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一种用于长通道地下空间的改进声学扩散方程模型。

An Improved Acoustic Diffusion Equation Model for Long-Channel Underground Spaces.

作者信息

Mou Chao, Yang Qiliang, Xing Jianchun, Chen Tao, Zou Rongwei

机构信息

College of Defense Engineering, Army Engineering University of PLA, Nanjing 210001, China.

出版信息

Sensors (Basel). 2023 Sep 7;23(18):7738. doi: 10.3390/s23187738.

Abstract

The acoustic diffusion equation model has been widely applied in various scenarios, but a larger prediction error exists when applied to underground spaces, showing a significantly lower characteristic of the sound pressure level in the later stage compared to field tests since underground spaces have a more closed acoustic environment. Therefore, we analyze the characteristics of underground spaces differentiating from aboveground spaces when applying the model and propose an improved model from the perspective of energy balance. The energy neglected in the calculation of the acoustic diffusion equation model is compensated in long channel underground spaces named "acoustic escape compensation". A simulation and two field experiments are conducted to verify the effectiveness of the proposed compensation strategy in long-channel underground spaces. The mean square error is used to evaluate the differences between the classical model and the improved model, which shows a numerical improvement of 1.3 in the underground field test. The results show that the improved model is more suitable for describing underground spaces. The proposed strategy provides an effective extension of the acoustic diffusion equation model to solve the problem of sound field prediction and management in underground spaces.

摘要

声学扩散方程模型已在各种场景中广泛应用,但应用于地下空间时存在较大的预测误差,由于地下空间具有更封闭的声学环境,与现场测试相比,后期声压级特征明显更低。因此,我们分析了应用该模型时地下空间与地上空间不同的特性,并从能量平衡的角度提出了一种改进模型。在名为“声学逃逸补偿”的长通道地下空间中,对声学扩散方程模型计算中忽略的能量进行了补偿。进行了一次模拟和两次现场实验,以验证所提出的补偿策略在长通道地下空间中的有效性。使用均方误差来评估经典模型和改进模型之间的差异,在地下现场测试中显示出数值上提高了1.3。结果表明,改进后的模型更适合描述地下空间。所提出的策略为声学扩散方程模型提供了有效的扩展,以解决地下空间中的声场预测和管理问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4b2/10534945/824e6b6fa89d/sensors-23-07738-g001.jpg

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