Invention Application
- Patent Title: GRAPH-LEARNING NEURAL NETWORKS USING SPECTRAL DATA FOR DETECTION OF DEFECTS IN ADDITIVE MANUFACTURING
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Application No.: US18324878Application Date: 2023-05-26
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Publication No.: US20240394538A1Publication Date: 2024-11-28
- Inventor: Qin Jiang , Eric Clough , Navid Naderializadeh , Heiko Hoffmann
- Applicant: The Boeing Company
- Applicant Address: US VA Arlington
- Assignee: The Boeing Company
- Current Assignee: The Boeing Company
- Current Assignee Address: US VA Arlington
- Main IPC: G06N3/084
- IPC: G06N3/084 ; G06T7/00

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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