The stator current in an induction motor contains a large amount of information, which is
unrelated to bearing faults. This information is considered as the noise component for the …

Rolling bearings often run under variable speed condition, in addition to constant speed
condition. How to achieve the bearing fault diagnosis under variable speed condition has …

Bearing weak fault feature extraction under time-varying speed conditions is a challenging
task. The classic time-frequency analysis (TFA) based ridge detection algorithms cannot …

This study proposes a novel resonance demodulation frequency band selection method
named the initial center frequency-guided filter (ICFGF) to diagnose the bearing fault. The …

Rolling element bearing (REB) vibration signals under variable speed (VS) have non-
stationary characteristics. Order tracking (OT) and time-frequency analysis (TFA) are two …

The dependence on big data and lengthy training time discount the advantages of deep
learning methods applied in machinery fault diagnosis. Moreover, the performance of deep …

The health of rolling bearing is of great importance for the normal operation of rotating
machinery. The fault diagnosis process can be roughly summarized as signal processing …

For bearing fault diagnosis at time-varying speed with tachometer-free and non-resampling,
the crucial process is to obtain a high-resolution time-frequency representation and extract …

The extraction of weak fault signatures with periodic impulse characteristics is a crucial
aspect of detecting an early fault of bearing. In order to suppress the interference of …

The vibration signals of faulty bearings under non-stationary conditions are inherently multi-
component and time-varying, which presents a challenge for effective fault diagnosis …