Application of dynamic evidential networks in reliability analysis of complex systems with epistemic uncertainty and multiple life distributions

With the modernization and intelligent of industrial equipment and systems, the challenges of dynamic characteristics, failure dependency and uncertainties have aroused by the increasing of system complexity. Besides, various types of components may follow different life distributions which bring th...

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Veröffentlicht in:Annals of operations research Jg. 311; H. 1; S. 311 - 333
Hauptverfasser: Mi, Jinhua, Cheng, Yuhua, Song, Yufei, Bai, Libing, Chen, Kai
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.04.2022
Springer
Springer Nature B.V
Schlagworte:
Business and Management
Combinatorics
Complex systems
Complexity
Dynamic characteristics
Dynamic models
Epistemology
Fault location (Engineering)
Graphical representations
Industrial equipment
Inference
Logic circuits
Methods
Modernization
Network reliability
Operations research
Operations Research/Decision Theory
Reasoning
Reliability (Engineering)
Reliability analysis
Reliability aspects
S.I.: Reliability Modeling with Applications Based on Big Data
System reliability
Theory of Computation
Time dependence
Uncertainty
China
Epistemic uncertainty
Dynamic evidential networks
Evidence theory
Multiple life distribution
ISSN:0254-5330, 1572-9338
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Zusammenfassung:With the modernization and intelligent of industrial equipment and systems, the challenges of dynamic characteristics, failure dependency and uncertainties have aroused by the increasing of system complexity. Besides, various types of components may follow different life distributions which bring the multiple life distributions problem in systems. In order to model the impact of time dependency and epistemic uncertainty on the failure behavior of system, this paper combines the flexible dynamic modeling with the uncertainty expression. Its advantages are intuitively graphical representation and reasoning that brought by evidential network (EN). After that, the discrete time dynamic evidential network (DT-DEN) is introduced to analyze the reliability of complex systems, and the network inference mechanism is clearly defined. The evidence theory and original definition and inference mechanism of conventional EN is firstly recommended, and the DT-DEN is further presented. Furthermore, the multiple life distributions are synthesized into the DT-DEN to tackle the epistemic uncertainty and mixed life distribution challenges. Specifically, the dynamic logic gates are converted into equivalent DENs with distinguished conditional mass tables, and then the belief interval of system reliability can be calculated by network forward reasoning. Finally, the availability and efficiency of the proposed method is verified by some numerical examples.
Bibliographie:ObjectType-Article-1
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-019-03211-4