GRAPH-LEARNING NEURAL NETWORKS USING SPECTRAL DATA FOR DETECTION OF DEFECTS IN ADDITIVE MANUFACTURING
Abstract:
Examples for detection of defects in an additively manufactured object are provided. In one aspect, a method is provided. The method comprises receiving in-situ spectral data measured from the additively manufactured object during an additive manufacturing process, constructing a graph data structure using the in-situ spectral data, and outputting a predicted defect region using the graph data structure and a trained graph-learning neural network.
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