Materials Science & Technology

FULLTEXT SEARCH
NEW: Advanced Search

Study of Intelligent Prediction Control of Surface Roughness in Grinding

Journal Key Engineering Materials (Volume 329)
Volume Advances in Abrasive Technology IX
Edited by Dongming Guo, Tsunemoto Kuriyagawa, Jun Wang and Jun’ichi Tamaki
Pages 93-98
DOI 10.4028/www.scientific.net/KEM.329.93
Citation Ning Ding et al., 2007, Key Engineering Materials, 329, 93
Online since January, 2007
Authors Ning Ding, Long Shan Wang, Guang Fu Li
Keywords Control, Fuzzy Neural Network (FNN), Prediction, Roughness, Vibration
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.

Full Paper PDF Get the full paper by clicking here

First page example

Preview of first page