US 12,463,263 B2
X-ray radiographs based fault detection and prediction for battery cells
Diana M. Wegner, Bloomfield Hills, MI (US); Megan E. Mcgovern, Detroit, MI (US); Dmitriy Bruder, Clinton Township, MI (US); Sean Robert Wagner, Shelby Township, MI (US); Tanjina Ahmed, Warren, MI (US); and Evan William Schmitz, Oxford, MI (US)
Assigned to GM GLOBAL TECHNOLOGY OPERATIONS LLC, Detroit, MI (US)
Filed by GM GLOBAL TECHNOLOGY OPERATIONS LLC, Detroit, MI (US)
Filed on Sep. 20, 2022, as Appl. No. 17/948,841.
Prior Publication US 2024/0097215 A1, Mar. 21, 2024
Int. Cl. H01M 10/42 (2006.01); G01N 23/083 (2018.01); G01N 23/18 (2018.01)
CPC H01M 10/4285 (2013.01) [G01N 23/083 (2013.01); G01N 23/18 (2013.01); G01N 2223/1016 (2013.01); G01N 2223/646 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for detecting defects in battery cells, the method comprising:
receiving an X-Ray radiographic image of a battery cell;
segmenting the X-Ray radiographic image into regions of interest using a classifier;
processing the segmented X-Ray radiographic image using the classifier to identify features of the battery cell;
detecting whether one or more of the features in the processed X-Ray radiographic image is defective by using the classifier; and
determining, using the classifier, whether the battery cell is defective based on whether one or more of the features in the processed X-Ray radiographic image is defective.