The monitoring of rolling element bearing is indexed as a critical task for condition-based
maintenance in various industrial applications. It allows avoiding unscheduled maintenance …

Bearings are the core components of rotating machinery and are vulnerable to failure. Early
fault prediction is a significant and challenging task for bearing due to the weakness of fault …

Deep learning techniques have recently brought many improvements in the field of neural
network training, especially for prognosis and health management. The success of such an …

Since bearing deterioration patterns are difficult to collect from real, long lifetime scenarios,
data-driven research has been directed towards recovering them by imposing accelerated …

Featured Application The proposed GWO-VMD-and DE-KELM-based hybrid fault diagnosis
method can be applied to offline and high-precision fault diagnosis of gearboxes in wind …

Failure detection and diagnosis are of crucial importance for the reliable and safe operation
of industrial equipment and systems, while gearbox failures are one of the main factors …

Nowadays, bearings installed in industrial electric motors are constituted as the primary
mode of a failure affecting the global energy consumption. Since industries' energy demand …

Due to the mechanical equipment working under variable speed and load for a long time,
the distribution of samples is different (domain shift). The general intelligent fault diagnosis …

The complex operational environment brings challenges to vibration signal-based rotating
mechanical equipment fault identification. On one hand, the fault features under heavy …

Remaining Useful Life (RUL) prediction of mechanical equipment is an application of
Prognostics and Health Management (PHM) technology in mechanical equipment, and is …