Bin Jou

Non-intrusive electrical and mechanical fault diagnosis of induction motors via Fourier-transform-aided learning

This paper proposes a knowledge-based input configuration to inform deep learning models for both electrical and mechanical fault diagnosis, rather than increasing model complexity, and confirms that, while conventional feature processing techniques perform well for electrical fault diagnosis, only the proposed FFT-informed input effectively captures both electrical and mechanical fault patterns.