A Model to Predict Probability of Common Cause Failure in Redundant System

According to the mathematic theory of reliability and the physical model of components failure,i.e.,the stress-strength interference model,components failure probability is regarded as a random variable complying with a certain distribution.The mathematical expression of a prediction model of the probability of common cause failure in redundant system is thus derived.Using the Monte Carlo simulation method and neural network technique,the distribution type and parameters of the random variable are obtained.Based on the limited failure data,the model can predict the failure probability of arbitrary order for a redundant system,and it can make up for what have been omitted by the traditional models for common cause failure.A typical example is given to illustrate the application of the model with the calculated results compared to those resulting from BFR model.The results show that the approach proposed is more accurate.