A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings

A Rai, SH Upadhyay - Tribology International, 2016 - Elsevier
Rolling element bearings play a crucial role in the functioning of rotating machinery.
Recently, the use of diagnostics and prognostics methodologies assisted by artificial …

State-of-the-art methods and results in tool condition monitoring: a review

AG Rehorn, J Jiang, PE Orban - The International Journal of Advanced …, 2005 - Springer
This paper presents a review of the state-of-the-art in sensors and signal processing
methodologies used for tool condition monitoring (TCM) systems in industrial machining …

Vibration-based intelligent fault diagnosis for roller bearings in low-speed rotating machinery

L Song, H Wang, P Chen - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper proposes a new signal feature extraction and fault diagnosis method for fault
diagnosis of low-speed machinery. Statistic filter (SF) and wavelet package transform (WPT) …

A medical records managing and securing blockchain based system supported by a genetic algorithm and discrete wavelet transform

AF Hussein, N ArunKumar, G Ramirez-Gonzalez… - Cognitive Systems …, 2018 - Elsevier
The privacy of patients is jeopardised when medical records and data are spread or shared
beyond the protected cloud of institutions. This is because breaches force them to the brink …

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 …

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 …

Bearing fault detection by one‐dimensional convolutional neural networks

L Eren - Mathematical Problems in Engineering, 2017 - Wiley Online Library
Bearing faults are the biggest single source of motor failures. Artificial Neural Networks
(ANNs) and other decision support systems are widely used for early detection of bearing …

Fault diagnosis of ball bearings using machine learning methods

PK Kankar, SC Sharma, SP Harsha - Expert Systems with applications, 2011 - Elsevier
Ball bearings faults are one of the main causes of breakdown of rotating machines. Thus,
detection and diagnosis of mechanical faults in ball bearings is very crucial for the reliable …

Review of condition monitoring of rolling element bearing using vibration analysis and other techniques

C Malla, I Panigrahi - Journal of Vibration Engineering & Technologies, 2019 - Springer
Background Different types of machines having rotary component are linked together in
process industries, to perform the process of manufacturing. The failure of any single …

Using multi-sensor data fusion for vibration fault diagnosis of rolling element bearings by accelerometer and load cell

MS Safizadeh, SK Latifi - Information fusion, 2014 - Elsevier
This paper presents a new method for bearing fault diagnosis using the fusion of two primary
sensors: an accelerometer and a load cell. A novel condition-based monitoring (CBM) …