[HTML][HTML] Insights into modern machine learning approaches for bearing fault classification: A systematic literature review
Rolling bearings are essential components in a wide range of equipment, such as
aeroplanes, trains, and wind turbines. Bearing failure has the potential to result in complete …
aeroplanes, trains, and wind turbines. Bearing failure has the potential to result in complete …
[HTML][HTML] A review on rolling bearing fault signal detection methods based on different sensors
G Wu, T Yan, G Yang, H Chai, C Cao - Sensors, 2022 - mdpi.com
As a precision mechanical component to reduce friction between components, the rolling
bearing is widely used in many fields because of its slight friction loss, strong bearing …
bearing is widely used in many fields because of its slight friction loss, strong bearing …
Brain tumor classification using modified local binary patterns (LBP) feature extraction methods
Automatic classification of brain tumor types is very important for accelerating the treatment
process, planning and increasing the patient's survival rate. Today, MR images are used to …
process, planning and increasing the patient's survival rate. Today, MR images are used to …
Bearing fault diagnosis using transfer learning and optimized deep belief network
H Zhao, X Yang, B Chen, H Chen… - … Science and Technology, 2022 - iopscience.iop.org
Bearing is an important component in mechanical equipment. Its main function is to support
the rotating mechanical body and reduce the friction coefficient and axial load. In the actual …
the rotating mechanical body and reduce the friction coefficient and axial load. In the actual …
A new automatic bearing fault size diagnosis using time-frequency images of CWT and deep transfer learning methods
Y Kaya, F Kuncan… - Turkish Journal of Electrical …, 2022 - journals.tubitak.gov.tr
Bearings are generally used as bearings or turning elements. Bearings are subjected to
high loads and rapid speeds. Furthermore, metal-to-metal contact within the bearing makes …
high loads and rapid speeds. Furthermore, metal-to-metal contact within the bearing makes …
Bearing fault diagnosis with envelope analysis and machine learning approaches using CWRU dataset
Predictive maintenance in machines aims to anticipate failures. In rotating machines, the
component that suffers the most wear and tear is the bearings. Currently, based on the …
component that suffers the most wear and tear is the bearings. Currently, based on the …
Effective feature selection with fuzzy entropy and similarity classifier for chatter vibration diagnosis
Feature selection represents the main challenge against the classification strategies for
several applications of signal processing. Besides, the high computational speed and …
several applications of signal processing. Besides, the high computational speed and …
Interpretability of deep convolutional neural networks on rolling bearing fault diagnosis
Despite the rapid development of deep learning-based intelligent fault diagnosis methods
on rotating machinery, the data-driven approach generally remains a'black box'to …
on rotating machinery, the data-driven approach generally remains a'black box'to …
[HTML][HTML] A wind turbine bearing fault diagnosis method based on fused depth features in time–frequency domain
Z Tang, M Wang, T Ouyang, F Che - Energy Reports, 2022 - Elsevier
Diagnosis of bearing faults has significant meaning to the maintenance of wind turbines in
real industry. Well-performed bearing fault diagnosis generally requires effective features …
real industry. Well-performed bearing fault diagnosis generally requires effective features …
Data-driven intelligent condition adaptation of feature extraction for bearing fault detection using deep responsible active learning
The detection of faulty bearings is an essential step in guaranteeing the safe and efficient
operation of rotating machinery. Bearings, which also transmit the loads and pressures …
operation of rotating machinery. Bearings, which also transmit the loads and pressures …