Rolling element bearings play a crucial role in the functioning of rotating machinery.
Recently, the use of diagnostics and prognostics methodologies assisted by artificial …

This paper presents an empirical study of feature extraction methods for the application of
low-speed slew bearing condition monitoring. The aim of the study is to find the proper …

A rolling bearing is an essential component of a rotating mechanical transmission system. Its
performance and quality directly affects the life and reliability of machinery. Bearings' …

Wind turbine blade bearings are often operated in harsh circumstances, which may easily
be damaged causing the turbine to lose control and to further result in the reduction of …

The failure of a rolling bearing may cause the shutdown of mechanical equipment and even
induce catastrophic accidents, resulting in tremendous economic losses and a severely …

Fault feature extraction and broadband noise elimination are the keys to weak bearing fault
diagnosis. Morphological filtering is a typical fault feature extraction method. However, the …

Bearing faults of rotating machinery are observed as impulses in the vibration signal, but it is
mostly immersed in noise. In order to effectively remove this noise and detect the impulses, a …

Feature extraction plays an essential role in bearing fault detection. However, the measured
vibration signals are complex and non-stationary in nature, and meanwhile impulsive …

Incipient vibration signals of rolling element bearing are usually characterized by weak fault
symptoms and multiple interference source components, which imply that it is difficult to …

This paper presents a novel signal processing scheme, diagonal slice spectrum assisted
optimal scale morphological filter (DSS-OSMF), for rolling element fault diagnosis. In this …