QUIESST database of European NRD

Cluster analysis for the laboratory method for sound insulation (EN 1793-2)

In order to identify NRD families based on the frequency spectra of the collected data a cluster analysis has been performed. An implementation of the k-means algorithm, designed to work specifically on longitudinal data, was used. Firstly, the optimal number of clusters was chosen according to the Calinski-Harabasz criterion. The definitions of clusters A, B and C are shown in the top diagram. The second step was to analyse in detail which material types are present in the identified clusters, considering also the roughness of the barrier surface (if available) as an additional parameter for the classification of the spectra. For each available material the identification with one or more clusters can be seen. A perfect correspondence between cluster and material type was not always found. In the present case 3 clusters have been identified. Cluster A contains 62% of the data representing mainly metal (SM) and timber (ST) barriers. Cluster B with around 33% of the data represents also metal (SM) and timber (ST) barriers. Cluster C with only 4% of the data represents only a few concrete barriers with small roughness.

figure figure