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论文类型：期刊论文

发表时间：2018-03-01

发表刊物：IEEE-CAA JOURNAL OF AUTOMATICA SINICA

收录刊物：SCIE、EI

卷号：5

期号：2

页面范围：587-594

ISSN号：2329-9266

关键字：Blast furnace gas system; causal fuzzy C-means (CFCM) clustering; causality diagram; scheduling

摘要：Rational use of blast furnace gas (BFG) in steel industry can raise economic profit, save fossil energy resources and alleviate the environment pollution. In this paper, a causality diagram is established to describe the causal relationships among the decision objective and the variables of the scheduling process for the industrial system, based on which the total scheduling amount of the BFG system can be computed by using a causal fuzzy C-means (CFCM) clustering algorithm. In this algorithm, not only the distances among the historical samples but also the effects of different solutions on the gas tank level are considered. The scheduling solution can be determined based on the proposed causal probability of the causality diagram calculated by the total amount and the conditions of the adjustable units. The causal probability quantifies the impact of different allocation schemes of the total scheduling amount on the BFG system. An evaluation method is then proposed to evaluate the effectiveness of the scheduling solutions. The experiments by using the practical data coming from a steel plant in China indicate that the proposed approach can effectively improve the scheduling accuracy and reduce the gas diffusion.