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Estimation of the background noise levels in large atria with known room acoustic properties and function

机译:估计具有已知房间声学特性和功能的大型Atria中的背景噪声水平

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One of the major identified acoustic problems in large halls such as atria or shopping malls is continuous unpleasant background noise, based on typically long reverberation of sound. Levels of background noise caused by internal sound sources depend on activity performed in the place on one hand and on room acoustic conditions on the other hand. Present noise can be measured relatively easily, by means of sound level meters and evaluated through statistical noise analysis, expressed e.g. by histogram of noise levels. However, the prediction of statistical noise levels, such as L_(95), L_(90) or even L_(eq), in rooms is very difficult, as it doesn't depend only on the overall sound power spectrum of sound source (typical sound source definition in ray-based algorithms), but also on the time varying character of sound. Function and thus activity performed in an atrium plays therefore an important role in terms of acoustic comfort analysis and without the information on time variation in source signal, parameters such as L_(90) or L_5 cannot be successfully predicted. In this paper several typical signal sounds (such as human steps, speech, music, ventilation etc.) are synthesized and auralized in Odeon software and assessed in parametric study of an atrium, followed by statistical analysis of predicted auralized wave files. Correlation between the activity and room acoustic parameters is calculated and estimation of background noise levels L_(99) is shown together with equivalent sound pressure level L_(A,eq).
机译:大厅中的主要发现的声学问题之一是Atria或购物中心等大厅中的一个是持续的令人不快的背景噪音,基于通常的声音长时间的混响。内部声音源引起的背景噪声水平取决于一方面和另一方面的房间声条件中的活动。目前噪声可以通过声级仪表相对容易地测量,并通过统计噪声分析评估,表达例如:通过噪声水平的直方图。然而,房间中的统计噪声水平(例如L_(95),L_(90)甚至L_(EQ))的预测非常困难,因为它不仅仅取决于声源的整体声音功率谱(基于射线的算法中的典型声源定义),但也是在声音的时变特征上。因此,在庭在中庭上执行的活动在声学舒适性分析方面发挥着重要作用,并且没有关于源信号的时间变化的信息,不能成功预测诸如L_(90)或L_5的参数。在本文中,在Odeon软件中合成和经历典型的信号声音(例如人工步骤,语音,音乐,通风等),并在庭的参数研究中进行评估,然后进行预测的顶发波文件的统计分析。计算活动和房间声学参数之间的相关性,并且背景噪声水平L_(99)的估计与等效声压级L_(A,EQ)一起示出。

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