System-Level Vulnerability Assessment for EME: From Fault Tree Analysis to Bayesian Networks—Part I: Methodology Framework

2016 ◽  
Vol 58 (1) ◽  
pp. 180-187 ◽  
Author(s):  
Congguang Mao ◽  
Flavio Canavero
Keyword(s):  
Bayesian Networks ◽  
Vulnerability Assessment ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
System Level ◽  
Tree Analysis

Application of Bayesian Network in Safety Evaluation of Metro Construction

2013 ◽  
Vol 838-841 ◽  
pp. 1463-1468
Author(s):  
Xiang Ke Liu ◽  
Zhi Shen Wang ◽  
Hai Liang Wang ◽  
Jun Tao Wang
Keyword(s):  
Bayesian Networks ◽  
Bayesian Network ◽  
Posterior Probability ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Safety Evaluation ◽  
Tree Analysis ◽  
Tunnel Blasting ◽  
Better Than

The paper introduced the Bayesian networks briefly and discussed the algorithm of transforming fault tree into Bayesian networks at first, then regarded the structures impaired caused by tunnel blasting construction as a example, introduced the built and calculated method of the Bayesian networks by matlab. Then assumed the probabilities of essential events, calculated the probability of top event and the posterior probability of each essential events by the Bayesian networks. After that the paper contrast the characteristics of fault tree analysis and the Bayesian networks, Identified that the Bayesian networks is better than fault tree analysis in safety evaluation in some case, and provided a valid way to assess risk in metro construction.

Fault Tree Analysis Aimed to Design and Implement On-Field Fault Detection and Isolation Schemes for SOFC Systems

2010 ◽  
Author(s):  
Ivan Arsie ◽  
Arturo Di Filippi ◽  
Dario Marra ◽  
Cesare Pianese ◽  
Marco Sorrentino
Keyword(s):  
Fault Detection ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Diagnostic Techniques ◽  
Fault Detection And Isolation ◽  
System Level ◽  
Diagnostic Tools ◽  
Specific Component ◽  
Tree Analysis ◽  
Diagnostic Applications

The paper focuses on a methodological study oriented towards the development of diagnostic tools for on-field operating solid oxide fuel cell (SOFC) systems. This work is motivated by the increasing demand for diagnostic techniques aimed at both increasing durability and fully exploiting SOFC benefits throughout system lifetime. Nowadays many SOFC diagnostic applications are available in lab-controlled environment, but few studies are proposed for on-field use. Main contribution of this work is thus the development of suited methodologies for detection and isolation of typical SOFC system faults. Fault tree analysis (FTA) is proposed as a tool for the isolation process. For each specific component, the most significant faults are correlated, via a top-down approach, to the corresponding symptom(s). The knowledge gained through the FTA is exploited to understand the mutual interactions among all devices within the entire SOFC system. Such an approach resulted in the definition of a fault signature matrix that conveniently links system-level symptoms to specific component faults. Such an approach is therefore suitable to perform fault detection and isolation (FDI) of an SOFC system as a whole.

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