Details
| Translated title of the contribution | Oparta na sieci bayesowskiej miara ważności probabilistycznych uszkodzeń spowodowanych wspólną przyczyną w warunkach niepewności hybrydowej systemu |
|---|---|
| Original language | English |
| Pages (from-to) | 112-120 |
| Number of pages | 9 |
| Journal | Eksploatacja i Niezawodnosc |
| Volume | 22 |
| Issue number | 1 |
| Publication status | Published - 2020 |
Abstract
When dealing with modern complex systems, the relationship existing between components can lead to the appearance of various dependencies between component failures, where multiple items of the system fail simultaneously in unpredictable fashions. These probabilistic common cause failures affect greatly the performance of these critical systems. In this paper a novel methodology is developed to quantify the importance of common cause failures when hybrid uncertainties are presented in systems. First, the probabilistic common cause failures are modeled with Bayesian networks and are incorporated into the system exploiting the α factor model. Then, probability-boxes (bound analysis method) are introduced to model the hybrid uncertainties and quantify the effect of uncertainties on system reliability. Furthermore, an extended Birnbaum importance measure is defined to identify the critical common cause failure events and coupling impact factors when uncertainties are expressed by probability-boxes. Finally, the effectiveness of the method is demonstrated through a numerical example.
Keywords
- Bayesian network, Extended Birnbaum importance, Probabilistic common cause failure, α factor model
ASJC Scopus subject areas
- Engineering(all)
- Safety, Risk, Reliability and Quality
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Eksploatacja i Niezawodnosc, Vol. 22, No. 1, 2020, p. 112-120.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Importance measure of probabilistic common cause failures under system hybrid uncertainty based on Bayesian network
AU - Mi, Jinhua
AU - Li, Yan-Feng
AU - Beer, Michael
AU - Broggi, Matteo
AU - Cheng, Yuhua
N1 - Funding information: This work was partially supported by the National Natural Science Foundation of China under contract No. 51805073 and U1830207, the Chinese Universities Scientific Fund under contract No. ZYGX2018J061, the Sichuan Science and Technology Project under contract No. 2019JDJQ0015. Jinhua Mi wishes to acknowledge the financial support of the China Scholarship Council.
PY - 2020
Y1 - 2020
N2 - When dealing with modern complex systems, the relationship existing between components can lead to the appearance of various dependencies between component failures, where multiple items of the system fail simultaneously in unpredictable fashions. These probabilistic common cause failures affect greatly the performance of these critical systems. In this paper a novel methodology is developed to quantify the importance of common cause failures when hybrid uncertainties are presented in systems. First, the probabilistic common cause failures are modeled with Bayesian networks and are incorporated into the system exploiting the α factor model. Then, probability-boxes (bound analysis method) are introduced to model the hybrid uncertainties and quantify the effect of uncertainties on system reliability. Furthermore, an extended Birnbaum importance measure is defined to identify the critical common cause failure events and coupling impact factors when uncertainties are expressed by probability-boxes. Finally, the effectiveness of the method is demonstrated through a numerical example.
AB - When dealing with modern complex systems, the relationship existing between components can lead to the appearance of various dependencies between component failures, where multiple items of the system fail simultaneously in unpredictable fashions. These probabilistic common cause failures affect greatly the performance of these critical systems. In this paper a novel methodology is developed to quantify the importance of common cause failures when hybrid uncertainties are presented in systems. First, the probabilistic common cause failures are modeled with Bayesian networks and are incorporated into the system exploiting the α factor model. Then, probability-boxes (bound analysis method) are introduced to model the hybrid uncertainties and quantify the effect of uncertainties on system reliability. Furthermore, an extended Birnbaum importance measure is defined to identify the critical common cause failure events and coupling impact factors when uncertainties are expressed by probability-boxes. Finally, the effectiveness of the method is demonstrated through a numerical example.
KW - Bayesian network
KW - Extended Birnbaum importance
KW - Probabilistic common cause failure
KW - α factor model
UR - http://www.scopus.com/inward/record.url?scp=85082430980&partnerID=8YFLogxK
U2 - 10.17531/ein.2020.1.13
DO - 10.17531/ein.2020.1.13
M3 - Article
AN - SCOPUS:85082430980
VL - 22
SP - 112
EP - 120
JO - Eksploatacja i Niezawodnosc
JF - Eksploatacja i Niezawodnosc
SN - 1507-2711
IS - 1
ER -