The entire workpiece vibrates when a it is excited at a single point. The frequency and time domain time series techniques can obtain the force-displacement relationships between the excitation and the individual points of the workpiece. In this paper, the use of neural networks is proposed to represent the force-displacement relationship between the applied excitation force and the whole workpiece with a single neural network. One neural network was trained with experimental workpiece data and used to demonstrate the accuracy of the proposed approach.
