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The LIFE DYNAMAP project: Towards a procedure for dynamic noise mapping in urban areas

机译:LIFE DYNAMAP项目:建立城市动态噪声映射程序

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Noise maps are considered a powerful tool for determining the population exposure to environmental noise. To make the process of updating noise maps easier, more cost effective and more frequent, there is a need for integrated systems that combine real-time measurement and processing to assess the acoustic impact of noise sources. To this end, a dedicated project, named Dynamic Acoustic Mapping (DYNAMAP), has been proposed and co-financed in the framework of the Financial Instrument for the Environment (LIFE) 2013 program with the aim of developing a dynamic noise mapping system capable of detecting and representing in real-time the acoustic impact of road infrastructures. Noise maps are updated by scaling the noise levels of pre-calculated noise maps as functions of the differences observed between measured and calculated original grid data. The total map is updated by energetic summation of single source levels from updated noise maps. Given the large number of roads present in Milan city, obtaining the dynamics acoustics map of this city requires application of a statistical approach where the roads having similar flow conditions and thus similar noise trends are grouped (clustered) together. In order to obtain these groups (clusters), an extensive measurement campaign was executed. The maps obtained using this method can be associated with an error that will depend on the chosen integration time of noise levels. Results show that two statistical clusters differentiated by rush hour traffic flow are sufficient and better for categorization than the road types provided by Italian road regulation. (C) 2016 Elsevier Ltd. All rights reserved.
机译:噪声图被认为是确定人群暴露于环境噪声中的强大工具。为了使更新噪声图的过程更加容易,更具成本效益和更加频繁,需要集成了实时测量和处理功能的集成系统,以评估噪声源的声学影响。为此,已提出了一个名为动态声学映射(DYNAMAP)的专门项目,并在2013年环境金融工具(LIFE)计划的框架内共同出资,目的是开发一种能够消除噪声的动态噪声映射系统。实时检测和表示道路基础设施的声学影响。通过将预先计算的噪声图的噪声级别缩放为已测量和计算的原始网格数据之间观察到的差异的函数,可以更新噪声图。通过对来自更新后的噪声图的单个源级别进行有力求和来更新总图。考虑到米兰市中存在大量道路,要获得该市的动力学声学地图,需要采用统计方法,其中具有相似流动条件并因此相似噪声趋势的道路被分组(聚类)在一起。为了获得这些群体(群体),进行了广泛的测量运动。使用此方法获得的映射可能与误差相关,该误差将取决于所选的噪声水平积分时间。结果表明,与意大利道路法规提供的道路类型相比,按高峰时间交通流量区分的两个统计聚类足以进行分类,并且效果更好。 (C)2016 Elsevier Ltd.保留所有权利。

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