Open access
Aug 2026
MSFTNet: multi-scale frequency-temporal network for machinery fault diagnosis under complex working conditions
A multi-scale frequency-temporal network that achieves an average accuracy of 99.58% under variable speeds and maintains a robust accuracy of 70.14% even under extreme noise conditions, outperforming baseline methods across a range of complex scenarios.
Deguang Li, Zhen Ding, Yixin Chen et al.
· Engineering Research Express · 0 citations