面向指标优化的高炉布料过程建模与控制

Iron and steel industry is one of the pillar industries in the national economyof China, which is also an industry with high energy consumption and high emissionthat is dominated by the iron making process of blast furnaces.In the optimizationof blast furnace production, burden distribution plays a fundamental role, which is characterized by complicated operation mechanism, poor environment,difficultiesin the detection of key states and the optimization of production index. This project will develop new methodologies for the modeling, optimization and control of burden distribution process based on burden distribution control.The objective is to keep the proper operation of blast furnace and to optimize the production index. The details are as follows:. 1. Relationship between the production index and blast furnace status, and therelationship between the blast furnace status and the parameters in burden distribution;. 2. Methods of detection and reconstruction for the burden surface shape and gas flow distribution;. 3. Method of hybrid dynamic modeling based on mechanism analysis and data driven approach;. 4. Production index optimization methods for the furnace status diagnosis, evaluation and optimal setting; . 5. Control method for the process in which the blast furnace runs continually while the burden distribution executes only intermittently;. 6. Real-time visualization and simulation platform as well as application system;. This project will reveal the relationship between the production index and theburden distribution process, and lay the foundation for the full automation and visualization of blast furnace burden distribution process. As the outcome, a set of new theories, methods and technologies will be established for the modeling andcontrol of complicated production process that can optimize the production index and significantly contribute to the energy saving and emission reduction. . In summary, the project is significant scientifically and promising in engineering applications.

钢铁工业是我国国民经济的支柱，也是高耗能和高排放产业；高炉炼铁能耗和排放占其主要部分。高炉炼铁的布料过程是影响高炉指标优化最关键的环节，具有运行机理复杂、环境恶劣、关键参量检测和指标优化控制困难的特点。本项目以布料控制为手段，以高炉顺行和生产指标优化为目标，研究高炉布料过程建模、优化与控制的新理论与新方法。具体包括：分析高炉生产指标与高炉炉况、高炉炉况与布料参数之间的关联性；高炉料面形状与煤气流分布的检测与重建方法；高炉布料过程机理与数据驱动的混合动态建模方法；面向指标优化的炉况状态诊断评价与优化设定方法；高炉连续运行间歇布料过程控制理论与方法；高炉布料过程可视化实时仿真验证平台与应用系统设计。本项目研究将揭示生产指标和布料的关系，为高炉布料完全自动化和可视化奠定基础，实现指标优化，提高节能减排效果，为复杂生产过程建模与控制提供新的理论、方法和技术，具有重要科学意义和广阔应用前景。

钢铁工业是我国国民经济的支柱，高炉炼铁占钢铁工业能耗70%以上。高炉布料是影响生产指标关键环节，具有机理复杂、参量检测、指标优化和自动控制困难的特点，是典型的复杂工业生产过程。项目以生产指标优化为目标，以布料过程料面形状精准控制为手段，在料面的形状和料层运动实时检测与可视化、料面形状特征及料流运动模型构建、料面特征和煤气流分布以及炉况关联关系、基于生产指标优化的最优料面设定、料面形状的精准控制等方面进行了系统的研究，完成了研究内容，达到了研究目标，取得了如下创新成果：.（1）提出并构建了面向指标优化的大型高炉布料过程建模与控制体系，为实现料面精准控制和布料过程自动化奠定了基础；.（2）研发了阵列、摆动和相控阵雷达料面检测装置，实现了高炉料面形状的实时在线检测，获取了料层分布及运动数据，并实现了可视化；.（3）提出并建立了高炉料面线形和环形特征模型体系及建模方法，提出了基于料面形状和温度检测的煤气流分布模型，以及铁水硅含量和煤气利用率预测模型；.（4）建立了完善的从料罐到料面的料流运动和料面形成的模型体系；.（5）构建了多目标维度、多空间位置和多时间尺度的高炉生产过程指标体系，提出了基于铁水质量、燃料消耗、高炉顺行三大指标和料面特征的关系模型，形成了面向指标优化的期望料面形成机制，并建立了从料面特征到布料矩阵的映射方法；.（6）提出了高炉连续运行间歇布料过程控制方法，实现了料面和煤气流分布的精准控制；.（7）设计并实现了高炉布料过程可视化实时仿真验证平台与应用系统，该系统应用于宝武钢铁、南京钢铁和首钢集团公司，取得了明显的社会经济效益。.这些成果为实现高炉布料过程可视化和自动化奠定了基础，工业应用表明项目研究成果对高炉生产指标优化和节能减排有明显效果，并为复杂生产过程建模与控制提供了创新性的方法和技术，具有重要的科学意义和应用前景。