This paper presents a comprehensive survey on interpretable intelligent fault diagnosis for
rotating machinery, addressing the challenge of the “black box” nature of machine learning …

In order to precisely diagnose the fault type of rotating machinery, a fault diagnosis method
for rotating machinery based on improved multiscale attention entropy and random forests is …

A gearbox is an indispensable component of a mechanical transmission system, and in the
event of an anomaly, it can have a serious impact on the stability of the system. Graph …

Fault diagnosis of mechanical equipment is critical to energy storage, and stochastic
resonance shows great potential in the field of diagnosing weak fault signals. To enhance …

Stochastic resonance is widely used in bearing fault detection due to its ability to enhance
weak signals. This paper proposes a fault detection method that combines noise reduction …

Gear disengaging, back-side tooth contact or poor dynamic behavior during operating leads
to dynamic instability in planetary gear trains (PGTs). A novel nonlinear dynamic model of …

Diagnosing incipient faults in rotating machinery is crucial for reducing maintenance costs
and preventingthe occurrence of other faults. Accurately extracting fault-related features from …

The noise transfer capability of stochastic resonance makes it excellent in the field of weak
signal detection. The classic bistable potential well has a simple structure, few parameters …

Bearings are one of the important parts of rotating machinery, and the collected vibration
signals containing bearing fault information have strong background noise. Stochastic …