Journal
JOURNAL OF ADVANCED TRANSPORTATION
Volume 2020, Issue -, Pages -Publisher
WILEY-HINDAWI
DOI: 10.1155/2020/8849734
Keywords
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Funding
- Shift2Rail Joint Undertaking under the European Union's Horizon 2020 Research and Innovation Programme [730849]
- project TAR [CK01000091Vyhybka 4.0]
- [FAST-J-19-6062]
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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.
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