Incipient fault diagnosis of bearings based on parameter-optimized VMD and envelope spectrum weighted kurtosis index with a new sensitivity assessment threshold
Due to difficulties in identifying localized and incipient bearing faults, most proposed fault
diagnosis methods focus on detecting these faults. However, it is not clear to what extent of …
diagnosis methods focus on detecting these faults. However, it is not clear to what extent of …
A new statistical features based approach for bearing fault diagnosis using vibration signals
In condition based maintenance, different signal processing techniques are used to sense
the faults through the vibration and acoustic emission signals, received from the machinery …
the faults through the vibration and acoustic emission signals, received from the machinery …
Novel bearing fault diagnosis using gaussian mixture model-based fault band selection
This paper proposes a Gaussian mixture model-based (GMM) bearing fault band selection
(GMM-WBBS) method for signal processing. The proposed method benefits reliable feature …
(GMM-WBBS) method for signal processing. The proposed method benefits reliable feature …
Compound fault diagnosis of bearings using improved fast spectral kurtosis with VMD
S Wan, X Zhang, L Dou - Journal of Mechanical Science and Technology, 2018 - Springer
The fast spectrum kurtosis (FSK) algorithm can adaptively identify resonance bands of a
signal, and fault characteristics can be extracted by analyzing the selected frequency bands …
signal, and fault characteristics can be extracted by analyzing the selected frequency bands …
A novel correntropy-based band selection method for the fault diagnosis of bearings under fault-irrelevant impulsive and cyclostationary interferences
Demodulation analysis is one of the most effective methods for bearing fault diagnosis.
However, in practical applications, the interferences from ambient noises or other rotating …
However, in practical applications, the interferences from ambient noises or other rotating …
Composite fault diagnosis for rolling bearing based on parameter-optimized VMD
H Li, X Wu, T Liu, S Li, B Zhang, G Zhou, T Huang - Measurement, 2022 - Elsevier
Variational mode decomposition (VMD) is a recently introduced adaptive signal analysis
method, which is widely used in fault diagnosis of rotating machinery due to its excellent …
method, which is widely used in fault diagnosis of rotating machinery due to its excellent …
Bearing fault diagnosis based on variational mode decomposition and total variation denoising
S Zhang, Y Wang, S He, Z Jiang - Measurement Science and …, 2016 - iopscience.iop.org
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 …
vibration signals are complex and non-stationary in nature, and meanwhile impulsive …
A new approach based on OMA-empirical wavelet transforms for bearing fault diagnosis
Amplitude demodulation is a key means of diagnosing bearing faults. The quality of
demodulation determines the effectiveness of spectrum analysis in detecting defects …
demodulation determines the effectiveness of spectrum analysis in detecting defects …
Smart multichannel mode extraction for enhanced bearing fault diagnosis
In bearing fault diagnosis, multichannel data can contain more abundant and complete fault
information to alleviate the influence of accidental factors in a single channel. To fully …
information to alleviate the influence of accidental factors in a single channel. To fully …
Diagnosis of compound faults of rolling bearings through adaptive maximum correlated kurtosis deconvolution
G Tang, X Wang, Y He - Journal of Mechanical Science and Technology, 2016 - Springer
This paper proposes a new diagnosis method based on Adaptive maximum correlated
kurtosis deconvolution (AMCKD) for accurate identification of compound faults of rolling …
kurtosis deconvolution (AMCKD) for accurate identification of compound faults of rolling …