TY - GEN
T1 - Dynamic Alarm Causality Analysis Method Integrating Monitoring Contribution and Transfer Entropy
AU - Luo, Yi
AU - Yang, Lingkai
AU - Nie, Linhao
AU - Xu, Yuan
AU - Zhu, Qunxiong
AU - Cheng, Jian
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Alarm flooding poses a significant safety hazard in industry. It is of paramount importance to uncover the causality behind alarm flooding at its early stages. On one hand, limited data samples make it challenging to accurately determine the causal relationships among alarms. On the other hand, a massive volume of data samples may lead to delays in causal inference. This paper proposes a Contribution and Transfer-entropy based Dynamic Alarm Causality analysis method (CT-DAC) to address this. CT-DAC reconstructs the contribution of each monitored variable to the dynamic anomalies in the system, enabling dynamic causal relationship mining based on limited data. This approach offers a faster and more accurate solution for identifying the initial alarm causality triggering alarm flooding problems. Experimental work conducted on the Tennessee Eastman Process demonstrates the superior performance of the CT-DAC method.
AB - Alarm flooding poses a significant safety hazard in industry. It is of paramount importance to uncover the causality behind alarm flooding at its early stages. On one hand, limited data samples make it challenging to accurately determine the causal relationships among alarms. On the other hand, a massive volume of data samples may lead to delays in causal inference. This paper proposes a Contribution and Transfer-entropy based Dynamic Alarm Causality analysis method (CT-DAC) to address this. CT-DAC reconstructs the contribution of each monitored variable to the dynamic anomalies in the system, enabling dynamic causal relationship mining based on limited data. This approach offers a faster and more accurate solution for identifying the initial alarm causality triggering alarm flooding problems. Experimental work conducted on the Tennessee Eastman Process demonstrates the superior performance of the CT-DAC method.
KW - Alarm Causality Analysis
KW - Contribution Analysis
KW - Tennessee Eastman Process
KW - Transfer Entropy
UR - http://www.scopus.com/inward/record.url?scp=85189304463&partnerID=8YFLogxK
U2 - 10.1109/CAC59555.2023.10450495
DO - 10.1109/CAC59555.2023.10450495
M3 - Conference contribution
AN - SCOPUS:85189304463
T3 - Proceedings - 2023 China Automation Congress, CAC 2023
SP - 9274
EP - 9278
BT - Proceedings - 2023 China Automation Congress, CAC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 China Automation Congress, CAC 2023
Y2 - 17 November 2023 through 19 November 2023
ER -