Rui Yang

Multimodal Adversarial Transfer Learning for Bearing Fault Diagnosis of Unmanned Mining Trucks in Realistic Noisy Environments

This study provides an effective technical pathway for real-time and highly reliable “edge-terminal” fault diagnosis of unmanned mining trucks operating in realistic noisy environments with strong noise and limited samples, significantly outperforming conventional approaches.