Custom Simplified Machine Learning Algorithms for Fault Diagnosis in Electrical Machines

Author:

Raja Hadi Ashraf1,Asad Bilal1,Vaimann Toomas1,Kallaste Ants1,Rassolkin Anton1,Belahcen Anouar2

Affiliation:

1. Tallinn University of Technology,Department of Electrical Power Engineering and Mechatronics,Tallinn,Estonia

2. Aalto University,Department of Electrical Engineering and Automation,Espoo,Finland

Publisher

IEEE

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fault Detection in Electric Drives Based on LSTM Autoencoder Model Machine Learning Approach;2024 IEEE 25th International Conference of Young Professionals in Electron Devices and Materials (EDM);2024-06-28

2. Use of Modern Routing Methods in Data Transmission Networks;2024 IEEE 25th International Conference of Young Professionals in Electron Devices and Materials (EDM);2024-06-28

3. Improved Fault Classification and Localization in Power Transmission Networks Using VAE-Generated Synthetic Data and Machine Learning Algorithms;Machines;2023-10-16

4. Fault Diagnosis for Automotive Electric Machines Based on a Combined Machine Learning and Parameter Estimation Method: An Approch for Predective Maintenance;2023 International Conference on Control, Automation and Diagnosis (ICCAD);2023-05-10

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