燃料与化工 ›› 2023, Vol. 54 ›› Issue (2): 11-14.

• 煤焦技术 • 上一篇    下一篇

基于支持向量回归模型的焦炭质量智能分析

  

  1. (国家能源集团煤焦化有限责任公司,乌海 016000)
  • 出版日期:2023-03-23 发布日期:2023-04-04

Intelligent analysis of coke quality based on support vector regression model

  1. (National Energy Group Coal Coking Co.,Ltd.,Wuhai 016000,China)
  • Online:2023-03-23 Published:2023-04-04

摘要: 炼焦配煤是焦化企业生产过程中的一项关键工作。在钢铁工业中,焦炭在高温下的 CSR 和 CRI 质量指 标尤其重要。为了改善需依赖经验的传统配煤手段,基于原料煤指标预测焦炭质量的思路被提出。通过分析国 内外的一些预测方法,针对目前存在的不足进行改良,以西来峰焦化厂一期和二期为例,采用支持向量回归模型, 对焦炭的 CSR 和 CRI 这 2 个质量指标进行了智能分析,并通过系统分析训练样本比例与预测精度的关系,指明 进一步提升焦炭质量预测性能的工作方向。

关键词: 支持向量回归模型, CSR, CRI

Abstract:  Coal blending plays a key role in the production of a coking plant. In the iron and steel industry,CSR and CRI indexes of coke at high temperature are of particular importance. In order to improve traditional coal blending process that relies on expert experience,the idea of predicting coke quality based on raw coal indexes has been put forward. This article aims to analyze some coke quality prediction methods at home and abroad and improve the existing deficiencies. Taking Phase I and II projects of Xilaifeng coking plant as an example,this article conducts intelligent analysis, using SVR model,on CSR and CRI indexes of coke. By showing the relationship between training sample proportion and prediction accuracy,it further points out research orientation of coke quality prediction work.

Key words:  , Support vector regression(SVR), Coke strength after reaction(CSR), Coke reactivity index(CRI)

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