Dynamic simulation of shaft furnace roasting process with METSIM

LU Shaowen; DING Jinliang; LIU Linlin

doi:10.11949/j.issn.0438-1157.20141539

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Dynamic simulation of shaft furnace roasting process with METSIM

更新时间：2025-12-10

- Dynamic simulation of shaft furnace roasting process with METSIM
- CIESC Journal Issue 1, Pages: 244-250(2015)
- 作者机构：
  
  东北大学流程工业综合自动化国家重点实验室,辽宁,沈阳,110819
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20141539
  CLC： D951
- Online First：05 January 2015，
  
  Published：05 January 2015
- 稿件说明：
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LU Shaowen, DING Jinliang, LIU Linlin. Dynamic simulation of shaft furnace roasting process with METSIM[J]. CIESC Journal, 2015, (1): 244-250.
DOI：

LU Shaowen, DING Jinliang, LIU Linlin. Dynamic simulation of shaft furnace roasting process with METSIM[J]. CIESC Journal, 2015, (1): 244-250. DOI： 10.11949/j.issn.0438-1157.20141539.

摘要

竖炉焙烧是我国赤铁矿选矿工业中常见的工艺环节。其关键工艺指标是磁选管回收率

反映了矿石焙烧的质量。但磁选管回收率无法在线实时测量。在实际生产中

对竖炉焙烧磁选管回收率的控制一般通过运行优化控制实现。而运行优化控制策略的设计需要进行大量工业现场实验

建立磁选管回收率相对于主要控制变量的动态响应关系

这样做的成本高

风险大。为了解决这一问题

基于冶金模拟软件METSIM设计了竖炉焙烧工艺动态模型

并采用与实际一致的过程控制软硬件系统建立了竖炉过程半实物仿真系统。通过仿真实验获得磁选管回收率与燃烧时温度设定值之间的动态关系

并与实际数据进行了比较验证。表明该平台能够作为运行优化控制方法设计的实验和测试工具。

Abstract

Shaft furnace roasting is widely used in the mineral concentration industry in China. Its key production quality index is magnetic tube recovery ratio (MTRR)

which cannot be measured online. Therefore

in practice MTRR is controlled by the operational optimal control technique. The design of operational optimal control strategy heavily relies on experiments conducted on real industrial process

to establish the dynamic response relationship between MTRR and the major control variables. Such practice is of high cost and risk. To solve this problem

this paper introduces a dynamic model of shaft furnace roasting process based on METSIM

a metallurgical process simulation package. The model connects to a process controller

which is similar to the control system used in practice

forming a semi-physical simulation system. The dynamic relationship between MTRR and the temperature of the burning chamber can be achieved by carrying out virtual simulation experiment on the proposed system. The model has been validated by real data. The proposed system can be used as a testing and experiment tool for the design of operational optimal control system.

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