171 / 2024-09-01 11:11:25

A novel federated transfer learning strategy for bearing cross-machine fault diagnosis

Domain adaptation Federated transfer learning Data privacy Fault diagnosis Rotating machines

Special Sessions > SS01 AI for Failure Analysis and Reliability of Integrated Circuit(IC)

In recent years, although traditional intelligent fault diagnosis methods have achieved satisfactory development in transfer learning tasks, the sample information that the single client can generally provide is extremely limited in real industrial scenarios. And the private data needs to be guaranteed not to leave the local storage during the application process, which leads to obstacles for fault diagnosis methods to solve cross-device and cross-scenario client transfer tasks. Therefore, a novel federated transfer learning strategy based on dual-correction training (FTSDC) is proposed, which enables fault diagnosis for multi-device tasks without target domain samples to participate in model training.