A Gramian Angular Field for Constructing Graph-Based GNNs and Its Applications in Rolling Bearing Defect Detection
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DOI: 10.1109/jsen.2024.3458409
Abstract: Graph neural networks (GNNs) have unique advantages in terms of processing non-Euclidean spatial data with significant differences and effectively diagnosing faults. However, GNNs typically rely on high-quality graph structures. The current graph construction methods often… read more here.
Keywords: graph based; angular field; gramian angular; field constructing ... See more keywords