TY - JOUR
T1 - Two new methods for analyzing global reliability sensitivity using augmented reliability
AU - Wan, Yue
AU - Lv, Zhenzhou
AU - Yuan, Xiukai
PY - 2009/10
Y1 - 2009/10
N2 - Section 1 of the full paper briefs the probability density function, which can be estimated by the existing methods in Refs. 4 and 5 and by the two new methods; in section 1, eq. (2), which is related to augmented reliability, is particularly important. Subsection 2.1 establishes the new adaptive kernel density approximation method; in subsection 2.1, eq. (8) can be used for estimating the probability density function. Subsection 2.2 establishes the new polynomial approximation method; in subsection 2.2, eq. (14) can be used for estimating the probability density function. Section 3 gives the simulation results of three examples and their analysis. The simulation results are presented in: Figs. 1 and 2 for example 1; Figs.3 and 4 for example 2. The analysis of the results shows mainly and preliminarily that the existing maximum entropy method and the new polynomial approximation method for analyzing global reliability sensitivity are more robust than the other two methods.
AB - Section 1 of the full paper briefs the probability density function, which can be estimated by the existing methods in Refs. 4 and 5 and by the two new methods; in section 1, eq. (2), which is related to augmented reliability, is particularly important. Subsection 2.1 establishes the new adaptive kernel density approximation method; in subsection 2.1, eq. (8) can be used for estimating the probability density function. Subsection 2.2 establishes the new polynomial approximation method; in subsection 2.2, eq. (14) can be used for estimating the probability density function. Section 3 gives the simulation results of three examples and their analysis. The simulation results are presented in: Figs. 1 and 2 for example 1; Figs.3 and 4 for example 2. The analysis of the results shows mainly and preliminarily that the existing maximum entropy method and the new polynomial approximation method for analyzing global reliability sensitivity are more robust than the other two methods.
KW - Adaptive kernel density approximation
KW - Maximum entropy
KW - Polynomial approximation
KW - Probability density function
KW - Reliability
KW - Sensitivity analysis
UR - http://www.scopus.com/inward/record.url?scp=71049188012&partnerID=8YFLogxK
M3 - 文章
AN - SCOPUS:71049188012
SN - 1000-2758
VL - 27
SP - 664
EP - 668
JO - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
JF - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
IS - 5
ER -