• DocumentCode
    638930
  • 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
  • fYear
    2013
  • fDate
    4-7 Aug. 2013
  • Firstpage
    1636
  • Lastpage
    1640
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation (ICMA), 2013 IEEE International Conference on
  • Conference_Location
    Takamatsu
  • Print_ISBN
    978-1-4673-5557-5
  • Type

    conf

  • DOI
    10.1109/ICMA.2013.6618160
  • Filename
    6618160