17937649. METHODS AND SYSTEMS FOR PREDICTING STATOR INSULATION CONDITION FROM STATOR SECTIONS simplified abstract (Ford Global Technologies, LLC)
Contents
- 1 METHODS AND SYSTEMS FOR PREDICTING STATOR INSULATION CONDITION FROM STATOR SECTIONS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHODS AND SYSTEMS FOR PREDICTING STATOR INSULATION CONDITION FROM STATOR SECTIONS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
METHODS AND SYSTEMS FOR PREDICTING STATOR INSULATION CONDITION FROM STATOR SECTIONS
Organization Name
Inventor(s)
Robert Schroeter of Livonia MI (US)
Chris Wolf of Ann Arbor MI (US)
Jackson Lenz of Dearborn MI (US)
Boratha Tan of Dearborn MI (US)
METHODS AND SYSTEMS FOR PREDICTING STATOR INSULATION CONDITION FROM STATOR SECTIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 17937649 titled 'METHODS AND SYSTEMS FOR PREDICTING STATOR INSULATION CONDITION FROM STATOR SECTIONS
Simplified Explanation
The abstract describes a method and system for analyzing the insulation system of a stator using deep learning tools to process images and quantify varnish fill percentages.
- Receiving images of the stator and feeding them to a deep learning tool
- Generating processed images by segmenting and cropping based on identified slots
- Quantifying varnish in processed images based on fluorescence
- Converting varnish quantification into estimated varnish fill percentages
- Displaying estimated varnish fill percentages in a report
Potential Applications
This technology could be applied in industries such as manufacturing, electrical engineering, and quality control for stator insulation systems.
Problems Solved
This innovation helps in accurately analyzing varnish fill percentages in stator insulation systems, which can be a challenging and time-consuming task.
Benefits
The benefits of this technology include improved efficiency, accuracy, and reliability in assessing the insulation system of a stator.
Potential Commercial Applications
A potential commercial application of this technology could be in the production and maintenance of electric motors where stators are used.
Possible Prior Art
One possible prior art could be traditional methods of manually inspecting and quantifying varnish fill percentages in stator insulation systems.
What are the limitations of this technology in real-world applications?
This technology may have limitations in processing images with poor quality or inconsistent lighting conditions, which could affect the accuracy of varnish fill percentage estimation.
How does this technology compare to existing methods for analyzing stator insulation systems?
This technology offers a more automated and efficient approach compared to traditional manual methods, leading to faster and more accurate results in assessing varnish fill percentages.
Original Abstract Submitted
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.
