Domain Generalization of RUL Prediction for Bearings via Multisource Domain Mix-Up Transfer

Accurate prediction of the remaining useful life for bearings is essential to predictive maintenance and health management. Nonetheless, the initial operating phase often suffers from limited and incomplete data, which poses significant challenges to the development of robust life prediction models. To address this problem, this article introduces a multi-source domain mix-up transfer (MDMT) model, integrated with a data reproduction mechanism. The proposed approach utilizes a bidirectional gate