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My bibliography Save this articleFault Detection of Induction Motors with Combined Modeling- and Machine-Learning-Based Framework
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- Alasmer Ibrahim & Fatih Anayi & Michael Packianather & Osama Ahmad Alomari, 2022. "New Hybrid Invasive Weed Optimization and Machine Learning Approach for Fault Detection," Energies, MDPI, vol. 15(4), pages 1-24, February.
- Ana L. Martinez-Herrera & Edna R. Ferrucho-Alvarez & Luis M. Ledesma-Carrillo & Ruth I. Mata-Chavez & Misael Lopez-Ramirez & Eduardo Cabal-Yepez, 2022. "Multiple Fault Detection in Induction Motors through Homogeneity and Kurtosis Computation," Energies, MDPI, vol. 15(4), pages 1-11, February.
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- Reza Bazghandi & Mohammad Hoseintabar Marzebali & Vahid Abolghasemi & Shahin Hedayati Kia, 2023. "A Novel Mode Un-Mixing Approach in Variational Mode Decomposition for Fault Detection in Wound Rotor Induction Machines," Energies, MDPI, vol. 16(14), pages 1-17, July.
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Keywords
induction motors; fault detection; machine learning; supervised learning; multiple coupled circuit model; parameter identification;All these keywords.
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