Data-driven monitoring of raceway dynamics in ironmaking blast furnaces

炼铁高炉滚道动力学的数据驱动监测

• 批准号: LP200100106
• 负责人: Prof Yansong Shen
• 金额: $ 37.72万
• 依托单位: The University of New South Wales
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2021
• 资助国家: 澳大利亚
• 起止时间: 2021-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP200100106
• 关键词: Data; driven; monitoring; raceway; dynamics

Raceway dynamics in ironmaking blast furnaces affect operational stability and cost considerably, yet their dynamic behaviour has not been well monitored online. The project aims to develop a data-driven model for monitoring the internal state of gas-solid-powder reacting flow in the raceway and predicting raceway anomalies online. It will be achieved by combining particle-fluid numerical simulations with data processing and reduced-order state observer, supported by lab/plant experiments, and collaborating with two industry partners from coal and steel industries. The project outcomes including codes, models and raceway control strategies can help promote Australian metallurgical coal's global markets and ultimately the Australian economy.

炼铁高炉滚道动力学对高炉的运行稳定性和成本影响很大，但其动力学特性还没有得到很好的在线监测。该项目旨在开发一个数据驱动的模型，用于监测滚道内气-固-粉反应流动的内部状态，并在线预测滚道异常。它将通过将颗粒流体数值模拟与数据处理和降阶状态观测器相结合，在实验室/工厂实验的支持下，与煤炭和钢铁行业的两个行业合作伙伴合作来实现。项目成果包括规范、模型和滚道控制策略，有助于促进澳大利亚冶金煤的全球市场，最终促进澳大利亚经济。