Inversed Sound Insulation Prediction to a Wall Based on Artificial Immune Algorithm
The sound insulation properties mainly depend on three physical parameters of a wall or partition, namely the density of material, the Youngs modulus and the thickness of the wall. Generally, density can be obtained from published data easily, the Youngs modulus of specific material and the thickness of wall can be measured. With the development of measurement technology of Youngs 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 Youngs 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.
artificial immune algorithm wall inversed sound insulation prediction
黄险峰
广西大学,土木建筑工程学院,广西,南宁,530004
国际会议
The 3rd International Symposium on Temporal Design(第三届时间性设计国际研讨会)
广州
英文
124-127
2007-11-02（万方平台首次上网日期，不代表论文的发表时间）