基于人工免疫算法的墙体隔声反向预测(英文)

Inversed Sound Insulation Prediction to a Wall Based on Artificial Immune Algorithm

隔声量主要取决于墙板的面密度、材料的杨氏模量和墙的厚度,所测数据参量可以通过资料和实测获得.随着杨氏模量测试技术的发展,这些量越来越精确可靠.文中探讨如何在已知隔声要求的前提下,确定这3个参量,从而确定墙体的材料和构造.为此,在应用统计能量分析法进行建筑隔声预测的基础上,采用人工免疫算法建立单墙的隔声反演模型,在已知期望隔声量的情况下,对墙体的面密度、厚度和杨氏模量(或声波的纵波速度)等参数进行了反向预测,从而可以确定墙体材料和厚度等构造参数.

The sound insulation properties mainly depend on three physical parameters of a wall or partition, namely the density of material, the Young＇s modulus and the thickness of the wall. Generally, density can be obtained from published data easily, the Young＇s modulus of specific material and the thickness of wall can be measured. With the development of measurement technology of Young＇ s modulus, the measured data are becoming more and more precise and reliable. In order to predict the three above-mentinned parameters in the restriction of certain sound insulation, and furthermore, to determine the material and eonstruction of the wall, this paper adopts the statistic energy analysis （SEA） to predict the sound insulation first, and then uses the artificial immune algorithm （ AIA ） to establish the inversed sound insulation prediction model of a wall. By the proposed model, the surface density of the wall, the thickness and the Young＇s modulus （or the longitudinal sound wave speed） ean be inversely predicted when the expected sound insulation or criteria of a wall is known. Therefore, the material, the thickness and even the configuration of a wall ean be determined.