Abstract: In contemporary industries, diagnosing bearing faults is crucial, yet the complexity and diversity of these faults pose challenges to traditional methods. Existing algorithms typically treat ...
Abstract: Hybrid GNNs, which learn both long-term structural information encoded in static graphs and temporal interactions within dynamic graphs, have attracted attention for their high predictive ...