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

摘要

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-mentioned parameters in the restriction of certain sound insulation, and furthermore, to determine the material and construction 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) can 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 can be determined.