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Entropy 2017, 19(12), 663; https://doi.org/10.3390/e19120663

Capturing Causality for Fault Diagnosis Based on Multi-Valued Alarm Series Using Transfer Entropy

1
Shandong Electric Power Research Institute for State Grid Corporation of China, Jinan 250003, China
2
College of Urban Rail Transit and Logistics, Beijing Union University, Beijing 100101, China
3
Tsinghua Laboratory for Information Science and Technology and Department of Automation, Tsinghua University, Beijing 100084, China
*
Author to whom correspondence should be addressed.
Received: 1 November 2017 / Revised: 24 November 2017 / Accepted: 29 November 2017 / Published: 4 December 2017
(This article belongs to the Special Issue Entropy and Complexity of Data)
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Abstract

Transfer entropy (TE) is a model-free approach based on information theory to capture causality between variables, which has been used for the modeling and monitoring of, and fault diagnosis in, complex industrial processes. It is able to detect the causality between variables without assuming any underlying model, but it is computationally burdensome. To overcome this limitation, a hybrid method of TE and the modified conditional mutual information (CMI) approach is proposed by using generated multi-valued alarm series. In order to obtain a process topology, TE can generate a causal map of all sub-processes and modified CMI can be used to distinguish the direct connectivity from the above-mentioned causal map by using multi-valued alarm series. The effectiveness and accuracy rate of the proposed method are validated by simulated and real industrial cases (the Tennessee-Eastman process) to capture process topology by using multi-valued alarm series. View Full-Text
Keywords: multi-valued alarm series; direct causality; industrial alarm system; transfer entropy; modified condition mutual information; Tennessee-Eastman process multi-valued alarm series; direct causality; industrial alarm system; transfer entropy; modified condition mutual information; Tennessee-Eastman process
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Su, J.; Wang, D.; Zhang, Y.; Yang, F.; Zhao, Y.; Pang, X. Capturing Causality for Fault Diagnosis Based on Multi-Valued Alarm Series Using Transfer Entropy. Entropy 2017, 19, 663.

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