Wavenumber–domain separation of rail contribution to pass-by noise

Autor: Ines Lopez Arteaga, Luca Manzari, David Thompson, Leping Feng, Elias Zea, Giacomo Squicciarini
Přispěvatelé: Dynamics and Control
Rok vydání: 2017
Předmět:
Zdroj: Journal of Sound and Vibration, 409, 24-42. Academic Press Inc.
ISSN: 0022-460X
DOI: 10.1016/j.jsv.2017.07.040
Popis: In order to counteract the problem of railway noise and its environmental impact, passing trains in Europe must be tested in accordance to a noise legislation that demands the quantification of the noise generated by the vehicle alone. However, for frequencies between about 500 Hz and 1600 Hz, it has been found that a significant part of the measured noise is generated by the rail, which behaves like a distributed source and radiates plane waves as a result of the contact with the train's wheels. Thus the need arises for separating the rail contribution to the pass-by noise in that particular frequency range. To this end, the present paper introduces a wavenumber–domain filtering technique, referred to as wave signature extraction, which requires a line microphone array parallel to the rail, and two accelerometers on the rail in the vertical and lateral direction. The novel contributions of this research are: (i) the introduction and application of wavenumber (or plane–wave) filters to pass-by data measured with a microphone array located in the near-field of the rail, and (ii) the design of such filters without prior information of the structural properties of the rail. The latter is achieved by recording the array pressure, as well as the rail vibrations with the accelerometers, before and after the train pass-by. The performance of the proposed method is investigated with a set of pass-by measurements performed in Germany. The results seem to be promising when compared to reference data from TWINS, and the largest discrepancies occur above 1600 Hz and are attributed to plane waves radiated by the rail that so far have not been accounted for in the design of the filters. QC 20170801 Roll2Rail
Databáze: OpenAIRE