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首页> 外文期刊>ISIJ international >Identification of the Optimal Control Center for Blast Furnace Thermal State Based on the Fuzzy C-means Clustering
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Identification of the Optimal Control Center for Blast Furnace Thermal State Based on the Fuzzy C-means Clustering

机译：基于模糊C-均值聚类的高炉热态最优控制中心识别

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It is required to maintain silicon content in hot metal ([Si]) at a stable level to ensure smooth operation of the blast furnace ironmaking process. However, current blast furnace control strategy always leads to frequent fluctuation of silicon content in hot metal. To stabilize blast furnace operation, this article attempts to identify the optimum control centre of silicon content through exploring the operational data of blast furnace ironmaking process. A quantitative analysis of the impact of thermal state on the smelting efficiency and intensity is presented by combining wavelet denoising and fuzzy c-means (FCM) clustering. Simulation results show that the commonly adopted mean value of historical data is not necessarily the optimum state of blast furnace operation. There exists some optimum state lower than the mean value, under which higher smelting efficiency and intensity can be achieved. It is also proved that the “low silica smelting practice” attempt in the steel industry is feasible and meaningful.
机译：需要将铁水中的硅含量保持在稳定的水平，以确保高炉炼铁工艺的顺利进行。然而，当前的高炉控制策略总是导致铁水中硅含量的频繁波动。为了稳定高炉操作，本文试图通过探索高炉炼铁工艺的操作数据来确定最佳的硅含量控制中心。结合小波去噪和模糊c均值（FCM）聚类，对热态对熔炼效率和强度的影响进行了定量分析。仿真结果表明，历史数据的均值不一定是高炉运行的最佳状态。存在一些低于平均值的最佳状态，在此状态下可以实现更高的熔炼效率和强度。还证明了在钢铁行业进行“低硅冶炼实践”的尝试是可行和有意义的。

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