Overall
- Language
- English
- Conflict of Interest
- In relation to this article, we declare that there is no conflict of interest.
- Publication history
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Received December 5, 2023
Accepted May 1, 2024
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This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Most Cited
Variable Time Delay-Based Granger Causality Approach Integrated with Dynamic Coupling Analysis for Root Cause Diagnosis in Chemical Processes
Abstract
Due to the dynamic characteristics of chemical industry systems, the time delay tends to be variable, which leads to changes
in coupling intensity. This is contrary to the assumptions in causal analysis, where the time delay and the coupling are
typically assumed to be fi xed. In this article, a new causal analysis framework that integrates Granger causality with dynamic
coupling analysis based on variable time delay is proposed, which not only fully considers the variable time delay in dynamic
processes, but also studies the dynamic change of coupling intensity. First, the moving window is used to explore real-time
variations in average mutual information to obtain the variable time delay. Then by further analyzing the normal data, the
dynamic coupling relationship caused by continuous changes in time delay is distinguished. On this basis, the extended
Granger causality and convergent cross mapping are integrated to relax their assumptions of fi xed time delay and coupling.
Finally, the direction of fault propagation is guided by the results of causal analysis. The eff ectiveness of proposed method
is demonstrated by chemical industry case studies.
