FE-MCFormer: An interpretable fault diagnosis framework for rotating machinery under strong noise based on time-frequency fusion transformer

Fuente: arXiv

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Bibliographic Details
Main Authors:	Yuan, Yuhan, Jiang, Xiaomo, Yang, Haibin, Zhao, Haixin, Wang, Shengbo, Cheng, Xueyu, Meng, Jigang, Yang, Shuhua
Format:	Preprint
Published:	2025
Subjects:	Signal Processing Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2505.06285