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Acoustic amenity analysis for high-rise building along urban expressway: Modeling traffic noise vertical propagation using neural networks

机译:沿城市高速公路的高层建筑的声学舒适性分析:使用神经网络对交通噪声垂直传播进行建模

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摘要

Traditional noise propagation models are built for particular height of building. Residents living in high-rise buildings are severely affected by noise. The main objective of this study is to analyze acoustic amenity and develop noise analysis model for high-rise buildings, especially those along urban expressway. The study was carried out in three stages. Firstly, noise survey on different floors of high-rise buildings along free flow expressway was conducted using noise measuring equipment. Furthermore, C-weighted network was used in conjunction with A-weighted network to determine low frequency noise, which is perhaps less noticed for most survey. Secondly, the noise indicators change rule on vertical plane was explored. Combining change rule with frequency spectrum analysis, the acoustic amenity for high-rise buildings was carried out deeply and strictly. In the last stage, traffic noise prediction model for high-rise building along expressway was constructed with neural network. A point worth emphasizing is that the comparison between developed model, FHWA model and measurement shows that the proposed model fits well with measurement as compared to FHWA model at 5% significance level. The developed method could be used as a tool for acoustic amenity analysis and model building. It would be possible to provide reference for urban expressway and building design. (C) 2017 Elsevier Ltd. All rights reserved.
机译:传统的噪声传播模型是针对建筑物的特定高度而构建的。居住在高层建筑中的居民受到噪音的严重影响。这项研究的主要目的是分析声学舒适性并开发高层建筑(尤其是城市高速公路沿线建筑物)的噪声分析模型。该研究分三个阶段进行。首先,使用噪声测量设备对沿自由流动高速公路的高层建筑的不同楼层进行噪声测量。此外,C加权网络与A加权网络结合使用来确定低频噪声,这在大多数调查中可能不太引起人们的注意。其次,探讨了噪声指标在垂直面上的变化规律。将变化规律与频谱分析相结合,对高层建筑的声学舒适性进行了严格而深入的研究。最后,利用神经网络构建了高速公路沿线高层建筑交通噪声的预测模型。值得强调的一点是,已开发的模型,FHWA模型和测量值之间的比较表明,与FHWA模型相比,在5%的显着性水平上,该模型与测量值非常吻合。所开发的方法可用作声学舒适性分析和模型构建的工具。为城市高速公路和建筑设计提供参考。 (C)2017 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Transportation Research》 |2017年第6期|63-77|共15页
  • 作者单位

    Qingdao Univ, Coll Comp Sci & Technol, Postdoctoral Stn Syst Sci, 308 Ningxia Rd, Qingdao 266071, Peoples R China;

    Qingdao Univ, Coll Comp Sci & Technol, Postdoctoral Stn Syst Sci, 308 Ningxia Rd, Qingdao 266071, Peoples R China;

    Qingdao Univ, Coll Comp Sci & Technol, Postdoctoral Stn Syst Sci, 308 Ningxia Rd, Qingdao 266071, Peoples R China;

    Qingdao Univ, Coll Comp Sci & Technol, Postdoctoral Stn Syst Sci, 308 Ningxia Rd, Qingdao 266071, Peoples R China;

    Qingdao Univ, Coll Comp Sci & Technol, Postdoctoral Stn Syst Sci, 308 Ningxia Rd, Qingdao 266071, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Urban noise; Noise perpendicular propagation; High-rise building; Acoustic amenity; Neural network;

    机译:城市噪声;噪声垂直传播;高层建筑;声学舒适度;神经网络;

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