Acoustic Roughness Measurement of Railway Tracks: Laboratory Investigation of External Disturbances on the Chord-Method with an Optical Measurement Approach
Source abstract
Abstract
For acoustic roughness monitoring of the railway network at train travelling speed, new direct measurement methods are required. Common direct measurement methods need the blocking of track sections, as they are based on manually operated devices. Indirect measurement methods such as accelerometer or microphone measurements can be installed on the train, but require a conversion of the obtained measurement data to rail roughness. Optical measurement methods allow a direct measurement from the moving train, even at higher speeds, due to the contact-free nature of the measurement. This paper investigates the influence of various disturbances on the measurement result, which are expected on the train. The frequently used chord method deploying laser triangulation sensors is used. Four sensors are integrated into the setup, thus providing the possibility to combine the results from four chord methods. The measurements of the optical system are compared with a tactile measurement of METAS (Swiss Federal Institute of Metrology) on a test bench equipped with a reference rail segment. It is shown that dust and water on the rail have a significant influence in the range of small wavelengths. Displacements and tilting of the sensor array, as well as vibrations, can be compensated to a certain level by the chord method, while a single sensor is significantly disturbed. The combination of four different chord lengths and selection of the theoretically optimal method for each one-third octave band shows an improvement of the measurement result. Based on the observations made, recommendations for practical tests on the train are concluded.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Railway Engineering and Dynamics · Structural Health Monitoring Techniques · Surface Roughness and Optical Measurements
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute for Machine Tools and Manufacturing, ETH Zürich, 8092 Zurich, Switzerland
Inspire AG, 8005 Zurich, Switzerland
Funding
Federal Office for the Environment (FOEN) · Federal Office of Transport (FOT) · ETH Zurich
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