Use of Deep Learning Algorithms To Prevent Pantograph-Catenary Malfunctions

Year 2022, Volume: 14 Issue: 2, 394 - 405, 31.07.2022

Şakir Parlakyıldız , Muhsin Gençoğlu , Mehmet Sait Cengız

https://doi.org/10.29137/umagd.957018

Abstract

Today, the demand for rail transport is increasing. Studies in this area are increasing worldwide. While the railway infrastructure is increasing in the world, the suitability of the railroads and train sets built is of great importance in terms of road and passenger safety. The most important test to ensure road and passenger safety is on the electrification line. The energy required for the movement of the electric train is provided by the power line. Continuous contact between the power line and the pantograph is desired while in motion by providing continuous energy for the rail system to operate. Even short-term non-contact between the pantograph and the catenary adversely affects the rail system vehicle and the electronic systems inside. For this reason, the pantograph and catenary interaction should be controlled dynamically and statically in certain periods. In this study, dynamic and static control was provided by using deep learning. The data received from the system are recorded in CSV format. Using deep learning algorithms, failure points have been successfully detected up to 99.4%.

Keywords

Catenary, data acquisition, high speed train, fault detection, pantograph, Catenary, data acquisition, high speed train, fault detection, pantograph

Supporting Institution

TUBITAK

Project Number

EEEAG‑118E322

Thanks

This work has been supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant EEEAG‑118E322. (EEE‑AG: Electrical Electronics Engineering Research Group).

Pantograf-Katener Arızalarını Önlemek İçin Derin Öğrenme Algoritmalarının Kullanımı

Abstract

Günümüzde demiryolu taşımacılığına olan talep artmaktadır. Bu alanda yapılan çalışmalar dünya çapında artmaktadır. Dünyada demiryolu altyapısı artarken, inşa edilen demiryollarının ve tren setlerinin uygunluğu yol ve yolcu güvenliği açısından büyük önem taşımaktadır. Yol ve yolcu güvenliğini sağlamak için en önemli test elektrifikasyon hattındadır. Elektrikli trenin hareketi için gerekli olan enerji, elektrik hattı tarafından sağlanmaktadır. Raylı sistemin çalışması için sürekli enerji sağlanarak hareket halindeyken enerji hattı ile pantograf arasında sürekli temas istenmektedir. Pantograf ile katener arasındaki kısa süreli temassızlık bile raylı sistem aracı ve içindeki elektronik sistemleri olumsuz etkiler. Bu nedenle pantograf ve katener etkileşimi belirli periyotlarda dinamik ve statik olarak kontrol edilmelidir. Bu çalışmada derin öğrenme kullanılarak dinamik ve statik kontrol sağlanmıştır. Sistemden alınan veriler CSV formatında kaydedilmiştir. Derin öğrenme algoritmaları kullanılarak hata noktaları %99,4'e kadar başarıyla tespit edilmiştir.

Keywords

Katener, veri toplama, yüksek hızlı tren, arıza tespiti, pantograf, Katener, veri toplama, yüksek hızlı tren, arıza tespiti, pantograf

Project Number

EEEAG‑118E322

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