Quan-Jun Li

Bearing Fault Diagnosis Under Data Imbalance and Heavy Noise: An Adaptive Weighted Heterogeneous Ensemble Learning Framework

This study proposes a robust bearing fault diagnosis method based on an adaptive weighted heterogeneous ensemble learning framework, capable of effectively reducing and eliminating noise interference in two-dimensional image data, thus enhancing fault diagnosis accuracy.