[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 …
Enhanced fault diagnosis of rolling bearings using an improved inception-lstm network
L Wei, X Peng, Y Cao - Nondestructive Testing and Evaluation, 2024 - Taylor & Francis
Rolling bearings are integral to the operation of various mechanical systems, where their
condition directly impacts equipment reliability and performance. Accurate fault diagnosis is …
condition directly impacts equipment reliability and performance. Accurate fault diagnosis is …
Advancing machine fault diagnosis: a detailed examination of convolutional neural networks
G Vashishtha, S Chauhan, M Sehri… - Measurement …, 2024 - iopscience.iop.org
The growing complexity of machinery and the increasing demand for operational efficiency
and safety have driven the development of advanced fault diagnosis techniques. Among …
and safety have driven the development of advanced fault diagnosis techniques. Among …
Cost effective detection of uneven mounting fault in rotary wing drone motors with a CNN based method
Rotary wing drones stand out among Unmanned Aerial Vehicles with their vertical landing
and take-off feature and are used in many industrial applications and different sectors …
and take-off feature and are used in many industrial applications and different sectors …
A novel convolutional neural network with global perception for bearing fault diagnosis
X Li, Y Chen, Y Liu - Engineering Applications of Artificial Intelligence, 2025 - Elsevier
Bearings are key support components in rotating machinery, and their stability is crucial to
the reliability of the entire mechanical system. To address the limitations of existing …
the reliability of the entire mechanical system. To address the limitations of existing …
Inverse Design of FBG-Based Optical Filters Using Deep Learning: A Hybrid CNN-MLP Approach
Optical filters have always been a critical challenge for advancing communication systems.
Despite significant progress in optical filters, the process of designing, fabricating, and …
Despite significant progress in optical filters, the process of designing, fabricating, and …
Anomaly Detection in Multi-Level Model Space
Anomaly detection (AD) is gaining prominence, especially in situations with limited labeled
data or unknown anomalies, demanding an efficient approach with minimal reliance on …
data or unknown anomalies, demanding an efficient approach with minimal reliance on …
[HTML][HTML] Investigating bearing and gear vibrations with a Micro-Electro-Mechanical Systems (MEMS) and machine learning approach
Bearings and gears are the pivotal components of mechanical systems and are prone to
faults that can impact the system's overall performance. These components' condition …
faults that can impact the system's overall performance. These components' condition …
Enhancing induction machine fault detection through machine learning: Time and frequency analysis of vibration signals
The integration of machine learning algorithms into fault diagnosis is regarded as an
advanced and effective method for detecting electrical system faults. Vibration signals are …
advanced and effective method for detecting electrical system faults. Vibration signals are …
Intelligent diagnosis method of torque-angle dynamometer cards for beam pum** units based on transfer learning
J Huang, W Huang, Z Feng, D Gao - Geoenergy Science and Engineering, 2024 - Elsevier
Remote monitoring and intelligent diagnosis of operating conditions are two critical aspects
for achieving cloud intelligent diagnosis of the beam pum** unit. However, the current …
for achieving cloud intelligent diagnosis of the beam pum** unit. However, the current …