Journal ArticleDOI
Reliability analysis of multi-state systems with common cause failures based on Bayesian network and fuzzy probability
TLDR
A method incorporating fuzzy probability and Bayesian network (BN) into multi-state systems (MSSs) with CCFs is proposed and can improve the ability of BN on reliability evaluation of complex system with uncertainty issues.Abstract:
Multi-state components, common cause failures (CCFs) and data uncertainty are the general problems for reliability analysis of complex engineering systems. In this paper, a method incorporating fuzzy probability and Bayesian network (BN) into multi-state systems (MSSs) with CCFs is proposed. In particular, basic theories of multi-state BN and fuzzy probability are developed. Moreover, a model integrating CCFs with BN has also been illustrated. In order to incorporate fuzzy probability into MSSs reliability evaluation considering common parent node generated by CCFs, fuzzy probability has to be translated into accurate probability through defuzzification and normalization methods which are both elaborated. In addition, quantitative analysis based on BN is carried out. In this paper, feed system of boring spindle in computer numerical control machine is analyzed as an example to validate the feasibility of the proposed method. It can improve the ability of BN on reliability evaluation of complex system with uncertainty issues.read more
Citations
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CaFtR: A Fuzzy Complex Event Processing Method
TL;DR: The proposed CaFtR method adequately makes use of network resources to achieve continuous and highly available complex event processing regardless of dynamic operator migrations under fuzzy environment.
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An Enhanced Deep Learning-Based Fusion Prognostic Method for RUL Prediction
TL;DR: A novel deep learning based fusion prognostic method for remaining useful life (RUL) prediction of engineering systems that strategically combines the advantages of bidirectional long short-term memory (BLSTM) networks and particle filter method and meanwhile mitigates their limitations.
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Reliability assessment for systems suffering common cause failure based on Bayesian networks and proportional hazards model
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Time-variant reliability analysis for industrial robot RV reducer under multiple failure modes using Kriging model
TL;DR: A time-variant reliability method for an industrial robot rotate vector (RV) reducer with multiple failure modes using a Kriging model that combines multiple response Gaussian process model and Monte Carlo simulation.
Journal ArticleDOI
A novel single-loop procedure for time-variant reliability analysis based on Kriging model
TL;DR: A new strategy is presented to decouple the double-loop Kriging model for time-variant reliability analysis, in which the extreme value response in double- loop procedure is replaced by the best value in the current sampled points to avoid the inner optimization loop.
References
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Semi-Markov Processes and Reliability
Nikolaos Limnios,G. Oprisan +1 more
TL;DR: The theory of Markov processes has its origins in the studies by A. A. Markov (1856-1922) of sequences of experiments "connected in a chain" and in the attempts to describe mathematically the physical phenomenon known as Brownian mo- tion.
Journal ArticleDOI
Coherent Systems with Multi-State Components
TL;DR: In this paper, the theory of binary coherent systems is generalized for multi-state components, where the system state is defined to be the state of the worst component in the best min path, or equivalently, the best components in the worst min cut.
Journal ArticleDOI
Multistate Coherent Systems.
TL;DR: Basic theory is developed for the study of systems of components in which any of a finite number of states may occur, representing at one extreme perfect functioning and at the other extreme complete failure.