A roadmap to fault diagnosis of industrial machines via machine learning: a brief review
In fault diagnosis, machine learning theories are gaining popularity as they proved to be an
efficient tool that not only reduces human effort but also identifies the health conditions of the …
efficient tool that not only reduces human effort but also identifies the health conditions of the …
Infrared thermography-based fault diagnosis of induction motor bearings using machine learning
Bearing is one of the most crucial parts in induction motor (IM) as a result there is a constant
call for effective diagnosis of bearing faults for reliable operation. Infrared thermography …
call for effective diagnosis of bearing faults for reliable operation. Infrared thermography …
[HTML][HTML] Artificial intelligence integrated grid systems: Technologies, potential frameworks, challenges, and research directions
Real-time monitoring and control are crucial for ensuring the resilient, coordinated, and
optimal operation of next-generation power systems, such as virtual power plants and …
optimal operation of next-generation power systems, such as virtual power plants and …
ANN-based pattern recognition for induction motor broken rotor bar monitoring under supply frequency regulation
The requisite of direct-on-line (DOL) starting for various applications in underground mines
subjects the rotor bars of heavy-duty squirrel cage induction motors (SCIMs) to severe …
subjects the rotor bars of heavy-duty squirrel cage induction motors (SCIMs) to severe …
[HTML][HTML] AI-driven thermography-based fault diagnosis in single-phase induction motor
Single-phase induction motors (SIMs) are commonly used in industrial applications. The
extensive industrial usage of SIMs requires proper maintenance and fault detection. Among …
extensive industrial usage of SIMs requires proper maintenance and fault detection. Among …
A method of online anomaly perception and failure prediction for high-speed automatic train protection system
R Kang, J Wang, J Chen, J Zhou, Y Pang, L Guo… - Reliability Engineering & …, 2022 - Elsevier
Automatic train protection (ATP) system is the key to ensure the safe operation of high-speed
trains. However, the existing operation and maintenance mode for ATP systems cannot …
trains. However, the existing operation and maintenance mode for ATP systems cannot …
Fault detection in rotating elements by using fuzzy integrated improved local binary pattern method
An infrared thermography method is a promising tool for defect detection in rotating
machines, as this approach is a non-intrusive and no-contact kind of approach. Although the …
machines, as this approach is a non-intrusive and no-contact kind of approach. Although the …
Experimental Diagnosis of Broken Rotor Bar Faults in Induction Motors at Low Slip via Hilbert Envelope and Optimized Subtractive Clustering Adaptive Neuro-Fuzzy …
Knowledge of the distinctive frequencies and amplitudes of broken rotor bar (BRB) faults in
the induction motor (IM) is essential for most fault diagnosis methods. Fast Fourier transform …
the induction motor (IM) is essential for most fault diagnosis methods. Fast Fourier transform …
Review of Data Processing Methods Used in Predictive Maintenance for Next Generation Heavy Machinery
Vibration-based condition monitoring plays an important role in maintaining reliable and
effective heavy machinery in various sectors. Heavy machinery involves major investments …
effective heavy machinery in various sectors. Heavy machinery involves major investments …
[HTML][HTML] Optimized Fault Classification in Electric Vehicle Drive Motors Using Advanced Machine Learning and Data Transformation Techniques
The increasing use of electric vehicles has made fault diagnosis in electric drive motors,
particularly in variable speed drives (VSDs) using three-phase induction motors, a critical …
particularly in variable speed drives (VSDs) using three-phase induction motors, a critical …