Defect identification using machine learning in an additive manufacturing system
US11536671B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 30, 2021 |
| Grant date | Dec 27, 2022 |
| Priority date | — |
| Expiry date | Jul 30, 2041 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02P90/02
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
An additive manufacturing system comprises an apparatus arranged to distribute layer of metallic powder across a build plane and a power source arranged to emit a beam of energy at the build plane and fuse the metallic powder into a portion of a part. The system includes a processor configured to steer the beam of energy across the build plane and receive data generated by one or more sensors that detect electromagnetic energy emitted from the build plane when the beam of energy fuses the metallic powder. The received data is converted into one or more parameters that indicate one or more conditions at the build plane while the beam of energy fuses the metallic powder. The one or more parameters are used as input into a machine learning algorithm to detect one or more defects in the fused metallic powder.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.