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Train detection methods as the foundation of positioning systems of railroad traffic control

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Języki publikacji
EN
Abstrakty
EN
Detection of the current location of rail vehicles in the railway infrastructure network determines the safety, efficiency and reliability of rail transport. In addition, it indirectly affects the safety at rail-road crossings, i.e. also the BRD (Road Safety). In terms of efficiency and reliability of transport systems, the ability to detect a moving vehicle can improve the effective capacity of railway lines. As in the case of technical diagnostics, effective recognition of the current state of the transport network determines the efficiency of the transport system. The development of railways, with particular emphasis on high-speed railways, makes it necessary to modernize and improve railway traffic control devices and systems. A special area of development, ensuring the safe and effective use of rail transport, is the detection and location of rail vehicles moving on the railway infrastructure. The ability to determine the precise location of a rail vehicle is a key element in the reliable operation of rail transport. Therefore, in the field of devices and systems for the detection and location of rail vehicles, many studies and analyzes are carried out to develop existing or create new solutions dedicated to positioning rail vehicles.
Czasopismo
Rocznik
Strony
art. no. 2023305
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
  • Silesian University of Technology, Doctoral School, Akademicka 2a, 44-100 Gliwice, Poland
  • Silesian University of Technology, Doctoral School, Akademicka 2a, 44-100 Gliwice, Poland
  • Silesian University of Technology, Doctoral School, Akademicka 2a, 44-100 Gliwice, Poland
  • Silesian University of Technology, Doctoral School, Akademicka 2a, 44-100 Gliwice, Poland
  • Silesian University of Technology, Faculty of Transport and Aviation Engineering, Krasińskiego 8, 40-019 Katowice
Bibliografia
  • 1. Natke HG, Cempel C. Model-aided diagnosis of mechanical systems: Fundamentals, detection, localization, assessment. Springer Science & Business Media; 2012. https://doi.org/10.1007/978-3-642- 60413-3.
  • 2. Dąbrowski Z, Zawisza M. Diagnostics of mechanical defects not recognized by the OBD system in selfignition engines. Silniki Spalinowe; 2011;50(3).
  • 3. Li X, Su K, He Q, Wang X, Xie Z. Research on fault diagnosis of highway Bi-LSTM based on attention mechanism. Eksploatacja i Niezawodność - Maintenance and Reliability. 2023;25(2). https://doi.org/10.17531/ein/162937.
  • 4. Yudhistira Y, Yoppy Y, Trivida E, Wahyu Wijanarko TA, Nugroho HW, Mandaris D. Electromagnetic interference measurement for axle counters light rapid transit railway in Indonesia. Int J Electr Comput Eng (IJECE); 2022;12(5):4632-4639. https://doi.org/10.11591/ijece.v12i5.pp4632-4639.
  • 5. Chetty K, Che, Q, Woodbridge K. Train monitoring using GSM-R based passive radar. IEEE Radar Conference; Philadelphia, PA; USA; 2016:1-4. https://doi.org/10.1109/RADAR.2016.7485069.
  • 6. Kulpa K, Malanowski M, Misiurewicz J, Samczynski, P. Passive radar for strategic object protection. IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS 2011); Tel Aviv; Israel; 2011:1-4. https://doi.org/10.1109/COMCAS.2011.6105922.
  • 7. Marais J, Beugin J, Berbineau M. A survey of GNSSbased research and developments for the European railway signaling. IEEE Transactions on Intelligent Transportation Systems, 2017;18(1):2602-2618. https://doi.org/10.1109/TITS.2017.2658179.
  • 8. Jonáš, M. GNSS integrity for railway transportation. Transactions On Transport Sciences, 2011;4(4):183-192.
  • 9. Himrane O, Beugin J, Ghazel M. Toward formal safety and performance evaluation of GNSS-based railway localisation function. IFAC Pap; 2021; 54(2); 159-66. https://doi.org/10.1016/j.ifacol.2021.06.049.
  • 10. Zhang S, Lee WK, Pong PT. Train detection by magnetic field sensing. Sensors and Materials; 2013; 25(6):423-436.
  • 11. Angrisani L, Grillo D, Schiano L, Moriello R. Automatic detection of train arrival through an accelerometer. Instrumentation & Measurement Technology Conference Proceedings; Austin, 2010: 898-902, https://doi.org/10.1109/IMTC.2010.5488089.
  • 12. Zanin M, Messelodi S, Modena C. An efficient vehicle queue detection system based on image processing. 12th International Conference on Image Analysis and Processing; Proceedings. Mantova, Italy; 2003;232-237.
  • 13. Fioretti F, Ruffaldi E, Avizzano C. A single camera inspection system to detect and localize obstacles on railways based on manifold Kalman filtering. IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA); Turin; Italy; 2018:768-775. https://doi.org/10.1109/ETFA.2018.8502651.
  • 14. Ishida S, Fukuda A, Tagashira S. Initial evaluation of acoustic train detection system. In: Proc. ITS Asia- Pacific Forum Fukuoka; 2018:1-12.
  • 15. https://utk.gov.pl/pl/interoperacyjnosc/ertms/etcs/174 22,ETCS.html; 13.04.2023 17:38.
  • 16. Barger P, Schön W, Bouali M. A study of railway ERTMS safety with colored perti nets. The European Safety and Reliability Conference (ESREL'09). 2009:1303-1309.
  • 17. Landex A, Jensen LW, Jokiranta A, Mustro M. ERTMS/ETCS level 2 capacity benefits on the city lines of the Helsinki Region. Finnish Transport Infrastructure Agency; FTIA publications 2019;43.
  • 18. Landex A, Jensen LW. Infrastructure capacity in the ERTMS signaling system. In RailNorrköping 2019; 8th International Conference on Railway Operations Modelling and Analysis (ICROMA), Norrköping. 2019;069:607-622.
  • 19. Kochan A, Folęga P, Skirkus R, Bureika G. Multigraph is: part 1. A formal description of railway infrastructure for the digital twin of the ETCS application. Transport Problems, 2023;18(2):43-52. https://doi.org/10.20858/tp.2023.18.2.04.
  • 20. Mindur L, Mindur M. The development of high-speed rail in the Federal Republic of Germany between 2002-2020. Scientific Journal of Silesian University of Technology. Series Transport, 2022;117;151-174. https://doi.org/10.20858/sjsutst.2022.117.11.
  • 21. Celiński I, Burdzik R, Młyńczak J, Kłaczyński M. research on the applicability of vibration signals for real-time train and track condition monitoring. Sensors, 2022;22(6);2368. http://dx.doi.org/10.3390/s22062368.
  • 22. Burdzik R, Konieczny Ł, Nowak B, Rozmus J. Research on vibration employed for the train traffic control. Vibroengineering Procedia, 2017;14; 227-232. https://doi.org/10.21595/vp.2017.19237.
  • 23. Michalski R. (edit.). Diagnostyka maszyn roboczych. ITE Radom, 2004.
  • 24. Niziński S, Wierzbicki S. Zintegrowany system informatyczny sterowania pojazdów. Diagnostyka. 2004;30:47-52.
  • 25. Merkisz J, Pielecha I, Łegowik A. The assessment of autoignition of modified jet fuels. Energies 2021:14: 633. https://doi.org/10.3390/en14030633.
  • 26. Gągorowski A. Analysis of the combustion engine exhaust system structure in aspect of shaping acoustic energy. Combustion Engines. 2023;193(2):112-116. https://doi.org/10.19206/CE-162935.
  • 27. Szaciłło L, Jacyna M, Szczepański E, Izdebski M. Risk assessment for rail freight transport operations. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2021;23(3):476–488. http://doi.org/10.17531/ein.2021.3.8.
  • 28. Merkisz J, Pielecha J, Lijewski P, MerkiszGuranowska A, Nowak M. Exhaust emissions from vehicles in real traffic conditions in the Poznan agglomeration. WIT Transactions on Ecology and the Environment 2013;174:27-38.
  • 29. Regulski P. The material and economic assessment of the life cycle of city buses in the operational phase. Combustion Engines. 2023;192(1):50-54. https://doi.org/10.19206/CE-151942.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e8b07760-31a7-4b2b-a05f-824f5833826e
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