Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal
functioning states are related to specific patterns that can be extracted from vibration signals …

Health condition monitoring of rotating machinery is a crucial task to guarantee reliability in
industrial processes. In particular, bearings are mechanical components used in most …

With the rapid progress in the deep learning technology, it is being used for vibration-based
structural health monitoring. When the vibration is used for extracting features for system …

Artificial intelligence (AI)-based rotor fault diagnosis (RFD) poses a variety of challenges to
the prognostics and health management (PHM) of the Industry 4.0 revolution. Rotor faults …

Effective fault diagnosis is essential for maintaining the safe running of machine systems.
Recently, the data-driven methods have shown great potential in intelligent fault diagnosis …

Machinery fault diagnosis has progressed over the past decades with the evolution of
machineries in terms of complexity and scale. High-value machineries require condition …

Deep transfer learning has evolved into a powerful method for defect identification,
particularly in mechanical systems that lack sufficient training data. Nonetheless, domain …

Ubiquitous vibration sensing forms a core requirement of Internet of Things (IoT)
applications in condition-based monitoring (CbM). Such sensors can enable cost savings by …

The vibrations of a shaft in rotary mechanical systems supported by angular contact ball
bearings are investigated theoretically and experimentally for various preloads in this paper …

Utilizing shaft-speed information to analyse vibration signals is an important method for fault
diagnosis and condition monitoring of rotating machineries, especially for those running at …