Zhaoqi Liu

Mechanical fault diagnosis under long-tailed data: an improved federated learning method integrating attention, asymmetric convolution, and margin calibration

Abstract Due to the inability to collect sufficient fault samples for specific types of gear and bearing faults, the data presents a long-tailed distribution, which hinders the effective construction of neural network diagnostic models. Furthermore, when Federated Learning (FL) methods are introduced to address this lo...