Abstract
Nowadays, monitoring the condition of railway infrastructure has become necessary and led railway companies to take advantage of artificial intelligence (AI) technologies to improve safety and reduce operating costs. This paper aims to present an unsupervised methodology to detect railway wheel flats. The automatic damage detection algorithm is based on the acceleration evaluated on the rails for the passage of traffic loads. The results of this research study show that only one sensor is enough to detect wheel flat automatically, which enables the development of a low-cost monitoring system that can be easily implemented in actual operating conditions.
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 callDisclaimer: 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.
