Method for Determining Airflow Resistance Of Porous Materials Based on Sound Absorption Coefficient

2019;
: pp. 52 - 65
1
Lviv Polytechnic National University
2
Lviv Polytechnic National University
3
AGH University of Science and Technology, Krakow, Poland
4
AGH University of Science and Technology, Krakow, Poland

The article presents software developed in the Labview system to automate the process of calculating the flow resistance of porous materials. The approach is to automatically collect and process information from a pressure sensors and a flow meter. The developed software made it possible to automate the process of determining the sound absorption coefficients of porous materials by the method of blowing airflow. The software allows performing real-time data analysis. The relationship between the change in pressure and the airflow are represented with a graph. This, in turn, makes it possible to evaluate the accuracy of measurements in real time. Measurement procedure and measurement methods are described. A method of rapid determination of airflow resistance based on sound absorption coefficients was developed and implemented. This allowed comparing the results obtained from an impedance tube and a laboratory stand for determining airflow resistance by the air-blowing method, comparing only the value of air resistance but not the function of the dependence of the absorption coefficient on the frequency. For the calculation of the sound absorption coefficient, an empirical Miki model was selected, which is a modification of the Delaney-Bazley model, but, unlike the latter, excludes the appearance of negative values of the sound absorption coefficient at low frequencies. To test the methods, the values of the airflow resistance were determined in three ways: calculated as a result of the experiment, calculated using a linear approximation for the entire data set, and calculated using the proposed method. The example of melamine foam shows that the proposed method is better able to map the regression line with the experimental data which minimizes the measurement error compared to the previously used method.

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