US 12,333,735 B2
Methods and systems for predicting stator insulation condition from stator sections
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. 17/937,649.
Prior Publication US 2024/0112351 A1, Apr. 4, 2024
Int. Cl. G06T 7/174 (2017.01); G06V 10/26 (2022.01)
CPC G06T 7/174 (2017.01) [G06V 10/26 (2022.01); G06T 2207/10064 (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 varnish deposited in slots of the stator;
feeding the images to a deep learning tool implemented at the processor to generate processed images by segmenting and cropping the images according to slots identified in the images;
extracting and quantifying the varnish in the processed images, via the deep learning tool, based on fluorescence of the varnish, the deep learning tool trained to identify and analyze the fluorescence using results from machine learning-based color distribution analysis;
converting quantification of the varnish into estimated varnish fill percentages, via the deep learning tool, based on an output from analysis of the processed images; and
displaying the estimated varnish fill percentages in a report at a display device.