Degradation Test Analysis Based On Symmetric Laplace Process

Reliability assessment plays an important role in the engineering industry,and degradation test analysis is an important means to solve the problem of long-life product reliability.The use of a specific random process to describe the degradation process of the product occupies a very important position in the analysis of degradation tests.Since degradation performance data of most electronic products are not monotonically increasing,degradation models based on traditional stochastic processes deal with such degradation.There are certain limitations to the data.Therefore,we propose a new applicable model for the non-monotonic degenerate data,the symmetrical Laplace process.This paper first establishes a degenerate data model for products whose performance degradation obeys a symmetric Laplace process,and proposes a Bayesian method for its reliability evaluation.The symmetry Laplace process is used to describe the degradation process of the product.Given the conjugate prior distribution of the parameters in the model,a Bayesian estimation model based on the degenerate data is established.The Bayesian estimation of the parameters is obtained by Gibbs sampling.Then Monte Carlo simulations were used to calculate the reliability curve,and the validity of the model was verified by simulation.Finally,the reliability evaluation method of laser data is given.Second,we further study accelerated degradation test based on the symmetric Laplace process.Accelerated degradation model based on symmetric Laplace process is given on the basis of accelerating the degradation factor and accelerating the degradation equation.Bayesian estimation of model parameters is given using Gibbs sampling.Finally,the validity of the deceleration model under accelerated stress was verified by numerical simulation.The Monte Carlo simulation was used to obtain the reliability curve.At the end of the article,the content of the full text is summarized and the future work is prospected.