Multi-state system reliability analysis methods based on Bayesian networks merging dynamic and fuzzy fault information

2019 ◽  
Vol 13 (1/2) ◽  
pp. 44
Author(s):  
Yabing Zha ◽  
Jie Liu ◽  
Ruijun Zhang ◽  
Tianyu Liu ◽  
Qin He
Keyword(s):  
Bayesian Networks ◽  
Reliability Analysis ◽  
System Reliability ◽  
State System ◽  
Analysis Methods ◽  
System Reliability Analysis ◽  
Fault Information

Multi-state system reliability analysis methods based on Bayesian networks merging dynamic and fuzzy fault information

2019 ◽  
Vol 13 (1/2) ◽  
pp. 44 ◽  
Author(s):  
Qin He ◽  
Ruijun Zhang ◽  
Tianyu Liu ◽  
Yabing Zha ◽  
Jie Liu
Keyword(s):  
Bayesian Networks ◽  
Reliability Analysis ◽  
System Reliability ◽  
State System ◽  
Analysis Methods ◽  
System Reliability Analysis ◽  
Fault Information

Modeling multi-state system reliability analysis in a power station under fatal and nonfatal shocks: a simulation approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Reza Pourhassan ◽  
Sadigh Raissi ◽  
Arash Apornak
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
System Performance ◽  
Failure Process ◽  
State System ◽  
Failure Behavior ◽  
Simulation Approach ◽  
Critical System ◽  
Content Type ◽  
System Reliability Analysis

PurposeIn some environments, the failure rate of a system depends not only on time but also on the system condition, such as vibrational level, efficiency and the number of random shocks, each of which causes failure. In this situation, systems can keep working, though they fail gradually. So, the purpose of this paper is modeling multi-state system reliability analysis in capacitor bank under fatal and nonfatal shocks by a simulation approach.Design/methodology/approachIn some situations, there may be several levels of failure where the system performance diminishes gradually. However, if the level of failure is beyond a certain threshold, the system may stop working. Transition from one faulty stage to the next can lead the system to more rapid degradation. Thus, in failure analysis, the authors need to consider the transition rate from these stages in order to model the failure process.FindingsThis study aims to perform multi-state system reliability analysis in energy storage facilities of SAIPA Corporation. This is performed to extract a predictive model for failure behavior as well as to analyze the effect of shocks on deterioration. The results indicate that the reliability of the system improved by 6%.Originality/valueThe results of this study can provide more confidence for critical system designers who are engaged on the proper system performance beyond economic design.

scholarly journals Dynamic Bayesian Networks in System Reliability Analysis

2007 ◽  
pp. 444-449 ◽  
Author(s):  
Abdeljabbar Ben Salem ◽  
Alexandre Muller ◽  
Philippe Weber
Keyword(s):  
Bayesian Networks ◽  
Reliability Analysis ◽  
System Reliability ◽  
Dynamic Bayesian Networks ◽  
System Reliability Analysis

scholarly journals DYNAMIC BAYESIAN NETWORKS IN SYSTEM RELIABILITY ANALYSIS

2006 ◽  
Vol 39 (13) ◽  
pp. 444-449 ◽  
Author(s):  
Abdeljabbar BEN SALEM ◽  
Alexandre MULLER ◽  
Philippe WEBER
Keyword(s):  
Bayesian Networks ◽  
Reliability Analysis ◽  
System Reliability ◽  
Dynamic Bayesian Networks ◽  
System Reliability Analysis
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