Prediction of Particle Damping Parameters Using RBF Neural Network

Particle damping is one of the recent passive damping methods used for effective vibration suppression. This paper discusses two different Artificial Neural Networks - Feed Forward Back Propagation Network and Radial Basis Function - applied to determine the relationship between the damping ratio and system parameters based on extensive experiments carried out on an aluminium alloy beam. The experiments are carried out with different combinations of system parameters for the estimation of damping ratio. Based on the Neural Network predictions, the factors which affect the damping performances are studied in detail for the given combination of system parameters.