most citedModel-Agnostic Meta-Learning for Fault Diagnosis of Induction Motors in Data-Scarce Environments with Varying Operating Conditions and Electric Drive Noise

7 citations · 7 across the 1 of their papers we have counts for

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eess.SY2024★ 7 cited

Model-Agnostic Meta-Learning for Fault Diagnosis of Induction Motors in Data-Scarce Environments with Varying Operating Conditions and Electric Drive Noise

Ali Pourghoraba, MohammadSadegh KhajueeZadeh, Ali Amini +3

Reliable mechanical fault detection with limited data is crucial for the effective operation of induction machines, particularly given the real-world challenges present in industri…