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Experimental motor fault detection and identification of a quadrotor UAV using a hybrid deep learning approach

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Τίτλος: Experimental motor fault detection and identification of a quadrotor UAV using a hybrid deep learning approach
Συγγραφείς: Khaneghaei, Mohammad, Asadi, DavoodAff2, Aff4, IDs40435025017864_cor1, Mowla, Md. Najmul, Dişken, Gökay
Πηγή: International Journal of Dynamics and Control. 13(8)
Βάση Δεδομένων: Springer Nature Journals
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  – Url: https://dx.doi.org/doi:10.1007/s40435-025-01786-4
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  Data: Experimental motor fault detection and identification of a quadrotor UAV using a hybrid deep learning approach
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  Data: <searchLink fieldCode="AR" term="%22Khaneghaei%2C+Mohammad%22">Khaneghaei, Mohammad</searchLink><br /><searchLink fieldCode="AR" term="%22Asadi%2C+Davood%22">Asadi, Davood</searchLink><relatesTo>Aff2, Aff4, IDs40435025017864_cor1</relatesTo><br /><searchLink fieldCode="AR" term="%22Mowla%2C+Md%2E+Najmul%22">Mowla, Md. Najmul</searchLink><br /><searchLink fieldCode="AR" term="%22Dişken%2C+Gökay%22">Dişken, Gökay</searchLink>
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  Data: <i>International Journal of Dynamics and Control</i>. 13(8)
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      – Type: doi
        Value: 10.1007/s40435-025-01786-4
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      – Text: English
    Titles:
      – TitleFull: Experimental motor fault detection and identification of a quadrotor UAV using a hybrid deep learning approach
        Type: main
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            NameFull: Khaneghaei, Mohammad
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            NameFull: Asadi, Davood
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            NameFull: Mowla, Md. Najmul
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            NameFull: Dişken, Gökay
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          Dates:
            – D: 01
              M: 08
              Type: published
              Y: 2025
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              Value: 13
            – Type: issue
              Value: 8
          Titles:
            – TitleFull: International Journal of Dynamics and Control
              Type: main
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