- 专利标题： ROBUST AUTOMATIC TRACKING OF INDIVIDUAL TRISO-FUELED PEBBLES THROUGH A NOVEL APPLICATION OF X-RAY IMAGING AND MACHINE LEARNING
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申请号： US17799202申请日： 2021-03-10
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公开(公告)号： US20230072324A1公开(公告)日： 2023-03-09
- 发明人: Kyle Hartig , Hongcheng Liu , Emily Kwapis
- 申请人： University of Florida Research Foundation, Inc.
- 申请人地址： US FL Gainesville
- 专利权人： University of Florida Research Foundation, Inc.
- 当前专利权人： University of Florida Research Foundation, Inc.
- 当前专利权人地址： US FL Gainesville
- 国际申请： PCT/US2021/021658 WO 20210310
- 主分类号： G06T7/00
- IPC分类号： G06T7/00 ; G21C17/06 ; G06V20/50 ; G06T7/20 ; G06V10/82 ; G06V10/774
摘要：
The present disclosure presents systems and methods of tagging TRISO-fueled pebbles. One such method comprises acquiring an ionizing radiation image of a TRISO-fueled pebble; analyzing, using a machine learning algorithm, the acquired image of the TRISO-fueled pebble to identify a unique pattern of particle distributions that is visible in the acquired image of the TRISO-fueled pebble; deriving a TRISO-particle distribution fingerprint for the TRISO-fueled pebble that corresponds to the unique pattern of particle distributions; assigning an individual identifier to the TRISO-fueled pebble that corresponds to a TRISO-particle distribution fingerprint; and storing the TRISO-particle distribution fingerprint and the individual identifier for the TRISO-fueled pebble in an image database, wherein the image database stores a plurality of TRISO-particle distribution fingerprints and individual identifiers for a plurality of TRISO-fueled pebbles. Other systems and methods are also presented.