Damage Equivalent Method of Fatigue Reliability Analysis of Load-Sharing Parallel System

2008 ◽  
Vol 44-46 ◽  
pp. 853-858 ◽  
Author(s):  
Guang Bo Hao ◽  
Li Yang Xie
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
Load Sharing ◽  
Parallel System ◽  
Reliability Model ◽  
Fatigue Reliability ◽  
Life Distribution ◽  
Life Distributions ◽  
Equivalent Method ◽  
Full Probability

As for load-sharing parallel system like multi-engine system and wire cable, dependence-failure must occur due to load redistributing, so the component life distributions changed. After the analysis of the disadvantage of failure probability equivalent principle and the transformation of equivalent working time of different life distribution based on damage equivalent principle, the parallel system reliability model applying full probability formula is established. The established reliability model provides a new method for reliability analysis of load-sharing parallel system whose component life follows any distribution.

Reliability analysis and state transfer scheduling optimization of degrading load-sharing system equipped with warm standby components

2021 ◽  
pp. 1748006X2110017
Author(s):  
Sheng-Jia Ruan ◽  
Yan-Hui Lin
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
High Reliability ◽  
Quadrature Rule ◽  
Load Sharing ◽  
Measurement Information ◽  
Model Parameters ◽  
Scheduling Optimization ◽  
State Transfer ◽  
Warm Standby

Standby redundancy can meet system safety requirements in industries with high reliability standards. To evaluate reliability of standby systems, failure dependency among components has to be considered especially when systems have load-sharing characteristics. In this paper, a reliability analysis and state transfer scheduling optimization framework is proposed for the load-sharing 1-out-of- N: G system equipped with M warm standby components and subject to continuous degradation process. First, the system reliability function considering multiple dependent components is derived in a recursive way. Then, a Monte Carlo method is developed and the closed Newton-Cotes quadrature rule is invoked for the system reliability quantification. Besides, likelihood functions are constructed based on the measurement information to estimate the model parameters of both active and standby components, whose degradation paths are modeled by the step-wise drifted Wiener processes. Finally, the system state transfer scheduling is optimized by the genetic algorithm to maximize the system reliability at mission time. The proposed methodology and its effectiveness are illustrated through a case study referring to a simplified aircraft hydraulic system.

Fatigue Reliability Functions in Semilogarithmic Coordinates

1991 ◽  
Author(s):  
Vladimir A. Avakov
Keyword(s):  
Fatigue Life ◽  
Coordinate System ◽  
Strength Distribution ◽  
Fatigue Reliability ◽  
Life Distribution ◽  
Similar Transformation ◽  
Asymptotic Type ◽  
Life Distributions ◽  
Strength Distributions

Abstract In the previous publication [2], the transformation between fatigue life and strength distribution was established using double-logarithmic coordinate system (lnN-lnS). Here, a similar transformation is established using a semi logarithmic (lnN-S) coordinate system. With the aid of the developed orthogonal relations, lognormal, Weibull and three-parameter logweibull life distributions have been transformed into normal, asymptotic type 1 of smallest value, and three-parameter Weibull strength distributions, respectively. This procedure may be applied to other types of fatigue life distribution.

A Mixed-Effect Multi-Failure-Mechanism Fatigue Reliability Model

2010 ◽  
Vol 118-120 ◽  
pp. 37-42
Author(s):  
Li Yang Xie ◽  
Wen Qiang Lin ◽  
Feng Lu
Keyword(s):  
Distribution Function ◽  
Probability Function ◽  
Failure Mechanisms ◽  
Reliability Model ◽  
Conditional Survival ◽  
Cycle Fatigue ◽  
Fatigue Reliability ◽  
Life Distribution ◽  
Mixed Effect ◽  
Reliability Models

Based on the concept of multilevel statistics, mixed-effect fatigue reliability models are presented, by which fatigue reliability can be directly calculated according to stress distribution and fatigue life distribution function condition to stress. Mathematically, the fatigue reliability is estimated as the expectation of a conditional survival probability function to the stochastic stress history. Especially, such models are capable of estimating the fatigue reliability of a component with competing failure mechanisms such as conventional fatigue and giga-cycle fatigue, where two groups of P-S-N curves are involved.

Fatigue Reliability Functions in Semilogarithmic Coordinates

1991 ◽  
Vol 113 (3) ◽  
pp. 352-358 ◽  
Author(s):  
V. A. Avakov
Keyword(s):  
Fatigue Life ◽  
Coordinate System ◽  
Strength Distribution ◽  
Fatigue Reliability ◽  
Life Distribution ◽  
Similar Transformation ◽  
Asymptotic Type ◽  
Life Distributions ◽  
Straight Lines

In the previous publication [2], the transformation between fatigue life and strength distribution was established using double-logarithmic coordinate system (InN-InS). Here, a similar transformation is established using a semilogarithmic (InN-S) coordinate system. It is assumed that the set of S = Sj (N/Qj) (j = 1,2,...,p) relations, plotted in the InN-S coordinates, becomes a family of parallel straight lines. With the aid of the developed orthogonal relations, lognormal, Weibull and three-parameter logweibull life distributions have been transformed into normal, asymptotic type 1 of smallest value, and three-parameter Weibull strength distributions, respectively. This procedure may be applied to other types of fatigue life distribution.

scholarly journals A Load Sharing System Reliability Model With Managed Component Degradation

2014 ◽  
Vol 63 (3) ◽  
pp. 721-730 ◽  
Author(s):  
Zhisheng Ye ◽  
Matthew Revie ◽  
Lesley Walls
Keyword(s):  
System Reliability ◽  
Load Sharing ◽  
Reliability Model

scholarly journals System Reliability Assessment with Imprecise Probabilities

2019 ◽  
Vol 9 (24) ◽  
pp. 5422 ◽  
Author(s):  
Guodong Yang ◽  
Xianzhen Huang ◽  
Yuxiong Li ◽  
Pengfei Ding
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
Reliability Assessment ◽  
Statistical Characteristics ◽  
Imprecise Probabilities ◽  
Limited Sample ◽  
Numerical Examples ◽  
Practical Engineering ◽  
Life Distributions ◽  
High Level

The exact statistical characteristics of some components may be unavailable because of the limited sample information in practical engineering. One challenge that system reliability analysis faces is dealing with limited sample sizes, which introduces the potential for a high level of uncertainty in the analysis results. In this paper, we propose a procedure for the reliability analysis of complex systems with a limited number of samples. Bayesian inference is used to estimate the parameter intervals of the life distributions of the components with a limited number of samples. Then, probability boxes (p-box) are constructed from the parameter intervals to represent the life distributions of the components with a limited number of samples. In addition, the theory of survival signature is applied to calculate the reliability of the system with a mixture of precise and imprecise knowledge of the life distributions of the components. Finally, two numerical examples are given to illustrate the validity of the methods.

Sign in / Sign up

Export Citation Format

Share Document