17937658. METHODS AND SYSTEMS FOR VARNISH ANALYSIS OF STATOR IMAGES simplified abstract (Ford Global Technologies, LLC)
Contents
- 1 METHODS AND SYSTEMS FOR VARNISH ANALYSIS OF STATOR IMAGES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHODS AND SYSTEMS FOR VARNISH ANALYSIS OF STATOR IMAGES - 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 VARNISH ANALYSIS OF STATOR IMAGES
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 VARNISH ANALYSIS OF STATOR IMAGES - A simplified explanation of the abstract
This abstract first appeared for US patent application 17937658 titled 'METHODS AND SYSTEMS FOR VARNISH ANALYSIS OF STATOR IMAGES
Simplified Explanation
The abstract describes a method and system for an insulation system of a stator, involving processing images of the stator to estimate varnish fill percentages using artificial intelligence.
- Images of the stator are received and processed to generate varnish estimates and void estimates.
- The processed images are used to train a deep learning tool to estimate varnish fill percentages.
- The varnish fill percentages are displayed at a display device.
Potential Applications
This technology could be applied in industries such as manufacturing, electrical engineering, and automation for efficient stator insulation analysis and maintenance.
Problems Solved
This technology helps in accurately estimating varnish fill percentages in stators, which is crucial for ensuring optimal performance and longevity of electrical equipment.
Benefits
The benefits of this technology include improved accuracy in varnish fill percentage estimation, enhanced maintenance planning, and increased efficiency in stator insulation analysis.
Potential Commercial Applications
A potential commercial application of this technology could be in the development of advanced stator insulation analysis tools for manufacturers and maintenance service providers.
Possible Prior Art
One possible prior art could be traditional methods of stator insulation analysis, which may involve manual inspection and estimation techniques that are less accurate and efficient compared to the AI-based approach described in this patent application.
Unanswered Questions
How does this technology compare to existing stator insulation analysis methods?
This technology offers a more accurate and efficient way to estimate varnish fill percentages in stators compared to traditional manual inspection methods. It utilizes artificial intelligence and deep learning to process images and generate estimates, leading to improved accuracy and reliability in stator insulation analysis.
What are the potential limitations or challenges of implementing this technology in real-world applications?
One potential limitation could be the initial cost and resources required to set up the AI model and deep learning tool for estimating varnish fill percentages. Additionally, there may be challenges in integrating this technology into existing stator maintenance workflows and systems.
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 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.
