Iron and steel industry is one of the pillar industries in the national economy of China, and blast furnace iron making process is the basic production process of the iron and steel industry which is significant for the energy saving and consumption reduction. The shape of the blast furnace surface and its change process are closely related to the blast furnace condition. Currently, the relationship between them relies on the operator's experience to direct the production process in the results of the uncertainty of the blast furnace iron making process. It causes the high energy emission. This project will aim at the design and development of the theory and methods for the blast furnace surface modeling based on the complex blast furnace condition and the surface feature extraction during the blast furnace production process. The project will establish a new system to represent the surface model and define the characteristic parameters of the blast furnace surface from the height of the blast furnace to the longitudinal section line of the blast furnace surface until the 3D surface shape reconstruction. The research will investigate the model and algorithm of the relationship between the characteristic parameters and the furnace condition parameters of the blast furnace. The project will reconstruct the 3D surface model combined with the mechanism model of it based on our research results of the detection technology about 3D surface measurement and the real time phased array radar data. The surface clustering and matching algorithm will also be investigated in the research in order to establish the history information database of the blast furnace based on the combined information of the characteristic parameters of the surface and the furnace condition parameters of the blast furnace. The research will be a systematic study and theory of the blast furnace surface and it will radiate the related research fields. The research results have important theoretical significance and application value for the automation and visualization of the burden distribution control of the blast furnace together with the energy saving and the emission reduction.
钢铁工业是国民经济的支柱产业,高炉炼铁过程是钢铁工业的基础生产环节,对行业节能降耗有重要意义。高炉料面的形状和变化过程与炉况密切相关。目前对高炉料面与炉况之间的关系还凭炉长的感性经验,用于指导生产,导致高炉生产的不稳定性,使能耗居高不下。本项目在已有成果基础上,针对复杂的高炉生产过程,重点研究基于复杂炉况参数和特征提取的高炉料面建模理论与方法;建立从料面高度到纵向截面料线再到3D料面的表征模型及特征参数的新体系结构;研究高炉料面特征参数与炉况参数的关系模型和算法;利用课题组的相控阵雷达3D料面检测技术成果和实时数据,结合机理模型,重构三维料面模型;研究料面聚类与匹配算法,建立基于高炉料面特征与炉况参数相结合的高炉历史炉况信息库;形成一套比较系统的高炉料面研究的新理论、方法和技术,并可辐射相关领域的研究。研究成果对于高炉的布料控制自动化和可视化,节能减排,具有重要的理论意义和应用价值。
钢铁工业是国民经济的重要支柱产业,其存在着产能过剩矛盾加剧、自主创新水平不高、资源环境约束增强等问题,亟需优化当前生产工艺以进一步提高能源利用率、实现冶炼智能化。高炉炼铁是钢铁工业中最为重要的环节。实现高炉炼铁智能化和信息化,符合国家发展的需要。高炉炼铁中的布料制度是高炉四大操作制度之一。布料制度决定着炉料在炉内的分布状况。并且,布料制度是改善高炉炉况、保证高炉顺行常用的操作手段。布料环节机理复杂、环境恶劣、关键参数检测困难,其优化过程一直是研究热点。本研究从最先进的建模理论出发,基于真实高炉数据,建立了高炉料面从定义,特征提取到三维料面重构的一套完整的体系结构模型,而且建模的同时综合考虑了高炉炉况的状态参数的关联性,从而建立了最优料面库,为高炉可视化信息平台以及将来达到自动化的高炉操作提供理论依据。该项工作可以为高炉操作提供可靠的理论指导,具有重大的现实意义。具体来说:.(1)高炉料面形状能够反映高炉炉况信息,对高炉料面进行三维建模,具有重要的研究价值。本研究结合了高炉生产机理和数据驱动机理,实现了料面的精确建模。.(2)高炉运行错综复杂,研究高炉炉况参数与料面之间的关系,建立了高炉炉况关联性分析模型,为后续的高炉运行研究可以提供理论支持。.(3)对高炉历史料面与炉况进行了分类与匹配,建立了料面炉况信息库,能够为炉长操作高炉提供理论指导。
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数据更新时间:2023-05-31
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