Estimation of Failure Probability and its Applications in Reliability Data Analysis

2010 ◽  
Vol 118-120 ◽  
pp. 601-605
Author(s):  
Han Ming

Evaluation method of reliability parameter estimation needs to be improved effectively with the advance of science and technology. This paper develops a new method of parameter estimation, which is named E-Bayesian estimation method. In the case one hyper-parameter, the definition of E-Bayesian estimation of the failure probability is provided, moreover, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation, and the property of E-Bayesian estimation of the failure probability are also provided. Finally, calculation on practical problems shows that the provided method is feasible and easy to perform.

2011 ◽  
Vol 199-200 ◽  
pp. 308-312
Author(s):  
Ming Han

Evaluation method of reliability of industrial products needs to be improved effectively with the advance of science and technology. This paper introduces a new method, named E-Bayesian estimation method, to estimate failure probability in reliability engineering. The definition of E-Bayesian estimation of the failure probability is provided, moreover, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation of the failure probability were provided, and properties of the E-Bayesian estimation, i.e. relations between E-Bayesian estimation and hierarchical Bayesian estimation, are also provided. Finally, calculation on practical problems shows that the provided method is feasible and easy to perform.


2014 ◽  
Vol 915-916 ◽  
pp. 318-322 ◽  
Author(s):  
Ming Han

This paper introduces a new method, named E-Bayesian estimation method, to estimate failure probability. In the case of zero-failure data, the definition of E-Bayesian estimation of failure probability is provided; moreover, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation and the property of E-Bayesian estimation of the failure probability are also provided. For the estimate failure probability, in the following sections we will see simple the E-Bayesian estimation method is method than hierarchical Bayesian estimation method. Finally, the calculated results of bearing show that the proposed method is feasible and convenient in engineering application.


2014 ◽  
Vol 945-949 ◽  
pp. 1046-1049
Author(s):  
Ming Han

This paper introduces a new method, named E-Bayesian estimation method, to estimate failure rate in zero-failure data. The definition of E-Bayesian estimation of the failure rate is given, based on the definition, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation of the failure rate were provided, and properties of the E-Bayesian estimation, i. e. relations between E-Bayesian estimation and hierarchical Bayesian estimation, was discussed. Calculations were performed on practical problems, showing that the proposed new method is feasible and easy to operate.


2013 ◽  
Vol 756-759 ◽  
pp. 3149-3152
Author(s):  
Ming Han

This paper introduces a new parameter estimation method, E-Bayesian estimation method, to estimate failure rate. The definition, properties, E-Bayesian estimation and hierarchical Bayesian estimation of failure rate are given. A example is also discussed. Through the example the efficiency and easiness of operation of this method are commended.


2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
Ming Han

Since Lindley and Smith introduced the idea of hierarchical prior distribution, some results have been obtained on hierarchical Bayesian method to deal with lifetime data. But all those results obtained by means of hierarchical Bayesian methods involve complicated integration compute. Though some computing methods such as Markov Chain Monte Carlo (MCMC) are available, doing integration is still very inconvenient for practical problems. This paper introduces a new method, named E-Bayesian estimation method, to estimate failure probability. In the case of one hyperparameter, the definition of E-Bayesian estimation of the failure probability is provided; moreover, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation and the property of E-Bayesian estimation of the failure probability are also provided. Finally, calculation on practical problems shows that the provided method is feasible and easy to perform.


2016 ◽  
Vol 138 (2) ◽  
Author(s):  
A. Moftakhari ◽  
C. Aghanajafi

The aim of this study is to introduce a new solution methodology for thermal parameter estimation in building engineering science. By defining a good numerical modeling, inverse algorithm provides us a chance to enhance design conditions in building thermal analysis. The definition of mathematical governing equations and a good solution method to solve them direct the analysis procedure to find temperature distribution using dynamic coding in the computational field. In fact, inverse algorithm utilizes known data resulted from numerical modeling in order to determine the unknown value of important thermal design properties in building problems. The results obtained from implementation of such algorithms demonstrate the accuracy and precision of this new thermal analysis methodology with those of real data resulted from experiments in building problems.


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