SATT: Partial Transfer Machinery Fault Diagnosis Based on Subdomain Adaptation and Two-Stage Training
In recent years, unsupervised transfer learning based on deep domain adaptation techniques has successfully solved the domain shift problem in machinery fault diagnosis, with a basic assumption that target and source domains share the same label space. However, the label space of the target domain is usually a subset o...