Variable Time Delay-Based Granger Causality Approach Integrated with Dynamic Coupling Analysis for Root Cause Diagnosis in Chemical Processes-Reference-Cited by-同舟云学术

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Variable Time Delay-Based Granger Causality Approach Integrated with Dynamic Coupling Analysis for Root Cause Diagnosis in Chemical Processes

Published:2024-05-17 Issue:7 Volume:41 Page:1955-1976
ISSN:0256-1115
Container-title:Korean Journal of Chemical Engineering
language:en
Short-container-title:Korean J. Chem. Eng.

Author:

Li Yuting,Yang Xu,Huang Jian,Gao Jingjing

Funder

National Natural Science Foundation of China

State Administration of Foreign Experts Affairs

Fundamental Research Funds for the Central Universities of Beijing University of Chemical Technology

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11814-024-00180-8.pdf

Reference36 articles.

1. Y.J. Zhou, K. Xu, F. He, Root cause diagnosis in multivariate time series based on modified temporal convolution and multi-head self-attention. J. Process Control 117, 14–25 (2022)

2. H. Liu, D.C. Pi, S.Y. Qiu, X.X. Wang, C. Chang, Data-driven identification model for associated fault propagation path. Measurement 188, 110628 (2022)

3. W.Q. Wu, C.Y. Song, J. Liu, J. Zhao, Data-knowledge-driven distributed monitoring for large-scale processes based on digraph. J. Process Control 109, 60–73 (2022)

4. H.T. Zhang, Q.Q. Zhu, An improved dynamic latent variable regression model for fault diagnosis and causal analysis. Can. J. Chem. Eng. 101(6), 3333–3350 (2023)

5. H.J. Zhang, K.X. Peng, L. Ma, A systematic nonstationary causality analysis framework for root cause diagnosis of faults in manufacturing processes. Control Eng. Pract. 131, 105404 (2023)

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