Abstract: Methods and systems are provided for an insulation system of a stator. In one example, a method may include receiving images of the stator at an automated tool implemented at a processor of a computing system, the images depicting slots in in an inner surface of the stator, and processing the images using image processing and deep learning algorithms to provide processed images. The processed images may be input to an artificial intelligence (AI) model of the automated tool, the AI model trained to identify varnish in the processed images. obtained two-dimensional presentation of varnish distribution may be output from the AI model.

Abstract: Methods and systems are provided for an insulation system of a stator. In one example, a method may include receiving images of the stator at a processor of a computing system and processing the images by converting the images to one or more of cluster-only images and binary masks. The images may be fed to an artificial intelligence (AI) model to obtain one or more of varnish estimates and void estimates to generate a training dataset which may be used to train a deep learning tool to estimate varnish fill percentages from the images and display the varnish fill percentages at a display device.

Abstract: Methods and systems are provided for an insulation system of a stator. In one example, a method may include receiving images of the stator at a processor of a computing system and feeding the images to a deep learning tool to generate processed images by segmenting and cropping the images according to slots identified in the images. Further, the varnish in the processed images may be quantified based on fluorescence of the varnish, converted into estimated varnish fill percentages, based on an output from analysis of the processed images, and the estimated varnish fill percentages may be displayed in a report.