DocumentCode :
1507566
Title :
A Framework for Reliability Approximation of Multi-State Weighted k -out-of- n Systems
Author :
Ding, Yi ; Zuo, Ming J. ; Lisnianski, Anatoly ; Li, Wei
Author_Institution :
Sch. of EEE, Nanyang Technol. Univ., Singapore, Singapore
Volume :
59
Issue :
2
fYear :
2010
fDate :
6/1/2010 12:00:00 AM
Firstpage :
297
Lastpage :
308
Abstract :
The multi-state k -out-of-n system model finds wide applications in industry, and has been extensively studied in recent years. This model has also been generalized to the multi-state weighted k -out-of-n system model. Recursive methods, and universal generating functions (UGF) are two primary algorithms for exact performance evaluation of multi-state k-out-of-n systems. However the computational burden becomes the crucial factor when there is a “dimension damnation” problem caused by the increase in the number of components in the system, and the number of possible states a component may be in. In situations wherein exact values of system reliability are not necessary, we may use more efficient algorithms to approximate system reliability. In this paper, we develop a comprehensive framework for reliability approximation of multi-state weighted k -out-of-n systems. Two fuzzy based multi-state weighted k-out-of- n system models are defined. Procedures for building these two models from the conventional models are also introduced. The fuzzy recursive methods, and fuzzy UGF techniques are developed to evaluate such systems. The clustering technique, and curve fitting method are used to determine the fuzzy weights, and probabilities of states in the models.
Keywords :
approximation theory; consecutive system reliability; curve fitting; fuzzy set theory; pattern clustering; reliability theory; statistical analysis; clustering technique; curve fitting method; dimension damnation problem; fuzzy UGF technique; fuzzy recursive method; fuzzy weight; multistate weighted k-out-of-n system; reliability approximation; system reliability; universal generating function; Approximation algorithms; Clustering algorithms; Councils; Curve fitting; Fuzzy systems; Mechanical engineering; Power engineering and energy; Power system modeling; Reliability; Systems engineering and theory; $k$-out-of-$n$ system; Fuzzy set; multi-state system; recursive algorithm; reliability approximation; universal generating function; weighted $k$ -out-of-$n$ system;
fLanguage :
English
Journal_Title :
Reliability, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9529
Type :
jour
DOI :
10.1109/TR.2010.2048659
Filename :
5475446
Link To Document :
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