Next Article in Journal
Mutual Information Loss in Pyramidal Image Processing
Previous Article in Journal
GAP: Geometric Aggregation of Popularity Metrics
Previous Article in Special Issue
SAVTA: A Hybrid Vehicular Threat Model: Overview and Case Study
Open AccessArticle

Reliability Dynamic Analysis by Fault Trees and Binary Decision Diagrams

1
Ingenium Research Group, University of Castilla-La Mancha, 13071 Ciudad Real, Spain
2
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran
3
Business & Marketing School, ESIC, 28043 Madrid, Spain
*
Authors to whom correspondence should be addressed.
Information 2020, 11(6), 324; https://doi.org/10.3390/info11060324
Received: 29 April 2020 / Revised: 10 June 2020 / Accepted: 11 June 2020 / Published: 15 June 2020
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. View Full-Text
Keywords: fault tree; binary decision diagrams; wind turbines; maintenance management; wind energy; dynamic analysis fault tree; binary decision diagrams; wind turbines; maintenance management; wind energy; dynamic analysis
Show Figures

Figure 1

MDPI and ACS Style

García Márquez, F.P.; Segovia Ramírez, I.; Mohammadi-Ivatloo, B.; Marugán, A.P. Reliability Dynamic Analysis by Fault Trees and Binary Decision Diagrams. Information 2020, 11, 324.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop