Mutual-assistance semisupervised domain generalization network for intelligent fault diagnosis under unseen working conditions

Generalizing deep models to unseen working conditions is an essential topic for intelligent fault diagnosis. Existing domain generalization-based fault diagnosis (DGFD) methods usually require sufficient annotated samples from all observed domains during the training phase, while annotating abundant samples is an expensive and difficult task. Therefore, this study proposes a mutual-assistance network for semisupervised domain generalization …