Smart Diagnosis And Maintenance Systems For Railway Tracks

Autor: Tunay Uzbay Yelce, Niyazi Özgür Bezgin, Ertan Yalçin, Erdem Balci
Rok vydání: 2021
Předmět:
Zdroj: Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi. 4:134-147
ISSN: 2636-820X
Popis: In recent years, advanced technologies such as artificial intelligence (AI), the internet of things (IoT), and big data came into prominence. These technologies found an extensive area of utilization in various sectors. Railway systems as an important part of the transportation of people and goods should be improved by the integration of novel technologies. Successful detection of track faults and operating maintenance tasks accordingly are essential for the safety of railway operations. Currently, image processing and pattern recognition via machine learning applications are in common use for automated track inspections. However, it is not possible to claim that railway tracks are integrated with current technology perfectly. In this work, differences between the traditional way and the smart way of track inspection and maintenance are presented. Shortcomings of the application of advanced technologies into railway tracks are detected and required actions for further improvements are discussed. Lastly, the effects of the use of smart systems on the life cycle of the structures are evaluated.
Databáze: OpenAIRE