RESEARCH PAPER
A new assessment method of mechanism reliability based on chance measure under fuzzy and random uncertainties
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Science and Technology on Reliability and Environmental Engineering Laboratory Beihang University Xueyuan Road No.37, Haidian District, Beijing 100083, China
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School of Reliability and Systems Engineering Beihang University Xueyuan Road No.37, Haidian District, Beijing 100083, China
Publication date: 2018-06-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2018;20(2):219-228
KEYWORDS
ABSTRACT
The traditional reliability analysis methods based on probability theory and fuzzy set theory have been widely used in engineering
practice. However, these methods are unable directly measure the uncertainty of mechanism reliability with uncertain variables,
i.e., subjective random and fuzzy variables. In order to address this problem, a new quantification method for the mechanism reliability based on chance theory is presented to simultaneously satisfy the duality of randomness and the subadditivity of fuzziness in
the reliability problem. Considering the fact that systems usually have multilevel performance and the components have multimode
failures, this paper proposes a chance theory based multi-state performance reliability model. In the proposed method, the chance
measure is adopted instead of probability and possibility measures to quantify the mechanism reliability for the subjective probability or fuzzy variables. The hybrid variables are utilized to represent the random and fuzzy parameters, based on which solutions are derived to analyze the chance theory based mechanism reliability with chance distributions. Since the input parameters of
the model contain fuzziness and randomness simultaneously, an algorithm based on chance measure is designed. The experimental
results on the case application demonstrate the validity of the proposed method.
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