公开(公告)号：US12217402B2

公开(公告)日：2025-02-04

申请号：US17535766

申请日：2021-11-26

Applicant: BWXT Advanced Technologies LLC

Inventor： Simon Mason ,  Ryan Scott Kitchen ,  Travis McFalls

IPC: G06T5/73 ,  G06T5/50 ,  G06T7/00

Abstract: A method is provided for enhancing image resolution for sequences of 2-D images of additively manufactured products. For each of a plurality of additive manufacturing processes, the process obtains a respective plurality of sequenced low-resolution 2-D images of a respective product during the respective additive manufacturing process and obtains a respective high-resolution 3-D image of the respective product after completion of the respective additive manufacturing process. The process selects tiling maps that subdivide the low-resolution 2-D images and the high-resolution 3-D images into low-resolution tiles and high-resolution tiles, respectively. The process also builds an image enhancement generator iteratively in a generative adversarial network using training inputs that includes ordered pairs of low-resolution and high-resolution tiles. The process stores the image enhancement generator for subsequent use to enhance sequences of low-resolution 2-D images captured for products during additive manufacturing.

公开(公告)号：US12023857B2

公开(公告)日：2024-07-02

申请号：US18228077

申请日：2023-07-31

Applicant: BWXT Advanced Technologies LLC

Inventor： Ryan Scott Kitchen ,  Benjamin D. Fisher

IPC: B29C67/00 ,  B22F10/85 ,  B22F12/90 ,  B29C64/129 ,  B29C64/268 ,  B29C64/393 ,  B33Y10/00 ,  B33Y50/02 ,  G06T7/00 ,  G06T7/62 ,  B22F10/28

CPC classification number: B29C64/129 ,  B22F10/85 ,  B22F12/90 ,  B29C64/268 ,  B29C64/393 ,  B33Y10/00 ,  B33Y50/02 ,  G06T7/0008 ,  G06T7/001 ,  G06T7/62 ,  B22F10/28 ,  G06T2207/30164

Abstract: Methods to in-situ monitor production of additive manufacturing products collects images from the deposition process on a layer-by-layer basis, including a void image of the pattern left in a slurry layer after deposition of a layer and a displacement image formed by immersing the just-deposited layer in a renewed slurry layer. Image properties of the void image and displacement image are corrected and then compared to a binary expected image from a computer generated model to identify defects in the just-deposited layer on a layer-by-layer basis. Additional methods use the output from the comparison to form a 3D model corresponding to at least a portion of the additive manufacturing product. Components to control the additive manufacturing operation based on digital model data and to in-situ monitor successive layers for manufacturing defects can be embodied in a computer system or computer-aided machine, such as a computer controlled additive manufacturing machine.

公开(公告)号：US11760005B2

公开(公告)日：2023-09-19

申请号：US16951543

申请日：2020-11-18

Applicant: BWXT Advanced Technologies LLC

Inventor： Ryan Scott Kitchen ,  Benjamin D. Fisher

IPC: B29C67/00 ,  B29C64/129 ,  B29C64/268 ,  B29C64/393 ,  B33Y10/00 ,  G06T7/00 ,  G06T7/62 ,  B33Y50/02 ,  B22F12/90 ,  B22F10/85 ,  B22F10/28

CPC classification number: B29C64/129 ,  B22F10/85 ,  B22F12/90 ,  B29C64/268 ,  B29C64/393 ,  B33Y10/00 ,  B33Y50/02 ,  G06T7/001 ,  G06T7/0008 ,  G06T7/62 ,  B22F10/28 ,  G06T2207/30164

Abstract: Methods to in-situ monitor production of additive manufacturing products collects images from the deposition process on a layer-by-layer basis, including a void image of the pattern left in a slurry layer after deposition of a layer and a displacement image formed by immersing the just-deposited layer in a renewed slurry layer. Image properties of the void image and displacement image are corrected and then compared to a binary expected image from a computer generated model to identify defects in the just-deposited layer on a layer-by-layer basis. Additional methods use the output from the comparison to form a 3D model corresponding to at least a portion of the additive manufacturing product. Components to control the additive manufacturing operation based on digital model data and to in-situ monitor successive layers for manufacturing defects can be embodied in a computer system or computer-aided machine, such as a computer controlled additive manufacturing machine.