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Multi-objective optimization of the layout of damping material for reducing the structure-borne noise of thin-walled structures

机译:减少薄壁结构结构噪声的阻尼材料布局的多目标优化

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A multi-objective optimization of the layout of damping material for reducing the structure-borne noise of an enclosed cylindrical thin-walled structure was investigated by using the panel acoustic contribution (PAC) method and response surface methodology (RSM). Critical frequencies of each excitation were obtained by the control equations of structural-acoustic coupling system. The acoustic contributions of panels with different excitations at critical frequencies were calculated by the PAC method. Combined with the correlation coefficient matrix (CCM) method, the sum of panel acoustic contribution (SPAC) was proposed to identify and group the panels with different acoustic contributions under multiple excitations. In order to reduce the noise, a damping material was pasted. The thicknesses of the damping material applied to different groups were used as the design variables of the response surface functions, the sample data obtained by the finite element model was used to achieve the response surface functions for each excitation. Through these response surface functions, a multi-objective optimization model for discrete thicknesses of the damping material was established to reduce the structure-borne noise, and the optimization calculation was carried out by using genetic algorithm (GA). It is shown that the structure-borne noise was reduced more without increasing the amount of the damping material, and the present method is efficient enough to study and reduce the structure-borne noise. Compared with the traditional finite element nonlinear coupling calculation, the present method is more feasible and efficient.
机译:通过使用面板声学贡献(PAC)方法和响应表面方法(RSM)研究了降低封闭式圆壁结构的结构噪声的阻尼材料布局的多目标优化。通过结构声耦合系统的控制方程获得每个激励的临界频率。 PAC方法计算了在临界频率下具有不同激励的面板的声学贡献。结合相关系数矩阵(CCM)方法,提出了面板声学贡献(SPAC)的总和,以在多种激励下识别和分组具有不同声学贡献的面板。为了降低噪音,粘贴阻尼材料。施加到不同组的阻尼材料的厚度用作响应面功能的设计变量,通过有限元模型获得的样本数据用于实现每个激励的响应面功能。通过这些响应面功能,建立了一种用于降低阻尼材料的离散厚度的多目标优化模型,以降低结构传播的噪声,并且通过使用遗传算法(GA)进行优化计算。结果表明,在不增加阻尼材料的量的情况下,越来越多地降低了结构的噪声,并且本方法足够有效地学习和降低结构 - 传承的噪音。与传统的有限元非线性耦合计算相比,本方法更加可行,高效。

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