Inverse physics–informed neural networks for digital twin–based bearing fault diagnosis under imbalanced samples

已完结 10 由 Guodong Qu 发布于 2026/4/10 9:22:01

DOI:10.1016/j.knosys.2024.111641
作者：Yi Qin ,?Hongyu Liu ,?Yi Wang ,?Yongfang Mao
文献类型：期刊论文
补充材料：只需要正文

Elsevier

Abstract：In actual engineering, insufficient bearing samples for each fault category presents a substantial obstacle to the intelligent fault diagnosis of rolling bearings. To address sample imbalanc

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