Title :
Cascading failure assessment of complex systems based on Bayesian networks
Author :
Nuo Jia ; Hongzhang Jin ; Yanli Zhang ; Aili Zou
Author_Institution :
Coll. of Autom., Harbin Eng. Univ., Harbin, China
Abstract :
A cascading failure assessment method based on Bayesian network (BN) is proposed in order to improve the reliability of complex system and show cascading failure longitudinal relationship among system, subsystems and components. The probability index of cascading failure is given by using conditional probability of BN which is transformed from fault tree (FT). After that, junction tree inference algorithm is adopted here to carry out bidirectional reasoning to exhibit quantitative assessment of influence on system failure due to subsystem or component failure and possibility of component failure under the condition of system failure. Finally, the method is applied to cascading failure assessment of 2-bus automatic alarm subsystem in ship wet sprinkler system to demonstrate its effectiveness.
Keywords :
alarm systems; belief networks; inference mechanisms; probability; reliability; ships; trees (mathematics); 2-bus automatic alarm subsystem; Bayesian networks; bidirectional reasoning; cascading failure assessment method; cascading failure longitudinal relationship; cascading failure probability index; complex system reliability; conditional probability; fault tree; junction tree inference algorithm; quantitative assessment; ship wet sprinkler system; Bayes methods; Inference algorithms; Marine vehicles; Power system faults; Power system protection; Reliability; Bayesian networks; cascading failure assessment; complex system; junction tree inference algorithm; ship wet sprinkler system;
Conference_Titel :
Mechatronics and Automation (ICMA), 2013 IEEE International Conference on
Conference_Location :
Takamatsu
Print_ISBN :
978-1-4673-5557-5
DOI :
10.1109/ICMA.2013.6618160
