文章基本信息

标题：Abnormal Condition Identification for the Electro-fused Magnesia Smelting Process
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作者：Hui Li ; Fuli Wang ; Hongru Li 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：18
页码：720-725
DOI：10.1016/j.ifacol.2018.09.278
语种：English
出版社：Elsevier
摘要：AbstractTo improve the performance of the abnormal condition identification, the multi-source information of the abnormal conditions in the electro-fused magnesia smelting process is analyzed in this paper. An intelligent abnormal condition identification method is proposed based on Bayesian network (BN). By analyzing three main abnormal conditions and the experience of the operators, the characteristics related with the abnormal conditions are extracted. The BNs are established to identify the abnormal conditions by fusing the multi-source information. The simulation results show that the proposed method can realize abnormal condition identification, distinguish the degree of the abnormal condition, and obtain better performance.
关键词：KeywordsAbnormal condition identificationBayesian networkElectro-fused magnesium furnacemulti-source information extractioninformation fusion