Model-based slopping warning in the LD steel converter process

被引：12

作者：

Evestedt, Magnus ^{[1
]}

Medvedev, Alexander ^{[1
]}

机构：

[1] Uppsala Univ, Dept Informat Technol, S-75105 Uppsala, Sweden

来源：

JOURNAL OF PROCESS CONTROL | 2009年 / 19卷 / 06期

关键词：

Modelling; Adaptive filters; Soft sensors; Metals industry; Steel; RECURSIVE PARAMETER-ESTIMATION; CAO-SIO2-FEO SLAGS; IDENTIFICATION; ALGORITHMS; EXCITATION;

D O I：

10.1016/j.jprocont.2009.01.002

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 most prevalent steel-making process is the basic oxygen steel-making (BOS) process. Problems arise when the layer of foaming slag created on the surface of the molten metal exceeds the height of the vessel and overflows, causing metal loss, process disruption and environmental pollution. This phenomenon is commonly referred to as slopping. A method for automatic slopping detection is described in this contribution. The sound signal from a microphone located in the off-gas funnel is processed to obtain an estimate of the slag level in the converter. A model describing the relationship between off-gas flow rate, pressure and the slag level estimate is updated recursively in time. The output error is fed to a change detector yielding a warning system with three alarm levels indicating the persistence of slopping symptoms. The algorithm was tested on data from 100 heats at SSAB Oxelosund. Slopping was correctly detected in 80% of the blows. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：1000 / 1010

页数：11

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