Currently, study on the relevant methods of variational mode decomposition (VMD) is mainly focused on the selection of the number of decomposed modes and the bandwidth parameter using various optimization algorithms. Most of these methods utilize the genetic-like algorithms to quantitatively analyze these parameters, which increase the additional initial parameters and inevitably the computational burden due to ignoring the inherent characteristics of the VMD. From the perspective to locate the initial center frequency (ICF) during the VMD decomposition process, we propose an enhanced VMD with the guidance of envelope negentropy spectrum for bearing fault diagnosis, thus effectively avoiding the drawbacks of the current VMD-based algorithms...
International audienceIn bearing fault diagnosis, ensemble empirical mode decomposition (EEMD) is a ...
Vibration signals of the defect rolling element bearings are usually immersed in strong background ...
Rolling bearings are key components of rotary machines. To ensure early effective fault diagnosis fo...
In view of the incipient fault characteristics are difficult to be extracted from the raw bearing fa...
International audienceThe accurate fault diagnosis of rolling bearings is of great significance to e...
The variational mode decomposition (VMD) method for signal decomposition is severely affected by the...
Variational mode decomposition (VMD) is a new method of signal adaptive decomposition. In the VMD fr...
This paper proposes a novel method to improve the variational mode decomposition (VMD) method and to...
Variational Mode Decomposition (VMD) provides a robust and feasible scheme for the analysis of mecha...
When rolling bearings have a local fault, the real bearing vibration signal related to the local fau...
Variational Mode Decomposition (VMD) can decompose signals into multiple intrinsic mode functions (I...
To improve the accuracy of bearing fault recognition, a novel bearing fault diagnosis (PAVMD-EE-PNN)...
International audienceThis work presents a variational mode decomposition (VMD) based detector for b...
Rolling bearing is an important part guaranteeing the normal operation of rotating machinery, which ...
To solve the intractable problems of optimal rank truncation threshold and dominant modes selection ...
International audienceIn bearing fault diagnosis, ensemble empirical mode decomposition (EEMD) is a ...
Vibration signals of the defect rolling element bearings are usually immersed in strong background ...
Rolling bearings are key components of rotary machines. To ensure early effective fault diagnosis fo...
In view of the incipient fault characteristics are difficult to be extracted from the raw bearing fa...
International audienceThe accurate fault diagnosis of rolling bearings is of great significance to e...
The variational mode decomposition (VMD) method for signal decomposition is severely affected by the...
Variational mode decomposition (VMD) is a new method of signal adaptive decomposition. In the VMD fr...
This paper proposes a novel method to improve the variational mode decomposition (VMD) method and to...
Variational Mode Decomposition (VMD) provides a robust and feasible scheme for the analysis of mecha...
When rolling bearings have a local fault, the real bearing vibration signal related to the local fau...
Variational Mode Decomposition (VMD) can decompose signals into multiple intrinsic mode functions (I...
To improve the accuracy of bearing fault recognition, a novel bearing fault diagnosis (PAVMD-EE-PNN)...
International audienceThis work presents a variational mode decomposition (VMD) based detector for b...
Rolling bearing is an important part guaranteeing the normal operation of rotating machinery, which ...
To solve the intractable problems of optimal rank truncation threshold and dominant modes selection ...
International audienceIn bearing fault diagnosis, ensemble empirical mode decomposition (EEMD) is a ...
Vibration signals of the defect rolling element bearings are usually immersed in strong background ...
Rolling bearings are key components of rotary machines. To ensure early effective fault diagnosis fo...