Abstract Porous material (PM) shows good sound absorption performance, however, the sound absorbing property of PM with different parameters are greatly different. In order to match the most suitable absorbing materials with the most satisfactory sound-absorbing performance according to the noise spectrum in different practical applications, multi-population genetic algorithm is used in this paper to optimize the parameters of porous sound absorbing structures that are commonly used according to the actual demand of noise reduction and experimental verification. The results shows that the optimization results of multi-population genetic algorithm are obviously better than the standard genetic algorithm in terms of sound absorption performance and sound absorption bandwidth. The average acoustic absorption coefficient of PM can reach above 0.6 in the range of medium frequency, and over 0.8 in the range of high frequency through optimization design. At a mid-to-high frequency environment, the PM has a better sound absorption effect and a wider frequency band than that of micro-perforated plate. However, it has a poor sound absorption effect at low frequency. So it is necessary to select suitable sound absorption material according to the actual noise spectrum.

中文翻译：

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基于多群体遗传算法的吸声多孔材料按需优化设计

摘要 多孔材料（PM）表现出良好的吸声性能，但不同参数的PM吸声性能差异很大。为了在不同的实际应用中根据噪声谱匹配最合适的吸声材料和最满意的吸声性能，本文采用多群体遗传算法对常用的多孔吸声结构参数进行优化。根据降噪和实验验证的实际需求。结果表明，多种群遗传算法的优化结果在吸声性能和吸声带宽方面明显优于标准遗传算法。PM的平均吸声系数可达0以上。通过优化设计，中频范围为6，高频范围为0.8以上。在中高频环境下，PM比微孔板吸音效果更好，频段更宽。但在低频下吸声效果较差。所以有必要根据实际噪声谱选择合适的吸声材料。