期刊
COMPUTERS & CHEMICAL ENGINEERING
卷 57, 期 -, 页码 173-180出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2013.05.011
关键词
Causal inference; Transfer entropy; Process safety
资金
- National Basic Research Program of China (973 Program) [2012CB720500]
Causality inference and root cause analysis are important for fault diagnosis in the chemical industry. Due to the increasing scale and complexity of chemical processes, data-driven methods become indispensable in causality inference. This paper proposes an approach based on the concept of transfer entropy which was presented by Schreiber in 2000 to generate a causal map. To get a better performance in estimating the time delay of causal relations, a modified form of the transfer entropy is presented in this paper. Case studies on two simulated chemical processes, including the benchmark Tennessee Eastman process are performed to illustrate the effectiveness of this approach. (C) 2013 Elsevier Ltd. All rights reserved.
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