基于树回归的石灰竖窑煅烧质量预测模型
Prediction model of calcination quality of lime shaft kiln based on tree regression
王刚 1刘前 2程伟娇 1何飞 1藏庆涛 1张友臣 1曲长乐1
作者信息
- 1. 建龙西林钢铁有限公司,伊春 153025
- 2. 国家烧结球团装备系统工程技术研究中心,长沙 410205;中冶长天国际工程有限责任公司,长沙 410205
- 折叠
摘要
为了提高石灰竖窑生产过程的自动化控制精确性,建龙西林钢铁厂提出采用树回归动态预测成品CaO含量;针对控制参量多,耦合关系复杂的问题,采用相关性分析的方法优化参量,由此提高随机森林回归算法预测的可靠性;通过 9 个特征参量样本数据测试表明,树回归模型可以很好地适应石灰煅烧多因素、非线性的工业场景,预测结果精度满足工业控制要求.
Abstract
In order to improve the accuracy of automatic control of the production process of lime shaft kiln,Jianlong Xilin Iron and Steel Plant proposed to use tree regression to dynamically predict the CaO content of finished products.Aiming at the problem of many control parameters and complex coupling relationship,the correlation analysis method is used to optimize the parameters,so as to improve the reliability of the prediction of the random forest regression algorithm.Through the test of 9 characteristic parameter sample data,it is shown that the tree regression model can adapt well to the multi-factor and nonlinear industrial scene of gray stone calcination,and the accuracy of the prediction results meets the requirements of industrial control.
关键词
竖窑/石灰/过程控制/树回归/预测Key words
Shaft kiln/Lime/Process control/Tree regression/Prediction引用本文复制引用
出版年
2024
NETL
NSTL
万方数据