Rolling bearing fault detection is critical for improving production efficiency and lowering
accident rates in complicated mechanical systems, as well as huge monitoring data, posing …

Attention Mechanism has become very popular in the field of mechanical fault diagnosis in
recent years and has become an important technique for scholars to study and apply. The …

To enable researchers to fully trust the decisions made by deep diagnostic models,
interpretable rotating machinery fault diagnosis (RMFD) research has emerged. Existing …

Mechanical system usually operates in harsh environments, and the monitored vibration
signal faces substantial noise interference, which brings great challenges to the robust fault …

With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …

Convolutional neural networks (CNNs) are being utilized for mechanical fault diagnosis, due
to its excellent automatic discriminative feature learning ability. However, the poor …

The industrial gearboxes usually work in harsh and variable conditions, which results in
partial failure of gears or bearings. Accordingly, the continuous irregular fluctuations of …

The traditional production paradigm of large batch production does not offer flexibility toward
satisfying the requirements of individual customers. A new generation of smart factories is …

With the development of intelligent manufacturing and automation, the precision and
complexity of mechanical equipment are increasing, which leads to a higher requirement for …

Fault diagnosis and prognosis (FDP) tries to recognize and locate the faults from the
captured sensory data, and also predict their failures in advance, which can greatly help to …