Rolling bearings are important in rotating machinery and equipment. This research
proposes variational mode decomposition (VMD)-DenseNet to diagnose faults in bearings …

Bearing elements are vital in induction motors; therefore, early fault detection of rolling-
element bearings is essential in machine health monitoring. With the advantage of fault …

The rapid development of big data leads to many researchers focusing on improving
bearing fault classification accuracy using deep learning models. However, implementing a …

Many industries are evaluating the use of the Internet of Things (IoT) technology to perform
remote monitoring and predictive maintenance on their mission-critical assets and …

Fault diagnosis of rolling bearing is crucial for safety of large rotating machinery. However, in
practical engineering, the fault modes of rolling bearings are usually compound faults and …

The key to intelligent fault diagnosis is to find relevant characteristics with the capability of
representing different types of faults. However, the engineering problem is that a few simple …

Bearing pitting, one of the common faults in mechanical systems, is a research hotspot in
both academia and industry. Traditional fault diagnosis methods for bearings are based on …

Intelligent fault diagnosis of bearings has been a heated research topic in the prognosis and
health management of rotary machinery systems, due to the increasing amount of available …

Rolling element bearings are a vital part of rotating machines and their sudden failure can
result in huge economic losses as well as physical causalities. Popular bearing fault …

Recent works suggest that using knowledge transfer strategies to tackle cross-domain
diagnosis problems is promising for achieving engineering diagnosis. This article presents a …