Sounds and acoustic emission-based early fault diagnosis of induction motor: A review study
O AlShorman, F Alkahatni, M Masadeh… - Advances in …, 2021 - journals.sagepub.com
Nowadays, condition-based maintenance (CBM) and fault diagnosis (FD) of rotating
machinery (RM) has a vital role in the modern industrial world. However, the remaining …
machinery (RM) has a vital role in the modern industrial world. However, the remaining …
[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 …
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 …
Multi-scale deep intra-class transfer learning for bearing fault diagnosis
The tremendous success of deep learning in machine fault diagnosis is dependent on the
hypothesis that training and test datasets are subordinated to the same distribution. This …
hypothesis that training and test datasets are subordinated to the same distribution. This …
Deep transfer learning with limited data for machinery fault diagnosis
Investigation of deep transfer learning on machinery fault diagnosis is helpful to overcome
the limitations of a large volume of training data, and accelerate the practical applications of …
the limitations of a large volume of training data, and accelerate the practical applications of …
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 …
Light neural network with fewer parameters based on CNN for fault diagnosis of rotating machinery
T **, C Yan, C Chen, Z Yang, H Tian, S Wang - Measurement, 2021 - Elsevier
Many recent studies on deep learning models have focused on increasing accuracy for
mechanical fault data sets, while disregarding the influences of model complexity on …
mechanical fault data sets, while disregarding the influences of model complexity on …
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 …
Classification of white blood cells using deep features obtained from Convolutional Neural Network models based on the combination of feature selection methods
White blood cells are cells in the blood and lymph tissue produced by the bone marrow in
the human body. White blood cells are an important part of the immune system. The most …
the human body. White blood cells are an important part of the immune system. The most …
A new adversarial domain generalization network based on class boundary feature detection for bearing fault diagnosis
In recent years, many researchers have attempted to achieve cross-domain diagnosis of
faults through domain adaptation (DA) methods. However, owing to the complex physical …
faults through domain adaptation (DA) methods. However, owing to the complex physical …