Estimation of absorber performance using reverberation techniques and artificial neural network models

Abstract

The Quality factors of an empty and loaded reverberant cavity were measured using time domain techniques. Measurements were performed for a set of frequencies under different loading conditions achieved by varying the material type and material amount. The measured data were used to develop an artificial neural network (ANN) model that predicts the amount of material required for a desired change in Q at a certain frequency for the cavity under consideration. The results show good comparison between the measured and the predicted values, thereby supporting the benefit of the ANN paradigm for studies like this, where experiments tend to be expensive.