Reliability Analysis of Nonrepairable Cold-Standby Systems Using Sequential Binary Decision Diagrams

2012 ◽  
Vol 42 (3) ◽  
pp. 715-726 ◽  
Author(s):  
Liudong Xing ◽  
Ola Tannous ◽  
Joanne Bechta Dugan
Keyword(s):  
Reliability Analysis ◽  
Binary Decision Diagrams ◽  
Decision Diagrams ◽  
Binary Decision ◽  
Cold Standby

scholarly journals Reliability Dynamic Analysis by Fault Trees and Binary Decision Diagrams

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 324 ◽  
Author(s):  
Fausto Pedro García Márquez ◽  
Isaac Segovia Ramírez ◽  
Behnam Mohammadi-Ivatloo ◽  
Alberto Pliego Marugán
Keyword(s):  
Wind Turbine ◽  
Reliability Analysis ◽  
Binary Decision Diagrams ◽  
Computational Cost ◽  
Optimal Order ◽  
Decision Diagrams ◽  
Breadth First Search ◽  
Ranking Methods ◽  
Binary Decision

New wind turbines are becoming more complex and reliability analysis of them rising in complexity. The systems are composed of many components. Fault tree is used as an useful tool to analyze these interrelations and provide a scheme of the wind turbine, to get a quick overview of the behavior of the system under certain conditions of the components. However, it is complicated and in some cases not possible, to identify the conditions that would generate a wind turbine failure. A quantitative and qualitative reliability analysis of the wind turbine is proposed in this study. Binary decision diagrams are employed as a suitable and operational method to facilitate this analysis and to get an analytical expression by the Boolean functions. The size of the binary decision diagram, i.e., the computational cost for solving the problem, has an important dependence on the order of the components or events considered. Different heuristic ranking methods are used to find an optimal order or one closed, and to validate the results: AND, level, top-down-left-right, deep-first search and breadth-first-search. Birnbaum and criticality importance measures are proposed to evaluate the relevance of each component. This analysis leads to classify the events according to their importance with respect to the probability of the top event. This analysis provides the basis for making medium and long-term maintenance strategies.

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