The paper presents a measurement setup capable of collecting wheel/rail contact noise and vibration signals from a passenger train. A data analysis method based on machine learning is developed for detecting events from the acquired data and classifying them according to relevant railway track components and noise phenomena. A classification rate higher than 84 % is achieved.
Monitoring Rail Condition Based on Sound and Vibration Sensors Installed on an Operational Train
Notes Numerical Fluid Mech.
Noise and Vibration Mitigation for Rail Transportation Systems ; Kapitel : 27 ; 205-212
2015-01-01
8 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Monitoring Rail Condition Based on Sound and Vibration Sensors Installed on an Operational Train
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