scholarly journals Estimating reliability of degraded system based on the probability density evolution with multi-parameter

2017 ◽  
Vol 119 ◽  
pp. 01050
Author(s):  
Ge Jiang ◽  
Hongjie Yuan ◽  
Hailong Zhang
2009 ◽  
Vol 03 (03) ◽  
pp. 209-226 ◽  
Author(s):  
LI JIE ◽  
CHEN JIANBING

The paper aims at clarifying the essential relationship between traditional probability density evolution equations and the generalized probability density evolution equation which is developed by the authors in recent years. Using the principle of preservation of probability as a uniform fundamental, the probability density evolution equations, including the Liouville equation, Fokker–Planck equation and the Dostupov–Pugachev equation, are derived from the physical point of view. It is pointed out that combining with Eulerian or Lagrangian description of the associated dynamical system will lead to different probability density evolution equations. Particularly, when both the principle and dynamical systems are viewed from Lagrangian description, we are led to the generalized probability density evolution equation.


Author(s):  
Xiaoyu Zhou ◽  
Hongxia Li ◽  
Yi Huang

A probability density evolution based exponential polynomial regression (PDEM-EPR) method to calculate the probability density function (PDF) of the high dimensional nonlinear stochastic dynamical systems is presented in this paper. Several typical examples, such as linear oscillator and Duffing oscillator are solved by PDEM-EPR method, and the results fit well with the analytical solutions. An engineering practice problem of ship nonlinear random roll in the beam waves is involved in this paper. The results obtained by PDEM-EPR is compared with those obtained by path integral method. The later results were given by Chai Wei [3]. It shows that PDEM-EPR method has the advantages as following: 1) The multi-degree-of-freedom (MDOF) nonlinear stochastic dynamical problems can be solved by PDEM-EPR method; 2) High efficiency can be obtained by PDEM-EPR method.


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