TY - GEN
T1 - A new metric for time-dependent mechanism reliability analysis
AU - Zhou, Shuang
AU - Zhang, Jianguo
AU - Wu, Jie
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/1
Y1 - 2020/1
N2 - In classical time-dependent mechanism reliability analysis, probability or fuzzy reliability theory is employed. However, the method based on probability theory requires probability distributions of all the uncertain parameters, but the accurate distributions of parameters in real life are sometimes difficult to obtain. Moreover, fuzzy theory fails to describe many subjective random variables due to the duality of randomness. In this paper, we utilize uncertain variables to uniformly represent the subjective random and epistemic uncertainties by quoting the uncertainty theory.
AB - In classical time-dependent mechanism reliability analysis, probability or fuzzy reliability theory is employed. However, the method based on probability theory requires probability distributions of all the uncertain parameters, but the accurate distributions of parameters in real life are sometimes difficult to obtain. Moreover, fuzzy theory fails to describe many subjective random variables due to the duality of randomness. In this paper, we utilize uncertain variables to uniformly represent the subjective random and epistemic uncertainties by quoting the uncertainty theory.
KW - Epistemic uncertainty
KW - Mechanism reliability
KW - Reliability metric
KW - Uncertainty theory
UR - https://www.scopus.com/pages/publications/85090461023
U2 - 10.1109/RAMS48030.2020.9153617
DO - 10.1109/RAMS48030.2020.9153617
M3 - 会议稿件
AN - SCOPUS:85090461023
T3 - Proceedings - Annual Reliability and Maintainability Symposium
BT - 2020 Annual Reliability and Maintainability Symposium, RAMS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Annual Reliability and Maintainability Symposium, RAMS 2020
Y2 - 27 January 2020 through 30 January 2020
ER -