Advanced signal processing methods for condition monitoring

R Jaros, R Byrtus, J Dohnal, L Danys, J Baros… - … Methods in Engineering, 2023 - Springer
Condition monitoring of induction motors (IM) among with the predictive maintenance
concept are currently among the most promising research topics of manufacturing industry …

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 …

Bearing fault diagnosis of induction motors using a genetic algorithm and machine learning classifiers

RN Toma, AE Prosvirin, JM Kim - Sensors, 2020 - mdpi.com
Efficient fault diagnosis of electrical and mechanical anomalies in induction motors (IMs) is
challenging but necessary to ensure safety and economical operation in industries …

[PDF][PDF] Научно-практические основы создания автоматизированных систем технического мониторинга и диагностики оборудования …

АЕ Яблоков, ИГ Благовещенский - Яблоков АЕ, Благовещенский ИГ–М …, 2022 - mgupp.ru
Зерноперерабатывающая отрасль России является системообразующей в задаче
обеспечения населения страны продуктами питания. Элеваторное хозяйство …

Studying the level of sustainable energy development of the European Union countries and their similarity based on the economic and demographic potential

M Tutak, J Brodny, D Siwiec, R Ulewicz, P Bindzár - Energies, 2020 - mdpi.com
The concept of sustainable economic development takes into account economic, social and
environmental aspects and strives to achieve balance between them. One of the basic areas …

Convolutional neural network-based stator current data-driven incipient stator fault diagnosis of inverter-fed induction motor

M Skowron, T Orlowska-Kowalska, M Wolkiewicz… - Energies, 2020 - mdpi.com
In this paper, the idea of using a convolutional neural network (CNN) for the detection and
classification of induction motor stator winding faults is presented. The diagnosis inference …

PMSM stator winding fault detection and classification based on bispectrum analysis and convolutional neural network

P Pietrzak, M Wolkiewicz… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The diagnosis of permanent magnet synchronous motor (PMSM) faults has been the subject
of much research in recent years, due to the growing reliability and safety requirements for …

New hybrid invasive weed optimization and machine learning approach for fault detection

A Ibrahim, F Anayi, M Packianather, OA Alomari - Energies, 2022 - mdpi.com
Fault diagnosis of induction motor anomalies is vital for achieving industry safety. This paper
proposes a new hybrid Machine Learning methodology for induction-motor fault detection …

Machine learning-based stator current data-driven PMSM stator winding fault diagnosis

P Pietrzak, M Wolkiewicz - Sensors, 2022 - mdpi.com
Permanent magnet synchronous motors (PMSMs) have become one of the most important
components of modern drive systems. Therefore, fault diagnosis and condition monitoring of …

Statistical machine learning strategy and data fusion for detecting incipient ITSC faults in IM

AY Jaen-Cuellar, DA Elvira-Ortiz, JJ Saucedo-Dorantes - Machines, 2023 - mdpi.com
The new technological developments have allowed the evolution of the industrial process to
this new concept called Industry 4.0, which integrates power machines, robotics, smart …