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Reliability modeling of modular k-out-of-n systems with functional dependency: A case study of radar transmitter systems.
- Source :
-
Reliability Engineering & System Safety . May2023, Vol. 233, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- • A new modular k -out-of- n system model with functional dependency is developed. • Bayesian network is used to model the reliability of modular k -out-of- n systems. • An algorithm is designed to automatically generate the CPTs of the BN model. • DBN model is developed to update the system reliability using observations. • A real-world radar transmitter system in the space launch site is studied. The k -out-of- n systems are among the most important redundancy structures in engineering practices, and their reliability assessment has been extensively studied in the past decades. However, components in a k -out-of- n structure are often subject to functional dependency (FDEP), in which component states are affected by other components' states in the system. In this article, we study a new system structure, namely modular k -out-of- n system with FDEP. In such a system, the failure of some specific components will disable some components in the k -out-of- n structure. Bayesian network (BN) models are used to construct the structure function of modular k -out-of- n systems. The parameters encoded in the graphical structure of the modular k -out-of- n system are automatically generated by a customized algorithm. Furthermore, a dynamic BN (DBN) is developed to update the reliability of modular k -out-of- n system dynamically when observation data are collected from either component or system level. The Birnbaum importance measure of the different types of components in the modular k -out-of- n system is also evaluated by the DBN model via inserting evidence of the components' states overtime. A real-world case of a radar transmitter system in the space launch site is studied to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09518320
- Volume :
- 233
- Database :
- Academic Search Index
- Journal :
- Reliability Engineering & System Safety
- Publication Type :
- Academic Journal
- Accession number :
- 161845309
- Full Text :
- https://doi.org/10.1016/j.ress.2023.109120