Methods of condition monitoring and fault detection for electrical machines

K Kudelina, B Asad, T Vaimann, A Rassõlkin… - Energies, 2021 - mdpi.com
Nowadays, electrical machines and drive systems are playing an essential role in different
applications. Eventually, various failures occur in long-term continuous operation. Due to the …

[HTML][HTML] Fault diagnosis for induction generator-based wind turbine using ensemble deep learning techniques

O Attallah, RA Ibrahim, NE Zakzouk - Energy Reports, 2022 - Elsevier
Fault diagnosis in induction machines (IM) require effective detection at early stages to
prevent permanent machine failure. This requires fast sensing of disturbances as well as …

Application of machine learning to a medium Gaussian support vector machine in the diagnosis of motor bearing faults

SL Lin - Electronics, 2021 - mdpi.com
In recent years, artificial intelligence technology has been widely used in fault prediction and
health management (PHM). The machine learning algorithm is widely used in the condition …

On-line detection and classification of PMSM stator winding faults based on stator current symmetrical components analysis and the KNN algorithm

P Pietrzak, M Wolkiewicz - Electronics, 2021 - mdpi.com
The significant advantages of permanent magnet synchronous motors, such as very good
dynamic properties, high efficiency and power density, have led to their frequent use in …

Effectiveness analysis of PMSM motor rolling bearing fault detectors based on vibration analysis and shallow neural networks

P Ewert, T Orlowska-Kowalska, K Jankowska - Energies, 2021 - mdpi.com
Permanent magnet synchronous motors (PMSMs) are becoming more popular, both in
industrial applications and in electric and hybrid vehicle drives. Unfortunately, like the …

Intelligent fault diagnosis and forecast of time-varying bearing based on deep learning VMD-DenseNet

SL Lin - Sensors, 2021 - mdpi.com
Rolling bearings are important in rotating machinery and equipment. This research
proposes variational mode decomposition (VMD)-DenseNet to diagnose faults in bearings …

Effectiveness of neural fault detectors of permanent magnet synchronous motor trained with symptoms from field-circuit modeling

M Skowron, M Krzysztofiak… - IEEE Access, 2022 - ieeexplore.ieee.org
Permanent magnet synchronous motors (PMSMs) are increasingly used in industrial drive
applications. However, these motors can also undergo various failures, causing production …

[HTML][HTML] A novel dataset and lightweight detection system for broken bars induction motors using optimizable neural networks

WA Elhaija, QA Al-Haija - Intelligent Systems with Applications, 2023 - Elsevier
Broken rotor bars (BRBs) in induction motors (IMs) are a common kind of failure and one of
the most difficult to detect since the induction motor continues to run properly in the absence …

[HTML][HTML] Convolutional Neural Networks Based on Resonance Demodulation of Vibration Signal for Rolling Bearing Fault Diagnosis in Permanent Magnet …

L Ding, H Guo, L Bian - Energies, 2024 - mdpi.com
Permanent magnet synchronous motors (PMSMs) are widely used due to their unique
advantages. Their transmission system mainly relies on rolling bearings; therefore …

[PDF][PDF] Increasing the efficiency of railway rolling stock operation with induction traction motors due to implementation of the operational system for diagnostic condition …

S Goolak, O Gorobchenko, H Holub, Y Dudnyk - Diagnostyka, 2024 - diagnostyka.net.pl
Traction drives with vector control are widely used on mainline locomotives with induction
motors. Traction motors can fail due to malfunctions that occur during the operation of …