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首页> 外文会议>International Congress on Sound and Vibration >INVERSE ESTIMATION OF SOUND ABSORPTION COEFFICIENT OF NATURAL JUTE MATERIAL BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM
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INVERSE ESTIMATION OF SOUND ABSORPTION COEFFICIENT OF NATURAL JUTE MATERIAL BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM

机译：基于粒子群优化算法的自然黄麻材料吸声系数逆估计

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摘要

Now a days use of natural materials have significantly increased in different fields of engineering mainly because of their environmental friendliness. In acoustics and noise control domain, natural material are also being effectively used. In this study, the acoustical characterization of three different types of natural jute felt material is performed by measurements in the laboratory and particle swarm optimization (PSO) based inverse acoustical characterization method. There are many empirical models available in literature which describes the acoustical behavior of a specific material accurately. In this work, measured values of air flow resistivity are used in Delany-Bazley model and Dunn-Davern model for sound absorption prediction of the natural material, jute. It is observed that, normal sound absorption coefficient values predicted using these two models deviate significantly from the experimental values throughout the frequency range of interest. Therefore, the inverse prediction of the eight regression coefficients in Dunn and Davern model using PSO method is conducted, and new regression coefficients for jute material are found. Results of predicted sound absorption using inverted coefficients for three types of jute felts are found to be better compared to prediction results from the original Delany and Bazley model and Dunn and Davern model, particularly in the low-frequency region.
机译：现在，在不同的工程领域，天然材料的使用量显着增加，主要是因为它们的环境友好。在声学和噪声控制域中，也有效地使用天然材料。在该研究中，通过基于实验室和粒子群优化（PSO）的逆声学表征方法的测量来进行三种不同类型的天然黄麻毡材料的声学表征。文献中有许多实证模型可准确地描述特定材料的声学行为。在这项工作中，测量的空气流动电阻率值用于Delany-Bazley Model和Dunn-Davern模型，用于天然材料的吸声预测，黄麻。观察到，使用这两种模型预测的正常声音吸收系数值显着地偏离在整个频率范围内的实验值。因此，对使用PSO方法进行DUNN和DAVERN模型中的八个回归系数的逆预测，并找到了黄麻材料的新回归系数。与原始Delany和Bazley Model和Dunn和Davern模型的预测结果相比，发现使用倒置系数的预测吸收的结果与原始Delany和Bazley Model和Dunn和Davern模型的预测结果相比，特别是在低频区域中更好。

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