAL OF PROCESS CONTROL | 2006年 / 16卷 / 08期

关键词：

multivariate statistics; process monitoring; continuous caster; transitional operation;

D O I：

10.1016/j.jprocont.2006.03.005

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes a state-of-the-art online monitoring system using multivariate statistical technologies for continuous steel casting process, which was commissioned at Dofasco's No. 2 caster to provide consistent indication of process health for caster's start-up, continuous production and transitional operations. The paper particularly focuses on development of a novel scheme to synchronize process trajectories for monitoring specific transitional operations such as equipment or steel product grade changes. The proposed scheme is demonstrated by several industrial examples with the results showing good detectability of various process abnormalities. With the aid of this fully integrated, innovative monitoring system, Dofasco has generated significant value through improved productivity and reduced maintenance costs. (C) 2006 Elsevier Ltd. All rights reserved.

引用

页码：819 / 829

页数：11

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