Abstract
To save labor and improve reliability of railway vehicle maintenance, we have been studying application of Artificial Intelligence (AI) technology to visual inspections of rolling stock equipment. This paper describes how we acquired appearance images for visual inspections, created training data and trained AI models. We built a practical AI development environment to find out what affects the judgment accuracy of AI models and how to improve accuracy through consistent creation and evaluation of AI models. Specifically, we worked on visual inspections of brake shoes for conventional trains and rubber tires for Maglev vehicle given importance of those parts. Our research established a procedure to develop highly precise AI models to distinguish conditions of railway vehicle underfloor equipment.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: The Proceedings of the Transportation and Logistics Conference
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
