Adaptive Active Learning for Online Reliability Prediction of Satellite Electronics
Accurate on-orbit reliability prediction for satellite electronics is often hindered by limited data availability, varying operational conditions, and considerable unit-to-unit variability. To overcome these obstacles, this paper proposes a novel integrated online reliability prediction framework. The main contributions are twofold. First, a Wiener process-based degradation model is developed, incorporating a generalized Arrhenius link function, individual random effects, and spatial correlations among adjacent units. A customized maximum likelihood estimation method is further devised to facilitate efficient and accurate parameter inference. Second, a two-stage active learning sampling s...
| Authors | Shixiang Li, Yubin Tian, Dianpeng Wang et al. |
|---|---|
| Primary category | stat.ME |
| Published | 10 March 2026 |
| Last updated at source | 10 March 2026 |
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