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Updated: Jan 13, 2026

Blast Quantification Using Hopkinson Pressure Bars

Blast Quantification Using Hopkinson Pressure Bars

Published on: July 5, 2016

高炉传感器收集的数据

Vladimir Borisovich Trofimov¹

¹Department of Automated Control Systems, National University of Science & Technology (MISIS), Leninsky pr., 4/1, Moscow, Russian Federation.

|October 29, 2025

概括

本研究提出了高炉炼技术参数的验证数据集. 每小时记录的数据包括用于流程优化和分析的关键变量.

科学领域:

金工程金工程金工程
过程控制过程控制
数据科学数据科学数据科学

背景情况:

高炉炼产生复杂的,高维数据.
原始数据通常含有噪音和异常值,需要仔细处理.
精确的技术参数对于高效的铁生产至关重要.

研究的目的:

提供高炉炼参数的验证,同步数据集.
促进过程监测和优化方面的研究.
为了使高炉运行数据驱动模型的开发.

主要方法:

从调度系统收集数据.
数据的清理,验证和异常值的删除.
在每小时间隔记录的时间序列数据的同步.

主要成果:

创建了两个数据集:原始,杂的数据和验证的,类标记的数据.
记录的关键参数包括气体压力,温度,成分 (CO2,H2) 和爆炸条件.
热金属中的含量也包括在内.

结论:

经过验证的数据集为高炉研究提供了可靠的资源.
清洁,同步数据的可用性支持先进的分析技术.
这项工作有助于提高炼过程的理解和控制.

关键词:

预测预测预测预测热金属中的含量时间序列时间序列

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