IEEE

Adversarial Multimodal Contrastive Learning for Robust Industrial Fault Diagnosis

Abstract: Fault diagnosis (FD) techniques leveraging self-supervised contrastive learning (SSCL) have demonstrated significant potential in industrial scenarios due to their reduced dependence on ...
IEEE

Graph Convolutional Contrastive Learning for Few-Shot Open-Set Fault Diagnosis in Electro-Hydrostatic Actuators

Abstract: Data-driven intelligent diagnosis methods for aerospace electro-hydraulic actuators (EHA) under few-shot conditions have achieved some progress. However, most approaches rely on a closed-set ...