Study of Intelligent Prediction Control of Surface Roughness in Grinding

Abstract

A surface roughness intelligent prediction control system during grinding is built. The system is composed of fuzzy neural network prediction subsystem and fuzzy neural network controller. In the fuzzy neural network prediction subsystem, the vibration data are added to the inputs besides the grinding condition, such as feed and speed, so as to improve the dynamic performance of the prediction subsystem. The fuzzy neural network controller is able to adapt grinding parameters in process to improve the surface roughness of machined parts when the roughness is not meeting requirements. Experiment verifies that the developed prediction control system is feasible and has high prediction and control accuracy.