Dirichlet analysis method for the accelerated storage test of electronic machine

System electronic machine level product has a complex structure and with many failure mechanisms, the method of using accelerated model to analysis the storage life and reliability is not correct. This paper presents a method based on the sequence Dirichlet distribution model. According to the acceleration model, electronic equipment experiences multiple-type, multiple-level environmental stresses, this model assumes that the failure rate is of exponential distribution at each stress level. Through priori information and the modified accelerated storage model based on the reaction theory, the priori message of failure rate is obtained. Then a multi-variable sequence Dirichlet distribution is applied to describe the probability density of priori failure rate. The parameters are calculated and the physical meaning is clearly stated. By analyzing the constant-stress experiment data, the likelihood function is generated. The Gibbs rejection sampling method is used to solve the posteriori inference problem and get the posterior modified message. A case study is then performed using this method. The sampling process and the quantile values of the failure rate are presented as a result of the case study. Through comparing the priori and posteriori reliability variation trend in the normal state, the effectiveness of this method is shown. Thus a new method of life prediction and evaluation for electronic equipment is developed.