30 citations · 47 across the 4 of their papers we have counts for
4 papers
Open-Set Fault Diagnosis in Multimode Processes via Fine-Grained Deep Feature Representation
Guangqiang Li, M. Amine Atoui, Xiangshun Li
A reliable fault diagnosis system should not only accurately classify known health states but also effectively identify unknown faults. In multimode processes, samples belonging to…
Fault Diagnosis across Heterogeneous Domains via Self-Adaptive Temporal-Spatial Attention and Sample Generation
Guangqiang Li, M. Amine Atoui, Xiangshun Li
Deep learning methods have shown promising performance in fault diagnosis for multimode process. Most existing studies assume that the collected health state categories from differ…
Attention-Based Multiscale Temporal Fusion Network for Uncertain-Mode Fault Diagnosis in Multimode Processes
Guangqiang Li, M. Amine Atoui, Xiangshun Li
Fault diagnosis in multimode processes plays a critical role in ensuring the safe operation of industrial systems across multiple modes. It faces a great challenge yet to be addres…
Dual adversarial and contrastive network for single-source domain generalization in fault diagnosis
Guangqiang Li, M. Amine Atoui, Xiangshun Li
Domain generalization achieves fault diagnosis on unseen modes. In process industrial systems, fault samples are limited, and it is quite common that the available fault data are f…