Beaton Douglas, Xiang Ning
Graduate Program in Architectural Acoustics, School of Architecture, Rensselaer Polytechnic Institute, 110 8th Street, Troy, New York 12180, USA.
J Acoust Soc Am. 2017 Jun;141(6):4480. doi: 10.1121/1.4983301.
Strong modal behavior can produce undesirable acoustical effects, particularly in recording studios and other small rooms. Although closed-form solutions exist to predict modes in rectangular rooms with parallel walls, such solutions are typically not available for rooms with even modest geometrical complexity. This work explores a method to identify multiple decaying modes in experimentally measured impulse responses from existing spaces. The method adopts a Bayesian approach working in the time domain to identify numerous decaying modes in an impulse response. Bayesian analysis provides a unified framework for two levels of inference: model selection and parameter estimation. In this context model selection determines the number of modes present in an impulse response, while parameter estimation determines the relevant parameters (e.g., decay time and frequency) of each mode. The Bayesian analysis in this work is implemented using an approximate numerical technique called nested sampling. Experimental measurements are performed in a test chamber in two different configurations. Experimentally measured results are compared with simulated values from the Bayesian analyses along with other, more classical calculations. Discussion of the results and the applicability of the method is provided.
强烈的模态行为会产生不良的声学效果，尤其是在录音棚和其他小房间中。尽管存在封闭形式的解决方案来预测平行墙壁矩形房间中的模态，但对于几何形状即使稍有复杂的房间，通常也没有这样的解决方案。这项工作探索了一种从现有空间的实验测量脉冲响应中识别多个衰减模态的方法。该方法采用贝叶斯方法在时域中工作，以识别脉冲响应中的众多衰减模态。贝叶斯分析为两个推理层次提供了一个统一的框架：模型选择和参数估计。在这种情况下，模型选择确定脉冲响应中存在的模态数量，而参数估计确定每个模态的相关参数（例如，衰减时间和频率）。这项工作中的贝叶斯分析是使用一种称为嵌套采样的近似数值技术来实现的。在测试室中以两种不同配置进行了实验测量。将实验测量结果与贝叶斯分析的模拟值以及其他更经典的计算结果进行了比较。并对结果和该方法的适用性进行了讨论。
