Abnormal condition identification and safe control scheme for the electro-fused magnesia smelting process. (May 2018)

• Record Type: Journal Article
• Authors: Li, Hui; Wang, Fuli; Li, Hongru
• Is Part Of: ISA transactions. Volume 76(2018)
• Page Start: 178
• Page End: 187
• Publication Date: 2018-05
• Subjects: Abnormal condition identification -- Bayesian network -- Case-based reasoning -- Fused magnesium furnace -- Safe control; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2018.03.011
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: This paper presents a control framework to identify the abnormal condition and make safe control scheme by fusing the related multi-source information based on the analysis of the abnormal exhausting condition in the electro-fused magnesia smelting process. For the abnormal condition identification, the case-based reasoning is used to infer the degree of the abnormal condition. When the similarity of the matched case doesn't exceed the set threshold, Bayesian network is used to infer the degree. For the safe control scheme, taking advantage of the idea of the remaining lifetime predicting, and the adjustment of the control variables is obtained. The application results show that the proposed method is effective and it owns better performance than the manual and the existing research results. Highlights: The multi-source information is used to analyze the abnormal exhausting condition. A control strategy is provided for the abnormal exhausting condition. The abnormal condition identification and safe control scheme are carried out. The case-based reasoning and Bayesian network are fused to identify the abnormity. The provided method has better performance than the method using sole information.