Hong-Kun Li

A cross-domain bearing fault diagnosis method under sample imbalance based on multi-view information cross-integration ensemble learning

This work proposes a multi-view information cross-integration ensemble learning method that employs a multi-view cross-integration strategy to generate mixed signals, thereby extracting complementary feature representations while reducing redundancy in cross-domain bearing fault diagnosis.