Integration of Fault Tree and Bayesian Network for Falling Risk of the Bridge Project—Precasting Prestressing Segmental Construction Method

2018 ◽  
pp. 102-119
Author(s):  
Ying-Chun Hung ◽  
Tung-Tsan Chen ◽  
Ting-Yu Yue
Keyword(s):  
Bayesian Network ◽  
Fault Tree ◽  
Construction Method ◽  
Falling Risk

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.

Study on Safety Evaluation of Flammable Solid Railway Transportation Based on the Bayesian Network

2013 ◽  
Vol 409-410 ◽  
pp. 1419-1422
Author(s):  
Feng Xu Li ◽  
Yue Fang Yang
Keyword(s):  
Quantitative Analysis ◽  
Bayesian Network ◽  
Fault Tree ◽  
Safety Evaluation ◽  
Railway Transportation ◽  
Loading And Unloading

Taking the fact that the fire explosion is the major danger during the transportation of flammable solid into account, the paper proposes a Fault Tree (FT) model about fire explosions affected greatly by packing, loading and unloading, vehicles, management and other factors, and converts the FT model into Bayesian Network (BN) one for quantitative analysis. Finally, the paper uses the data based on the BN model to prove that the model and algorithm are feasible.

Fault Diagnosis of the Foundation Brake Rigging System Based on Fault Tree and Bayesian Network

2016 ◽  
Vol 693 ◽  
pp. 1734-1740 ◽  
Author(s):  
Dan Wang ◽  
Ying Tian ◽  
Tai Yong Wang ◽  
Shi Feng Ye ◽  
Qiong Liu
Keyword(s):  
Complex System ◽  
Fault Diagnosis ◽  
Bayesian Network ◽  
Fault Tree ◽  
Fault Analysis ◽  
Inference Process ◽  
Tree Algorithm ◽  
Junction Tree ◽  
Bayesian Tree

Based on the analysis of the advantages and limits of the traditional fault tree and Bayesian network in fault diagnosis, the method that building the fault Bayesian network based on fault tree is proposed in this paper. The paper introduces the correspondences between elements of the fault tree and the fault Bayesian network, also describes the inference process of the junction tree algorithm in the fault Bayesian network. Then with the foundation brake rigging system of CRH380AL EMU as an example, we build up the fault tree, complete its transmission to the fault Bayesian network, proving the superiority of the fault Bayesian tree in fault analysis of the complex system at last.

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