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Many industrial systems inevitably suffer performance degradation. Thus, predicting the remaining useful life (RUL) for such degrading systems has attracted significant attention in the prognostics community. For some systems like batteries, one commonly encountered phenomenon is that the system performance degrades with usage and recovers in storage. However, almost all of the current prognostic...
The last decades have witnessed the development of degradation modeling based remaining useful life (RUL) estimation, especially for Wiener process based degradation models. However, most researchers paid their attention to the drift coefficient representing the degradation rate, while much fewer eyes focus on the diffusion coefficient. The under consideration of diffusion process may cause bias in...
Degradation-modeling based prognostic approach has been proved as an effective alternative to the conventional lifetime-data dependent residual life prediction method, and thus draw much attention of both scholars and engineers in the field of reliability. The degradation process of a system is the result of interaction between its inner states and working environments. To provide a reasonable reference...
Degradation data are widely used in the field of reliability analysis and remaining useful lifetime estimation. Usually, a critical threshold must be defined before both reliability analysis and lifetime estimation is executed. In this paper, we present a method to specify a critical threshold for Wiener degradation process, based on both historical lifetime data and degradation data. The lifetime,...
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