A Dynamic Fault Tree Analysis Method Based on Discrete-time Bayesian Network for the Core Processing System of IMA

2020 ◽  
Author(s):  
Qin Zhang ◽  
Lisong Wang ◽  
Hao Rong ◽  
Qingfan Gu ◽  
Yang Hong ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Discrete Time ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Processing System ◽  
Analysis Method ◽  
Tree Analysis ◽  
The Core ◽  
Dynamic Fault Tree

scholarly journals T-S Dynamic Fault Tree Analysis Method

2019 ◽  
Vol 55 (16) ◽  
pp. 17
Author(s):  
YAO Chengyu ◽  
RAO Leqing ◽  
CHEN Dongning ◽  
HOU Xin ◽  
Lü Shijun ◽  
...  
Keyword(s):  
Fault Tree ◽  
Fault Tree Analysis ◽  
Analysis Method ◽  
Tree Analysis ◽  
Dynamic Fault Tree

Cause factors in emergency process of fire accident for oil–gas storage and transportation based on fault tree analysis and modified Bayesian network model

2018 ◽  
Vol 29 (5) ◽  
pp. 802-821 ◽  
Author(s):  
Changfeng Yuan ◽  
Hui Cui ◽  
Bin Tao ◽  
Siming Ma
Keyword(s):  
Bayesian Network ◽  
Network Model ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Analysis Method ◽  
Bayesian Network Model ◽  
Tree Analysis ◽  
Oil Gas ◽  
Emergency Process ◽  
Fire Accident

From the perspective of the safety of emergency process, in this paper, we put forward a new analysis method of cause factors based on fault tree analysis and modified Bayesian network in emergency process of fire accident for oil–gas storage and transportation. Nineteen cause factors are found based on the statistical analysis of actual accident cases. We adopt fault tree analysis method and Bayesian network model to analyze cause factors qualitatively and quantitatively. In order to more accurately determine the quantitative influencing degree of each cause factor, the conditional probabilities in Bayesian network are modified by using expert scoring method and modified Bayesian network model is established. Finally, the proposed method is applied to analyze cause factors in emergency process of two practical accident cases. Research results have an important scientific significance to reveal evolution mechanism of secondary accidents in emergency process and ensure system safety in whole life cycle.

Dynamic Fault Tree Based on Weibull Distribution

2011 ◽  
Vol 308-310 ◽  
pp. 1322-1327
Author(s):  
Wei Gang Guo ◽  
Wei Han ◽  
Shu Yan Liu
Keyword(s):  
Markov Model ◽  
Weibull Distribution ◽  
Markov Models ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Analysis Method ◽  
Tree Analysis ◽  
Dynamic Fault Tree ◽  
Complex Interactions ◽  
Quantitative Analysis Method

The fault tree analysis is a widely used method for evaluation of systems reliability and safety. Dynamic fault tree (DFT) extend traditional FT by defining additional gates called dynamic gates to model these complex interactions. Markov models are used in solving dynamic gates. However, state space becomes too large for calculation with Markov models when the number of gate inputs increases. In addition, Markov model is applicable for only exponential failure and repair distributions. But in engineering, the failure mode is mostly obeyed to weibull distribution for mechanism and electronic units. Combined the weibull distribution and Markov model, this paper presents dynamic fault tree quantitative analysis method based on weibull distribution.

Gear Transmission Fault Tree Analysis Based on Bayesian Network

2012 ◽  
Vol 499 ◽  
pp. 482-486
Author(s):  
Zhen Zhou ◽  
Jin Biao Zhang ◽  
De Zhong Ma ◽  
Yong Qin ◽  
Bo Zhang
Keyword(s):  
Fault Diagnosis ◽  
Failure Analysis ◽  
Bayesian Network ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Gear Transmission ◽  
Analysis Method ◽  
Tree Analysis ◽  
Reliability Level ◽  
Mechanical Products

As a kind of important mechanical drive forms, the reliability level of gear transmission directly haves an effect on the performance of mechanical products. At present, the analysis method of main gear transmission failure is the fault tree analysis, which has several limits in describing multi-state events. Bayesian network which is very suitable to express multi-state events and uncertain logical relationships has been successfully applied to fault diagnosis field. Therefore, Bayesian network is researched in this paper in order to improve gear transmission fault tree, solve limits of the fault tree out and make the failure analysis results more objective and accurate.

scholarly journals Continuous-time T-S Dynamic Fault Tree Analysis Method

2020 ◽  
Vol 56 (10) ◽  
pp. 244
Author(s):  
YAO Chengyu ◽  
WANG Chuanlu ◽  
CHEN Dongning ◽  
WEI Xing ◽  
Lü Shijun
Keyword(s):  
Continuous Time ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Analysis Method ◽  
Tree Analysis ◽  
Dynamic Fault Tree

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.

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