A review on data-driven fault severity assessment in rolling bearings
Health condition monitoring of rotating machinery is a crucial task to guarantee reliability in
industrial processes. In particular, bearings are mechanical components used in most …
industrial processes. In particular, bearings are mechanical components used in most …
Rotating machinery fault diagnosis based on typical resonance demodulation methods: a review
H Li, X Wu, T Liu, S Li - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
The increasing integration and complexity of rotating machinery have led to the difficulty of
its fault diagnosis. Condition-based maintenance (CBM) strategy is becoming more and …
its fault diagnosis. Condition-based maintenance (CBM) strategy is becoming more and …
Sparsity guided empirical wavelet transform for fault diagnosis of rolling element bearings
Rolling element bearings are widely used in various industrial machines, such as electric
motors, generators, pumps, gearboxes, railway axles, turbines, and helicopter …
motors, generators, pumps, gearboxes, railway axles, turbines, and helicopter …
A coarse-to-fine decomposing strategy of VMD for extraction of weak repetitive transients in fault diagnosis of rotating machines
Abstract Variational Mode Decomposition (VMD) has attracted much attention and been
used to analyze different kinds of signals, such as mechanical signals, medical data, and …
used to analyze different kinds of signals, such as mechanical signals, medical data, and …
A new family of model-based impulsive wavelets and their sparse representation for rolling bearing fault diagnosis
Y Qin - IEEE Transactions on Industrial Electronics, 2017 - ieeexplore.ieee.org
The localized faults of rolling bearings can be diagnosed by the extraction of the impulsive
feature. However, the approximately periodic impulses may be submerged in strong …
feature. However, the approximately periodic impulses may be submerged in strong …
Application of CSA-VMD and optimal scale morphological slice bispectrum in enhancing outer race fault detection of rolling element bearings
X Yan, M Jia - Mechanical Systems and Signal Processing, 2019 - Elsevier
The bearing vibration signal with strong non-stationary properties is normally composed of
multiple components (eg periodic impulses, background noise and other external signal) …
multiple components (eg periodic impulses, background noise and other external signal) …
Fault diagnosis for rotating machinery using vibration measurement deep statistical feature learning
Fault diagnosis is important for the maintenance of rotating machinery. The detection of
faults and fault patterns is a challenging part of machinery fault diagnosis. To tackle this …
faults and fault patterns is a challenging part of machinery fault diagnosis. To tackle this …
Improvement of kurtosis-guided-grams via Gini index for bearing fault feature identification
A group of kurtosis-guided-grams, such as Kurtogram, Protrugram and SKRgram, is
designed to detect the resonance band excited by faults based on the sparsity index …
designed to detect the resonance band excited by faults based on the sparsity index …
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 …
[HTML][HTML] AI-based neural network models for bus passenger demand forecasting using smart card data
Accurate short-term forecasting of public transport demand is essential for the operation of
on-demand public transport. Knowing where and when future demands for travel are …
on-demand public transport. Knowing where and when future demands for travel are …