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

Li, Yanfeng; Mi, Jinhua; Liu, Yu; Yang, Yun; Huang, Hong‐Zhong

doi:10.1177/1748006x15588446

Cited by 45 publications

(38 citation statements)

References 35 publications

(35 reference statements)

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“…All the modules can be regarded as independent bottom events in the modularized FT model and the system reliability can be assessed by the PMS-BDD method [2] and the module reliabilities. If there are any dynamic logic gates, the modules are dynamic modules [30]. The reliability of the static modules can be easily evaluated by their own RBD.…”

Section: Simplified By Modularization Methodsmentioning

confidence: 99%

Reliability assessment of phased-mission systems under random shocks

Huang

et al. 2018

Reliability Engineering & System Safety

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Phased-mission systems (PMSs) are widely used, especially in the aerospace industry. As in the outer space there are many kinds of cosmic rays, such as the Galactic Cosmic Rays (GCR), randomly hitting on these systems and causing significant impact on the electronics inside or outside the equipment, a reliability model for PMSs considering both finite and infinite random shocks is proposed in this paper. The modularization method is used to simplify the state space model for each phase and reduce the amount of system states, and the Markov regenerative process (MRGP) is used to describe the hybrid components' lifetime distributions and the dynamic behaviors within the modules. Then, two kinds of scenarios, finite and infinite random shocks effect, are both integrated into the dynamic modules. For demonstration, a phased altitude and orbit control system (AOCS) subjected to infinite random shocks is illustrated to demonstrate the procedure of the proposed Monte Carlo simulation. Thirdly, the evaluated system reliability under infinite random shocks is compared with the same system without considering random shocks. At last, a sensitivity analysis is also provided for completion.

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Section: Simplified By Modularization Methodsmentioning

confidence: 99%

Reliability assessment of phased-mission systems under random shocks

Huang

et al. 2018

Reliability Engineering & System Safety

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“…In addition to classical fault trees, fuzzy numbers have also been used in dynamic fault trees (e.g. (Li, Huang, Liu, Xiao, & Li, 2012;Li, Mi, Liu, Yang, & Huang, 2015;Verma, Srividya, Prabhudeva, & Vinod, 2006;Yang, 2011)) and temporal fault trees (e.g. (Kabir, Edifor, Walker, & Gordon, 2014;Kabir, Walker, Papadopoulos, Rüde, & Securius, 2016)).…”

Section: Fuzzy Fault Treesmentioning

confidence: 99%

An overview of fault tree analysis and its application in model based dependability analysis

Kabir

2017

Expert Systems with Applications

325

134

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Fault Tree Analysis (FTA) is a well-established and well-understood technique, widely used for dependability evaluation of a wide range of systems. Although many extensions of fault trees have been proposed, they suffer from a variety of shortcomings. In particular, even where software tool support exists, these analyses require a lot of manual effort. Over the past two decades, research has focused on simplifying dependability analysis by looking at how we can synthesise dependability information from system models automatically. This has led to the field of modelbased dependability analysis (MBDA). Different tools and techniques have been developed as part of MBDA to automate the generation of dependability analysis artefacts such as fault trees. Firstly, this paper reviews the standard fault tree with its limitations. Secondly, different extensions of standard fault trees are reviewed. Thirdly, this paper reviews a number of prominent MBDA techniques where fault trees are used as a means for system dependability analysis and provides an insight into their working mechanism, applicability, strengths and challenges. Finally, the future outlook for MBDA is outlined, which includes the prospect of developing expert and intelligent systems for dependability analysis of complex open systems under the conditions of uncertainty.

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“…AND logic gate and OR logic gate are both in common use; and sometimes, other logic gates can be simplified to these two gates. DTBN means using continuous nodes with sampling the time of the failure distribution of components to analyze reliability of a system. Generally, the logic structure of a DTBN can be transformed and built by the FT of a system, then, the reliability of the system can be calculated based on DTBN reasoning.…”

Section: The Construction Of Dtbn For Uncertain Systemmentioning

confidence: 99%

Application of discrete‐time Bayesian network on reliability analysis of uncertain system with common cause failure

Song

Cheng

et al. 2018

Quality & Reliability Eng

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With the increasing complexity of engineering systems, reliability analysis and evaluation of systems with traditional methods can't meet practical engineering requirements. Based on limited experimental conditions, lack of data, complex structure models, insufficient cognitive abilities, and many other issues, people have to consider many uncertain factors in system reliability research. Besides, common cause failure (CCF) has become an important factor of system failure. In this paper, a discrete‐time Bayesian network (DTBN) associated with an eight‐rotor unmanned aerial vehicle (UAV) system is presented to discuss above problems. In this approach, the system is assumed as a two‐state system. After that, interval analysis theory is employed to deal with uncertainty. We consider the four sets of auxiliary propellers in the auxiliary power group as a 3/8 voting system, and β factor model is used to process CCF in the auxiliary power group. The proposed methods prove the validity of proposing interval analysis theory to solve uncertain problems and it is necessary to consider reducing or avoiding CCFs in system.

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

Cited by 45 publications

References 35 publications

Reliability assessment of phased-mission systems under random shocks

Reliability assessment of phased-mission systems under random shocks

An overview of fault tree analysis and its application in model based dependability analysis

Application of discrete‐time Bayesian network on reliability analysis of uncertain system with common cause failure

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