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多孔吸声材料吸声性能优化及工程应用

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本文采用粒子群优化技术拟合多孔吸声材料JCA(Johnson-Champonx-Allward)模型中的非声学参数,并作为多孔吸声材料改进方向的依据,将其平均吸声系数从0.51提高至0.85.实验证明:优化后,在某体育馆建筑中的空调机组降噪工程中,进行实测敏感建筑处的夜间噪声,噪声由61.6dBA降低至48.6dBA,达到了降噪整改的效果.
Optimization and Application of Sound Absorption Performance of Porous Sound-absorbing Material
In this paper,particle swarm optimization(PSO)was used to fit the non-acoustic parameters in the JCA(Johnson-Champonx-Allward)model,and as a basis for the improvement direction of porous sound absorb-ing materials,the average absorption coefficient of porous sound absorbing materials was increased from 0.51 to 0.85.The experiment shows that:after optimization,in the noise reduction project of air conditioning unit in a gymnasium building,the night noise in the sensitive building is measured,and the noise is reduced from 61.6dBA to 48.6dBA,and the effect of noise reduction and rectification is achieved.

porous coefficient materialJCA modelparticle swarm optimization algorithmsound absorption coeffi-cient

李中云、王继承

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四川内江高信建设投资有限责任公司

广东省质量监督海洋工程装备振动噪声检验站

多孔吸声材料 JCA模型 粒子群优化算法 吸声系数

2024

计量与测试技术
成都市计量监督检定测试所

计量与测试技术

影响因子:0.175
ISSN:1004-6941
年,卷(期):2024.51(3)
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