Train Type Identification at S&C
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Date
2020-11-24
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Referee
Mark
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Hindawi
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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.
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Citation
JOURNAL OF ADVANCED TRANSPORTATION. 2020, vol. 2020, issue 1, p. 1-12.
https://www.hindawi.com/journals/jat/2020/8849734/
https://www.hindawi.com/journals/jat/2020/8849734/
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Peer-reviewed
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en