Information-modeling system for prediction of the composition and properties of final slag in a blast furnace in real time

A. Pavlov, N. Spirin, I. Gurin, V. Lavrov, V. A. Beginyuk, A. Istomin
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Abstract

The article considers general characteristics of the algorithm for prediction of the composition of the final slag in a blast furnace in real time. This algorithm is based on fundamental knowledge on the processes occurring in the furnace and general laws of transient processes. It allows predicting at the current moment of time and for every hour ten hours ahead. A linearized model of the blast furnace process and a natural-mathematical approach are used. The model takes into account the dynamic characteristics of blast furnaces in various impact channels, which change and depend on the type of impact, operating parameters of the furnaces and properties of the melted raw material. This makes it possible to adjust the model to operating conditions of the object, to take into account changes in the composition and properties of iron ore and coke, blast and regime parameters of blast furnace smelting when modeling. The software of the information-modeling system for prediction of the composition and properties of the final slag in a blast furnace in real time was developed in the C# programming language based on the ASP.NET MVC framework using the .NET 5 cross-platform. The web application includes the following main functions: visualization of change APCS parameters and design parameters over time; slag mode diagnostics; modeling of transient processes of composition and properties of slag; prediction of slag composition and properties in real time and prediction history. The software architecture is described and its operation is illustrated. An assessment of the accuracy and reliability of the simulation results based on statistical indicators was carried out. The root-mean-square deviation of the predicted basicity of the CaO/SiO2 slag from that measured at taps is 0.023, the prediction reliability is 92 %, which indicates a satisfactory agreement between the predicted and actual values of the content of individual components in the slag. The information modeling system developed on the basis of the presented algorithm is integrated into the information system of the blast furnace shop of PJSC Magnitogorsk Iron and Steel Works.
实时预测高炉终渣组成和性能的信息建模系统
本文考虑了实时预测高炉终渣成分算法的一般特点。该算法基于炉内过程的基本知识和瞬态过程的一般规律。它可以预测当前时刻和未来十小时的每小时。采用了高炉过程的线性化模型和自然数学方法。该模型考虑了不同冲击通道中高炉的动态特性,这些特性随冲击类型、高炉运行参数和熔体原料性质的变化而变化。这使得模型可以根据对象的操作条件进行调整,在建模时考虑到铁矿石和焦炭的成分和性质、高炉冶炼的高炉和状态参数的变化。基于ASP,采用c#编程语言开发了高炉终渣成分及性能实时预测信息建模系统软件。.NET MVC框架使用。NET 5跨平台。web应用程序包括以下主要功能:APCS参数和设计参数随时间变化的可视化;渣模诊断;炉渣成分与性能的瞬态过程建模实时预测炉渣成分和性能,预测历史。介绍了该系统的软件体系结构,并对其操作进行了说明。基于统计指标对仿真结果的准确性和可靠性进行了评估。预测结果表明,CaO/SiO2矿渣碱度与实测碱度的均方根偏差为0.023,预测可靠性为92%,矿渣中各组分含量的预测值与实测值吻合较好。在此基础上开发的信息建模系统已集成到PJSC马格尼托戈斯克钢铁厂高炉车间信息系统中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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