A Model-Based Reliability Metric Considering Aleatory and Epistemic Uncertainty

IEEE Access

Rui Kang¹  Zhiguo Zeng²  Meilin Wen³  Enrico Zio³ 

[1] Paris-Saclay, Chatenay-Malabry, France;Chair System Science and the Energy Challenge, Fondation Electricité de France, CentraleSupélec, Universit&x00E9;School of Reliability and Systems Engineering, Beihang University, Beijing, China;

关键词: Reliability;    physics-of-failure;    epistemic uncertainty;    model uncertainty;    belief reliability;   

DOI  :  10.1109/ACCESS.2017.2733839

来源: DOAJ

【 摘 要 】

Model-based reliability analysis and assessment methods rely on models, which are assumed to be precise, to predict reliability. In practice, however, the precision of the model cannot be guaranteed due to the presence of epistemic uncertainty. In this paper, a new reliability metric, called belief reliability, is defined to explicitly account for epistemic uncertainty in model-based reliability analysis and assessment. A new method is developed to explicitly quantify epistemic uncertainty by measuring the effectiveness of the engineering analysis and assessment activities related to reliability. To evaluate belief reliability, an integrated framework is presented where the contributions of design margin, aleatory uncertainty, and epistemic uncertainty are integrated to yield a comprehensive and systematic description of reliability. The developed methods are demonstrated by two case studies.

【 授权许可】

Unknown