Publication detail

Train Type Identification at S&C

KRATOCHVÍLOVÁ, M. PODROUŽEK, J. APELTAUER, J. VUKUŠIČ, I. PLÁŠEK, O.

Original Title

Train Type Identification at S&C

Type

journal article in Web of Science

Language

English

Original Abstract

The presented paper concerns the development of condition monitoring system for railroad switches and crossings that utilizes vibration data. Successful utilization of such system requires a robust and efficient train type identification. Given the complex and unique dynamical response of any vehicle track interaction, the machine learning was chosen as a suitable tool. For design and validation of the system, real on-site acceleration data were used. The resulting theoretical and practical challenges are discussed.

Keywords

SVM, Train type Identification; Railway Switches and Crossings; Accelerometer Data

Authors

KRATOCHVÍLOVÁ, M.; PODROUŽEK, J.; APELTAUER, J.; VUKUŠIČ, I.; PLÁŠEK, O.

Released

24. 11. 2020

Publisher

Hindawi

ISBN

0197-6729

Periodical

JOURNAL OF ADVANCED TRANSPORTATION

Year of study

2020

Number

1

State

United Kingdom of Great Britain and Northern Ireland

Pages from

1

Pages to

12

Pages count

12

URL

https://www.hindawi.com/journals/jat/2020/8849734/

Full text in the Digital Library

http://hdl.handle.net/11012/196331

BibTex

@article{BUT168010,
  author="Martina {Floriánová} and Jan {Podroužek} and Jiří {Apeltauer} and Ivan {Vukušič} and Otto {Plášek}",
  title="Train Type Identification at S&C",
  journal="JOURNAL OF ADVANCED TRANSPORTATION",
  year="2020",
  volume="2020",
  number="1",
  pages="1--12",
  doi="10.1155/2020/8849734",
  issn="0197-6729",
  url="https://www.hindawi.com/journals/jat/2020/8849734/"
}