An advanced diagnostic approach for broken rotor bar detection and classification in DTC controlled induction motors by leveraging dynamic SHAP interaction feature selection (DSHAP-IFS) GBDT methodologyKhan, Muhammad Amir; Asad, Bilal; Vaimann, Toomas; Kallaste, AntsMachines2024 / art. 495 https://doi.org/10.3390/machines12070495 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

The bearing faults detection methods for electrical machines — the state of the artKhan, Muhammad Amir; Asad, Bilal; Kudelina, Karolina; Vaimann, Toomas; Kallaste, AntsEnergies2023 / art. 296 https://doi.org/10.3390/en16010296 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

Improved diagnostic approach for BRB detection and classification in inverter-driven induction motors employing sparse stacked autoencoder (SSAE) and lightGBMKhan, Muhammad Amir; Asad, Bilal; Vaimann, Toomas; Kallaste, AntsElectronics (Switzerland)2024 / art. 1292 https://doi.org/10.3390/electronics13071292 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

Improved fault classification and localization in power transmission networks using vae-generated synthetic data and machine learning algorithmsKhan, Muhammad Amir; Asad, Bilal; Vaimann, Toomas; Kallaste, Ants; Pomarnacki, Raimondas; Hyunh, Van KhangMachines2023 / art. 963 https://doi.org/10.3390/machines11100963 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

MWFA model based synthetic data creation and utilization for the training of XGBoost based fault diagnostic algorithm of a squirrel cage induction motorAsad, Bilal; Khan, Muhammad Amir; Raja, Hadi Ashraf; Vaimann, Toomas; Kallaste, Ants; Naseer, Muhammad Usman2024 International Conference on Electrical Machines (ICEM)2024 / 7 p https://doi.org/10.1109/ICEM60801.2024.10700453