Hierarchical Causal Graph-Based Fault Root Cause Diagnosis and Propagation Path Identification for Complex Industrial Process Monitoring-Reference-Cited by-同舟云学术

Hierarchical Causal Graph-Based Fault Root Cause Diagnosis and Propagation Path Identification for Complex Industrial Process Monitoring

Published:2023 Issue: Volume:72 Page:1-11
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Dong Jie¹^ORCID,Cao Keren¹^ORCID,Peng Kaixiang²^ORCID

Affiliation:

1. Key Laboratory of Knowledge Automation for Industrial Processes of the Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China

2. Key Laboratory of Knowledge Automation for Industrial Processes of the Ministry of Education, School of Automation and Electrical Engineering, and the National Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10105856.pdf?arnumber=10105856

Reference31 articles.

1. Root cause analysis of process fault conditions on an industrial concentrator circuit by use of causality maps and extreme learning machines

2. A novel dynamic PCA algorithm for dynamic data modeling and process monitoring

3. Fault Root Cause Diagnosis Method Based on Recurrent Neural Network and Granger Causality

4. Cause-and-effect analysis in chemical processes utilizing XML, plant connectivity and quantitative process history

5. A systematic nonstationary causality analysis framework for root cause diagnosis of faults in manufacturing processes

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