An Application of Fuzzy Fault Tree Analysis to Uncontained Events of an Areo-Engine Rotor

Li, Yanfeng; Huang, Hong‐Zhong; Zhu, Shun‐Peng; Liu, Yu; Xiao, Ning‐Cong

doi:10.1515/tjj-2012-0032

Cited by 9 publications

(8 citation statements)

References 12 publications

(27 reference statements)

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“…It reflects the lower bound of the probability that the hypothesis A is true. As opposite to equation (1), the mass function mðAÞ can be computed by the belief function through the Mo¨bius transformation, 27 and it can be written as…”

Section: The Belief Functionmentioning

confidence: 99%

“…As engineered systems become more complicated and sophisticated, high reliability and safety are required for these systems. Various probabilistic tools have been investigated to analyze the reliability of complex systems, including the fault tree analysis (FTA), 1 the Markov chains, 2,3 the stochastic petri nets, 4 and the Bayesian networks. 5 Among them, the FTA is one of the prominent methods and received extensive applications in industry.…”

Section: Introductionmentioning

confidence: 99%

“…5 Among them, the FTA is one of the prominent methods and received extensive applications in industry. 1,6 The FTA was first introduced by the Bell Laboratories 7 to evaluate the failure probability of a ballistic missile. Recently, a sizable amount of efforts has been made to enhance the FTA method to accommodate a diversity of systems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evidential network-based failure analysis for systems suffering common cause failure and model parameter uncertainty

Zuo

Xiahou

Liu

2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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The fault tree analysis has been extensively implemented in failure analysis of engineered systems. In most cases, the probabilities of basic events, e.g. components’ failures, are represented by crisp values in the fault tree analyses. However, due to lack of knowledge, scarcity of failure data, or vague judgments from experts, it may produce parameter uncertainty associated with degradation models of components/systems, and such model parameter uncertainty can be quantified by the epistemic uncertainty. In addition, the common cause failure, related to the simultaneous failures of two or more components caused by physical interactions or shared environments, often exists in advanced engineered systems and computing systems. In this paper, by considering both the common cause failure and the epistemic uncertainty associated with model parameters, an evidential network model embedded with common cause failure is proposed to facilitate system failure analysis. The detailed transformations from some logic gates of a fault tree to an evidential network model are given. Moreover, the conditional belief mass tables are constructed to quantify the dependency between the states of components and the entire system. An engineering case of an aero-engine oil system, together with comparative results, is presented to demonstrate the effectiveness of the proposed evidential network model.

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Section: The Belief Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evidential network-based failure analysis for systems suffering common cause failure and model parameter uncertainty

Zuo

Xiahou

Liu

2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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show abstract

“…According to the work by Lai and Chen, 13 Nakagawa and Murthy, 14 Satow and Osaki 15 and Li and colleagues, [16][17][18] the failure interaction can be classified into three categories. The first one is that the failure of one component will result in the immediate failure of other components.…”

Section: Interactive Failure Rate Analysismentioning

confidence: 99%

A failure rate interaction model for two-component systems based on copula function

Peng

Huang

2016

Proceedings of the Institution of Mechanical Engineers, Part O:

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Failure rate estimation of a component or a system plays an important role for reliability analysis and maintenance decision-making. In some systems, failure mechanisms from different components interact with each other, and the interaction may accelerate the failure procedure of a certain component. Therefore, it is necessary to consider the correlation of failures from different components for obtaining an accurate reliability prediction. In this article, a failure rate interaction model for two components based on copula function is proposed. In this model, the failure correlation of two components in the same system is estimated using copula function. Then, the joint failure probability distribution function of the two components and the conditional failure probability distribution of failures for each component are determined. Finally, the failure rate is calculated considering the correlation of failures between components, and the failure rate estimation of the oil pump and oil seal is presented and discussed to illustrate the validity of the proposed method.

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“…1 FTA is usually conducted at two levels: a qualitative level, in which all the possible combinations of basic events which lead to the occurrence of a top event (TE) are determined; and a quantitative level, in which the probability of the occurrence of the TE and other quantitative reliability indexes are calculated. Li et al 2 investigated the application of FTA method for the uncontained fault events of an aero-engine rotor. Taking into account common cause failure, Li et al 3 proposed a method to investigate the reliability of train rear-end collision accident considering common cause failure.…”

Section: Introductionmentioning

confidence: 99%

Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers

Liu

et al. 2015

Proceedings of the Institution of Mechanical Engineers, Part O:

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In the calculation of dynamic fault trees, the existing state space–based methods, such as Markov chain method, are basically global-state models, which make the solution procedure very complex. Bayesian networks have become a popular tool to build probability models and conduct inference for reliability design and analysis in various industry fields. The “state explosion” problem can be alleviated by Bayesian networks. Furthermore, to obtain sufficient failure data sets in real engineering systems is extremely difficult and thus causes the parametric uncertainty in failure data. To address these issues, a novel dynamic fault tree analysis method based on the continuous-time Bayesian networks under fuzzy numbers is proposed in this article. The probability distributions under fuzzy numbers for the output variable of dynamic logic gates are determined. The calculation of fuzzy failure probability of a system is presented. Finally, an example is given to demonstrate the effectiveness of the proposed method.

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An Application of Fuzzy Fault Tree Analysis to Uncontained Events of an Areo-Engine Rotor

Cited by 9 publications

References 12 publications

Evidential network-based failure analysis for systems suffering common cause failure and model parameter uncertainty

Evidential network-based failure analysis for systems suffering common cause failure and model parameter uncertainty

A failure rate interaction model for two-component systems based on copula function

Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers

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