Advances in machine fault diagnosisVaimann, ToomasAdvances in machine fault diagnosis2022 / p. 1-5 https://doi.org/10.3390/app11167348 The cluster computation-based hybrid FEM–analytical model of induction motor for fault diagnosticsAsad, Bilal; Vaimann, Toomas; Belahcen, Anouar; Kallaste, Ants; Rassõlkin, Anton; Iqbal, Muhammad NaveedAdvances in machine fault diagnosis2022 / p. 27-41 https://doi.org/10.3390/app10217572 Transient modeling and recovery of non-stationary fault signature for condition monitoring of induction motorsAsad, Bilal; Vaimann, Toomas; Belahcen, Anouar; Kallaste, Ants; Rassõlkin, Anton; Ghahfarokhi, Payam ShamsAdvances in machine fault diagnosis2022 / p. 43-59 https://doi.org/10.3390/app11062806 Trends and challenges in intelligent condition monitoring of electrical machines using machine learningKudelina, Karolina; Vaimann, Toomas; Asad, Bilal; Rassõlkin, Anton; Kallaste, Ants; Demidova, GalinaAdvances in machine fault diagnosis2022 / p. 7-25 https://doi.org/10.3390/app11062761