Abstract:

Aiming at the product which its performance degradation process obeys to the Wiener process, a reliability assessment method for accelerated degradation test (ADT) data of like products and field degradation data of individual is put forward by using Bayesian statistical inference. Considering the difference between field stress environment and laboratory stress environment, the Wiener process double-parameters modified model with the correction factors is constructed. The step-stress ADT data model and the field degradation model are built to obtain estimated values of distribution parameters under each stress. The accelerated factor is used to convert these estimated values under accelerated stress into regular stress and constitute data sample for prior distribution of unknown parameters. The CvM checkout method is used to determine the optimal prior distribution of unknown parameters and its estimated values of hyper parameters. Posterior distribution function of unknown parameters under field degradation data is built and the markov chain monte carlo (MCMC) method is used to obtain mean values of the posterior distribution. Accuracy and practical applicability of the present method is verified by an example. Result shows this method can deal with the integrated assessment problem for prior ADT data and field degradation data.