A Time-Dependent Reliability Analysis Method using a Niching Genetic Algorithm

2007 ◽  
Author(s):  
Jing Li ◽  
Zissimos P. Mourelatos
2019 ◽  
Vol 61 (5) ◽  
pp. 2125-2134
Author(s):  
YouRui Tao ◽  
BoWen Liang ◽  
Jianhua Zhang

Author(s):  
Zhen Hu ◽  
Zhifu Zhu ◽  
Xiaoping Du

Time-dependent system reliability is measured by the probability that the responses of a system do not exceed prescribed failure thresholds over a period of time. In this work, an efficient time-dependent reliability analysis method is developed for bivariate responses that are general functions of random variables and stochastic processes. The proposed method is based on single and joint upcrossing rates, which are calculated by the First Order Reliability Method (FORM). The method can efficiently produce accurate upcrossing rates for the systems with two responses. The upcrossing rates can then be used for system reliability predictions with two responses. As the general system reliability may be approximated with the results from reliability analyses for individual responses and bivariate responses, the proposed method can be extended to reliability analysis for general systems with more than two responses. Two examples, including a parallel system and a series system, are presented.


Author(s):  
Liyang Xie ◽  
Enjun Bai ◽  
Wenxue Qian ◽  
Ningxiang Wu

A gear transmission system such as a gear train is a series system in sense of reliability evaluation, while it is different from a traditional series system such as a chain. Therefore, the conventional series system reliability model is not appropriate for gear transmission system. Based on the time-dependent configuration and the time-dependent loading path of a gear train, system specific reliability modeling technique is presented, by which a gear train is taken as a time-dependent series system, consisting of different components (gear teeth) in different time intervals. To illustrate the application of the reliability analysis method, several time-dependent series system reliability models are developed for different types of gear trains, the reliability estimation results are compared with those obtained by traditional series system reliability model.


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