Modeling workpiece vibrations with neural networks

Abstract

The entire workpiece on a lathe vibrates when it is excited at a single point. Frequency and time-domain/time-series techniques can estimate the force-displacement relationships between excitation and the individual points on the workpiece. In this paper, the use of single neural network is proposed to represent the force-displacement relationship between the applied excitation force and the vibration of the whole workpiece. The accuracy of the proposed approach is evaluated on the experimental data. Also, another neural network is used to store the frequency response characteristics of the workpiece. © 1993 Chapman & Hall.