Abstract
Although Wiener process models with the consideration of uncertainties, which are nonlinearity, random effects, and measurement errors, have been developed for lifetime prediction in the accelerated degradation test (ADT), they fail to describe the real degradation process because these models assume that the drift parameter correlates with the applied stress, while the diffusion parameter is constant. This paper put forward a nonlinear doubly Wiener constant-stress accelerated degradation model, where both diffusion and drift parameters were compatible with the applied stress according to the acceleration factor constant principle. When degradation data were available, we obtained the unknown parameters by applying a maximum likelihood estimation (MLE) algorithm in the constant-stress ADT (CSADT) model taking uncertainties into account. In addition, the proposed model’s effectiveness was validated through an illustrative example, and an application to the traveling wave tube (TWT) was carried out to demonstrate the superiority of our model in practical applications.
Highlights
Due to time constraints and cost, close attention has been paid to acquiring reliable information from field data with minimal effort, especially those products with high reliability and longevity
Given that performance data can be monitored either with or without failure, degradation data could offer more reliability analysis compared to Accelerated life test (ALT), including providing more reliable information and more credible reliability estimation, and the basis for stronger extrapolation and prognosis estimation, in which cases using degradation modeling and analysis with accelerated degradation test (ADT) may be more appropriate
Based on the different stress loading methods, ADT can be divided into constant-stress ADT (CSADT), step-stress ADT (SSADT), and progressive-stress ADT (PSADT)
Summary
Due to time constraints and cost, close attention has been paid to acquiring reliable information from field data with minimal effort, especially those products with high reliability and longevity. Given the variation among units, Tang, et al [15] introduced a random variable into an acceleration model to characterize the random effects and performed a nonlinear analysis of LED CASDT data under current stress using the Wiener process model with a time-scale-transform. A nonlinear doubly Wiener degradation model of CSADT with the principle of constant acceleration factor consistency was proposed, taking uncertainties into accounts, such as nonlinearity and measurement errors, we only regarded the drift parameter as random values to represent the random effects, similar to [17,18,19,20].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
