Spectral kurtosis for fault detection, diagnosis and prognostics of rotating machines: A review with applications
Condition-based maintenance via vibration signal processing plays an important role to
reduce unscheduled machine downtime and avoid catastrophic accidents in industrial …
reduce unscheduled machine downtime and avoid catastrophic accidents in industrial …
A survey of condition monitoring and protection methods for medium-voltage induction motors
P Zhang, Y Du, TG Habetler, B Lu - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
Medium-voltage (MV) induction motors are widely used in the industry and are essential to
industrial processes. The breakdown of these MV motors not only leads to high repair …
industrial processes. The breakdown of these MV motors not only leads to high repair …
Multi-layer domain adaptation method for rolling bearing fault diagnosis
In the past years, data-driven approaches such as deep learning have been widely applied
on machinery signal processing to develop intelligent fault diagnosis systems. In real-world …
on machinery signal processing to develop intelligent fault diagnosis systems. In real-world …
Understanding and improving deep learning-based rolling bearing fault diagnosis with attention mechanism
In the recent years, deep learning-based intelligent fault diagnosis methods of rolling
bearings have been widely and successfully developed. However, the data-driven method …
bearings have been widely and successfully developed. However, the data-driven method …
Motor Bearing Fault Detection Using Spectral Kurtosis-Based Feature Extraction Coupled With K-Nearest Neighbor Distance Analysis
Bearing faults are the main contributors to the failure of electric motors. Although a number
of vibration analysis methods have been developed for the detection of bearing faults, false …
of vibration analysis methods have been developed for the detection of bearing faults, false …
Bearing health monitoring based on Hilbert–Huang transform, support vector machine, and regression
A Soualhi, K Medjaher… - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
The detection, diagnostic, and prognostic of bearing degradation play a key role in
increasing the reliability and safety of electrical machines, especially in key industrial …
increasing the reliability and safety of electrical machines, especially in key industrial …
[HTML][HTML] An adaptive multi-sensor data fusion method based on deep convolutional neural networks for fault diagnosis of planetary gearbox
L Jing, T Wang, M Zhao, P Wang - Sensors, 2017 - mdpi.com
A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with
complicated damage detection problems of mechanical systems. Nevertheless, this …
complicated damage detection problems of mechanical systems. Nevertheless, this …
Novel particle swarm optimization-based variational mode decomposition method for the fault diagnosis of complex rotating machinery
XB Wang, ZX Yang, XA Yan - IEEE/ASME Transactions on …, 2017 - ieeexplore.ieee.org
The vibration signals of faulty rotating machinery are typically nonstationary, nonlinear, and
mixed with abundant compounded background noise. To extract the potential excitations …
mixed with abundant compounded background noise. To extract the potential excitations …
Bearing fault detection by a novel condition-monitoring scheme based on statistical-time features and neural networks
MD Prieto, G Cirrincione, AG Espinosa… - IEEE Transactions …, 2012 - ieeexplore.ieee.org
Bearing degradation is the most common source of faults in electrical machines. In this
context, this work presents a novel monitoring scheme applied to diagnose bearing faults …
context, this work presents a novel monitoring scheme applied to diagnose bearing faults …
Motor bearing fault diagnosis using trace ratio linear discriminant analysis
Bearings are critical components in induction motors and brushless direct current motors.
Bearing failure is the most common failure mode in these motors. By implementing health …
Bearing failure is the most common failure mode in these motors. By implementing health …