Modelling Features of Switching Device Errors for 2-out-of-3 and Sliding Redundancy Systems Based on k-Terminal Dynamic Fault Tree

Lobur, Mykhaylo; Stefanovych, Tetyana; Shcherbovskykh, Serhiy

doi:10.1109/cadsm.2019.8779334

Cited by 3 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For each

t \in T

X( t )

is a random variable. A typical continuous stochastic process

\{ X( t ), t \in T \}

is called a Markov process if its conditional probability satisfies the relation 40 . The conversion process is shown in Figure 6.…”

Section: The Realization Methods Of Dftmentioning

confidence: 99%

See 1 more Smart Citation

A review on the realization methods of dynamic fault tree

Zhu

Zhang

2022

Quality & Reliability Eng

View full text Add to dashboard Cite

Dynamic fault tree (DFT) is an extended technology of Fault tree analysis (FTA). It has been widely used in many fields and plays an important role in improving the security performance of the system. Although DFT has developed for many years, new research in recent years is still worthy of attention. In this study, the research status of different realization methods/analysis techniques of DFT is comprehensively reviewed. First, the development and research trend of DFT are described. Second, the research on dynamic gates and components in the analysis techniques is introduced in detail. Third, the mainstream realization methods of DFT, such as Markov chain, Bayesian network (BN) and so on, are summarized. At the same time, the application of other auxiliary analysis techniques is also introduced. Then, based on the research progress of different realization methods, the future development direction and challenges of DFT are prospected. The realization methods of DFT not only need the rigorous theoretical foundation. Moreover, it is also necessary to consider the combination of real‐time data and system modeling technology to realize dynamic assessment and smart system in the future.

show abstract

“…For each

t \in T

X( t )

is a random variable. A typical continuous stochastic process

\{ X( t ), t \in T \}

is called a Markov process if its conditional probability satisfies the relation 40 . The conversion process is shown in Figure 6.…”

Section: The Realization Methods Of Dftmentioning

confidence: 99%

“…A typical continuous stochastic process{𝑋(𝑡), 𝑡 ∈ 𝑇} is called a Markov process if its conditional probability satisfies the relation. 40 The conversion process is shown in Figure 6.…”

Section: Markov Chainmentioning

confidence: 99%