US 12,293,507 B2
Methods and systems for varnish analysis of stator images
Robert Schroeter, Livonia, MI (US); Seth Avery, Livonia, MI (US); Chris Wolf, Ann Arbor, MI (US); Jackson Lenz, Dearborn, MI (US); and Boratha Tan, Dearborn, MI (US)
Assigned to Ford Global Technologies, LLC, Dearborn, MI (US)
Filed by Ford Global Technologies, LLC, Dearborn, MI (US)
Filed on Oct. 3, 2022, as Appl. No. 17/937,658.
Prior Publication US 2024/0112319 A1, Apr. 4, 2024
Int. Cl. G06T 7/00 (2017.01)
CPC G06T 7/0004 (2013.01) [G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30164 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for automatically analyzing images of a stator, comprising:
receiving images of the stator at a processor of a computing system, the images depicting cross-sections of the stator;
processing the images using deep learning algorithms by cropping and filtering a region of the images corresponding to slots of the stator and converting the images to one or more of cluster-only images and binary masks;
feeding the one or more of the cluster-only images and binary masks to an artificial intelligence (AI) model implemented at the processor;
obtaining one or more of varnish estimates and void estimates from the AI model to generate a training dataset; and
training a deep learning tool, based on the training dataset, to estimate varnish fill percentages from the images and display the varnish fill percentages at a display device.