Contribution
Data-Driven Track Condition Analysis via Airborne Sound Monitoring in Tram Track Systems
* Presenting author
Abstract:
The Berliner Verkehrsbetriebe (BVG) operates one of the largest tram networks worldwide. With the shift towards more sustainable, efficient, and environmentally friendly transportation systems, this network will continue to expand, making noise reduction essential to gaining public acceptance. One source of sound emissions originates from the rolling contact between rail and wheel, whereas degraded rail surfaces increase noise and contribute to further degradation.Within this context, this work aims to develop single-value indicators capable of assessing the rail surface condition using measurement runs on the tram track system in Berlin. Two indicators, both using airborne sound, are developed, implemented and tested.First, a symptomatic indicator is constructed, which evaluates the general sound pressure level of a given track, adjusted for the vehicle speed.Second, an indicator is designed to detect and locate rail corrugation via a frequency analysis. Validation of proposed indicators is carried out on track sections by visual inspection.The symptomatic indicator successfully detects track sections with increased sound emissions caused by impulse-type defects, periodic rolling surface defects and infrastructure elements. The corrugation detection indicator proves to be capable of indicating the presence of a characteristic spectrum commonly attributed to corrugation.