QUIESST database of European NRD

Cluster analysis for the in-situ method for sound reflection (CEN/TS 1793-5)

In order to identify NRD families based on the frequency spectra of the collected a data 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 and B 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 only 2 clusters have been identified. Cluster A contains 77% of the data representing mainly metal (SM) and concrete barriers (C and SC) with small roughness. Cluster B contains around 23% of the data and represents mainly metal barriers (SM) or concrete barriers with large or normal roughness (SC). Metal barriers are only present in cluster B, while concrete barriers can be found in both clusters, meaning that the difference in roughness of the surfaces is influencing the frequency spectra particularly for concrete barriers.

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