Rolling Bearing Datasets for Transfer Learning Fault Diagnosis

More detail can be found on the paper "A Deep Transfer Model With Wasserstein Distance Guided Multi-Adversarial Networks for Bearing Fault Diagnosis Under Different Working Conditions" and the code is on the GitHub and link below.

更多详细信息可参阅论文《面向不同工作工况的轴承故障诊断：基于瓦瑟斯坦距离（Wasserstein Distance）引导多对抗网络（Multi-Adversarial Networks）的深度迁移模型》，相关代码已上传至GitHub，链接如下。