基于物理信息深度学习与稀疏数据的电力电子器件剩余寿命预测

Accurate remaining useful life (RUL) prediction of silicon carbide mosfets is essential for ensuring the reliability of power electronic systems, particularly under irradiation environments. However, most existing deep learning approaches rely on densely sampled degradation data, making them unsuitable for sparse-data conditions where degradation observations are limited. To address this limitatio...