Ermittlung des sekundären Luftschalls aus dem Schienenverkehr.
Springer-VDI-Verl.
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Springer-VDI-Verl.
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DE
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Düsseldorf
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0174-1098
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ZLB: 4-Zs 2529
BBR: Z 189
TIB: ZA 4580
BBR: Z 189
TIB: ZA 4580
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Abstract
Bei der Planung des Baus oder der erheblichen Veränderung von Schienenverkehrswegen ist neben einer allgemeinen Prognose des Verkehrslärms (Direkt- oder Primärschall) auch eine Prognose des durch schwingende Raumbegrenzungsflächen verursachten sekundären Luftschalls im Gebäude erforderlich. Aufbauend auf weitergehenden Auswertungen von vorliegendem Datenmaterial aus früheren Untersuchungen wird ein Verfahren vorgestellt, mit dem es möglich ist, den sekundären Luftschall durch Regressionsbeziehungen aus den bekannten oder prognostizierten Schwingschnellen in der Deckenmitte von Wohnräumen zu ermitteln. Mit dem vorgestellten Verfahren ist eine Abschätzung des sekundären Luftschalls sowohl als Einzahlwert (Summenpegel) als auch spektral im Frequenzbereich von 25 bis 80 Hz möglich. difu
In former studies regression analysis was already used to determine functional relationships between overall vibration velocity level measured at the centre of a floor slab due to railway traffic and the groundborne noise level in the room. The article presents further evaluations of these data as well as spectral regression functions for the relationship of groundborne noise level and vibration velocity level. The investigations showed that considering at-grade railway traffic regression equations for determining groundborne noise can be specified without taking into account the type of train. Furthermore it turned out that the higher frequency range often comprises level determining background noise emitted by lively items of furniture. From experience it is known that the spectrum of groundborne noise does not contain considerable components above 100 Hz. This statement could be verified by measurements of groundborne noise generated in buildings by rail systems in tunnels. Therefore limiting the regression analysis considering overall level to a frequency range up to 100 Hz leads to higher correlation coefficients than taking a frequency range up to 315 Hz into account. Using the spectral regression functions, one 3rd octave band spectra of the groundborne noise level can be predicted. With regard to assessing groundborne noise immissions the 3rd octave band levels have to be summed up to get the overall level. In general values resulting from overall level regression are slightly higher than those arising from spectral regression analysis and therefore in favour of affected occupants. difu
In former studies regression analysis was already used to determine functional relationships between overall vibration velocity level measured at the centre of a floor slab due to railway traffic and the groundborne noise level in the room. The article presents further evaluations of these data as well as spectral regression functions for the relationship of groundborne noise level and vibration velocity level. The investigations showed that considering at-grade railway traffic regression equations for determining groundborne noise can be specified without taking into account the type of train. Furthermore it turned out that the higher frequency range often comprises level determining background noise emitted by lively items of furniture. From experience it is known that the spectrum of groundborne noise does not contain considerable components above 100 Hz. This statement could be verified by measurements of groundborne noise generated in buildings by rail systems in tunnels. Therefore limiting the regression analysis considering overall level to a frequency range up to 100 Hz leads to higher correlation coefficients than taking a frequency range up to 315 Hz into account. Using the spectral regression functions, one 3rd octave band spectra of the groundborne noise level can be predicted. With regard to assessing groundborne noise immissions the 3rd octave band levels have to be summed up to get the overall level. In general values resulting from overall level regression are slightly higher than those arising from spectral regression analysis and therefore in favour of affected occupants. difu
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Journal
Zeitschrift für Lärmbekämpfung
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Nr. 1
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S. 12-18