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Noise Predictions with Sound Systems using System Data Complex Summation (Implemented in SoundPLAN NoizCalc)

机译:使用系统数据和复杂求和的声音系统的噪声预测(在SoundPLAN和NoizCalc中实现)

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As the number of out-door events in urban areas is increasing, so are the challenges with accompanied noise immissions and therefore the need for accurate noise predictions. A method for noise predictions with sound systems is introduced, that uses real system data and applies complex summation. The system data, including all acoustic relevant characteristics such as relative positioning, orientation and directivity of loudspeakers, delays and electronic filters, is imported with a system design file (d&b's ArrayCalc simulation software). This procedure eliminates any friction losses, because it spares the repeated process of re-modeling a sound system in the noise prediction software and ensures predictions with the actual system design. It also is a sensible way to include specific electronic filters such as llR and FIR of a sound system. Noise prediction software did not consider complex summation because noise sources are assumed not to be correlated with each other (e.g. in traffic and industry). Sound systems are different, because the signals sent to the loudspeakers are usually correlated. Further more, modern sound systems use coherence effects to influence directivity. The sound propagation calculation was extended for complex summation and the method was implemented in SoundPLAN software and in NoizCalc (d&b).
机译:随着城市地区户外活动数量的增加,伴随着噪声排放的挑战也在增加,因此需要精确的噪声预测。介绍了一种使用声音系统进行噪声预测的方法,该方法使用真实的系统数据并应用复杂的求和。系统数据,包括所有与声学相关的特性,例如扬声器的相对位置,方向和方向性,延迟和电子滤波器,都通过系统设计文件(d&b的ArrayCalc仿真软件)导入。此过程消除了任何摩擦损失,因为它省去了在噪声预测软件中对声音系统进行重新建模的重复过程,并确保了根据实际系统设计进行的预测。包括特定的电子滤波器(例如声音系统的llR和FIR)也是一种明智的方法。噪声预测软件未考虑复杂的求和,因为假定噪声源彼此之间不相关(例如,在交通和工业中)。声音系统是不同的,因为发送到扬声器的信号通常是相关的。此外,现代声音系统使用相干效应来影响方向性。声音传播计算扩展为复杂的求和,并且该方法在SoundPLAN软件和NoizCalc(d&b)中实现。

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