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Characterisation of meteorological conditions for sound propagation predictions

机译:声音传播预测的气象条件表征

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Atmospheric or meteorological condition is one of the most influential environmental factor in outdoor sound propagation. Yet it is also one the most difficult to characterise because of its variability with time and space. Sophisticated monitoring equipment such as radio-sonde, acoustically based SODAR or optically based LIDAR can be used to scan the atmosphere but they are generally not readily available for outdoor sound measurements in practice. Instead typical meteorological monitoring in a typical acoustic field trial uses a single wind mast to measure wind and temperature data at two heights. It is then common practice to simulate sound speed profile and turbulence parameters from these measurements to represent the meteorological condition over the entire propagation path. In this paper a set of meteorological and sound propagation data measured at three sites of different terrain features over several weeks is examined to look at the correlation between the meteorological and acoustic data. The meteorological data were measured by a wind mast near the source at two heights. Wind speeds measured covers both upwind and downwind conditions up to 10m/s. Prediction accuracy of sound propagation using these meteorological data by means of standard procedures and a heuristic ray tracing procedure is also investigated. It was found that the sound speed profile cannot be simulated by taking the simple difference between the data measured at two height. A sonic profile simulated by a simple logarithmic fit produces better results but the prediction accuracy is affected by high wind noise and uncertainties in the complex sites.
机译:大气或气象状况是户外声音传播中最有影响力的环境因素之一。然而,由于随着时间和空间的可变性,它也是最难以表征的。复杂的监测设备如无线电姑娘,基于声学的SODAR或光学的激光雷达,可用于扫描大气,但它们通常在实践中通常不容易获得户外声音测量。相反,典型的声场试验中的典型气象监测使用单个风桅杆来测量两个高度的风和温度数据。然后,常见的做法是为了从这些测量测量来模拟声速曲线和湍流参数来表示整个传播路径上的气象状态。在本文中,在几周内在不同地形特征的三个站点上测量的一组气象和声音传播数据,以查看气象和声学数据之间的相关性。气象数据由两个高度附近的风桅杆测量。测量的风速涵盖高达10m / s的上风和下行条件。还研究了通过标准程序使用这些气象数据的声音传播预测精度和启发式射线跟踪程序。发现不能通过在两个高度测量的数据之间的简单差异来模拟声速分布。通过简单的对数拟合模拟的声音轮廓产生更好的结果,但预测精度受到复杂部位中的高风噪声和不确定性的影响。

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