DocumentCode :
2701737
Title :
Unified uncertainty analysis by the extension universal generating functions
Author :
Xiao, Ning-Cong ; Huang, Hong-Zhong ; Liu, Yu ; Li, Yanfeng ; Wang, Zhonglai
Author_Institution :
Sch. of Mechatron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear :
2012
fDate :
15-18 June 2012
Firstpage :
1160
Lastpage :
1166
Abstract :
In this paper, a unified uncertainty analysis method based on the extension universal generating function is proposed for engineering problems described by the mixture of random, interval and p-box variables. In the method, the univariate approximation approach is extended for mixed variables, and then the performance function is divided into three parts. Traditional universal generating function can only model the case that all variables exist in system are random variables. However, in order to calculate the bounds of system probability of failure under mixed variables, the mixed universal generating function is developed to extend the traditional universal generating function. The optimization models based on the mixed universal generating function are presented to calculate system probability of failure under mixed variables. An engineering example is used to validate the proposed method.
Keywords :
approximation theory; failure analysis; probability; random processes; reliability theory; engineering problems; extension universal generating functions; interval variables; mixed universal generating function; p-box variables; performance function; random variables; system probability; unified uncertainty analysis method; univariate approximation approach; Approximation methods; Optimization; Probability density function; Random variables; Reliability; Uncertainty; mixed variables; reliability; unified uncertianty analysis; universal generating function;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-0786-4
Type :
conf
DOI :
10.1109/ICQR2MSE.2012.6246427
Filename :
6246427
Link To Document :
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