Train-Induced Vibration and Structure-Borne Noise Measurement and Prediction of Low-Rise Building
Auteur(s): |
Jialiang Chen
Sen Hou Bokai Zheng Xuming Li Fangling Peng Yingying Wang Junjie Chen |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Buildings, 25 août 2024, n. 9, v. 14 |
Page(s): | 2883 |
DOI: | 10.3390/buildings14092883 |
Abstrait: |
The advancement of urban rail transit is increasingly confronted with environmental challenges related to vibration and noise. To investigate the critical issues surrounding vibration propagation and the generation of structure-borne noise, a two-story frame building was selected for on-site measurements of both vibration and its induced structure-borne noise. The collected data were analyzed in both the time and frequency domains to explore the correlation between these phenomena, leading to the proposal of a hybrid prediction method for structural noise that was subsequently compared with measured results. The findings indicate that the excitation of structure-borne noise produces significant waveforms within sound signals. The characteristic frequency of the structure-borne noise is 25–80 Hz, as well as that of the train-induced vibration. Furthermore, there exists a positive correlation between structural vibration and structure-borne noise, whereby increased levels of vibration correspond to more pronounced structure-borne noise; additionally, indoor distribution patterns of structure-borne noise are non-uniform, with corner wall areas exhibiting greater intensity than central room locations. Finally, a hybrid prediction methodology that is both semi-analytical and semi-empirical is introduced. The approach derives dynamic response predictions of the structure through analytical solutions, subsequently estimating the secondary noise within the building’s interior using a newly formulated empirical equation to facilitate rapid predictions regarding indoor building vibrations and structure-borne noises induced by subway train operations. |
Copyright: | © 2024 by the authors; licensee MDPI, Basel, Switzerland. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10799981 - Publié(e) le:
23.09.2024 - Modifié(e) le:
25.01.2025