Reliability and Sensitivity Analysis of Embedded Systems with Modular Dynamic Fault Trees

Lo, Hsiang-Kai; Huang, Chin‐Yu; Chang, Yung‐Ruei; Huang, Wei‐Chih; Chang, Jun-Ru

doi:10.1109/tencon.2005.300968

Cited by 2 publications

(2 citation statements)

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“…Many researches on finding ways to modularize the fault tree have been employed [17][18][19][20] . An modular solution to non repairable dynamic systems, which provides a combination of BDD solution techniques for static modules and Markov chain solution techniques for dynamic modules, was presented [19] .…”

Section: Modularization Idea Of the Dftmentioning

confidence: 99%

“…For the sake of simplicity, the concept of modular decomposition, which was proposed by Helman and Rosenthal [16] , was introduced into the DFT analysis [17][18][19][20] . Qu and Dugan [19] presented a modular solution to non repairable dynamic systems, which provides a combination of BDD solution techniques for static modules and Markov chain solution techniques for dynamic modules.…”

Section: Introductionmentioning

confidence: 99%

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Numerical simulation to reliability analysis of fault-tolerant repairable system

Liang

Hong

Zhang

et al. 2010

J. Shanghai Jiaotong Univ. (Sci.)

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In the traditional method for the reliability analysis of fault-tolerant system, the system structure is described by means of binary decision diagram (BDD) and Markov process, and then the reliability indexes are calculated. However, as the size of system augments, the size of state space will increase exponentially. Additionally, Markov approach requires that the failure and repair time of the components obey an exponential distribution. In this study, by combining dynamic fault tree (DFT) and numerical simulation based on the minimal sequence cut set (MSCS), a new method to evaluate reliability of fault-tolerant system with repairable components is proposed. The method presented does not depend on Markov model, so that it can effectively solve the problem of the state-space combination explosion. Moreover, it is suitable for systems whose failure and repair time obey an arbitrary distribution. Therefore, our method is more flexible than the traditional method. At last, an example is given to verify the method.

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Section: Modularization Idea Of the Dftmentioning

confidence: 99%