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Wavenumber-domain separation of rail contribution to pass-by noise
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Marcus Wallenberg Laboratory MWL.ORCID iD: 0000-0001-5723-9571
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Marcus Wallenberg Laboratory MWL.ORCID iD: 0000-0003-2498-2558
University of Southampton, Institute of Sound and Vibration Research.ORCID iD: 0000-0003-2437-6398
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Marcus Wallenberg Laboratory MWL.ORCID iD: 0000-0002-9632-8398
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2017 (English)In: Journal of Sound and Vibration, ISSN 0022-460X, E-ISSN 1095-8568, Vol. 409, 24-42 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 409, 24-42 p.
Keyword [en]
Railway, Noise separation, Microphone array, Wavenumber–domain
National Category
Fluid Mechanics and Acoustics
Research subject
Vehicle and Maritime Engineering
Identifiers
URN: urn:nbn:se:kth:diva-211293DOI: 10.1016/j.jsv.2017.07.040ISI: 000413117300002OAI: oai:DiVA.org:kth-211293DiVA: diva2:1128832
Projects
Roll2Rail
Funder
EU, Horizon 2020, 636032Swedish Research Council, 20123723; 2015-04258
Note

QC 20170801

Available from: 2017-07-29 Created: 2017-07-29 Last updated: 2017-11-16Bibliographically approved
In thesis
1. Sound field separation with microphone arrays
Open this publication in new window or tab >>Sound field separation with microphone arrays
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Sound field analysis is a fundamental tool in the design, manufacturing, testing and diagnosis of machines and transportation means, as well as the legislations that regulate noise levels in order to minimize environmental pollution. Customary solutions to the problem of sound field analysis are microphone array technologies such as near-field acoustic holography (NAH) and beamforming. One of the challenges of using these technologies often lies in the difficulty for separating disturbing sounds from the target source, specially when these are correlated. For example, NAH requires that no reflecting surfaces are found in the vicinity of the array, which is in theory only possible in an echo-free chamber. On the other hand, beamforming is most suitably used to separate uncorrelated sound sources, which is not the case of, for instance, the noise generated by the contact between the wheel of a train and a railway track. The present thesis examines the research problems of separating a sound source from its reflections, and separating the rail noise from the total noise radiated by a passing train. The overall goal of the thesis is to push the limits of microphone array technologies in the context of sound field separation, to the end of minimizing the cost and complexity of measurements and analyses. The proposed separation methods are formulated in the wavenumber domain, and the measurements are done with uniform single layer microphone arrays. The problem of separating reflections is addressed in three different papers: (i) compact sources and a parallel reflector, (ii) planar source and a parallel reflector, and (iii) a perpendicular reflector with respect to the microphone array, and the common requirement is the knowledge of the reflector impedance. The problem of separating rail noise is studied in a fourth paper, and the proposed method is formulated such that it does not require prior knowledge of the rail properties. Upon the findings obtained in the papers, a comprehensive description of areas for future work, as well as strategies to approach them, is given at the end of the thesis. 

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2017. 45 p.
Series
TRITA-AVE, ISSN 1651-7660 ; 2017:79
Keyword
Sound field separation, Microphone arrays, Near-field acoustic holography, Reflecting surfaces, Railway rolling noise
National Category
Fluid Mechanics and Acoustics Vehicle Engineering Signal Processing
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-217811 (URN)978-91-7729-602-7 (ISBN)
Public defence
2017-12-15, Kollegiesalen, Brinellvägen 8, KTH-huset (tr. 4), Stockholm, 09:15 (English)
Opponent
Supervisors
Funder
Swedish Research Council, 621-2012-3723EU, Horizon 2020, 636032
Note

QC 20171117

Available from: 2017-11-17 Created: 2017-11-16 Last updated: 2017-11-17Bibliographically approved

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