基于冷却壁温度信息粒度分析的高炉炉况智能预测方法
Intelligent prediction method for blast furnace condition based on information granules analysis of temperature in cooling stave
黄元峰 1杜胜 1胡杰 1吴敏 1Pedrycz Witold2
作者信息
- 1. 中国地质大学(武汉)自动化学院,湖北武汉 430074;复杂系统先进控制与智能自动化湖北省重点实验室,湖北武汉 430074;地球探测智能化技术教育部工程研究中心,湖北武汉 430074
- 2. 阿尔伯塔大学电子与计算机工程系,加拿大埃德蒙顿T6R 2V4
- 折叠
摘要
稳定顺行的高炉炉况对提高铁水的产量和质量有着至关重要的作用,渣皮稳定性是表征炉况的重要指标,而冷却壁温度常用于衡量渣皮稳定性.为了利用冷却壁温度的动态特征预测炉况,本文提出了一种基于冷却壁温度信息粒度分析的炉况智能预测方法.首先,采用斯皮尔曼相关性分析方法,选择与冷却壁温度波动相关性较大的参数.然后,针对选取的参数,利用信息粒化方法进行动态特征提取,构成信息粒.再次,利用相应参数的信息粒作为输入,建立基于支持向量回归的冷却壁温度信息粒预测模型,预测冷却壁温度信息粒.最后,结合炉况预测方法,分析预测的冷却壁温度信息粒完成炉况预测.利用实际钢铁企业数据进行的实验表明,所提方法能有效预测冷却壁温度信息粒与高炉炉况,为操作人员制定合理的布料策略提供了有力指导.
Abstract
The smooth condition of the blast furnace is important for the production and quality of the hot metal.The stability of the slag crust indicates the stability of the conditions in the blast furnace,and the temperature in the cooling stave can describe the stability of the slag crust.For predicting the conditions of the blast furnace according to the dynamic features of the temperature in the cooling stave,this study presented an intelligent method for predicting the conditions of the blast furnace based on the information granules of the temperature in the cooling stave.Firstly,the Spearman corre-lation analysis method is employed to select the parameters that affect the dynamic features of the temperature in the cooling stave.Secondly,the information granulation method is used to extract the dynamic features of the selected parameters and represent the data in a granular form.Then,the pre-diction model of the information granule of temperature in the cooling stave is built based on the sup-port vector regression with the inputs of information granules of the selected parameters,realizing the prediction of the temperature in the cooling stave.Finally,based on the predicted information gran-ules,the conditions of the blast furnace can be recognized using a condition prediction method.Ex-periments conducted using actual steel enterprise data show that the presented method can predict the conditions in the blast furnace and provides powerful guidance for operators to make a proper burden distribution decision-making strategy.
关键词
高炉/炉况预测/冷却壁温度/信息粒/时间序列Key words
blast furnace/condition prediction/temperature in cooling stave/information granule/time senes引用本文复制引用
基金项目
国家自然科学基金面上项目(62373336)
国家自然科学基金青年科学基金(62303431)
中国博士后科学基金面上项目(2023M733306)
湖北省自然科学基金青年基金(2022CFB582)
高等学校学科创新引智计划(111计划)(B17040)
出版年
2024
NETL
NSTL
万方数据