Open Access

ARTICLE

SEFormer: A Lightweight CNN-Transformer Based on Separable Multiscale Depthwise Convolution and Efficient Self-Attention for Rotating Machinery Fault Diagnosis

Hongxing Wang¹, Xilai Ju², Hua Zhu^1,*, Huafeng Li^1,*

1 State Key Laboratory of Mechanics and Control for Aerospace Structures, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China
2 School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, Singapore

* Corresponding Authors: Hua Zhu. Email: ; Huafeng Li. Email: