The imbalance is an inevitable problem in mechanical fault diagnostics, as most of the
monitored samples for mechanical devices are normal, which results in the decision …

To accurately diagnose the quayside container crane (QCC) gearbox faults, this article
proposes a method that combines the frequency-domain Markov transformation field …

Rotating machinery typically consists of multiple rotating components, and its fault signals
contain not only periodic impulse components caused by local defects but also periodic …

The entropy-based feature extraction is a promising tool for extracting weak features from
rotating machinery. However, the existing research has paid little attention to the state …

Multiscale-based entropy methods have proven to be a promising tool for extracting fault
information due to their high feature extraction ability and easy application. Despite …

The extraction of fault-induced repetitive transients which possess cyclo-stationarity is the
key to the fault diagnosis of rotating machinery, which is of considerable significance for …

Vibration signals, serving as critical sources of information for monitoring the status of
rotating machinery, demand effective extraction and rational utilization of its features to …

Prompt fault diagnosis of rotating machinery is crucial for minimizing economic losses and
preventing safety accidents in industrial applications. Fourier transform (FT) is a fundamental …

Rolling bearing plays an important role in carrying and transmitting power in rotating
machinery, and the bearing fault is easy to lead to mechanical accidents, resulting in huge …

In the field of gear health monitoring, the measured signals are traditionally derived from a
single sensor or a single direction. However, with the increasing complexity and size of …