Artificial Neural Network Approach to Extension of the Frequency Range for Experimental Determination of Dispersion Relationship Using Sparse Spatial Data

Abstract

In the case of sparse spatial data, the experimental determination of a dispersion relationship of mechanical waves using correlation method meets the challenges caused both by the discrete nature of the measurement data and by the discrete nature of wavenumber sets used by the method. This paper presents an effort aimed to overcome the challenges using an artificial neural network which includes knowledge about previously determined points of dispersion relationship into the process of determination of its new points. The results show that the application of the neural network contributes to extension of the frequency range for experimental determination of dispersion relationship of flexural waves in beams, but that it also may be used for other mechanical structures.