A summary of fault modelling and predictive health monitoring of rolling element bearings

I El-Thalji, E Jantunen - Mechanical systems and signal processing, 2015 - Elsevier
The rolling element bearing is one of the most critical components that determine the
machinery health and its remaining lifetime in modern production machinery. Robust …

A review of research on wind turbine bearings' failure analysis and fault diagnosis

H Peng, H Zhang, Y Fan, L Shangguan, Y Yang - Lubricants, 2022 - mdpi.com
Bearings are crucial components that decide whether or not a wind turbine can work
smoothly and that have a significant impact on the transmission efficiency and stability of the …

Dynamic modelling of the defect extension and appearance in a cylindrical roller bearing

J Liu, L Wang, Z Shi - Mechanical Systems and Signal Processing, 2022 - Elsevier
Local defects in cylindrical roller (CR) bearings usually occur on the contact surfaces. The
ideal sharp-edged rectangular defect models given by the previous works are almost …

A new dynamic model and transfer learning based intelligent fault diagnosis framework for rolling element bearings race faults: Solving the small sample problem

Y Dong, Y Li, H Zheng, R Wang, M Xu - ISA transactions, 2022 - Elsevier
Intelligent fault diagnosis of rolling element bearings gains increasing attention in recent
years due to the promising development of artificial intelligent technology. Many intelligent …

Data-model combined driven digital twin of life-cycle rolling bearing

Y Qin, X Wu, J Luo - IEEE Transactions on Industrial Informatics, 2021 - ieeexplore.ieee.org
The digital twin of a life-cycle rolling bearing is significant for its degradation performance
analysis and health management. This article proposes a digital twin model of life-cycle …

Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network

JB Ali, B Chebel-Morello, L Saidi, S Malinowski… - … Systems and Signal …, 2015 - Elsevier
Accurate remaining useful life (RUL) prediction of critical assets is an important challenge in
condition based maintenance to improve reliability and decrease machine's breakdown and …

A dynamic modelling method of a rotor-roller bearing-housing system with a localized fault including the additional excitation zone

J Liu - Journal of Sound and Vibration, 2020 - Elsevier
Rotor-roller bearing-housing systems (RBHSs) are widely utilized in many industrial
machinery, such as aero-engines, high speed trains, wind turbine, etc. A clearly …

Simulation-driven machine learning: Bearing fault classification

C Sobie, C Freitas, M Nicolai - Mechanical Systems and Signal Processing, 2018 - Elsevier
Increasing the accuracy of mechanical fault detection has the potential to improve system
safety and economic performance by minimizing scheduled maintenance and the probability …

Heterogeneous feature models and feature selection applied to bearing fault diagnosis

TW Rauber, F de Assis Boldt… - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
Distinct feature extraction methods are simultaneously used to describe bearing faults. This
approach produces a large number of heterogeneous features that augment discriminative …

Dynamic modeling for rigid rotor bearing systems with a localized defect considering additional deformations at the sharp edges

J Liu, Y Shao - Journal of Sound and Vibration, 2017 - Elsevier
Rotor bearing systems (RBSs) play a very valuable role for wind turbine gearboxes, aero−
engines, high speed spindles, and other rotational machinery. An in− depth understanding …