Hurst based vibro-acoustic feature extraction of bearing using EMD and VMD
Fault feature extractions of the bearings using the vibration signals are an age old method to
anticipate faults in machines. However, the recent research shows that the acoustic sensing …
anticipate faults in machines. However, the recent research shows that the acoustic sensing …
Fault diagnosis for rolling bearing based on VMD-FRFT
X Li, Z Ma, D Kang, X Li - Measurement, 2020 - Elsevier
In order to solve the problems that the fault feature of rolling bearing in early failure period is
difficult to extract and the over-decomposition problem arises when applying the variational …
difficult to extract and the over-decomposition problem arises when applying the variational …
Adaptive energy-constrained variational mode decomposition based on spectrum segmentation and its application in fault detection of rolling bearing
J Li, X Cheng, Q Li, Z Meng - Signal Processing, 2021 - Elsevier
Variational mode decomposition (VMD), a practical adaptive signal decomposition method,
has been widely concerned in the fault detection of rolling bearings. However, the …
has been widely concerned in the fault detection of rolling bearings. However, the …
A denoising method of partial discharge signal based on improved SVD-VMD
A denoising method combined with singular value decomposition (SVD) and variational
mode decomposition (VMD) is proposed to eliminate noise in on-site partial discharge (PD) …
mode decomposition (VMD) is proposed to eliminate noise in on-site partial discharge (PD) …
Fault diagnosis method for hydraulic directional valves integrating PCA and XGBoost
Y Lei, W Jiang, A Jiang, Y Zhu, H Niu, S Zhang - Processes, 2019 - mdpi.com
A novel fault diagnosis method is proposed, depending on a cloud service, for the typical
faults in the hydraulic directional valve. The method, based on the Machine Learning …
faults in the hydraulic directional valve. The method, based on the Machine Learning …
A novel method to classify bearing faults by integrating standard deviation to refined composite multi-scale fuzzy entropy
A new method is proposed in the present work for identifying fault severity in the ball
bearings. Proposed method named as multi-scale refined composite standard deviation …
bearings. Proposed method named as multi-scale refined composite standard deviation …
Non-invasive vibration measurement for diagnosis of bearing faults in 3-phase squirrel cage induction motor using microwave sensor
The vibration is an important feature of the motor to diagnose the different faults. The existing
invasive and non-invasive methods to capture and analysis vibration signals have many …
invasive and non-invasive methods to capture and analysis vibration signals have many …
SHapley Additive exPlanations (SHAP) for Efficient Feature Selection in Rolling Bearing Fault Diagnosis
MR Santos, A Guedes, I Sanchez-Gendriz - Machine Learning and …, 2024 - mdpi.com
This study introduces an efficient methodology for addressing fault detection, classification,
and severity estimation in rolling element bearings. The methodology is structured into three …
and severity estimation in rolling element bearings. The methodology is structured into three …
A deep neural network-based feature fusion for bearing fault diagnosis
DT Hoang, XT Tran, M Van, HJ Kang - Sensors, 2021 - mdpi.com
This paper presents a novel method for fusing information from multiple sensor systems for
bearing fault diagnosis. In the proposed method, a convolutional neural network is exploited …
bearing fault diagnosis. In the proposed method, a convolutional neural network is exploited …
Supervisory algorithm based on reaction wheel modelling and spectrum analysis for detection and classification of electromechanical faults
This study presents the design of a supervisory software algorithm that can detect and
classify different types of electromechanical faults and determine the fault source in the …
classify different types of electromechanical faults and determine the fault source in the …