Demiryolu Hatları için Akıllı Teşhis ve Bakım Sistemleri

Year 2021, Volume: 4 Issue: 2, 134 - 147, 29.11.2021

Erdem Balcı , Ertan Yalçın , Tunay Uzbay Yelce , Niyazi Bezgin

https://doi.org/10.51513/jitsa.951322

Abstract

Son yıllarda yapay zeka (AI), nesnelerin interneti (IoT) ve büyük veri gibi ileri teknolojiler ön plana çıkmaktadır. Bu teknolojiler çeşitli sektörlerde geniş bir kullanım alanına sahiptir. İnsan ve yük taşımacılığının önemli bir parçası olan demiryolu sistemleri, bu yeni teknolojilerin entegrasyonu ile iyileştirilmelidir. Hat arızalarının başarılı bir şekilde tespiti ve bu tespitlere göre yapılan hat bakımları, demiryolu işletmesinin emniyeti için gereklidir. Şu anda, görüntü işleme ve makine öğrenimi yardımıyla örüntü tanıma uygulamaları, otomatik hat denetimleri için yaygın olarak kullanılmaktadır. Ancak demiryolu hatlarının günümüz teknolojisiyle mükemmel bir şekilde entegre olduğunu söylemek mümkün değildir. Bu çalışmada, geleneksel ve akıllı teşhis ve bakım yöntemleri arasındaki farklara yer verilmiştir. İleri teknolojilerin demiryolu hatlarına uygulanmasındaki eksiklikler tespit edilmiş ve daha iyi bir gelişim için gerekli eylemler tartışılmıştır. Son olarak, akıllı sistemlerin kullanımının, yapıların yaşam döngüsü üzerindeki etkileri değerlendirilmiştir.

Keywords

Demiryolu hattı, hat denetimi, hat bakımı, yapay zeka, makine öğrenimi

Smart Diagnosis And Maintenance Systems For Railway Tracks

Abstract

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.

Keywords

Railway track, track inspection, track maintenance, artificial intelligence, machine learning

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