基于K-Means聚类的炼钢生产过程控制目标优化
首发时间:2018-09-30
摘要:炼钢过程包括:铁水预处理、转炉(电弧炉)和精炼工序,是钢铁产品质量控制的核心环节之一。为了实现炼钢过程产品质量的窄窗口控制,本文基于K-means聚类方法和炼钢机理分析,提出了炼钢过程各工序的控制目标优化方法。进行了案例分析,分析结果验证了该方法的有效性。在现有生产条件下,RH处理后的炉次命中率可以从86.2%升至92.0%。
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Optimization of steelmaking process control objectives based on K-Means clustering
Abstract:Steelmaking process includes hot metal pretreatment, converter (electric arc furnace) and refining process, which are the key processes in quality control of iron and steel products. In order to realize the narrow window control of the quality of the steelmaking process, based on the K-means clustering method and the analysis of the steelmaking mechanism, the optimization method for the control target of each steelmaking process was put forward. A case study was carried out to verify the effectiveness of the method. Under the existing production conditions, the furnace quality rate with RH treatment can be increased from 86.2% to 92.0%.
Keywords: Steelmaking process quality control K-means controlling objectives
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基于K-Means聚类的炼钢生产过程控制目标优化
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