Identifying acoustic coefficients of sound insulation panels: A novel predictive approach

Abstract

This research introduces a novel predictive approach for estimating the acoustic coefficients of sound insulation materials, aiming to enhance both the accuracy and efficiency of acoustic performance assessments. The proposed method addresses the limitations of traditional testing techniques, which are often costly and labour-intensive by offering a fast-prototyping tool for acoustics engineers. The algorithm integrates fuzzy logic with a high-resolution microscope image analysis to predict key acoustic parameters, including absorption coefficient rate. The algorithm achieved a high predictive accuracy by being trained on a diverse dataset of material properties and validated against experimental laboratory results. This approach provides a cost-effective and reliable alternative to conventional testing methods, enabling rapid evaluation of material performance while maintaining precision.