TY - GEN
T1 - System Resilience Assessment Based on FRAM and DBN
AU - Yuan, Yuan
AU - Yang, Jian
AU - Zhao, Tingdi
AU - Wu, Zongcheng
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In a social technology system, intricate interactions and coupling relationships exist among the various components. Traditional approaches struggle to effectively assess the effects of risk factors on the overall performance effectively of the system. To address the challenge of complex system resilience assessment, a method integrating the functional resonance analysis method (FRAM) and dynamic Bayesian network (DBN) is introduced. Initially, a functional interaction model for the mission process of the system is constructed based on FRAM, and underlying risk factors are identified. Subsequently, a DBN model is established, predicated based on the interconnections among risk factors, resilience attribute nodes, and the functional state of the system. Furthermore, the resilience of the system is quantified, and pivotal factors influencing it are ascertained through sensitivity analysis. As a case study, the carrier-based aircraft take-off and landing system is evaluated to proffer recommendations for ensuring the regular operation of the system.
AB - In a social technology system, intricate interactions and coupling relationships exist among the various components. Traditional approaches struggle to effectively assess the effects of risk factors on the overall performance effectively of the system. To address the challenge of complex system resilience assessment, a method integrating the functional resonance analysis method (FRAM) and dynamic Bayesian network (DBN) is introduced. Initially, a functional interaction model for the mission process of the system is constructed based on FRAM, and underlying risk factors are identified. Subsequently, a DBN model is established, predicated based on the interconnections among risk factors, resilience attribute nodes, and the functional state of the system. Furthermore, the resilience of the system is quantified, and pivotal factors influencing it are ascertained through sensitivity analysis. As a case study, the carrier-based aircraft take-off and landing system is evaluated to proffer recommendations for ensuring the regular operation of the system.
KW - DBN
KW - FRAM
KW - resilience
KW - system control theory
UR - http://www.scopus.com/inward/record.url?scp=85212278493&partnerID=8YFLogxK
U2 - 10.1109/ICRMS59672.2023.00051
DO - 10.1109/ICRMS59672.2023.00051
M3 - 会议稿件
AN - SCOPUS:85212278493
T3 - Proceedings - 2023 14th International Conference on Reliability, Maintainability and Safety, ICRMS 2023
SP - 238
EP - 242
BT - Proceedings - 2023 14th International Conference on Reliability, Maintainability and Safety, ICRMS 2023
A2 - Ren, Liming
A2 - Wong, W. Eric
A2 - Cheng, Hailong
A2 - Li, Xiaopeng
A2 - Wang, Shu
A2 - Liu, Kanglun
A2 - Li, Ruifeng
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Conference on Reliability, Maintainability and Safety, ICRMS 2023
Y2 - 26 August 2023 through 29 August 2023
ER -