Fault diagnosis is of significance for ensuring the safe and reliable operation of machinery
equipment. Due to the heavy noise and interference, it is difficult to detect the fault directly …

Compound fault, as a primary failure leading to unexpected downtime of rotating machinery,
dramatically increases the difficulty in fault diagnosis. To deal with the difficulty encountered …

Being an effective methodology to adaptatively decompose a multi-component signal into a
series of amplitude-modulated-frequency-modulated (AMFM) sub-signals with limited …

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 …

Blind deconvolution has been proved to be an effective method for fault detection since it
can recover periodic impulses from mixed fault signals convoluted by noise and periodic …

In the case of a compound fault diagnosis of rotating machinery, when two failures with
unequal severity occur in distinct parts of the system, the detection of a minor fault is a …

The variational mode extraction (VME) developed on the similar basis of variational mode
decomposition (VMD) can effectively separate a specific mode by knowing an approximate …

Variational mode decomposition has been widely applied to machinery fault diagnosis
during these years. However, it remains difficult to set proper hyperparameters for the …

The selection of variational mode decomposition (VMD) parameters usually adopts the
empirical method, trial-and-error method, or single-objective optimization method. The …

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 …