In this article, a new decomposition theory, feature mode decomposition (FMD), is tailored
for the feature extraction of machinery fault. The proposed FMD is essentially for the purpose …

To overcome current challenges in variational mode decomposition (VMD) and its variants
for the fault diagnosis of rotating machines, the decomposing characteristics of two sub …

Rotating machinery covers a broad range of mechanical equipment and plays a significant
role in industrial applications. It generally operates under tough working environment and is …

In this paper, an empirical mode decomposition (EMD) based approach for rotating machine
fault diagnosis is investigated. EMD is a new time–frequency analyzing method for nonlinear …

The vibration signals of faulty rotating machinery are typically nonstationary, nonlinear, and
mixed with abundant compounded background noise. To extract the potential excitations …

Intelligent fault diagnosis of rotating machinery is vital for industries to improve fault
prediction performance and reduce the maintenance cost. The new fault diagnostic …

Vibration-based feature extraction of multiple transient fault signals is a challenge in the field
of rotating machinery fault diagnosis. Variational mode decomposition (VMD) has great …

Fault feature extraction is crucial to detect failures as earlier as possible in fault diagnosis of
rotating machinery. Due to the influence of environment noise and interference, the signal to …

Variational mode decomposition (VMD), an effective signal decomposing technique, has
attracted considerable attention in recent years. The successful applicability of the VMD …

A time–frequency analysis method based on ensemble local mean decomposition (ELMD)
and fast kurtogram (FK) is proposed for rotating machinery fault diagnosis. Local mean …