The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 04, 2022

Filed:

Nov. 17, 2020
Applicant:

UT Battelle, Llc, Oak Ridge, TN (US);

Inventors:

Luke R. Scime, Knoxville, TN (US);

Vincent C. Paquit, Knoxville, TN (US);

Desarae J. Goldsby, Knoxville, TN (US);

William H. Halsey, Knoxville, TN (US);

Chase B. Joslin, Knoxville, TN (US);

Michael D. Richardson, Knoxville, TN (US);

Derek C. Rose, Knoxville, TN (US);

Derek H. Siddel, Knoxville, TN (US);

Assignee:

UT-Battelle, LLC, Oak Ridge, TN (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
B29C 67/00 (2017.01); B22F 10/80 (2021.01); B29C 64/153 (2017.01); B29C 64/386 (2017.01); G06T 3/40 (2006.01); G06T 7/00 (2017.01); B33Y 50/02 (2015.01); B33Y 10/00 (2015.01);
U.S. Cl.
CPC ...
B22F 10/80 (2021.01); B29C 64/153 (2017.08); B29C 64/386 (2017.08); G06T 3/4046 (2013.01); G06T 3/4053 (2013.01); G06T 7/0004 (2013.01); B33Y 10/00 (2014.12); B33Y 50/02 (2014.12);
Abstract

Detection and classification of anomalies for powder bed metal additive manufacturing. Anomalies, such as recoater blade impacts, binder deposition issues, spatter generation, and some porosities, are surface-visible at each layer of the building process. A multi-scaled parallel dynamic segmentation convolutional neural network architecture provides additive manufacturing machine and imaging system agnostic pixel-wise semantic segmentation of layer-wise powder bed image data. Learned knowledge is easily transferrable between different additive manufacturing machines. The anomaly detection can be conducted in real-time and provides accurate and generalizable results.


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