Hierarchical k-nearest neighbours classification and binary differential evolution for fault diagnostics of automotive bearings operating under variable conditions
Electric traction motors in automotive applications work in operational conditions
characterized by variable load, rotational speed and other external conditions: this …
characterized by variable load, rotational speed and other external conditions: this …
Condition monitoring and intelligent diagnosis of rolling element bearings under constant/variable load and speed conditions
A Moshrefzadeh - Mechanical Systems and Signal Processing, 2021 - Elsevier
Extensive research has been conducted for intelligent fault diagnosis and prognosis of
rolling element bearings, a vital component in every rotating machinery, and many robust …
rolling element bearings, a vital component in every rotating machinery, and many robust …
Diagnosis methodology based on deep feature learning for fault identification in metallic, hybrid and ceramic bearings
JJ Saucedo-Dorantes, F Arellano-Espitia… - Sensors, 2021 - mdpi.com
Scientific and technological advances in the field of rotatory electrical machinery are leading
to an increased efficiency in those processes and systems in which they are involved. In …
to an increased efficiency in those processes and systems in which they are involved. In …
Fault detection of bearing: An unsupervised machine learning approach exploiting feature extraction and dimensionality reduction
The monitoring of rotating machinery is an essential activity for asset management today.
Due to the large amount of monitored equipment, analyzing all the collected signals/features …
Due to the large amount of monitored equipment, analyzing all the collected signals/features …
Automated diagnosis of rolling bearings using MRA and neural networks
C Castejón, O Lara, JC García-Prada - Mechanical Systems and Signal …, 2010 - Elsevier
Any industry needs an efficient predictive plan in order to optimize the management of
resources and improve the economy of the plant by reducing unnecessary costs and …
resources and improve the economy of the plant by reducing unnecessary costs and …
Fault diagnosis of motor bearing using ensemble learning algorithm with FFT-based preprocessing
N Sikder, K Bhakta, A Al Nahid… - … on Robotics, Electrical …, 2019 - ieeexplore.ieee.org
Rolling bearings are one of the pivotal mechanical elements in rotating machines like the
electric motor. However, they are liable for the majority of the faults encountered by rotating …
electric motor. However, they are liable for the majority of the faults encountered by rotating …
A feature extraction and machine learning framework for bearing fault diagnosis
Wind power generation has been widely adopted due to its renewable nature and
decreasing capital cost per kW. However, existing equipment ages rapidly, leading to higher …
decreasing capital cost per kW. However, existing equipment ages rapidly, leading to higher …
Spectral proper orthogonal decomposition and machine learning algorithms for bearing fault diagnosis
Vibration analysis has been extensively exploited for bearing fault diagnosis. However,
signal acquisition is quite expensive since external hardware is required. Moreover, for …
signal acquisition is quite expensive since external hardware is required. Moreover, for …
Condition monitoring method for the detection of fault graduality in outer race bearing based on vibration-current fusion, statistical features and neural network
JJ Saucedo-Dorantes, I Zamudio-Ramirez… - Applied Sciences, 2021 - mdpi.com
Bearings are the elements that allow the rotatory movement in induction motors, and the
fault occurrence in these elements is due to excessive working conditions. In induction …
fault occurrence in these elements is due to excessive working conditions. In induction …
A Support Vector Machine approach based on physical model training for rolling element bearing fault detection in industrial environments
KC Gryllias, IA Antoniadis - Engineering Applications of Artificial …, 2012 - Elsevier
A hybrid two stage one-against-all Support Vector Machine (SVM) approach is proposed for
the automated diagnosis of defective rolling element bearings. The basic concept and major …
the automated diagnosis of defective rolling element bearings. The basic concept and major …